mirror of
https://github.com/kennethreitz/tablib.git
synced 2026-06-05 15:00:19 +00:00
Compare commits
734 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 0e022d89e5 | |||
| a40852d1c6 | |||
| 9b9fb0aa8a | |||
| ca1aa3ad30 | |||
| 2cfde95fe2 | |||
| 5b94682df3 | |||
| f6bf14afd2 | |||
| f3d02aa3b0 | |||
| ca8dbcf9be | |||
| 4418535030 | |||
| 5bd896b954 | |||
| af414b69d7 | |||
| 91062672b5 | |||
| 34334e72a1 | |||
| 5595bb7993 | |||
| 5fde5259d9 | |||
| 591e8f7448 | |||
| 4dfe2c2f89 | |||
| 91608895d6 | |||
| 0d36390254 | |||
| 8ea082ce60 | |||
| a0df54ca22 | |||
| 0e06b7e328 | |||
| 8aeb5e5158 | |||
| a0d19a56cb | |||
| 8cc024e61b | |||
| a7c40a0881 | |||
| 20de7fad98 | |||
| 4969a71f7f | |||
| 743776371a | |||
| 326d07c2ed | |||
| 2f6ea8c644 | |||
| 8aaed50cc8 | |||
| a21b276d9c | |||
| e8838b5ce6 | |||
| 923711d99a | |||
| aac129db66 | |||
| d9df89f5da | |||
| 22bb20c74b | |||
| d25d24a9bb | |||
| 513bba2c20 | |||
| 2b9ce02e3c | |||
| f9f28d3d86 | |||
| 0cb50bb008 | |||
| f55f56ae1d | |||
| 0937c9f9ec | |||
| 25a66f95ac | |||
| 6ab511f8c0 | |||
| 64816258e6 | |||
| 41cbaa04b9 | |||
| c136940801 | |||
| cf03ecfe25 | |||
| 193b840da2 | |||
| 733d77ad1e | |||
| 3abd7e8c53 | |||
| 0be9e6a74b | |||
| ecd0afbcec | |||
| addaa090ef | |||
| f7b3fd4601 | |||
| 79dc77de49 | |||
| b057cdf05e | |||
| fc2f3c07c8 | |||
| a10327a283 | |||
| e0de42ef06 | |||
| f757ab84d1 | |||
| dc24fda415 | |||
| 3ba8d529fc | |||
| a8bdb4b28f | |||
| 1aaf235751 | |||
| 36ec60d5dd | |||
| babcbfd949 | |||
| 29b2c08da0 | |||
| 862a681263 | |||
| 102073c426 | |||
| 499ce52304 | |||
| c650b67e06 | |||
| 3e4d6fb5aa | |||
| dd2ba714d3 | |||
| a28a057559 | |||
| d38549ef1e | |||
| 5a359ba4de | |||
| 359007444c | |||
| 4f8949417e | |||
| 3d5943a8a4 | |||
| 38486231cc | |||
| 75f1bafd69 | |||
| 4749760e6f | |||
| ac3cf67620 | |||
| f812c29275 | |||
| 4c5d0b1a45 | |||
| 61063e2b09 | |||
| 4c300e65a5 | |||
| edbb16ec97 | |||
| dec5cea722 | |||
| 38183938dc | |||
| 7f1db4023f | |||
| b09fface1b | |||
| 69edb9def3 | |||
| ec54918f4a | |||
| ab6633549f | |||
| 56005d8022 | |||
| 36fa7ef097 | |||
| bb0abc863e | |||
| 58f6eefe01 | |||
| e4726cb85c | |||
| 412e690289 | |||
| 44e797d70e | |||
| 34c14aca18 | |||
| 7c318adde4 | |||
| 5dd74c0104 | |||
| a50ff92ff2 | |||
| 383d4b9c4e | |||
| 00e2ffa2ef | |||
| a3cd2c9cff | |||
| d89d243a30 | |||
| 69abfc3ada | |||
| 80e72cfa27 | |||
| 05bd0d1d42 | |||
| 62807734bd | |||
| c5c2dffe42 | |||
| 46102d4be7 | |||
| 44e9e24fec | |||
| 0ca5520bbc | |||
| e66eb4a189 | |||
| 0e720d78ca | |||
| 6afe716d64 | |||
| 76cbf9fadf | |||
| a93f93a458 | |||
| 3d44bdec40 | |||
| 319505817a | |||
| 6cb9a69746 | |||
| bb1354b61f | |||
| ddc4bd30f2 | |||
| 52e547daf9 | |||
| 7f0b7a0a22 | |||
| ddac443732 | |||
| e13f4d0aba | |||
| 54f9041f2c | |||
| 91d3299280 | |||
| cd67a63b43 | |||
| 19b3d6d06a | |||
| 59090d33a8 | |||
| a4f974287b | |||
| f59abe84be | |||
| cf23f2344f | |||
| e16bb38c48 | |||
| 71ca275dd1 | |||
| 75bbfbbaf4 | |||
| b35d505621 | |||
| cd491c062c | |||
| 9fdb72cc5c | |||
| a5b1f7987e | |||
| 8cf6770a76 | |||
| 5fa3d2f886 | |||
| d4c66c7a4e | |||
| af17586581 | |||
| 23d21f00f3 | |||
| 7ee924b5a6 | |||
| d720beadac | |||
| ee9666a146 | |||
| 77a9e25795 | |||
| d515724817 | |||
| 2814fbc381 | |||
| 9ca1d4ec54 | |||
| abbb4e32d8 | |||
| f6e757d569 | |||
| 9ba0451843 | |||
| d99db57d75 | |||
| 2299c00883 | |||
| 5ba6f5d91a | |||
| bbdf5f11ab | |||
| 851ba25702 | |||
| 039272b274 | |||
| d6a7832e60 | |||
| e51c4faec7 | |||
| f7fc3244ee | |||
| 53d69bd3ea | |||
| fcc9700d11 | |||
| 1ec9c18a66 | |||
| 99c28fa560 | |||
| fa7fb579fd | |||
| be24de19dc | |||
| 1d4f4b68ca | |||
| 8debeb26ac | |||
| 38e1ee6c3d | |||
| a774789252 | |||
| 995eabad37 | |||
| d90358bf69 | |||
| c5920249de | |||
| 9b6a73c97c | |||
| 679bd115b6 | |||
| 32cbc36fc1 | |||
| 8bded88559 | |||
| f8f57a467e | |||
| a11a993955 | |||
| 25894f2948 | |||
| 591b89693e | |||
| 85d9c2497e | |||
| eaf52b691e | |||
| 6f53c5d2b9 | |||
| 90ee799576 | |||
| c02a21ccd2 | |||
| fa045ca114 | |||
| 65703550c3 | |||
| 1fcb98f9ae | |||
| e2d45ecff7 | |||
| 47d92277cc | |||
| fdd74b5b0c | |||
| de052f0fac | |||
| 2f3acf5af4 | |||
| c4e8755cd2 | |||
| 79dc4524a0 | |||
| a785d77901 | |||
| b3485ec942 | |||
| 28b358c9da | |||
| 24657520e9 | |||
| 66d9e50984 | |||
| 541fba6786 | |||
| bc6398ffb0 | |||
| dca7bc9a7d | |||
| 2fbda0f43d | |||
| e350f9428b | |||
| 68dba0a77d | |||
| 028be03c2c | |||
| e1d65ba3c8 | |||
| e4cb3bcd9b | |||
| bf9510e0c7 | |||
| 82ae3ca507 | |||
| 5fbdd56fba | |||
| f187cef5f4 | |||
| 87892d7266 | |||
| 20e2ce5ba0 | |||
| 48e576954d | |||
| a21f8187f8 | |||
| 8479df725e | |||
| 333deb2311 | |||
| 0b714f21e1 | |||
| ae730b00b1 | |||
| 84e8b0384f | |||
| 7a2842a8af | |||
| 954bbdccf3 | |||
| 7acaa8460d | |||
| 84e7e251ae | |||
| dc868eff31 | |||
| 43356e908c | |||
| f7acc19523 | |||
| c5972db8f0 | |||
| 1cc051f3e8 | |||
| 3da155ce0d | |||
| 9a34cf0980 | |||
| 434f66b4eb | |||
| d056916c53 | |||
| cf5239f097 | |||
| 49d8cb816f | |||
| fbd277ff2e | |||
| 6f4572fa56 | |||
| 453fc8614c | |||
| 01cf58e431 | |||
| f6cd89c76c | |||
| 1e0f30e8a6 | |||
| 569d35bfca | |||
| d40cdfbcd0 | |||
| 86bbaf9bea | |||
| 0ed01d85b9 | |||
| fc4cc7fa14 | |||
| 70716fdd21 | |||
| 1146ec2341 | |||
| 1a7d597745 | |||
| 56b627a561 | |||
| 98e182bed2 | |||
| c8a5563309 | |||
| c225a64d68 | |||
| d611d5a14f | |||
| 45121ddd65 | |||
| c74357cb20 | |||
| 939b0af551 | |||
| 9c2018653f | |||
| 2bc6122ee8 | |||
| 7f0748aac9 | |||
| 41a5c67159 | |||
| 3efefcc8da | |||
| d19de6025b | |||
| 65ba937c0d | |||
| 79a2bb888f | |||
| 25eacaf6f0 | |||
| c2a9af7fb3 | |||
| 3b06f3760d | |||
| e7ee3195a7 | |||
| 5bd2e3df52 | |||
| 837b3f83e6 | |||
| ff8f23edd5 | |||
| 5ffcfd56f2 | |||
| 955c24c974 | |||
| 192a5efabb | |||
| 1aafc7e2f4 | |||
| 9e45b95d12 | |||
| d8f0a018ae | |||
| 7545f3726e | |||
| 85e2bd73fc | |||
| 37033903c5 | |||
| 02c38c2520 | |||
| 26748deb9f | |||
| 63f6cea132 | |||
| 1b035f9774 | |||
| 2c14486c33 | |||
| 8bc69c9d85 | |||
| d36a2cbd42 | |||
| 1ab0eb3fae | |||
| cd71e1a5b1 | |||
| 47f79a7ca1 | |||
| 9f38efe413 | |||
| 5d98239a7e | |||
| a3f0d02633 | |||
| b29007a0df | |||
| e75c3c1a66 | |||
| 47cebbc328 | |||
| e4c39524f7 | |||
| c88c794314 | |||
| 752443f077 | |||
| 7c0507bcce | |||
| 652ac85549 | |||
| 05ea3c35fc | |||
| d5fada7e1d | |||
| 511c58d4e1 | |||
| c469360a0e | |||
| 97b4401b18 | |||
| 40e0f41b4c | |||
| 39435727ba | |||
| eda9d5af03 | |||
| 15435047c6 | |||
| a3781e3c89 | |||
| 6a825a8a39 | |||
| 6a449d497a | |||
| d807c60346 | |||
| 71603662b1 | |||
| 21c11b9911 | |||
| e8c923d712 | |||
| bc581c08df | |||
| 4f9c9d09ec | |||
| 63e8a7172d | |||
| 45e0af9f0e | |||
| fa6f5b3af3 | |||
| 0528e0a500 | |||
| 8e83734985 | |||
| 783eccc67d | |||
| 7236415f42 | |||
| c0a3c3ea1e | |||
| 14bd964fb1 | |||
| 6bfc6634ba | |||
| 54affad292 | |||
| 7c963a0f4d | |||
| 02f27f15c5 | |||
| 9c65515e7a | |||
| c87a954a9e | |||
| 42e40ed0ab | |||
| 23ab6c4724 | |||
| 32a09ccd6a | |||
| 81a7f79b3d | |||
| 05c9b33003 | |||
| ec7273d02d | |||
| 19ee1997b5 | |||
| f01d65c2e9 | |||
| 9778a96351 | |||
| 906138b138 | |||
| 43c68b396f | |||
| d611233c80 | |||
| 3d02b866ce | |||
| 887ee2fbac | |||
| bfd211854a | |||
| bc75911500 | |||
| a2b4e4c6ba | |||
| fde6f11763 | |||
| 33a83316df | |||
| f6d7888d9e | |||
| c19e2f2c5b | |||
| eaa2b9b8ea | |||
| 2f8083bda6 | |||
| 2c5a9af76e | |||
| e74a8f41cc | |||
| cd5aa4fc06 | |||
| 1d460bac40 | |||
| 4a3fde37a3 | |||
| 62ad123ad8 | |||
| fefc7b4d1f | |||
| 6313437a27 | |||
| 23a5bb1443 | |||
| 864f29cc4b | |||
| c136b794a7 | |||
| d254c2d2b0 | |||
| 9b235150cf | |||
| 9f3e6eeaa1 | |||
| 51728f954f | |||
| 2949b7c656 | |||
| 07d243bbc9 | |||
| bf3484e606 | |||
| 9b2ab6fae9 | |||
| 7a3d55daab | |||
| eec0595c5c | |||
| 0c7c248b96 | |||
| 0d14f7f2b9 | |||
| d5f713024d | |||
| 415bc819e7 | |||
| 974258094e | |||
| ab16f69be6 | |||
| 28d9af852a | |||
| 39c6ea6503 | |||
| 39b66ad8e9 | |||
| 004b3da680 | |||
| d4923533eb | |||
| 29e0b76910 | |||
| 4f54de2630 | |||
| 1f0d68ee79 | |||
| cae8fa1276 | |||
| 4c0a20a7b9 | |||
| 6c1fa87138 | |||
| 0e30255836 | |||
| 1156d5a220 | |||
| 83b71967b9 | |||
| 4dab48cd76 | |||
| 5324526329 | |||
| 1dfcd42233 | |||
| f162b19bd6 | |||
| 707164e459 | |||
| 42f0a285c3 | |||
| d111cc7cc7 | |||
| 25fe211a22 | |||
| 4b675494c4 | |||
| a196b9a5dd | |||
| 5ba56c2bb3 | |||
| 36fbdda492 | |||
| 273d2729ee | |||
| 3036bc9e52 | |||
| b9c74eacc8 | |||
| 805ccfae34 | |||
| fddc018394 | |||
| 2477100062 | |||
| 983b979fda | |||
| 3edb45bac7 | |||
| 29d626fa1f | |||
| 1f22fc7321 | |||
| 8631f60f8d | |||
| 65873b6112 | |||
| 56e44bd45c | |||
| 87e65fd3e7 | |||
| ffbc3b122d | |||
| 9d71603dad | |||
| cceb41af98 | |||
| 60ffa898fd | |||
| a4a211b5a6 | |||
| c9766a48b0 | |||
| 6975685b89 | |||
| e920244a1b | |||
| ea63779baf | |||
| d826f6d0ae | |||
| f6fa3f2abc | |||
| eed6df45e0 | |||
| cb4c67767a | |||
| 1e21fee70e | |||
| 420dd36ab8 | |||
| 9a05770899 | |||
| 8e055f1c57 | |||
| 239e33aaed | |||
| bf4fdea187 | |||
| 03086052ed | |||
| 2128473938 | |||
| 74c64d66a9 | |||
| a4e77f22c4 | |||
| 2e03046a07 | |||
| 06a7b4cd4e | |||
| 6a70b84166 | |||
| 77d9fe8b41 | |||
| 64cb547e0a | |||
| 9146de36d4 | |||
| 9761ff5e9e | |||
| e5259cbb58 | |||
| 56ef89424f | |||
| 4a01299293 | |||
| 9399bf2fe7 | |||
| cbdaa09e83 | |||
| f30e760657 | |||
| a60e2f132e | |||
| 2b36d71554 | |||
| 690de63b7c | |||
| 6b6ef70c61 | |||
| 322283b8f9 | |||
| 3968729903 | |||
| 7b1e533e39 | |||
| 8dd7d73abc | |||
| 176c9615d6 | |||
| c65fd4201f | |||
| 11bca4f7a2 | |||
| 2b5818598a | |||
| 79fb82d69d | |||
| 5350355fbe | |||
| 85673b365c | |||
| 87ce64d4c8 | |||
| 2cd381389c | |||
| 35f21cf73e | |||
| 0ebc8f5e1b | |||
| 865ce62782 | |||
| 3b961c59e7 | |||
| 4be341be4f | |||
| 2c4337b317 | |||
| 0e4128c73e | |||
| 4ebd66cb09 | |||
| bfcfa37ebb | |||
| 5c50c1822e | |||
| 2e5577ee91 | |||
| 84e4bd9a47 | |||
| 7270ce49e1 | |||
| c3052cc02c | |||
| 999c49a4f0 | |||
| 59c996f9df | |||
| a2b62669b7 | |||
| 15e25ef735 | |||
| 7ae7d3ff46 | |||
| 69ed718191 | |||
| 328d3880d5 | |||
| ea3cc847a0 | |||
| 8efab51355 | |||
| e42d215833 | |||
| 10bc5549c9 | |||
| 1a5e2ecb33 | |||
| e1bf189847 | |||
| 0785328e21 | |||
| 6ba0cc9af3 | |||
| 36876205e7 | |||
| 1b97b7191e | |||
| 8b575df419 | |||
| 6a3928759a | |||
| 63348d883b | |||
| 5dce600969 | |||
| 0913b54f47 | |||
| c5bbc74b96 | |||
| 7f5342a1b8 | |||
| d42f9bc10f | |||
| c6565c9e29 | |||
| 1a9343750e | |||
| 8a393214c8 | |||
| b8ed741a36 | |||
| cddbd78a61 | |||
| b113f49ce6 | |||
| 1429b9f8c4 | |||
| 42700f98a5 | |||
| 0e56db632a | |||
| b07512071e | |||
| e4881809d6 | |||
| 54ab300d2d | |||
| 4368d64317 | |||
| 117344de14 | |||
| 58bc1c7dcf | |||
| 4c8b5e72e3 | |||
| b900236157 | |||
| dc14a16e04 | |||
| 2d2ac9b708 | |||
| 1efcb7a63d | |||
| 65c73dfc42 | |||
| 3803a7a21b | |||
| 8b5b29fc90 | |||
| e8ba765426 | |||
| 57001a5465 | |||
| c8493ff047 | |||
| 03914323c2 | |||
| 2f331cee8e | |||
| e1734f2315 | |||
| 22cddbcd63 | |||
| 76f09cd3b3 | |||
| d11c09febe | |||
| 9ab277a468 | |||
| 23c1831144 | |||
| 1cf9bd14b4 | |||
| c2331f7a23 | |||
| bccf0d1ba1 | |||
| c219972ccd | |||
| 52e9d44739 | |||
| e94ecd8472 | |||
| 96067e6380 | |||
| 1cc0f7d1f4 | |||
| f685bf548e | |||
| ca336926da | |||
| 1aa3d3b06a | |||
| be576135b2 | |||
| 0c05d0497e | |||
| 52e307ea35 | |||
| 5cac9bd97e | |||
| a285e993f1 | |||
| 0ed367a31c | |||
| c4815c24cc | |||
| 20fe1e0153 | |||
| 5db8d1c3a6 | |||
| 828017f9a7 | |||
| cff8a6ac9a | |||
| aa8590e8b8 | |||
| d2de647c47 | |||
| 7afef680f5 | |||
| 35763f8c24 | |||
| cc3d020914 | |||
| b8b5405f1c | |||
| b7aebbc74f | |||
| d776d78df5 | |||
| 6f9365d376 | |||
| 621b1bd45c | |||
| be21b6fadd | |||
| 832bfbbb1b | |||
| 288b15fb54 | |||
| 73df22303b | |||
| 4c125bd206 | |||
| ff0de1377a | |||
| ccb29c68fa | |||
| e077a7f2bc | |||
| dcc52bdc18 | |||
| 9cac54eefc | |||
| f69a96f07e | |||
| ca77ed6f64 | |||
| 806aba9ef3 | |||
| 23cbc0c333 | |||
| 34ab54de77 | |||
| 0843a15879 | |||
| 08ed309382 | |||
| 26b6faa88d | |||
| 140736ff33 | |||
| 5379c5683d | |||
| e8b44b5777 | |||
| a0822bc9b0 | |||
| 89b431213b | |||
| 695e8c5af7 | |||
| 0797ec67d4 | |||
| 1852624a7e | |||
| f81dc41a57 | |||
| 34415b89b8 | |||
| d25655588b | |||
| 22c4d185e1 | |||
| e3b3659ea4 | |||
| 22d337790a | |||
| 0784d4b32c | |||
| 332c5bccd9 | |||
| 7055d18a2e | |||
| 6a7c685111 | |||
| 0e5b8f7058 | |||
| e3e6b656e3 | |||
| 99896a5f28 | |||
| 25da44f569 | |||
| 7727171379 | |||
| 91bd4eb9c7 | |||
| 9b74b139fd | |||
| 823a543f41 | |||
| 1aa275bf99 | |||
| 17bb0d3b2c | |||
| 1a9aee9289 | |||
| 196edb82cc | |||
| a2990d5852 | |||
| d992ece86a | |||
| 46f302255d | |||
| 9e3ab4c13f | |||
| eaed0e48c2 | |||
| 501187b357 | |||
| ea4aef88b6 | |||
| 24d800fac3 | |||
| d8136ab613 | |||
| 36bbe2726b | |||
| 1427be2901 | |||
| 10ce000d31 | |||
| a91254117c | |||
| b67762604f | |||
| 83a8346e8f | |||
| 657ab98d04 | |||
| 9ddb4de942 | |||
| 5fad80a540 | |||
| cabab73045 | |||
| 2bb0525990 | |||
| f364bb576e | |||
| 09d057094e | |||
| 8082c4ad43 | |||
| 00e9ae0120 | |||
| f01c22213e | |||
| a58bf269d9 | |||
| 437a135dd3 | |||
| 0409ff50af | |||
| dd24edcc24 | |||
| cf28f4baa8 | |||
| 52dcf79c41 | |||
| 49f098ee22 | |||
| 642b1d8def | |||
| f6964bba8f | |||
| 8d6e75ad20 | |||
| 30487999ba | |||
| b74308e81e | |||
| 577289cbc3 | |||
| cf10703e31 | |||
| 778ad0265e | |||
| e3dedb8887 | |||
| c6e240fa52 | |||
| 5c747c9c2e | |||
| 0bbd990ed8 | |||
| fcada243a2 | |||
| fca8ad6182 | |||
| 35d9e390fd | |||
| 8ca180c461 | |||
| ff63558a67 | |||
| f621b56178 | |||
| 2b529bcb1c | |||
| 90c3435600 | |||
| 1fa28ee2ca | |||
| a5cae7c249 | |||
| 666991ca1e | |||
| 5f4162918f | |||
| b554ce36bb | |||
| e5e22d3ca2 | |||
| 8626351618 | |||
| cdfacb6d6e | |||
| 108c9de130 | |||
| 271aeebf56 | |||
| e75a00541d | |||
| 3b0e0c7991 | |||
| 23440fb7a3 | |||
| 459f310857 | |||
| f9021f53c2 | |||
| 7fda829d27 | |||
| ca08ac8a7b | |||
| 08b51113d3 | |||
| 3e391fc8e3 | |||
| a230844914 | |||
| bc82be09c5 | |||
| ed9fe01604 | |||
| e69546a0ff | |||
| d4b659ece9 | |||
| 55eb3f93e3 | |||
| be7182aea9 | |||
| 48def2cba6 | |||
| df8c0335d1 | |||
| d0b09f0fce | |||
| 9efd982bfa | |||
| a3c82804cd | |||
| 2e75e93f57 |
+10
@@ -0,0 +1,10 @@
|
||||
# .coveragerc to control coverage.py
|
||||
|
||||
[report]
|
||||
# Regexes for lines to exclude from consideration
|
||||
exclude_lines =
|
||||
# Have to re-enable the standard pragma:
|
||||
pragma: no cover
|
||||
|
||||
# Don't complain if non-runnable code isn't run:
|
||||
if __name__ == .__main__.:
|
||||
@@ -0,0 +1,10 @@
|
||||
[](https://jazzband.co/)
|
||||
|
||||
This is a [Jazzband](https://jazzband.co/) project. By contributing you agree to abide
|
||||
by the [Contributor Code of Conduct](https://jazzband.co/about/conduct) and follow the
|
||||
[guidelines](https://jazzband.co/about/guidelines).
|
||||
|
||||
If you'd like to contribute, simply fork
|
||||
[the repository](https://github.com/jazzband/tablib), commit your changes to a feature
|
||||
branch, and send a pull request to `master`. Make sure you add yourself to
|
||||
[AUTHORS](https://github.com/jazzband/tablib/blob/master/AUTHORS).
|
||||
+21
-1
@@ -17,4 +17,24 @@ profile
|
||||
|
||||
# vi noise
|
||||
*.swp
|
||||
docs/_build/*
|
||||
docs/_build/*
|
||||
coverage.xml
|
||||
nosetests.xml
|
||||
junit-py25.xml
|
||||
junit-py26.xml
|
||||
junit-py27.xml
|
||||
|
||||
# tox noise
|
||||
.tox
|
||||
|
||||
# pyenv noise
|
||||
.python-version
|
||||
tablib.egg-info/*
|
||||
|
||||
# Coverage
|
||||
.coverage
|
||||
htmlcov
|
||||
|
||||
# setuptools noise
|
||||
.eggs
|
||||
*.egg-info
|
||||
|
||||
@@ -0,0 +1,6 @@
|
||||
[settings]
|
||||
multi_line_output=3
|
||||
include_trailing_comma=True
|
||||
force_grid_wrap=0
|
||||
use_parentheses=True
|
||||
line_length=88
|
||||
+22
@@ -0,0 +1,22 @@
|
||||
language: python
|
||||
python:
|
||||
- 2.7
|
||||
- 3.6
|
||||
- 3.7
|
||||
- 3.8
|
||||
cache: pip
|
||||
dist: xenial
|
||||
install: travis_retry pip install tox-travis
|
||||
script: tox
|
||||
after_success: bash <(curl -s https://codecov.io/bash)
|
||||
deploy:
|
||||
provider: pypi
|
||||
user: jazzband
|
||||
server: https://jazzband.co/projects/tablib/upload
|
||||
distributions: sdist bdist_wheel
|
||||
password:
|
||||
secure: svV4fYtodwW+iTyFOm5ISEfhVwcA+6vTskD3x6peznc40TdMV9Ek8nT3Q/NB4lCbXoUw2qR4H6uhLCjesnv/VvVk/qbitCyD8ySlgwOV5n7NzJs8lC8EYaHSjGQjatTwJAokfGVYkPawkI7HXDqtDggLUQBK+Ag8HDW+XBSbQIU=
|
||||
on:
|
||||
tags: true
|
||||
repo: jazzband/tablib
|
||||
python: 3.7
|
||||
@@ -1,14 +1,30 @@
|
||||
Tablib is written and maintained by Kenneth Reitz and
|
||||
various contributors:
|
||||
Tablib was originally written by Kenneth Reitz and is now maintained
|
||||
by the Jazzband GitHub team.
|
||||
|
||||
Development Lead
|
||||
````````````````
|
||||
Here is a list of passed and present much-appreciated contributors:
|
||||
|
||||
- Kenneth Reitz <me@kennethreitz.com>
|
||||
|
||||
|
||||
Patches and Suggestions
|
||||
```````````````````````
|
||||
|
||||
- Luke Lee
|
||||
- Josh Ourisman
|
||||
Alex Gaynor
|
||||
Andrii Soldatenko
|
||||
Benjamin Wohlwend
|
||||
Bruno Soares
|
||||
Claude Paroz
|
||||
Erik Youngren
|
||||
Hugo van Kemenade
|
||||
Iuri de Silvio
|
||||
Jakub Janoszek
|
||||
James Douglass
|
||||
Joel Friedly
|
||||
Josh Ourisman
|
||||
Kenneth Reitz
|
||||
Luca Beltrame
|
||||
Luke Lee
|
||||
Marc Abramowitz
|
||||
Marco Dallagiacoma
|
||||
Mark Rogers
|
||||
Mark Walling
|
||||
Mathias Loesch
|
||||
Mike Waldner
|
||||
Rabin Nankhwa
|
||||
Tommy Anthony
|
||||
Tsuyoshi Hombashi
|
||||
Tushar Makkar
|
||||
|
||||
+273
@@ -0,0 +1,273 @@
|
||||
# History
|
||||
|
||||
## 0.14.0 (2019-10-19)
|
||||
|
||||
### Deprecations
|
||||
|
||||
- The 0.14.x series will be the last to support Python 2
|
||||
|
||||
### Breaking changes
|
||||
|
||||
- Dropped Python 3.4 support
|
||||
|
||||
### Improvements
|
||||
|
||||
- Added Python 3.7 and 3.8 support
|
||||
- The project is now maintained by the Jazzband team, https://jazzband.co
|
||||
- Improved format autodetection and added autodetection for the odf format.
|
||||
- Added search to all documentation pages
|
||||
- Open xlsx workbooks in read-only mode (#316)
|
||||
- Unpin requirements
|
||||
- Only install backports.csv on Python 2
|
||||
|
||||
### Bugfixes
|
||||
|
||||
- Fixed `DataBook().load` parameter ordering (first stream, then format).
|
||||
- Fixed a regression for xlsx exports where non-string values were forced to
|
||||
strings (#314)
|
||||
- Fixed xlsx format detection (which was often detected as `xls` format)
|
||||
|
||||
## 0.13.0 (2019-03-08)
|
||||
|
||||
- Added reStructuredText output capability (#336)
|
||||
- Added Jira output capability
|
||||
- Stopped calling openpyxl deprecated methods (accessing cells, removing sheets)
|
||||
(openpyxl minimal version is now 2.4.0)
|
||||
- Fixed a circular dependency issue in JSON output (#332)
|
||||
- Fixed Unicode error for the CSV export on Python 2 (#215)
|
||||
- Removed usage of optional `ujson` (#311)
|
||||
- Dropped Python 3.3 support
|
||||
|
||||
## 0.12.1 (2017-09-01)
|
||||
|
||||
- Favor `Dataset.export(<format>)` over `Dataset.<format>` syntax in docs
|
||||
- Make Panda dependency optional
|
||||
|
||||
## 0.12.0 (2017-08-27)
|
||||
|
||||
- Add initial Panda DataFrame support
|
||||
- Dropped Python 2.6 support
|
||||
|
||||
## 0.11.5 (2017-06-13)
|
||||
|
||||
- Use `yaml.safe_load` for importing yaml.
|
||||
|
||||
## 0.11.4 (2017-01-23)
|
||||
|
||||
- Use built-in `json` package if available
|
||||
- Support Python 3.5+ in classifiers
|
||||
|
||||
### Bugfixes
|
||||
|
||||
- Fixed textual representation for Dataset with no headers
|
||||
- Handle decimal types
|
||||
|
||||
## 0.11.3 (2016-02-16)
|
||||
|
||||
- Release fix.
|
||||
|
||||
## 0.11.2 (2016-02-16)
|
||||
|
||||
### Bugfixes
|
||||
|
||||
- Fix export only formats.
|
||||
- Fix for xlsx output.
|
||||
|
||||
## 0.11.1 (2016-02-07)
|
||||
|
||||
### Bugfixes
|
||||
|
||||
- Fixed packaging error on Python 3.
|
||||
|
||||
|
||||
## 0.11.0 (2016-02-07)
|
||||
|
||||
### New Formats!
|
||||
|
||||
- Added LaTeX table export format (`Dataset.latex`).
|
||||
- Support for dBase (DBF) files (`Dataset.dbf`).
|
||||
|
||||
### Improvements
|
||||
|
||||
- New import/export interface (`Dataset.export()`, `Dataset.load()`).
|
||||
- CSV custom delimiter support (`Dataset.export('csv', delimiter='$')`).
|
||||
- Adding ability to remove duplicates to all rows in a dataset (`Dataset.remove_duplicates()`).
|
||||
- Added a mechanism to avoid `datetime.datetime` issues when serializing data.
|
||||
- New `detect_format()` function (mostly for internal use).
|
||||
- Update the vendored unicodecsv to fix `None` handling.
|
||||
- Only freeze the headers row, not the headers columns (xls).
|
||||
|
||||
### Breaking Changes
|
||||
|
||||
- `detect()` function removed.
|
||||
|
||||
### Bugfixes
|
||||
|
||||
- Fix XLSX import.
|
||||
- Bugfix for `Dataset.transpose().transpose()`.
|
||||
|
||||
|
||||
## 0.10.0 (2014-05-27)
|
||||
|
||||
* Unicode Column Headers
|
||||
* ALL the bugfixes!
|
||||
|
||||
## 0.9.11 (2011-06-30)
|
||||
|
||||
* Bugfixes
|
||||
|
||||
## 0.9.10 (2011-06-22)
|
||||
|
||||
* Bugfixes
|
||||
|
||||
## 0.9.9 (2011-06-21)
|
||||
|
||||
* Dataset API Changes
|
||||
* `stack_rows` => `stack`, `stack_columns` => `stack_cols`
|
||||
* column operations have their own methods now (`append_col`, `insert_col`)
|
||||
* List-style `pop()`
|
||||
* Redis-style `rpush`, `lpush`, `rpop`, `lpop`, `rpush_col`, and `lpush_col`
|
||||
|
||||
## 0.9.8 (2011-05-22)
|
||||
|
||||
* OpenDocument Spreadsheet support (.ods)
|
||||
* Full Unicode TSV support
|
||||
|
||||
|
||||
## 0.9.7 (2011-05-12)
|
||||
|
||||
* Full XLSX Support!
|
||||
* Pickling Bugfix
|
||||
* Compat Module
|
||||
|
||||
|
||||
## 0.9.6 (2011-05-12)
|
||||
|
||||
* `seperators` renamed to `separators`
|
||||
* Full unicode CSV support
|
||||
|
||||
|
||||
## 0.9.5 (2011-03-24)
|
||||
|
||||
* Python 3.1, Python 3.2 Support (same code base!)
|
||||
* Formatter callback support
|
||||
* Various bug fixes
|
||||
|
||||
|
||||
|
||||
## 0.9.4 (2011-02-18)
|
||||
|
||||
* Python 2.5 Support!
|
||||
* Tox Testing for 2.5, 2.6, 2.7
|
||||
* AnyJSON Integrated
|
||||
* OrderedDict support
|
||||
* Caved to community pressure (spaces)
|
||||
|
||||
|
||||
## 0.9.3 (2011-01-31)
|
||||
|
||||
* Databook duplication leak fix.
|
||||
* HTML Table output.
|
||||
* Added column sorting.
|
||||
|
||||
|
||||
## 0.9.2 (2010-11-17)
|
||||
|
||||
* Transpose method added to Datasets.
|
||||
* New frozen top row in Excel output.
|
||||
* Pickling support for Datasets and Rows.
|
||||
* Support for row/column stacking.
|
||||
|
||||
|
||||
## 0.9.1 (2010-11-04)
|
||||
|
||||
* Minor reference shadowing bugfix.
|
||||
|
||||
|
||||
## 0.9.0 (2010-11-04)
|
||||
|
||||
* Massive documentation update!
|
||||
* Tablib.org!
|
||||
* Row tagging and Dataset filtering!
|
||||
* Column insert/delete support
|
||||
* Column append API change (header required)
|
||||
* Internal Changes (Row object and use thereof)
|
||||
|
||||
|
||||
## 0.8.5 (2010-10-06)
|
||||
|
||||
* New import system. All dependencies attempt to load from site-packages,
|
||||
then fallback on tenderized modules.
|
||||
|
||||
|
||||
## 0.8.4 (2010-10-04)
|
||||
|
||||
* Updated XLS output: Only wrap if '\\n' in cell.
|
||||
|
||||
|
||||
## 0.8.3 (2010-10-04)
|
||||
|
||||
* Ability to append new column passing a callable
|
||||
as the value that will be applied to every row.
|
||||
|
||||
|
||||
## 0.8.2 (2010-10-04)
|
||||
|
||||
* Added alignment wrapping to written cells.
|
||||
* Added separator support to XLS.
|
||||
|
||||
|
||||
## 0.8.1 (2010-09-28)
|
||||
|
||||
* Packaging Fix
|
||||
|
||||
|
||||
## 0.8.0 (2010-09-25)
|
||||
|
||||
* New format plugin system!
|
||||
* Imports! ELEGANT Imports!
|
||||
* Tests. Lots of tests.
|
||||
|
||||
|
||||
## 0.7.1 (2010-09-20)
|
||||
|
||||
* Reverting methods back to properties.
|
||||
* Windows bug compensated in documentation.
|
||||
|
||||
|
||||
## 0.7.0 (2010-09-20)
|
||||
|
||||
* Renamed DataBook Databook for consistency.
|
||||
* Export properties changed to methods (XLS filename / StringIO bug).
|
||||
* Optional Dataset.xls(path='filename') support (for writing on windows).
|
||||
* Added utf-8 on the worksheet level.
|
||||
|
||||
|
||||
## 0.6.4 (2010-09-19)
|
||||
|
||||
* Updated unicode export for XLS.
|
||||
* More exhaustive unit tests.
|
||||
|
||||
|
||||
## 0.6.3 (2010-09-14)
|
||||
|
||||
* Added Dataset.append() support for columns.
|
||||
|
||||
|
||||
## 0.6.2 (2010-09-13)
|
||||
|
||||
* Fixed Dataset.append() error on empty dataset.
|
||||
* Updated Dataset.headers property w/ validation.
|
||||
* Added Testing Fixtures.
|
||||
|
||||
## 0.6.1 (2010-09-12)
|
||||
|
||||
* Packaging hotfixes.
|
||||
|
||||
|
||||
## 0.6.0 (2010-09-11)
|
||||
|
||||
* Public Release.
|
||||
* Export Support for XLS, JSON, YAML, and CSV.
|
||||
* DataBook Export for XLS, JSON, and YAML.
|
||||
* Python Dict Property Support.
|
||||
-90
@@ -1,90 +0,0 @@
|
||||
History
|
||||
=======
|
||||
|
||||
0.8.5 (2010-10-06)
|
||||
------------------
|
||||
|
||||
* New import system. All dependencies attempt to load from site-packages,
|
||||
then fallback on vendorized modules.
|
||||
|
||||
|
||||
0.8.4 (2010-10-04)
|
||||
------------------
|
||||
|
||||
* Upated XLS output: Only wrap if '\n' in cell.
|
||||
|
||||
|
||||
0.8.3 (2010-10-04)
|
||||
------------------
|
||||
|
||||
* Ability to append new column passing a callable
|
||||
as the value that will be applied to every row.
|
||||
|
||||
|
||||
0.8.2 (2010-10-04)
|
||||
------------------
|
||||
|
||||
* Added alignment wrapping to written cells.
|
||||
* Added separator support to XLS.
|
||||
|
||||
|
||||
0.8.1 (2010-09-28)
|
||||
------------------
|
||||
* Packaging Fix
|
||||
|
||||
|
||||
0.8.0 (2010-09-25)
|
||||
------------------
|
||||
* New format plugin system!
|
||||
* Imports! ELEGANT Imports!
|
||||
* Tests. Lots of tests.
|
||||
|
||||
|
||||
0.7.1 (2010-09-20)
|
||||
------------------
|
||||
|
||||
* Reverting methods back to properties.
|
||||
* Windows bug compenated in documentation.
|
||||
|
||||
|
||||
0.7.0 (2010-09-20)
|
||||
------------------
|
||||
|
||||
* Renamed DataBook Databook for consistiency.
|
||||
* Export properties changed to methods (XLS filename / StringIO bug).
|
||||
* Optional Dataset.xls(path='filename') support (for writing on windows).
|
||||
* Added utf-8 on the worksheet level.
|
||||
|
||||
|
||||
0.6.4 (2010-09-19)
|
||||
------------------
|
||||
|
||||
* Updated unicode export for XLS.
|
||||
* More exhaustive unit tests.
|
||||
|
||||
|
||||
0.6.3 (2010-09-14)
|
||||
------------------
|
||||
* Added Dataset.append() support for columns.
|
||||
|
||||
|
||||
0.6.2 (2010-09-13)
|
||||
------------------
|
||||
* Fixed Dataset.append() error on empty dataset.
|
||||
* Updated Dataset.headers property w/ validation.
|
||||
* Added Testing Fixtures.
|
||||
|
||||
0.6.1 (2010-09-12)
|
||||
------------------
|
||||
|
||||
* Packaging hotfixes.
|
||||
|
||||
|
||||
0.6.0 (2010-09-11)
|
||||
------------------
|
||||
|
||||
* Public Release.
|
||||
* Export Support for XLS, JSON, YAML, and CSV.
|
||||
* DataBook Export for XLS, JSON, and YAML.
|
||||
* Python Dict Property Support.
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
Copyright (c) 2010 Kenneth Reitz.
|
||||
Copyright 2016 Kenneth Reitz
|
||||
Copyright 2019 Jazzband
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
@@ -16,4 +17,4 @@ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
|
||||
THE SOFTWARE.
|
||||
THE SOFTWARE.
|
||||
|
||||
+6
-1
@@ -1 +1,6 @@
|
||||
include HISTORY.rst README.rst LICENSE AUTHORS
|
||||
recursive-include docs *
|
||||
recursive-include tests *
|
||||
include pytest.ini tox.ini .isort.cfg .coveragerc HISTORY.md README.md LICENSE AUTHORS
|
||||
prune docs/_build
|
||||
prune *.pyc
|
||||
prune __pycache__
|
||||
|
||||
@@ -1,136 +0,0 @@
|
||||
Tablib includes some vendorized python libraries: pyyaml, simplejson, and xlwt.
|
||||
|
||||
|
||||
|
||||
PyYAML License
|
||||
==============
|
||||
|
||||
Copyright (c) 2006 Kirill Simonov
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy of
|
||||
this software and associated documentation files (the "Software"), to deal in
|
||||
the Software without restriction, including without limitation the rights to
|
||||
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
|
||||
of the Software, and to permit persons to whom the Software is furnished to do
|
||||
so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
|
||||
|
||||
|
||||
SimpleJSON License
|
||||
==================
|
||||
|
||||
Copyright (c) 2006 Bob Ippolito
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy of
|
||||
this software and associated documentation files (the "Software"), to deal in
|
||||
the Software without restriction, including without limitation the rights to
|
||||
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
|
||||
of the Software, and to permit persons to whom the Software is furnished to do
|
||||
so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
|
||||
|
||||
|
||||
|
||||
XLWT License
|
||||
============
|
||||
|
||||
Portions copyright © 2007, Stephen John Machin, Lingfo Pty Ltd
|
||||
All rights reserved.
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions are met:
|
||||
|
||||
1. Redistributions of source code must retain the above copyright notice,
|
||||
this list of conditions and the following disclaimer.
|
||||
|
||||
2. Redistributions in binary form must reproduce the above copyright notice,
|
||||
this list of conditions and the following disclaimer in the documentation
|
||||
and/or other materials provided with the distribution.
|
||||
|
||||
3. None of the names of Stephen John Machin, Lingfo Pty Ltd and any
|
||||
contributors may be used to endorse or promote products derived from this
|
||||
software without specific prior written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
||||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
|
||||
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS
|
||||
BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||||
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||||
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||||
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||||
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
|
||||
THE POSSIBILITY OF SUCH DAMAGE.
|
||||
"""
|
||||
|
||||
"""
|
||||
Copyright (C) 2005 Roman V. Kiseliov
|
||||
All rights reserved.
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions
|
||||
are met:
|
||||
|
||||
1. Redistributions of source code must retain the above copyright
|
||||
notice, this list of conditions and the following disclaimer.
|
||||
|
||||
2. Redistributions in binary form must reproduce the above copyright
|
||||
notice, this list of conditions and the following disclaimer in
|
||||
the documentation and/or other materials provided with the
|
||||
distribution.
|
||||
|
||||
3. All advertising materials mentioning features or use of this
|
||||
software must display the following acknowledgment:
|
||||
"This product includes software developed by
|
||||
Roman V. Kiseliov <roman@kiseliov.ru>."
|
||||
|
||||
4. Redistributions of any form whatsoever must retain the following
|
||||
acknowledgment:
|
||||
"This product includes software developed by
|
||||
Roman V. Kiseliov <roman@kiseliov.ru>."
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY Roman V. Kiseliov ``AS IS'' AND ANY
|
||||
EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
||||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL Roman V. Kiseliov OR
|
||||
ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
||||
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
|
||||
NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
|
||||
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
|
||||
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||||
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
|
||||
OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
|
||||
Roman V. Kiseliov
|
||||
Russia
|
||||
Kursk
|
||||
Libknecht St., 4
|
||||
|
||||
+7(0712)56-09-83
|
||||
|
||||
<roman@kiseliov.ru>
|
||||
Subject: pyExcelerator
|
||||
@@ -0,0 +1,177 @@
|
||||
# Tablib: format-agnostic tabular dataset library
|
||||
|
||||
[](https://jazzband.co/)
|
||||
[](https://travis-ci.org/jazzband/tablib)
|
||||
[](https://codecov.io/gh/jazzband/tablib)
|
||||
|
||||
_____ ______ ___________ ______
|
||||
__ /_______ ____ /_ ___ /___(_)___ /_
|
||||
_ __/_ __ `/__ __ \__ / __ / __ __ \
|
||||
/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
|
||||
\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
|
||||
|
||||
|
||||
Tablib is a format-agnostic tabular dataset library, written in Python.
|
||||
|
||||
Output formats supported:
|
||||
|
||||
- Excel (Sets + Books)
|
||||
- JSON (Sets + Books)
|
||||
- YAML (Sets + Books)
|
||||
- Pandas DataFrames (Sets)
|
||||
- HTML (Sets)
|
||||
- Jira (Sets)
|
||||
- TSV (Sets)
|
||||
- ODS (Sets)
|
||||
- CSV (Sets)
|
||||
- DBF (Sets)
|
||||
|
||||
Note that tablib *purposefully* excludes XML support. It always will. (Note: This is a
|
||||
joke. Pull requests are welcome.)
|
||||
|
||||
|
||||
## Overview
|
||||
|
||||
`tablib.Dataset()`
|
||||
|
||||
A Dataset is a table of tabular data.
|
||||
It may or may not have a header row.
|
||||
They can be build and manipulated as raw Python datatypes (Lists of tuples|dictionaries).
|
||||
Datasets can be imported from JSON, YAML, DBF, and CSV;
|
||||
they can be exported to XLSX, XLS, ODS, JSON, YAML, DBF, CSV, TSV, and HTML.
|
||||
|
||||
`tablib.Databook()`
|
||||
|
||||
A Databook is a set of Datasets.
|
||||
The most common form of a Databook is an Excel file with multiple spreadsheets.
|
||||
Databooks can be imported from JSON and YAML;
|
||||
they can be exported to XLSX, XLS, ODS, JSON, and YAML.
|
||||
|
||||
|
||||
## Usage
|
||||
|
||||
Populate fresh data files:
|
||||
|
||||
```python
|
||||
headers = ('first_name', 'last_name')
|
||||
|
||||
data = [
|
||||
('John', 'Adams'),
|
||||
('George', 'Washington')
|
||||
]
|
||||
|
||||
data = tablib.Dataset(*data, headers=headers)
|
||||
```
|
||||
|
||||
Intelligently add new rows:
|
||||
|
||||
```python
|
||||
>>> data.append(('Henry', 'Ford'))
|
||||
```
|
||||
|
||||
Intelligently add new columns:
|
||||
|
||||
```python
|
||||
>>> data.append_col((90, 67, 83), header='age')
|
||||
```
|
||||
|
||||
Slice rows:
|
||||
|
||||
```python
|
||||
>>> print(data[:2])
|
||||
[('John', 'Adams', 90), ('George', 'Washington', 67)]
|
||||
```
|
||||
|
||||
Slice columns by header:
|
||||
|
||||
```python
|
||||
>>> print(data['first_name'])
|
||||
['John', 'George', 'Henry']
|
||||
```
|
||||
|
||||
Easily delete rows:
|
||||
|
||||
```python
|
||||
>>> del data[1]
|
||||
```
|
||||
|
||||
|
||||
## Exports
|
||||
|
||||
Drumroll please...........
|
||||
|
||||
### JSON!
|
||||
|
||||
```python
|
||||
>>> print(data.export('json'))
|
||||
[
|
||||
{
|
||||
"last_name": "Adams",
|
||||
"age": 90,
|
||||
"first_name": "John"
|
||||
},
|
||||
{
|
||||
"last_name": "Ford",
|
||||
"age": 83,
|
||||
"first_name": "Henry"
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
### YAML!
|
||||
|
||||
```python
|
||||
>>> print(data.export('yaml'))
|
||||
- {age: 90, first_name: John, last_name: Adams}
|
||||
- {age: 83, first_name: Henry, last_name: Ford}
|
||||
```
|
||||
|
||||
### CSV...
|
||||
|
||||
```python
|
||||
>>> print(data.export('csv'))
|
||||
first_name,last_name,age
|
||||
John,Adams,90
|
||||
Henry,Ford,83
|
||||
```
|
||||
|
||||
### EXCEL!
|
||||
|
||||
```python
|
||||
>>> with open('people.xls', 'wb') as f:
|
||||
... f.write(data.export('xls'))
|
||||
```
|
||||
|
||||
### DBF!
|
||||
|
||||
```python
|
||||
>>> with open('people.dbf', 'wb') as f:
|
||||
... f.write(data.export('dbf'))
|
||||
```
|
||||
|
||||
### Pandas DataFrame!
|
||||
|
||||
```python
|
||||
>>> print(data.export('df')):
|
||||
first_name last_name age
|
||||
0 John Adams 90
|
||||
1 Henry Ford 83
|
||||
```
|
||||
|
||||
It's that easy.
|
||||
|
||||
|
||||
## Installation
|
||||
|
||||
To install tablib, simply:
|
||||
|
||||
```console
|
||||
$ pip install tablib[pandas]
|
||||
```
|
||||
|
||||
Make sure to check out [Tablib on PyPI](https://pypi.org/project/tablib/)!
|
||||
|
||||
|
||||
## Contribute
|
||||
|
||||
Please see the [contributing guide](https://github.com/jazzband/tablib/blob/master/.github/CONTRIBUTING.md).
|
||||
-188
@@ -1,188 +0,0 @@
|
||||
Tablib: format-agnostic tabular dataset library
|
||||
===============================================
|
||||
|
||||
::
|
||||
|
||||
_____ ______ ___________ ______
|
||||
__ /_______ ____ /_ ___ /___(_)___ /_
|
||||
_ __/_ __ `/__ __ \__ / __ / __ __ \
|
||||
/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
|
||||
\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
|
||||
|
||||
|
||||
|
||||
Tablib is a format-agnostic tabular dataset library, written in Python.
|
||||
|
||||
Output formats supported:
|
||||
|
||||
- Excel (Sets + Books)
|
||||
- JSON (Sets + Books)
|
||||
- YAML (Sets + Books)
|
||||
- CSV (Sets)
|
||||
|
||||
Import formats supported:
|
||||
|
||||
- JSON (Sets + Books)
|
||||
- YAML (Sets + Books)
|
||||
- CSV (Sets)
|
||||
|
||||
Note that tablib *purposefully* excludes XML support. It always will.
|
||||
|
||||
Overview
|
||||
--------
|
||||
|
||||
`tablib.Dataset()`
|
||||
A Dataset is a table of tabular data. It may or may not have a header row. They can be build and maniuplated as raw Python datatypes (Lists of tuples|dictonaries). Datasets can be imported from JSON, YAML, and CSV; they can be exported to Excel (XLS), JSON, YAML, and CSV.
|
||||
|
||||
`tablib.Databook()`
|
||||
A Databook is a set of Datasets. The most common form of a Databook is an Excel file with multiple spreadsheets. Databooks can be imported from JSON and YAML; they can be exported to Excel (XLS), JSON, and YAML.
|
||||
|
||||
Usage
|
||||
-----
|
||||
|
||||
|
||||
Populate fresh data files: ::
|
||||
|
||||
headers = ('first_name', 'last_name')
|
||||
|
||||
data = [
|
||||
('John', 'Adams'),
|
||||
('George', 'Washington')
|
||||
]
|
||||
|
||||
data = tablib.Dataset(*data, headers=headers)
|
||||
|
||||
|
||||
Intelligently add new rows: ::
|
||||
|
||||
>>> data.append(('Henry', 'Ford'))
|
||||
|
||||
Intelligently add new columns: ::
|
||||
|
||||
>>> data.append(col=('age', 90, 67, 83))
|
||||
|
||||
Slice rows: ::
|
||||
|
||||
>>> print data[:2]
|
||||
[('John', 'Adams', 90), ('George', 'Washington', 67)]
|
||||
|
||||
|
||||
Slice columns by header: ::
|
||||
|
||||
>>> print data['first_name']
|
||||
['John', 'George', 'Henry']
|
||||
|
||||
Easily delete rows: ::
|
||||
|
||||
>>> del data[1]
|
||||
|
||||
Exports
|
||||
-------
|
||||
|
||||
Drumroll please...........
|
||||
|
||||
JSON!
|
||||
+++++
|
||||
::
|
||||
|
||||
>>> print data.json
|
||||
[
|
||||
{
|
||||
"last_name": "Adams",
|
||||
"age": 90,
|
||||
"first_name": "John"
|
||||
},
|
||||
{
|
||||
"last_name": "Ford",
|
||||
"age": 83,
|
||||
"first_name": "Henry"
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
YAML!
|
||||
+++++
|
||||
::
|
||||
|
||||
>>> print data.yaml
|
||||
- {age: 90, first_name: John, last_name: Adams}
|
||||
- {age: 83, first_name: Henry, last_name: Ford}
|
||||
|
||||
CSV...
|
||||
++++++
|
||||
::
|
||||
|
||||
>>> print data.csv
|
||||
first_name,last_name,age
|
||||
John,Adams,90
|
||||
Henry,Ford,83
|
||||
|
||||
EXCEL!
|
||||
++++++
|
||||
::
|
||||
|
||||
>>> open('people.xls', 'wb').write(data.xls)
|
||||
|
||||
It's that easy.
|
||||
|
||||
Imports!
|
||||
--------
|
||||
|
||||
JSON
|
||||
++++
|
||||
|
||||
::
|
||||
|
||||
>>> data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
|
||||
>>> print data[0]
|
||||
('John', 'Adams', 90)
|
||||
|
||||
|
||||
YAML
|
||||
++++
|
||||
::
|
||||
|
||||
>>> data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
|
||||
>>> print data[0]
|
||||
('John', 'Adams', 90)
|
||||
|
||||
CSV
|
||||
+++
|
||||
::
|
||||
|
||||
>>> data.csv = 'age, first_name, last_name\n90, John, Adams'
|
||||
>>> print data[0]
|
||||
('John', 'Adams', 90)
|
||||
|
||||
>>> print data.yaml
|
||||
- {age: 90, first_name: John, last_name: Adams}
|
||||
|
||||
|
||||
|
||||
Installation
|
||||
------------
|
||||
|
||||
To install tablib, simply: ::
|
||||
|
||||
$ pip install tablib
|
||||
|
||||
Or, if you absolutely must: ::
|
||||
|
||||
$ easy_install tablib
|
||||
|
||||
|
||||
Contribute
|
||||
----------
|
||||
|
||||
If you'd like to contribute, simply fork `the repository`_, commit your changes to the **develop** branch (or branch off of it), and send a pull request. Make sure you add yourself to AUTHORS_.
|
||||
|
||||
|
||||
Roadmap
|
||||
-------
|
||||
- Release CLI Interface
|
||||
- Auto-detect import format
|
||||
- Add possible other exports (SQL?)
|
||||
- Ability to assign types to rows (set, regex=, &c.)
|
||||
|
||||
.. _`the repository`: http://github.com/kennethreitz/tablib
|
||||
.. _AUTHORS: http://github.com/kennethreitz/tablib/blob/master/AUTHORS
|
||||
@@ -0,0 +1,18 @@
|
||||
[[source]]
|
||||
name = "pypi"
|
||||
url = "https://pypi.org/simple"
|
||||
verify_ssl = true
|
||||
|
||||
[dev-packages]
|
||||
|
||||
[packages]
|
||||
"backports.csv" = "*"
|
||||
odfpy = "*"
|
||||
openpyxl = ">=2.4.0"
|
||||
pandas = "*"
|
||||
xlrd = "*"
|
||||
xlwt = "*"
|
||||
PyYAML = "*"
|
||||
|
||||
[requires]
|
||||
python_version = "3.6"
|
||||
Vendored
+11
@@ -0,0 +1,11 @@
|
||||
<h3><a href="https://tablib.readthedocs.io">About Tablib</a></h3>
|
||||
<p>
|
||||
Tablib is an MIT Licensed format-agnostic tabular dataset library, written in Python. It allows you to import, export, and manipulate tabular data sets. Advanced features include, segregation, dynamic columns, tags & filtering, and seamless format import & export.
|
||||
</p>
|
||||
<h3>Useful Links</h3>
|
||||
<ul>
|
||||
<li><a href="https://tablib.readthedocs.io">The Tablib Website</a></li>
|
||||
<li><a href="https://pypi.org/project/tablib">Tablib @ PyPI</a></li>
|
||||
<li><a href="https://github.com/jazzband/tablib">Tablib @ GitHub</a></li>
|
||||
<li><a href="https://github.com/jazzband/tablib/issues">Issue Tracker</a></li>
|
||||
</ul>
|
||||
Vendored
+4
@@ -0,0 +1,4 @@
|
||||
<h3><a href="https://tablib.readthedocs.io">About Tablib</a></h3>
|
||||
<p>
|
||||
Tablib is an MIT Licensed format-agnostic tabular dataset library, written in Python. It allows you to import, export, and manipulate tabular data sets. Advanced features include, segregation, dynamic columns, tags & filtering, and seamless format import & export.
|
||||
</p>
|
||||
@@ -1,3 +0,0 @@
|
||||
*.pyc
|
||||
*.pyo
|
||||
.DS_Store
|
||||
Vendored
-45
@@ -1,45 +0,0 @@
|
||||
Modifications:
|
||||
|
||||
Copyright (c) 2010 Kenneth Reitz.
|
||||
|
||||
|
||||
Original Project:
|
||||
|
||||
Copyright (c) 2010 by Armin Ronacher.
|
||||
|
||||
|
||||
Some rights reserved.
|
||||
|
||||
Redistribution and use in source and binary forms of the theme, with or
|
||||
without modification, are permitted provided that the following conditions
|
||||
are met:
|
||||
|
||||
* Redistributions of source code must retain the above copyright
|
||||
notice, this list of conditions and the following disclaimer.
|
||||
|
||||
* Redistributions in binary form must reproduce the above
|
||||
copyright notice, this list of conditions and the following
|
||||
disclaimer in the documentation and/or other materials provided
|
||||
with the distribution.
|
||||
|
||||
* The names of the contributors may not be used to endorse or
|
||||
promote products derived from this software without specific
|
||||
prior written permission.
|
||||
|
||||
We kindly ask you to only use these themes in an unmodified manner just
|
||||
for Flask and Flask-related products, not for unrelated projects. If you
|
||||
like the visual style and want to use it for your own projects, please
|
||||
consider making some larger changes to the themes (such as changing
|
||||
font faces, sizes, colors or margins).
|
||||
|
||||
THIS THEME IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
||||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
||||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
|
||||
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
||||
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||||
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||||
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||||
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||||
ARISING IN ANY WAY OUT OF THE USE OF THIS THEME, EVEN IF ADVISED OF THE
|
||||
POSSIBILITY OF SUCH DAMAGE.
|
||||
Vendored
-25
@@ -1,25 +0,0 @@
|
||||
krTheme Sphinx Style
|
||||
====================
|
||||
|
||||
This repository contains sphinx styles Kenneth Reitz uses in most of
|
||||
his projects. It is a drivative of Mitsuhiko's themes for Flask and Flask related
|
||||
projects. To use this style in your Sphinx documentation, follow
|
||||
this guide:
|
||||
|
||||
1. put this folder as _themes into your docs folder. Alternatively
|
||||
you can also use git submodules to check out the contents there.
|
||||
|
||||
2. add this to your conf.py: ::
|
||||
|
||||
sys.path.append(os.path.abspath('_themes'))
|
||||
html_theme_path = ['_themes']
|
||||
html_theme = 'flask'
|
||||
|
||||
The following themes exist:
|
||||
|
||||
**kr**
|
||||
the standard flask documentation theme for large projects
|
||||
|
||||
**kr_small**
|
||||
small one-page theme. Intended to be used by very small addon libraries.
|
||||
|
||||
Vendored
-86
@@ -1,86 +0,0 @@
|
||||
# flasky extensions. flasky pygments style based on tango style
|
||||
from pygments.style import Style
|
||||
from pygments.token import Keyword, Name, Comment, String, Error, \
|
||||
Number, Operator, Generic, Whitespace, Punctuation, Other, Literal
|
||||
|
||||
|
||||
class FlaskyStyle(Style):
|
||||
background_color = "#f8f8f8"
|
||||
default_style = ""
|
||||
|
||||
styles = {
|
||||
# No corresponding class for the following:
|
||||
#Text: "", # class: ''
|
||||
Whitespace: "underline #f8f8f8", # class: 'w'
|
||||
Error: "#a40000 border:#ef2929", # class: 'err'
|
||||
Other: "#000000", # class 'x'
|
||||
|
||||
Comment: "italic #8f5902", # class: 'c'
|
||||
Comment.Preproc: "noitalic", # class: 'cp'
|
||||
|
||||
Keyword: "bold #004461", # class: 'k'
|
||||
Keyword.Constant: "bold #004461", # class: 'kc'
|
||||
Keyword.Declaration: "bold #004461", # class: 'kd'
|
||||
Keyword.Namespace: "bold #004461", # class: 'kn'
|
||||
Keyword.Pseudo: "bold #004461", # class: 'kp'
|
||||
Keyword.Reserved: "bold #004461", # class: 'kr'
|
||||
Keyword.Type: "bold #004461", # class: 'kt'
|
||||
|
||||
Operator: "#582800", # class: 'o'
|
||||
Operator.Word: "bold #004461", # class: 'ow' - like keywords
|
||||
|
||||
Punctuation: "bold #000000", # class: 'p'
|
||||
|
||||
# because special names such as Name.Class, Name.Function, etc.
|
||||
# are not recognized as such later in the parsing, we choose them
|
||||
# to look the same as ordinary variables.
|
||||
Name: "#000000", # class: 'n'
|
||||
Name.Attribute: "#c4a000", # class: 'na' - to be revised
|
||||
Name.Builtin: "#004461", # class: 'nb'
|
||||
Name.Builtin.Pseudo: "#3465a4", # class: 'bp'
|
||||
Name.Class: "#000000", # class: 'nc' - to be revised
|
||||
Name.Constant: "#000000", # class: 'no' - to be revised
|
||||
Name.Decorator: "#888", # class: 'nd' - to be revised
|
||||
Name.Entity: "#ce5c00", # class: 'ni'
|
||||
Name.Exception: "bold #cc0000", # class: 'ne'
|
||||
Name.Function: "#000000", # class: 'nf'
|
||||
Name.Property: "#000000", # class: 'py'
|
||||
Name.Label: "#f57900", # class: 'nl'
|
||||
Name.Namespace: "#000000", # class: 'nn' - to be revised
|
||||
Name.Other: "#000000", # class: 'nx'
|
||||
Name.Tag: "bold #004461", # class: 'nt' - like a keyword
|
||||
Name.Variable: "#000000", # class: 'nv' - to be revised
|
||||
Name.Variable.Class: "#000000", # class: 'vc' - to be revised
|
||||
Name.Variable.Global: "#000000", # class: 'vg' - to be revised
|
||||
Name.Variable.Instance: "#000000", # class: 'vi' - to be revised
|
||||
|
||||
Number: "#990000", # class: 'm'
|
||||
|
||||
Literal: "#000000", # class: 'l'
|
||||
Literal.Date: "#000000", # class: 'ld'
|
||||
|
||||
String: "#4e9a06", # class: 's'
|
||||
String.Backtick: "#4e9a06", # class: 'sb'
|
||||
String.Char: "#4e9a06", # class: 'sc'
|
||||
String.Doc: "italic #8f5902", # class: 'sd' - like a comment
|
||||
String.Double: "#4e9a06", # class: 's2'
|
||||
String.Escape: "#4e9a06", # class: 'se'
|
||||
String.Heredoc: "#4e9a06", # class: 'sh'
|
||||
String.Interpol: "#4e9a06", # class: 'si'
|
||||
String.Other: "#4e9a06", # class: 'sx'
|
||||
String.Regex: "#4e9a06", # class: 'sr'
|
||||
String.Single: "#4e9a06", # class: 's1'
|
||||
String.Symbol: "#4e9a06", # class: 'ss'
|
||||
|
||||
Generic: "#000000", # class: 'g'
|
||||
Generic.Deleted: "#a40000", # class: 'gd'
|
||||
Generic.Emph: "italic #000000", # class: 'ge'
|
||||
Generic.Error: "#ef2929", # class: 'gr'
|
||||
Generic.Heading: "bold #000080", # class: 'gh'
|
||||
Generic.Inserted: "#00A000", # class: 'gi'
|
||||
Generic.Output: "#888", # class: 'go'
|
||||
Generic.Prompt: "#745334", # class: 'gp'
|
||||
Generic.Strong: "bold #000000", # class: 'gs'
|
||||
Generic.Subheading: "bold #800080", # class: 'gu'
|
||||
Generic.Traceback: "bold #a40000", # class: 'gt'
|
||||
}
|
||||
Vendored
-16
@@ -1,16 +0,0 @@
|
||||
{%- extends "basic/layout.html" %}
|
||||
{%- block extrahead %}
|
||||
{{ super() }}
|
||||
{% if theme_touch_icon %}
|
||||
<link rel="apple-touch-icon" href="{{ pathto('_static/' ~ theme_touch_icon, 1) }}" />
|
||||
{% endif %}
|
||||
<link media="only screen and (max-device-width: 480px)" href="{{
|
||||
pathto('_static/small_flask.css', 1) }}" type= "text/css" rel="stylesheet" />
|
||||
{% endblock %}
|
||||
{%- block relbar2 %}{% endblock %}
|
||||
{%- block footer %}
|
||||
<div class="footer">
|
||||
© Copyright {{ copyright }}.
|
||||
Created using <a href="http://sphinx.pocoo.org/">Sphinx</a>.
|
||||
</div>
|
||||
{%- endblock %}
|
||||
Vendored
-19
@@ -1,19 +0,0 @@
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="{{ pathto(master_doc) }}">Documentation overview</a><ul>
|
||||
{%- for parent in parents %}
|
||||
<li><a href="{{ parent.link|e }}">{{ parent.title }}</a><ul>
|
||||
{%- endfor %}
|
||||
{%- if prev %}
|
||||
<li>Previous: <a href="{{ prev.link|e }}" title="{{ _('previous chapter')
|
||||
}}">{{ prev.title }}</a></li>
|
||||
{%- endif %}
|
||||
{%- if next %}
|
||||
<li>Next: <a href="{{ next.link|e }}" title="{{ _('next chapter')
|
||||
}}">{{ next.title }}</a></li>
|
||||
{%- endif %}
|
||||
{%- for parent in parents %}
|
||||
</ul></li>
|
||||
{%- endfor %}
|
||||
</ul></li>
|
||||
</ul>
|
||||
Vendored
-387
@@ -1,387 +0,0 @@
|
||||
/*
|
||||
* flasky.css_t
|
||||
* ~~~~~~~~~~~~
|
||||
*
|
||||
* :copyright: Copyright 2010 by Armin Ronacher. Modifications by Kenneth Reitz.
|
||||
* :license: Flask Design License, see LICENSE for details.
|
||||
*/
|
||||
|
||||
{% set page_width = '940px' %}
|
||||
{% set sidebar_width = '220px' %}
|
||||
|
||||
@import url("basic.css");
|
||||
|
||||
/* -- page layout ----------------------------------------------------------- */
|
||||
|
||||
body {
|
||||
font-family: 'goudy old style', 'minion pro', 'bell mt', Georgia, 'Hiragino Mincho Pro';
|
||||
font-size: 17px;
|
||||
background-color: white;
|
||||
color: #000;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.document {
|
||||
width: {{ page_width }};
|
||||
margin: 30px auto 0 auto;
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
float: left;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin: 0 0 0 {{ sidebar_width }};
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
width: {{ sidebar_width }};
|
||||
}
|
||||
|
||||
hr {
|
||||
border: 1px solid #B1B4B6;
|
||||
}
|
||||
|
||||
div.body {
|
||||
background-color: #ffffff;
|
||||
color: #3E4349;
|
||||
padding: 0 30px 0 30px;
|
||||
}
|
||||
|
||||
img.floatingflask {
|
||||
padding: 0 0 10px 10px;
|
||||
float: right;
|
||||
}
|
||||
|
||||
div.footer {
|
||||
width: {{ page_width }};
|
||||
margin: 20px auto 30px auto;
|
||||
font-size: 14px;
|
||||
color: #888;
|
||||
text-align: right;
|
||||
}
|
||||
|
||||
div.footer a {
|
||||
color: #888;
|
||||
}
|
||||
|
||||
div.related {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.sphinxsidebar a {
|
||||
color: #444;
|
||||
text-decoration: none;
|
||||
border-bottom: 1px dotted #999;
|
||||
}
|
||||
|
||||
div.sphinxsidebar a:hover {
|
||||
border-bottom: 1px solid #999;
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
font-size: 14px;
|
||||
line-height: 1.5;
|
||||
}
|
||||
|
||||
div.sphinxsidebarwrapper {
|
||||
padding: 18px 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebarwrapper p.logo {
|
||||
padding: 0 0 20px 0;
|
||||
margin: 0;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
div.sphinxsidebar h3,
|
||||
div.sphinxsidebar h4 {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
color: #444;
|
||||
font-size: 24px;
|
||||
font-weight: normal;
|
||||
margin: 0 0 5px 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.sphinxsidebar h4 {
|
||||
font-size: 20px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar h3 a {
|
||||
color: #444;
|
||||
}
|
||||
|
||||
div.sphinxsidebar p.logo a,
|
||||
div.sphinxsidebar h3 a,
|
||||
div.sphinxsidebar p.logo a:hover,
|
||||
div.sphinxsidebar h3 a:hover {
|
||||
border: none;
|
||||
}
|
||||
|
||||
div.sphinxsidebar p {
|
||||
color: #555;
|
||||
margin: 10px 0;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul {
|
||||
margin: 10px 0;
|
||||
padding: 0;
|
||||
color: #000;
|
||||
}
|
||||
|
||||
div.sphinxsidebar input {
|
||||
border: 1px solid #ccc;
|
||||
font-family: 'Georgia', serif;
|
||||
font-size: 1em;
|
||||
}
|
||||
|
||||
/* -- body styles ----------------------------------------------------------- */
|
||||
|
||||
a {
|
||||
color: #004B6B;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
a:hover {
|
||||
color: #6D4100;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
div.body h1,
|
||||
div.body h2,
|
||||
div.body h3,
|
||||
div.body h4,
|
||||
div.body h5,
|
||||
div.body h6 {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
font-weight: normal;
|
||||
margin: 30px 0px 10px 0px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.body h1 { margin-top: 0; padding-top: 0; font-size: 240%; }
|
||||
div.body h2 { font-size: 180%; }
|
||||
div.body h3 { font-size: 150%; }
|
||||
div.body h4 { font-size: 130%; }
|
||||
div.body h5 { font-size: 100%; }
|
||||
div.body h6 { font-size: 100%; }
|
||||
|
||||
a.headerlink {
|
||||
color: #ddd;
|
||||
padding: 0 4px;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
a.headerlink:hover {
|
||||
color: #444;
|
||||
background: #eaeaea;
|
||||
}
|
||||
|
||||
div.body p, div.body dd, div.body li {
|
||||
line-height: 1.4em;
|
||||
}
|
||||
|
||||
div.admonition {
|
||||
background: #fafafa;
|
||||
margin: 20px -30px;
|
||||
padding: 10px 30px;
|
||||
border-top: 1px solid #ccc;
|
||||
border-bottom: 1px solid #ccc;
|
||||
}
|
||||
|
||||
div.admonition tt.xref, div.admonition a tt {
|
||||
border-bottom: 1px solid #fafafa;
|
||||
}
|
||||
|
||||
dd div.admonition {
|
||||
margin-left: -60px;
|
||||
padding-left: 60px;
|
||||
}
|
||||
|
||||
div.admonition p.admonition-title {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
font-weight: normal;
|
||||
font-size: 24px;
|
||||
margin: 0 0 10px 0;
|
||||
padding: 0;
|
||||
line-height: 1;
|
||||
}
|
||||
|
||||
div.admonition p.last {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.highlight {
|
||||
background-color: white;
|
||||
}
|
||||
|
||||
dt:target, .highlight {
|
||||
background: #FAF3E8;
|
||||
}
|
||||
|
||||
div.note {
|
||||
background-color: #eee;
|
||||
border: 1px solid #ccc;
|
||||
}
|
||||
|
||||
div.seealso {
|
||||
background-color: #ffc;
|
||||
border: 1px solid #ff6;
|
||||
}
|
||||
|
||||
div.topic {
|
||||
background-color: #eee;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
p.admonition-title:after {
|
||||
content: ":";
|
||||
}
|
||||
|
||||
pre, tt {
|
||||
font-family: 'Consolas', 'Menlo', 'Deja Vu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
}
|
||||
|
||||
tt.descname, tt.descclassname {
|
||||
font-size: 0.95em;
|
||||
}
|
||||
|
||||
tt.descname {
|
||||
padding-right: 0.08em;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
-moz-box-shadow: 2px 2px 4px #eee;
|
||||
-webkit-box-shadow: 2px 2px 4px #eee;
|
||||
box-shadow: 2px 2px 4px #eee;
|
||||
}
|
||||
|
||||
table.docutils {
|
||||
border: 1px solid #888;
|
||||
-moz-box-shadow: 2px 2px 4px #eee;
|
||||
-webkit-box-shadow: 2px 2px 4px #eee;
|
||||
box-shadow: 2px 2px 4px #eee;
|
||||
}
|
||||
|
||||
table.docutils td, table.docutils th {
|
||||
border: 1px solid #888;
|
||||
padding: 0.25em 0.7em;
|
||||
}
|
||||
|
||||
table.field-list, table.footnote {
|
||||
border: none;
|
||||
-moz-box-shadow: none;
|
||||
-webkit-box-shadow: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
table.footnote {
|
||||
margin: 15px 0;
|
||||
width: 100%;
|
||||
border: 1px solid #eee;
|
||||
background: #fdfdfd;
|
||||
font-size: 0.9em;
|
||||
}
|
||||
|
||||
table.footnote + table.footnote {
|
||||
margin-top: -15px;
|
||||
border-top: none;
|
||||
}
|
||||
|
||||
table.field-list th {
|
||||
padding: 0 0.8em 0 0;
|
||||
}
|
||||
|
||||
table.field-list td {
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
table.footnote td.label {
|
||||
width: 0px;
|
||||
padding: 0.3em 0 0.3em 0.5em;
|
||||
}
|
||||
|
||||
table.footnote td {
|
||||
padding: 0.3em 0.5em;
|
||||
}
|
||||
|
||||
dl {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
dl dd {
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
blockquote {
|
||||
margin: 0 0 0 30px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
ul, ol {
|
||||
margin: 10px 0 10px 30px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
pre {
|
||||
background: #eee;
|
||||
padding: 7px 30px;
|
||||
margin: 15px -30px;
|
||||
line-height: 1.3em;
|
||||
}
|
||||
|
||||
dl pre, blockquote pre, li pre {
|
||||
margin-left: -60px;
|
||||
padding-left: 60px;
|
||||
}
|
||||
|
||||
dl dl pre {
|
||||
margin-left: -90px;
|
||||
padding-left: 90px;
|
||||
}
|
||||
|
||||
tt {
|
||||
background-color: #ecf0f3;
|
||||
color: #222;
|
||||
/* padding: 1px 2px; */
|
||||
}
|
||||
|
||||
tt.xref, a tt {
|
||||
background-color: #FBFBFB;
|
||||
border-bottom: 1px solid white;
|
||||
}
|
||||
|
||||
a.reference {
|
||||
text-decoration: none;
|
||||
border-bottom: 1px dotted #004B6B;
|
||||
}
|
||||
|
||||
a.reference:hover {
|
||||
border-bottom: 1px solid #6D4100;
|
||||
}
|
||||
|
||||
a.footnote-reference {
|
||||
text-decoration: none;
|
||||
font-size: 0.7em;
|
||||
vertical-align: top;
|
||||
border-bottom: 1px dotted #004B6B;
|
||||
}
|
||||
|
||||
a.footnote-reference:hover {
|
||||
border-bottom: 1px solid #6D4100;
|
||||
}
|
||||
|
||||
a:hover tt {
|
||||
background: #EEE;
|
||||
}
|
||||
-70
@@ -1,70 +0,0 @@
|
||||
/*
|
||||
* small_flask.css_t
|
||||
* ~~~~~~~~~~~~~~~~~
|
||||
*
|
||||
* :copyright: Copyright 2010 by Armin Ronacher.
|
||||
* :license: Flask Design License, see LICENSE for details.
|
||||
*/
|
||||
|
||||
body {
|
||||
margin: 0;
|
||||
padding: 20px 30px;
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
float: none;
|
||||
background: white;
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
display: block;
|
||||
float: none;
|
||||
width: 102.5%;
|
||||
margin: 50px -30px -20px -30px;
|
||||
padding: 10px 20px;
|
||||
background: #333;
|
||||
color: white;
|
||||
}
|
||||
|
||||
div.sphinxsidebar h3, div.sphinxsidebar h4, div.sphinxsidebar p,
|
||||
div.sphinxsidebar h3 a {
|
||||
color: white;
|
||||
}
|
||||
|
||||
div.sphinxsidebar a {
|
||||
color: #aaa;
|
||||
}
|
||||
|
||||
div.sphinxsidebar p.logo {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.document {
|
||||
width: 100%;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
div.related {
|
||||
display: block;
|
||||
margin: 0;
|
||||
padding: 10px 0 20px 0;
|
||||
}
|
||||
|
||||
div.related ul,
|
||||
div.related ul li {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.footer {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
div.body {
|
||||
min-height: 0;
|
||||
padding: 0;
|
||||
}
|
||||
Vendored
-7
@@ -1,7 +0,0 @@
|
||||
[theme]
|
||||
inherit = basic
|
||||
stylesheet = flasky.css
|
||||
pygments_style = flask_theme_support.FlaskyStyle
|
||||
|
||||
[options]
|
||||
touch_icon =
|
||||
Vendored
-22
@@ -1,22 +0,0 @@
|
||||
{% extends "basic/layout.html" %}
|
||||
{% block header %}
|
||||
{{ super() }}
|
||||
{% if pagename == 'index' %}
|
||||
<div class=indexwrapper>
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
{% block footer %}
|
||||
{% if pagename == 'index' %}
|
||||
</div>
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
{# do not display relbars #}
|
||||
{% block relbar1 %}{% endblock %}
|
||||
{% block relbar2 %}
|
||||
{% if theme_github_fork %}
|
||||
<a href="http://github.com/{{ theme_github_fork }}"><img style="position: fixed; top: 0; right: 0; border: 0;"
|
||||
src="http://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png" alt="Fork me on GitHub" /></a>
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
{% block sidebar1 %}{% endblock %}
|
||||
{% block sidebar2 %}{% endblock %}
|
||||
-287
@@ -1,287 +0,0 @@
|
||||
/*
|
||||
* flasky.css_t
|
||||
* ~~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx stylesheet -- flasky theme based on nature theme.
|
||||
*
|
||||
* :copyright: Copyright 2007-2010 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
@import url("basic.css");
|
||||
|
||||
/* -- page layout ----------------------------------------------------------- */
|
||||
|
||||
body {
|
||||
font-family: 'Georgia', serif;
|
||||
font-size: 17px;
|
||||
color: #000;
|
||||
background: white;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
float: left;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin: 40px auto 0 auto;
|
||||
width: 700px;
|
||||
}
|
||||
|
||||
hr {
|
||||
border: 1px solid #B1B4B6;
|
||||
}
|
||||
|
||||
div.body {
|
||||
background-color: #ffffff;
|
||||
color: #3E4349;
|
||||
padding: 0 30px 30px 30px;
|
||||
}
|
||||
|
||||
img.floatingflask {
|
||||
padding: 0 0 10px 10px;
|
||||
float: right;
|
||||
}
|
||||
|
||||
div.footer {
|
||||
text-align: right;
|
||||
color: #888;
|
||||
padding: 10px;
|
||||
font-size: 14px;
|
||||
width: 650px;
|
||||
margin: 0 auto 40px auto;
|
||||
}
|
||||
|
||||
div.footer a {
|
||||
color: #888;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
div.related {
|
||||
line-height: 32px;
|
||||
color: #888;
|
||||
}
|
||||
|
||||
div.related ul {
|
||||
padding: 0 0 0 10px;
|
||||
}
|
||||
|
||||
div.related a {
|
||||
color: #444;
|
||||
}
|
||||
|
||||
/* -- body styles ----------------------------------------------------------- */
|
||||
|
||||
a {
|
||||
color: #004B6B;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
a:hover {
|
||||
color: #6D4100;
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
div.body {
|
||||
padding-bottom: 40px; /* saved for footer */
|
||||
}
|
||||
|
||||
div.body h1,
|
||||
div.body h2,
|
||||
div.body h3,
|
||||
div.body h4,
|
||||
div.body h5,
|
||||
div.body h6 {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
font-weight: normal;
|
||||
margin: 30px 0px 10px 0px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
{% if theme_index_logo %}
|
||||
div.indexwrapper h1 {
|
||||
text-indent: -999999px;
|
||||
background: url({{ theme_index_logo }}) no-repeat center center;
|
||||
height: {{ theme_index_logo_height }};
|
||||
}
|
||||
{% endif %}
|
||||
|
||||
div.body h2 { font-size: 180%; }
|
||||
div.body h3 { font-size: 150%; }
|
||||
div.body h4 { font-size: 130%; }
|
||||
div.body h5 { font-size: 100%; }
|
||||
div.body h6 { font-size: 100%; }
|
||||
|
||||
a.headerlink {
|
||||
color: white;
|
||||
padding: 0 4px;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
a.headerlink:hover {
|
||||
color: #444;
|
||||
background: #eaeaea;
|
||||
}
|
||||
|
||||
div.body p, div.body dd, div.body li {
|
||||
line-height: 1.4em;
|
||||
}
|
||||
|
||||
div.admonition {
|
||||
background: #fafafa;
|
||||
margin: 20px -30px;
|
||||
padding: 10px 30px;
|
||||
border-top: 1px solid #ccc;
|
||||
border-bottom: 1px solid #ccc;
|
||||
}
|
||||
|
||||
div.admonition p.admonition-title {
|
||||
font-family: 'Garamond', 'Georgia', serif;
|
||||
font-weight: normal;
|
||||
font-size: 24px;
|
||||
margin: 0 0 10px 0;
|
||||
padding: 0;
|
||||
line-height: 1;
|
||||
}
|
||||
|
||||
div.admonition p.last {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.highlight{
|
||||
background-color: white;
|
||||
}
|
||||
|
||||
dt:target, .highlight {
|
||||
background: #FAF3E8;
|
||||
}
|
||||
|
||||
div.note {
|
||||
background-color: #eee;
|
||||
border: 1px solid #ccc;
|
||||
}
|
||||
|
||||
div.seealso {
|
||||
background-color: #ffc;
|
||||
border: 1px solid #ff6;
|
||||
}
|
||||
|
||||
div.topic {
|
||||
background-color: #eee;
|
||||
}
|
||||
|
||||
div.warning {
|
||||
background-color: #ffe4e4;
|
||||
border: 1px solid #f66;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
p.admonition-title:after {
|
||||
content: ":";
|
||||
}
|
||||
|
||||
pre, tt {
|
||||
font-family: 'Consolas', 'Menlo', 'Deja Vu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
|
||||
font-size: 0.85em;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
}
|
||||
|
||||
tt.descname, tt.descclassname {
|
||||
font-size: 0.95em;
|
||||
}
|
||||
|
||||
tt.descname {
|
||||
padding-right: 0.08em;
|
||||
}
|
||||
|
||||
img.screenshot {
|
||||
-moz-box-shadow: 2px 2px 4px #eee;
|
||||
-webkit-box-shadow: 2px 2px 4px #eee;
|
||||
box-shadow: 2px 2px 4px #eee;
|
||||
}
|
||||
|
||||
table.docutils {
|
||||
border: 1px solid #888;
|
||||
-moz-box-shadow: 2px 2px 4px #eee;
|
||||
-webkit-box-shadow: 2px 2px 4px #eee;
|
||||
box-shadow: 2px 2px 4px #eee;
|
||||
}
|
||||
|
||||
table.docutils td, table.docutils th {
|
||||
border: 1px solid #888;
|
||||
padding: 0.25em 0.7em;
|
||||
}
|
||||
|
||||
table.field-list, table.footnote {
|
||||
border: none;
|
||||
-moz-box-shadow: none;
|
||||
-webkit-box-shadow: none;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
table.footnote {
|
||||
margin: 15px 0;
|
||||
width: 100%;
|
||||
border: 1px solid #eee;
|
||||
}
|
||||
|
||||
table.field-list th {
|
||||
padding: 0 0.8em 0 0;
|
||||
}
|
||||
|
||||
table.field-list td {
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
table.footnote td {
|
||||
padding: 0.5em;
|
||||
}
|
||||
|
||||
dl {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
dl dd {
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
pre {
|
||||
padding: 0;
|
||||
margin: 15px -30px;
|
||||
padding: 8px;
|
||||
line-height: 1.3em;
|
||||
padding: 7px 30px;
|
||||
background: #eee;
|
||||
border-radius: 2px;
|
||||
-moz-border-radius: 2px;
|
||||
-webkit-border-radius: 2px;
|
||||
}
|
||||
|
||||
dl pre {
|
||||
margin-left: -60px;
|
||||
padding-left: 60px;
|
||||
}
|
||||
|
||||
tt {
|
||||
background-color: #ecf0f3;
|
||||
color: #222;
|
||||
/* padding: 1px 2px; */
|
||||
}
|
||||
|
||||
tt.xref, a tt {
|
||||
background-color: #FBFBFB;
|
||||
}
|
||||
|
||||
a:hover tt {
|
||||
background: #EEE;
|
||||
}
|
||||
Vendored
-10
@@ -1,10 +0,0 @@
|
||||
[theme]
|
||||
inherit = basic
|
||||
stylesheet = flasky.css
|
||||
nosidebar = true
|
||||
pygments_style = flask_theme_support.FlaskyStyle
|
||||
|
||||
[options]
|
||||
index_logo = ''
|
||||
index_logo_height = 120px
|
||||
github_fork = ''
|
||||
@@ -0,0 +1,64 @@
|
||||
.. _api:
|
||||
|
||||
===
|
||||
API
|
||||
===
|
||||
|
||||
|
||||
.. module:: tablib
|
||||
|
||||
This part of the documentation covers all the interfaces of Tablib. For
|
||||
parts where Tablib depends on external libraries, we document the most
|
||||
important right here and provide links to the canonical documentation.
|
||||
|
||||
|
||||
--------------
|
||||
Dataset Object
|
||||
--------------
|
||||
|
||||
|
||||
.. autoclass:: Dataset
|
||||
:inherited-members:
|
||||
|
||||
|
||||
---------------
|
||||
Databook Object
|
||||
---------------
|
||||
|
||||
|
||||
.. autoclass:: Databook
|
||||
:inherited-members:
|
||||
|
||||
|
||||
|
||||
---------
|
||||
Functions
|
||||
---------
|
||||
|
||||
|
||||
.. autofunction:: detect_format
|
||||
|
||||
.. autofunction:: import_set
|
||||
|
||||
|
||||
----------
|
||||
Exceptions
|
||||
----------
|
||||
|
||||
|
||||
.. class:: InvalidDatasetType
|
||||
|
||||
You're trying to add something that doesn't quite look right.
|
||||
|
||||
|
||||
.. class:: InvalidDimensions
|
||||
|
||||
You're trying to add something that doesn't quite fit right.
|
||||
|
||||
|
||||
.. class:: UnsupportedFormat
|
||||
|
||||
You're trying to add something that doesn't quite taste right.
|
||||
|
||||
|
||||
Now, go start some :ref:`Tablib Development <development>`.
|
||||
+31
-24
@@ -10,18 +10,16 @@
|
||||
#
|
||||
# All configuration values have a default; values that are commented out
|
||||
# serve to show the default.
|
||||
|
||||
import sys, os
|
||||
from pkg_resources import get_distribution
|
||||
|
||||
# If extensions (or modules to document with autodoc) are in another directory,
|
||||
# add these directories to sys.path here. If the directory is relative to the
|
||||
# documentation root, use os.path.abspath to make it absolute, like shown here.
|
||||
#sys.path.insert(0, os.path.abspath('.'))
|
||||
|
||||
# sys.path.insert(0, os.path.abspath('..'))
|
||||
# -- General configuration -----------------------------------------------------
|
||||
|
||||
# If your documentation needs a minimal Sphinx version, state it here.
|
||||
#needs_sphinx = '1.0'
|
||||
# needs_sphinx = '1.0'
|
||||
|
||||
# Add any Sphinx extension module names here, as strings. They can be extensions
|
||||
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
|
||||
@@ -41,16 +39,17 @@ master_doc = 'index'
|
||||
|
||||
# General information about the project.
|
||||
project = u'Tablib'
|
||||
copyright = u'2010, Kenneth Reitz'
|
||||
copyright = u'2019 Jazzband'
|
||||
|
||||
# The version info for the project you're documenting, acts as replacement for
|
||||
# |version| and |release|, also used in various other places throughout the
|
||||
# built documents.
|
||||
#
|
||||
# The short X.Y version.
|
||||
version = '0.8.3'
|
||||
# The full version, including alpha/beta/rc tags.
|
||||
release = '0.8.3'
|
||||
release = get_distribution('tablib').version
|
||||
# The short X.Y version.
|
||||
version = '.'.join(release.split('.')[:2])
|
||||
# for example take major/minor
|
||||
|
||||
# The language for content autogenerated by Sphinx. Refer to documentation
|
||||
# for a list of supported languages.
|
||||
@@ -70,18 +69,18 @@ exclude_patterns = ['_build']
|
||||
#default_role = None
|
||||
|
||||
# If true, '()' will be appended to :func: etc. cross-reference text.
|
||||
#add_function_parentheses = True
|
||||
add_function_parentheses = True
|
||||
|
||||
# If true, the current module name will be prepended to all description
|
||||
# unit titles (such as .. function::).
|
||||
#add_module_names = True
|
||||
# add_module_names = True
|
||||
|
||||
# If true, sectionauthor and moduleauthor directives will be shown in the
|
||||
# output. They are ignored by default.
|
||||
#show_authors = False
|
||||
|
||||
# The name of the Pygments (syntax highlighting) style to use.
|
||||
pygments_style = 'sphinx'
|
||||
# pygments_style = ''
|
||||
|
||||
# A list of ignored prefixes for module index sorting.
|
||||
#modindex_common_prefix = []
|
||||
@@ -91,7 +90,7 @@ pygments_style = 'sphinx'
|
||||
|
||||
# The theme to use for HTML and HTML Help pages. See the documentation for
|
||||
# a list of builtin themes.
|
||||
html_theme = 'default'
|
||||
html_theme = 'alabaster'
|
||||
|
||||
# Theme options are theme-specific and customize the look and feel of a theme
|
||||
# further. For a list of options available for each theme, see the
|
||||
@@ -120,7 +119,7 @@ html_theme = 'default'
|
||||
# Add any paths that contain custom static files (such as style sheets) here,
|
||||
# relative to this directory. They are copied after the builtin static files,
|
||||
# so a file named "default.css" will overwrite the builtin "default.css".
|
||||
html_static_path = ['_static']
|
||||
# html_static_path = ['static']
|
||||
|
||||
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
|
||||
# using the given strftime format.
|
||||
@@ -128,10 +127,14 @@ html_static_path = ['_static']
|
||||
|
||||
# If true, SmartyPants will be used to convert quotes and dashes to
|
||||
# typographically correct entities.
|
||||
#html_use_smartypants = True
|
||||
html_use_smartypants = True
|
||||
|
||||
# Custom sidebar templates, maps document names to template names.
|
||||
#html_sidebars = {}
|
||||
html_sidebars = {
|
||||
'index': ['sidebarintro.html', 'sourcelink.html', 'searchbox.html'],
|
||||
'**': ['sidebarlogo.html', 'localtoc.html', 'relations.html',
|
||||
'sourcelink.html', 'searchbox.html']
|
||||
}
|
||||
|
||||
# Additional templates that should be rendered to pages, maps page names to
|
||||
# template names.
|
||||
@@ -147,10 +150,10 @@ html_static_path = ['_static']
|
||||
#html_split_index = False
|
||||
|
||||
# If true, links to the reST sources are added to the pages.
|
||||
#html_show_sourcelink = True
|
||||
html_show_sourcelink = True
|
||||
|
||||
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
|
||||
#html_show_sphinx = True
|
||||
html_show_sphinx = False
|
||||
|
||||
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
|
||||
#html_show_copyright = True
|
||||
@@ -179,9 +182,17 @@ htmlhelp_basename = 'Tablibdoc'
|
||||
# (source start file, target name, title, author, documentclass [howto/manual]).
|
||||
latex_documents = [
|
||||
('index', 'Tablib.tex', u'Tablib Documentation',
|
||||
u'Kenneth Reitz', 'manual'),
|
||||
u'Jazzband', 'manual'),
|
||||
]
|
||||
|
||||
latex_use_modindex = False
|
||||
|
||||
latex_elements = {
|
||||
'papersize': 'a4paper',
|
||||
'pointsize': '12pt',
|
||||
}
|
||||
latex_use_parts = True
|
||||
|
||||
# The name of an image file (relative to this directory) to place at the top of
|
||||
# the title page.
|
||||
#latex_logo = None
|
||||
@@ -212,9 +223,5 @@ latex_documents = [
|
||||
# (source start file, name, description, authors, manual section).
|
||||
man_pages = [
|
||||
('index', 'tablib', u'Tablib Documentation',
|
||||
[u'Kenneth Reitz'], 1)
|
||||
[u'Jazzband'], 1)
|
||||
]
|
||||
|
||||
sys.path.append(os.path.abspath('_themes'))
|
||||
html_theme_path = ['_themes']
|
||||
html_theme = 'kr'
|
||||
@@ -0,0 +1,207 @@
|
||||
.. _development:
|
||||
|
||||
Development
|
||||
===========
|
||||
|
||||
Tablib is under active development, and contributors are welcome.
|
||||
|
||||
If you have a feature request, suggestion, or bug report, please open a new
|
||||
issue on GitHub_. To submit patches, please send a pull request on GitHub_.
|
||||
|
||||
.. _GitHub: https://github.com/jazzband/tablib/
|
||||
|
||||
|
||||
|
||||
.. _design:
|
||||
|
||||
---------------------
|
||||
Design Considerations
|
||||
---------------------
|
||||
|
||||
Tablib was developed with a few :pep:`20` idioms in mind.
|
||||
|
||||
#. Beautiful is better than ugly.
|
||||
#. Explicit is better than implicit.
|
||||
#. Simple is better than complex.
|
||||
#. Complex is better than complicated.
|
||||
#. Readability counts.
|
||||
|
||||
A few other things to keep in mind:
|
||||
|
||||
#. Keep your code DRY.
|
||||
#. Strive to be as simple (to use) as possible.
|
||||
|
||||
.. _scm:
|
||||
|
||||
--------------
|
||||
Source Control
|
||||
--------------
|
||||
|
||||
|
||||
Tablib source is controlled with Git_, the lean, mean, distributed source
|
||||
control machine.
|
||||
|
||||
The repository is publicly accessible.
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
git clone git://github.com/jazzband/tablib.git
|
||||
|
||||
The project is hosted on **GitHub**.
|
||||
|
||||
GitHub:
|
||||
https://github.com/jazzband/tablib
|
||||
|
||||
|
||||
Git Branch Structure
|
||||
++++++++++++++++++++
|
||||
|
||||
Feature / Hotfix / Release branches follow a `Successful Git Branching Model`_ .
|
||||
Git-flow_ is a great tool for managing the repository. I highly recommend it.
|
||||
|
||||
``master``
|
||||
Current production release (|version|) on PyPi.
|
||||
|
||||
Each release is tagged.
|
||||
|
||||
When submitting patches, please place your feature/change in its own branch prior to opening a pull request on GitHub_.
|
||||
|
||||
|
||||
.. _Git: https://git-scm.org
|
||||
.. _`Successful Git Branching Model`: https://nvie.com/posts/a-successful-git-branching-model/
|
||||
.. _git-flow: https://github.com/nvie/gitflow
|
||||
|
||||
|
||||
.. _newformats:
|
||||
|
||||
------------------
|
||||
Adding New Formats
|
||||
------------------
|
||||
|
||||
Tablib welcomes new format additions! Format suggestions include:
|
||||
|
||||
* MySQL Dump
|
||||
|
||||
|
||||
Coding by Convention
|
||||
++++++++++++++++++++
|
||||
|
||||
Tablib features a micro-framework for adding format support.
|
||||
The easiest way to understand it is to use it.
|
||||
So, let's define our own format, named *xxx*.
|
||||
|
||||
1. Write a new format interface.
|
||||
|
||||
:class:`tablib.core` follows a simple pattern for automatically utilizing your format throughout Tablib.
|
||||
Function names are crucial.
|
||||
|
||||
Example **tablib/formats/_xxx.py**: ::
|
||||
|
||||
title = 'xxx'
|
||||
|
||||
def export_set(dset):
|
||||
....
|
||||
# returns string representation of given dataset
|
||||
|
||||
def export_book(dbook):
|
||||
....
|
||||
# returns string representation of given databook
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
...
|
||||
# populates given Dataset with given datastream
|
||||
|
||||
def import_book(dbook, in_stream):
|
||||
...
|
||||
# returns Databook instance
|
||||
|
||||
def detect(stream):
|
||||
...
|
||||
# returns True if given stream is parsable as xxx
|
||||
|
||||
.. admonition:: Excluding Support
|
||||
|
||||
If the format excludes support for an import/export mechanism (*e.g.*
|
||||
:class:`csv <tablib.Dataset.csv>` excludes
|
||||
:class:`Databook <tablib.Databook>` support),
|
||||
simply don't define the respective functions.
|
||||
Appropriate errors will be raised.
|
||||
|
||||
2. Add your new format module to the :class:`tablib.formats.available` tuple.
|
||||
|
||||
3. Add a mock property to the :class:`Dataset <tablib.Dataset>` class with verbose `reStructured Text`_ docstring.
|
||||
This alleviates IDE confusion, and allows for pretty auto-generated Sphinx_ documentation.
|
||||
|
||||
4. Write respective :ref:`tests <testing>`.
|
||||
|
||||
.. _testing:
|
||||
|
||||
--------------
|
||||
Testing Tablib
|
||||
--------------
|
||||
|
||||
Testing is crucial to Tablib's stability.
|
||||
This stable project is used in production by many companies and developers,
|
||||
so it is important to be certain that every version released is fully operational.
|
||||
When developing a new feature for Tablib, be sure to write proper tests for it as well.
|
||||
|
||||
When developing a feature for Tablib,
|
||||
the easiest way to test your changes for potential issues is to simply run the test suite directly.
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ tox
|
||||
|
||||
----------------------
|
||||
Continuous Integration
|
||||
----------------------
|
||||
|
||||
Every pull request is automatically tested and inspected upon receipt with `Travis CI`_.
|
||||
If you broke the build, you will receive an email accordingly.
|
||||
|
||||
Anyone may view the build status and history at any time.
|
||||
|
||||
https://travis-ci.org/jazzband/tablib
|
||||
|
||||
Additional reports will also be included here in the future, including :pep:`8` checks and stress reports for extremely large datasets.
|
||||
|
||||
.. _`Travis CI`: https://travis-ci.org/
|
||||
|
||||
|
||||
.. _docs:
|
||||
|
||||
-----------------
|
||||
Building the Docs
|
||||
-----------------
|
||||
|
||||
Documentation is written in the powerful, flexible,
|
||||
and standard Python documentation format, `reStructured Text`_.
|
||||
Documentation builds are powered by the powerful Pocoo project, Sphinx_.
|
||||
The :ref:`API Documentation <api>` is mostly documented inline throughout the module.
|
||||
|
||||
The Docs live in ``tablib/docs``.
|
||||
In order to build them, you will first need to install Sphinx.
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ pip install sphinx
|
||||
|
||||
|
||||
Then, to build an HTML version of the docs, simply run the following from the ``docs`` directory:
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ make html
|
||||
|
||||
Your ``docs/_build/html`` directory will then contain an HTML representation of the documentation,
|
||||
ready for publication on most web servers.
|
||||
|
||||
You can also generate the documentation in **epub**, **latex**, **json**, *&c* similarly.
|
||||
|
||||
.. _`reStructured Text`: http://docutils.sourceforge.net/rst.html
|
||||
.. _Sphinx: http://sphinx.pocoo.org
|
||||
.. _`GitHub Pages`: https://pages.github.com
|
||||
|
||||
----------
|
||||
|
||||
Make sure to check out the :ref:`API Documentation <api>`.
|
||||
+101
-19
@@ -3,32 +3,114 @@
|
||||
You can adapt this file completely to your liking, but it should at least
|
||||
contain the root `toctree` directive.
|
||||
|
||||
Welcome to Tablib's documentation!
|
||||
==================================
|
||||
Tablib: Pythonic Tabular Datasets
|
||||
=================================
|
||||
|
||||
Contents:
|
||||
Release v\ |version|. (:ref:`Installation <install>`)
|
||||
|
||||
.. Contents:
|
||||
..
|
||||
.. .. toctree::
|
||||
.. :maxdepth: 2
|
||||
..
|
||||
|
||||
.. Indices and tables
|
||||
.. ==================
|
||||
..
|
||||
.. * :ref:`genindex`
|
||||
.. * :ref:`modindex`
|
||||
.. * :ref:`search`
|
||||
|
||||
|
||||
Tablib is an `MIT Licensed <https://mit-license.org/>`_ format-agnostic tabular dataset library, written in Python.
|
||||
It allows you to import, export, and manipulate tabular data sets.
|
||||
Advanced features include segregation, dynamic columns, tags & filtering,
|
||||
and seamless format import & export.
|
||||
|
||||
::
|
||||
|
||||
>>> data = tablib.Dataset(headers=['First Name', 'Last Name', 'Age'])
|
||||
>>> for i in [('Kenneth', 'Reitz', 22), ('Bessie', 'Monke', 21)]:
|
||||
... data.append(i)
|
||||
|
||||
|
||||
>>> print(data.export('json'))
|
||||
[{"Last Name": "Reitz", "First Name": "Kenneth", "Age": 22}, {"Last Name": "Monke", "First Name": "Bessie", "Age": 21}]
|
||||
|
||||
>>> print(data.export('yaml'))
|
||||
- {Age: 22, First Name: Kenneth, Last Name: Reitz}
|
||||
- {Age: 21, First Name: Bessie, Last Name: Monke}
|
||||
|
||||
>>> data.export('xlsx')
|
||||
<redacted binary data>
|
||||
|
||||
>>> data.export('df')
|
||||
First Name Last Name Age
|
||||
0 Kenneth Reitz 22
|
||||
1 Bessie Monke 21
|
||||
|
||||
|
||||
Testimonials
|
||||
------------
|
||||
|
||||
`National Geographic <https://www.nationalgeographic.com/>`_,
|
||||
`Digg, Inc <https://digg.com/>`_,
|
||||
`Northrop Grumman <https://www.northropgrumman.com/>`_,
|
||||
`Discovery Channel <https://dsc.discovery.com/>`_,
|
||||
and `The Sunlight Foundation <https://sunlightfoundation.com/>`_ use Tablib internally.
|
||||
|
||||
|
||||
|
||||
**Greg Thorton**
|
||||
Tablib by @kennethreitz saved my life.
|
||||
I had to consolidate like 5 huge poorly maintained lists of domains and data.
|
||||
It was a breeze!
|
||||
|
||||
**Dave Coutts**
|
||||
It's turning into one of my most used modules of 2010.
|
||||
You really hit a sweet spot for managing tabular data with a minimal amount of code and effort.
|
||||
|
||||
**Joshua Ourisman**
|
||||
Tablib has made it so much easier to deal with the inevitable 'I want an Excel file!' requests from clients...
|
||||
|
||||
**Brad Montgomery**
|
||||
I think you nailed the "Python Zen" with tablib.
|
||||
Thanks again for an awesome lib!
|
||||
|
||||
|
||||
User's Guide
|
||||
------------
|
||||
|
||||
This part of the documentation, which is mostly prose, begins with some background information about Tablib, then focuses on step-by-step instructions for getting the most out of your datasets.
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
Indices and tables
|
||||
==================
|
||||
intro
|
||||
|
||||
* :ref:`genindex`
|
||||
* :ref:`modindex`
|
||||
* :ref:`search`
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
Dataset Object
|
||||
--------------
|
||||
.. module:: tablib
|
||||
install
|
||||
|
||||
.. autoclass:: Databook
|
||||
:members:
|
||||
:inherited-members:
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
Databook Object
|
||||
---------------
|
||||
tutorial
|
||||
|
||||
.. autoclass:: Dataset
|
||||
:members:
|
||||
:inherited-members:
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
development
|
||||
|
||||
|
||||
API Reference
|
||||
-------------
|
||||
|
||||
If you are looking for information on a specific function, class or
|
||||
method, this part of the documentation is for you.
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
api
|
||||
|
||||
@@ -0,0 +1,67 @@
|
||||
.. _install:
|
||||
|
||||
Installation
|
||||
============
|
||||
|
||||
This part of the documentation covers the installation of Tablib. The first step to using any software package is getting it properly installed.
|
||||
|
||||
|
||||
.. _installing:
|
||||
|
||||
-----------------
|
||||
Installing Tablib
|
||||
-----------------
|
||||
|
||||
Distribute & Pip
|
||||
----------------
|
||||
|
||||
Of course, the recommended way to install Tablib is with `pip <https://pip.pypa.io>`_:
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ pip install tablib[pandas]
|
||||
|
||||
|
||||
-------------------
|
||||
Download the Source
|
||||
-------------------
|
||||
|
||||
You can also install tablib from source.
|
||||
The latest release (|version|) is available from GitHub.
|
||||
|
||||
* tarball_
|
||||
* zipball_
|
||||
|
||||
.. _
|
||||
|
||||
Once you have a copy of the source,
|
||||
you can embed it in your Python package,
|
||||
or install it into your site-packages easily.
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ python setup.py install
|
||||
|
||||
|
||||
To download the full source history from Git, see :ref:`Source Control <scm>`.
|
||||
|
||||
.. _tarball: https://github.com/jazzband/tablib/tarball/master
|
||||
.. _zipball: https://github.com/jazzband/tablib/zipball/master
|
||||
|
||||
|
||||
.. _updates:
|
||||
|
||||
Staying Updated
|
||||
---------------
|
||||
|
||||
The latest version of Tablib will always be available here:
|
||||
|
||||
* PyPI: https://pypi.org/project/tablib/
|
||||
* GitHub: https://github.com/jazzband/tablib/
|
||||
|
||||
When a new version is available, upgrading is simple::
|
||||
|
||||
$ pip install tablib --upgrade
|
||||
|
||||
|
||||
Now, go get a :ref:`Quick Start <quickstart>`.
|
||||
@@ -0,0 +1,84 @@
|
||||
.. _intro:
|
||||
|
||||
Introduction
|
||||
============
|
||||
|
||||
This part of the documentation covers all the interfaces of Tablib.
|
||||
Tablib is a format-agnostic tabular dataset library, written in Python.
|
||||
It allows you to Pythonically import, export, and manipulate tabular data sets.
|
||||
Advanced features include segregation, dynamic columns, tags / filtering, and
|
||||
seamless format import/export.
|
||||
|
||||
|
||||
Philosophy
|
||||
----------
|
||||
|
||||
Tablib was developed with a few :pep:`20` idioms in mind.
|
||||
|
||||
#. Beautiful is better than ugly.
|
||||
#. Explicit is better than implicit.
|
||||
#. Simple is better than complex.
|
||||
#. Complex is better than complicated.
|
||||
#. Readability counts.
|
||||
|
||||
All contributions to Tablib should keep these important rules in mind.
|
||||
|
||||
.. mit:
|
||||
|
||||
MIT License
|
||||
-----------
|
||||
|
||||
A large number of open source projects you find today are `GPL Licensed`_.
|
||||
While the GPL has its time and place, it should most certainly not be your
|
||||
go-to license for your next open source project.
|
||||
|
||||
A project that is released as GPL cannot be used in any commercial product
|
||||
without the product itself also being offered as open source. The MIT, BSD, and
|
||||
ISC licenses are great alternatives to the GPL that allow your open-source
|
||||
software to be used in proprietary, closed-source software.
|
||||
|
||||
Tablib is released under terms of `The MIT License`_.
|
||||
|
||||
.. _`GPL Licensed`: https://opensource.org/licenses/gpl-license.php
|
||||
.. _`The MIT License`: https://opensource.org/licenses/mit-license.php
|
||||
|
||||
|
||||
.. _license:
|
||||
|
||||
Tablib License
|
||||
--------------
|
||||
|
||||
Copyright 2017 Kenneth Reitz
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in
|
||||
all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
|
||||
THE SOFTWARE.
|
||||
|
||||
|
||||
.. _pythonsupport:
|
||||
|
||||
Pythons Supported
|
||||
-----------------
|
||||
|
||||
At this time, the following Python versions are officially supported:
|
||||
|
||||
* CPython 2.7
|
||||
* CPython 3.5
|
||||
* CPython 3.6
|
||||
* CPython 3.7
|
||||
|
||||
Now, go :ref:`Install Tablib <install>`.
|
||||
@@ -0,0 +1,118 @@
|
||||
\definecolor{TitleColor}{rgb}{0,0,0}
|
||||
\definecolor{InnerLinkColor}{rgb}{0,0,0}
|
||||
|
||||
\renewcommand{\maketitle}{%
|
||||
\begin{titlepage}%
|
||||
\let\footnotesize\small
|
||||
\let\footnoterule\relax
|
||||
\ifsphinxpdfoutput
|
||||
\begingroup
|
||||
% This \def is required to deal with multi-line authors; it
|
||||
% changes \\ to ', ' (comma-space), making it pass muster for
|
||||
% generating document info in the PDF file.
|
||||
\def\\{, }
|
||||
\pdfinfo{
|
||||
/Author (\@author)
|
||||
/Title (\@title)
|
||||
}
|
||||
\endgroup
|
||||
\fi
|
||||
\begin{flushright}%
|
||||
%\sphinxlogo%
|
||||
{\center
|
||||
\vspace*{3cm}
|
||||
\includegraphics{logo.pdf}
|
||||
\vspace{3cm}
|
||||
\par
|
||||
{\rm\Huge \@title \par}%
|
||||
{\em\LARGE \py@release\releaseinfo \par}
|
||||
{\large
|
||||
\@date \par
|
||||
\py@authoraddress \par
|
||||
}}%
|
||||
\end{flushright}%\par
|
||||
\@thanks
|
||||
\end{titlepage}%
|
||||
\cleardoublepage%
|
||||
\setcounter{footnote}{0}%
|
||||
\let\thanks\relax\let\maketitle\relax
|
||||
%\gdef\@thanks{}\gdef\@author{}\gdef\@title{}
|
||||
}
|
||||
|
||||
\fancypagestyle{normal}{
|
||||
\fancyhf{}
|
||||
\fancyfoot[LE,RO]{{\thepage}}
|
||||
\fancyfoot[LO]{{\nouppercase{\rightmark}}}
|
||||
\fancyfoot[RE]{{\nouppercase{\leftmark}}}
|
||||
\fancyhead[LE,RO]{{ \@title, \py@release}}
|
||||
\renewcommand{\headrulewidth}{0.4pt}
|
||||
\renewcommand{\footrulewidth}{0.4pt}
|
||||
}
|
||||
|
||||
\fancypagestyle{plain}{
|
||||
\fancyhf{}
|
||||
\fancyfoot[LE,RO]{{\thepage}}
|
||||
\renewcommand{\headrulewidth}{0pt}
|
||||
\renewcommand{\footrulewidth}{0.4pt}
|
||||
}
|
||||
|
||||
\titleformat{\section}{\Large}%
|
||||
{\py@TitleColor\thesection}{0.5em}{\py@TitleColor}{\py@NormalColor}
|
||||
\titleformat{\subsection}{\large}%
|
||||
{\py@TitleColor\thesubsection}{0.5em}{\py@TitleColor}{\py@NormalColor}
|
||||
\titleformat{\subsubsection}{}%
|
||||
{\py@TitleColor\thesubsubsection}{0.5em}{\py@TitleColor}{\py@NormalColor}
|
||||
\titleformat{\paragraph}{\large}%
|
||||
{\py@TitleColor}{0em}{\py@TitleColor}{\py@NormalColor}
|
||||
|
||||
\ChNameVar{\raggedleft\normalsize}
|
||||
\ChNumVar{\raggedleft \bfseries\Large}
|
||||
\ChTitleVar{\raggedleft \rm\Huge}
|
||||
|
||||
\renewcommand\thepart{\@Roman\c@part}
|
||||
\renewcommand\part{%
|
||||
\pagestyle{empty}
|
||||
\if@noskipsec \leavevmode \fi
|
||||
\cleardoublepage
|
||||
\vspace*{6cm}%
|
||||
\@afterindentfalse
|
||||
\secdef\@part\@spart}
|
||||
|
||||
\def\@part[#1]#2{%
|
||||
\ifnum \c@secnumdepth >\m@ne
|
||||
\refstepcounter{part}%
|
||||
\addcontentsline{toc}{part}{\thepart\hspace{1em}#1}%
|
||||
\else
|
||||
\addcontentsline{toc}{part}{#1}%
|
||||
\fi
|
||||
{\parindent \z@ %\center
|
||||
\interlinepenalty \@M
|
||||
\normalfont
|
||||
\ifnum \c@secnumdepth >\m@ne
|
||||
\rm\Large \partname~\thepart
|
||||
\par\nobreak
|
||||
\fi
|
||||
\MakeUppercase{\rm\Huge #2}%
|
||||
\markboth{}{}\par}%
|
||||
\nobreak
|
||||
\vskip 8ex
|
||||
\@afterheading}
|
||||
\def\@spart#1{%
|
||||
{\parindent \z@ %\center
|
||||
\interlinepenalty \@M
|
||||
\normalfont
|
||||
\huge \bfseries #1\par}%
|
||||
\nobreak
|
||||
\vskip 3ex
|
||||
\@afterheading}
|
||||
|
||||
% use inconsolata font
|
||||
\usepackage{inconsolata}
|
||||
|
||||
% fix single quotes, for inconsolata. (does not work)
|
||||
%%\usepackage{textcomp}
|
||||
%%\begingroup
|
||||
%% \catcode`'=\active
|
||||
%% \g@addto@macro\@noligs{\let'\textsinglequote}
|
||||
%% \endgroup
|
||||
%%\endinput
|
||||
@@ -0,0 +1,395 @@
|
||||
.. _quickstart:
|
||||
|
||||
==========
|
||||
Quickstart
|
||||
==========
|
||||
|
||||
|
||||
Eager to get started?
|
||||
This page gives a good introduction in how to get started with Tablib.
|
||||
This assumes you already have Tablib installed.
|
||||
If you do not, head over to the :ref:`Installation <install>` section.
|
||||
|
||||
First, make sure that:
|
||||
|
||||
* Tablib is :ref:`installed <install>`
|
||||
* Tablib is :ref:`up-to-date <updates>`
|
||||
|
||||
|
||||
Let's get started with some simple use cases and examples.
|
||||
|
||||
|
||||
|
||||
------------------
|
||||
Creating a Dataset
|
||||
------------------
|
||||
|
||||
|
||||
A :class:`Dataset <tablib.Dataset>` is nothing more than what its name implies—a set of data.
|
||||
|
||||
Creating your own instance of the :class:`tablib.Dataset` object is simple. ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
|
||||
You can now start filling this :class:`Dataset <tablib.Dataset>` object with data.
|
||||
|
||||
.. admonition:: Example Context
|
||||
|
||||
From here on out, if you see ``data``, assume that it's a fresh
|
||||
:class:`Dataset <tablib.Dataset>` object.
|
||||
|
||||
|
||||
|
||||
-----------
|
||||
Adding Rows
|
||||
-----------
|
||||
|
||||
|
||||
Let's say you want to collect a simple list of names. ::
|
||||
|
||||
# collection of names
|
||||
names = ['Kenneth Reitz', 'Bessie Monke']
|
||||
|
||||
for name in names:
|
||||
# split name appropriately
|
||||
fname, lname = name.split()
|
||||
|
||||
# add names to Dataset
|
||||
data.append([fname, lname])
|
||||
|
||||
You can get a nice, Pythonic view of the dataset at any time with :class:`Dataset.dict`::
|
||||
|
||||
>>> data.dict
|
||||
[('Kenneth', 'Reitz'), ('Bessie', 'Monke')]
|
||||
|
||||
|
||||
|
||||
--------------
|
||||
Adding Headers
|
||||
--------------
|
||||
|
||||
|
||||
It's time to enhance our :class:`Dataset` by giving our columns some titles.
|
||||
To do so, set :class:`Dataset.headers`. ::
|
||||
|
||||
data.headers = ['First Name', 'Last Name']
|
||||
|
||||
Now our data looks a little different. ::
|
||||
|
||||
>>> data.dict
|
||||
[{'Last Name': 'Reitz', 'First Name': 'Kenneth'},
|
||||
{'Last Name': 'Monke', 'First Name': 'Bessie'}]
|
||||
|
||||
|
||||
|
||||
|
||||
--------------
|
||||
Adding Columns
|
||||
--------------
|
||||
|
||||
|
||||
Now that we have a basic :class:`Dataset` in place, let's add a column of **ages** to it. ::
|
||||
|
||||
data.append_col([22, 20], header='Age')
|
||||
|
||||
Let's view the data now. ::
|
||||
|
||||
>>> data.dict
|
||||
[{'Last Name': 'Reitz', 'First Name': 'Kenneth', 'Age': 22},
|
||||
{'Last Name': 'Monke', 'First Name': 'Bessie', 'Age': 20}]
|
||||
|
||||
It's that easy.
|
||||
|
||||
|
||||
--------------
|
||||
Importing Data
|
||||
--------------
|
||||
Creating a :class:`tablib.Dataset` object by importing a pre-existing file is simple. ::
|
||||
|
||||
imported_data = Dataset().load(open('data.csv').read())
|
||||
|
||||
This detects what sort of data is being passed in, and uses an appropriate formatter to do the import. So you can import from a variety of different file types.
|
||||
|
||||
--------------
|
||||
Exporting Data
|
||||
--------------
|
||||
|
||||
Tablib's killer feature is the ability to export your :class:`Dataset` objects into a number of formats.
|
||||
|
||||
**Comma-Separated Values** ::
|
||||
|
||||
>>> data.export('csv')
|
||||
Last Name,First Name,Age
|
||||
Reitz,Kenneth,22
|
||||
Monke,Bessie,20
|
||||
|
||||
**JavaScript Object Notation** ::
|
||||
|
||||
>>> data.export('json')
|
||||
[{"Last Name": "Reitz", "First Name": "Kenneth", "Age": 22}, {"Last Name": "Monke", "First Name": "Bessie", "Age": 20}]
|
||||
|
||||
|
||||
**YAML Ain't Markup Language** ::
|
||||
|
||||
>>> data.export('yaml')
|
||||
- {Age: 22, First Name: Kenneth, Last Name: Reitz}
|
||||
- {Age: 20, First Name: Bessie, Last Name: Monke}
|
||||
|
||||
|
||||
**Microsoft Excel** ::
|
||||
|
||||
>>> data.export('xls')
|
||||
<redacted binary data>
|
||||
|
||||
|
||||
**Pandas DataFrame** ::
|
||||
|
||||
>>> data.export('df')
|
||||
First Name Last Name Age
|
||||
0 Kenneth Reitz 22
|
||||
1 Bessie Monke 21
|
||||
|
||||
|
||||
------------------------
|
||||
Selecting Rows & Columns
|
||||
------------------------
|
||||
|
||||
|
||||
You can slice and dice your data, just like a standard Python list. ::
|
||||
|
||||
>>> data[0]
|
||||
('Kenneth', 'Reitz', 22)
|
||||
|
||||
|
||||
If we had a set of data consisting of thousands of rows,
|
||||
it could be useful to get a list of values in a column.
|
||||
To do so, we access the :class:`Dataset` as if it were a standard Python dictionary. ::
|
||||
|
||||
>>> data['First Name']
|
||||
['Kenneth', 'Bessie']
|
||||
|
||||
You can also access the column using its index. ::
|
||||
|
||||
>>> data.headers
|
||||
['Last Name', 'First Name', 'Age']
|
||||
>>> data.get_col(1)
|
||||
['Kenneth', 'Bessie']
|
||||
|
||||
Let's find the average age. ::
|
||||
|
||||
>>> ages = data['Age']
|
||||
>>> float(sum(ages)) / len(ages)
|
||||
21.0
|
||||
|
||||
|
||||
|
||||
-----------------------
|
||||
Removing Rows & Columns
|
||||
-----------------------
|
||||
|
||||
It's easier than you could imagine. Delete a column::
|
||||
|
||||
>>> del data['Col Name']
|
||||
|
||||
Delete a range of rows::
|
||||
|
||||
>>> del data[0:12]
|
||||
|
||||
|
||||
==============
|
||||
Advanced Usage
|
||||
==============
|
||||
|
||||
This part of the documentation services to give you an idea that are otherwise hard to extract from the :ref:`API Documentation <api>`
|
||||
|
||||
And now for something completely different.
|
||||
|
||||
|
||||
.. _dyncols:
|
||||
|
||||
---------------
|
||||
Dynamic Columns
|
||||
---------------
|
||||
|
||||
.. versionadded:: 0.8.3
|
||||
|
||||
Thanks to Josh Ourisman, Tablib now supports adding dynamic columns.
|
||||
A dynamic column is a single callable object (*e.g.* a function).
|
||||
|
||||
Let's add a dynamic column to our :class:`Dataset` object.
|
||||
In this example, we have a function that generates a random grade for our students. ::
|
||||
|
||||
import random
|
||||
|
||||
def random_grade(row):
|
||||
"""Returns a random integer for entry."""
|
||||
return (random.randint(60,100)/100.0)
|
||||
|
||||
data.append_col(random_grade, header='Grade')
|
||||
|
||||
Let's have a look at our data. ::
|
||||
|
||||
>>> data.export('yaml')
|
||||
- {Age: 22, First Name: Kenneth, Grade: 0.6, Last Name: Reitz}
|
||||
- {Age: 20, First Name: Bessie, Grade: 0.75, Last Name: Monke}
|
||||
|
||||
|
||||
Let's remove that column. ::
|
||||
|
||||
>>> del data['Grade']
|
||||
|
||||
|
||||
When you add a dynamic column, the first argument that is passed in to the given callable is the current data row.
|
||||
You can use this to perform calculations against your data row.
|
||||
|
||||
For example, we can use the data available in the row to guess the gender of a student. ::
|
||||
|
||||
def guess_gender(row):
|
||||
"""Calculates gender of given student data row."""
|
||||
m_names = ('Kenneth', 'Mike', 'Yuri')
|
||||
f_names = ('Bessie', 'Samantha', 'Heather')
|
||||
|
||||
name = row[0]
|
||||
|
||||
if name in m_names:
|
||||
return 'Male'
|
||||
elif name in f_names:
|
||||
return 'Female'
|
||||
else:
|
||||
return 'Unknown'
|
||||
|
||||
Adding this function to our dataset as a dynamic column would result in: ::
|
||||
|
||||
>>> data.export('yaml')
|
||||
- {Age: 22, First Name: Kenneth, Gender: Male, Last Name: Reitz}
|
||||
- {Age: 20, First Name: Bessie, Gender: Female, Last Name: Monke}
|
||||
|
||||
|
||||
.. _tags:
|
||||
|
||||
----------------------------
|
||||
Filtering Datasets with Tags
|
||||
----------------------------
|
||||
|
||||
.. versionadded:: 0.9.0
|
||||
|
||||
|
||||
When constructing a :class:`Dataset` object,
|
||||
you can add tags to rows by specifying the ``tags`` parameter.
|
||||
This allows you to filter your :class:`Dataset` later.
|
||||
This can be useful to separate rows of data based on arbitrary criteria
|
||||
(*e.g.* origin) that you don't want to include in your :class:`Dataset`.
|
||||
|
||||
Let's tag some students. ::
|
||||
|
||||
students = tablib.Dataset()
|
||||
|
||||
students.headers = ['first', 'last']
|
||||
|
||||
students.rpush(['Kenneth', 'Reitz'], tags=['male', 'technical'])
|
||||
students.rpush(['Bessie', 'Monke'], tags=['female', 'creative'])
|
||||
|
||||
Now that we have extra meta-data on our rows, we can easily filter our :class:`Dataset`. Let's just see Male students. ::
|
||||
|
||||
|
||||
>>> students.filter(['male']).yaml
|
||||
- {first: Kenneth, Last: Reitz}
|
||||
|
||||
It's that simple. The original :class:`Dataset` is untouched.
|
||||
|
||||
Open an Excel Workbook and read first sheet
|
||||
-------------------------------------------
|
||||
|
||||
To open an Excel 2007 and later workbook with a single sheet (or a workbook with multiple sheets but you just want the first sheet), use the following:
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.xlsx = open('my_excel_file.xlsx', 'rb').read()
|
||||
print(data)
|
||||
|
||||
Excel Workbook With Multiple Sheets
|
||||
------------------------------------
|
||||
|
||||
When dealing with a large number of :class:`Datasets <Dataset>` in spreadsheet format,
|
||||
it's quite common to group multiple spreadsheets into a single Excel file, known as a Workbook.
|
||||
Tablib makes it extremely easy to build workbooks with the handy :class:`Databook` class.
|
||||
|
||||
Let's say we have 3 different :class:`Datasets <Dataset>`.
|
||||
All we have to do is add them to a :class:`Databook` object... ::
|
||||
|
||||
book = tablib.Databook((data1, data2, data3))
|
||||
|
||||
... and export to Excel just like :class:`Datasets <Dataset>`. ::
|
||||
|
||||
with open('students.xls', 'wb') as f:
|
||||
f.write(book.xls)
|
||||
|
||||
The resulting ``students.xls`` file will contain a separate spreadsheet for each :class:`Dataset` object in the :class:`Databook`.
|
||||
|
||||
.. admonition:: Binary Warning
|
||||
|
||||
Make sure to open the output file in binary mode.
|
||||
|
||||
|
||||
.. _separators:
|
||||
|
||||
----------
|
||||
Separators
|
||||
----------
|
||||
|
||||
.. versionadded:: 0.8.2
|
||||
|
||||
When constructing a spreadsheet,
|
||||
it's often useful to create a blank row containing information on the upcoming data. So,
|
||||
|
||||
::
|
||||
|
||||
daniel_tests = [
|
||||
('11/24/09', 'Math 101 Mid-term Exam', 56.),
|
||||
('05/24/10', 'Math 101 Final Exam', 62.)
|
||||
]
|
||||
|
||||
suzie_tests = [
|
||||
('11/24/09', 'Math 101 Mid-term Exam', 56.),
|
||||
('05/24/10', 'Math 101 Final Exam', 62.)
|
||||
]
|
||||
|
||||
# Create new dataset
|
||||
tests = tablib.Dataset()
|
||||
tests.headers = ['Date', 'Test Name', 'Grade']
|
||||
|
||||
# Daniel's Tests
|
||||
tests.append_separator('Daniel\'s Scores')
|
||||
|
||||
for test_row in daniel_tests:
|
||||
tests.append(test_row)
|
||||
|
||||
# Susie's Tests
|
||||
tests.append_separator('Susie\'s Scores')
|
||||
|
||||
for test_row in suzie_tests:
|
||||
tests.append(test_row)
|
||||
|
||||
# Write spreadsheet to disk
|
||||
with open('grades.xls', 'wb') as f:
|
||||
f.write(tests.export('xls'))
|
||||
|
||||
The resulting **tests.xls** will have the following layout:
|
||||
|
||||
|
||||
Daniel's Scores:
|
||||
* '11/24/09', 'Math 101 Mid-term Exam', 56.
|
||||
* '05/24/10', 'Math 101 Final Exam', 62.
|
||||
|
||||
Suzie's Scores:
|
||||
* '11/24/09', 'Math 101 Mid-term Exam', 56.
|
||||
* '05/24/10', 'Math 101 Final Exam', 62.
|
||||
|
||||
|
||||
|
||||
.. admonition:: Format Support
|
||||
|
||||
At this time, only :class:`Excel <Dataset.xls>` output supports separators.
|
||||
|
||||
----
|
||||
|
||||
Now, go check out the :ref:`API Documentation <api>` or begin :ref:`Tablib Development <development>`.
|
||||
Vendored
-7
@@ -1,7 +0,0 @@
|
||||
from fabric.api import *
|
||||
|
||||
|
||||
def scrub():
|
||||
""" Death to the bytecode! """
|
||||
local("rm -fr dist build")
|
||||
local("find . -name \"*.pyc\" -exec rm '{}' ';'")
|
||||
@@ -0,0 +1,4 @@
|
||||
[pytest]
|
||||
norecursedirs = .git .*
|
||||
addopts = -rsxX --showlocals --tb=native --cov=tablib --cov-report xml --cov-report term --cov-report html
|
||||
python_paths = .
|
||||
@@ -2,56 +2,56 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
|
||||
from distutils.core import setup
|
||||
from setuptools import find_packages, setup
|
||||
|
||||
|
||||
def publish():
|
||||
"""Publish to PyPi"""
|
||||
os.system("python setup.py sdist upload")
|
||||
install = [
|
||||
'odfpy',
|
||||
'openpyxl>=2.4.0',
|
||||
'backports.csv;python_version<"3.0"',
|
||||
'markuppy',
|
||||
'xlrd',
|
||||
'xlwt',
|
||||
'pyyaml',
|
||||
]
|
||||
|
||||
if sys.argv[-1] == "publish":
|
||||
publish()
|
||||
sys.exit()
|
||||
|
||||
required = []
|
||||
|
||||
# if sys.version_info < (2, 6):
|
||||
# required.append('simplejson')
|
||||
|
||||
setup(
|
||||
name='tablib',
|
||||
version='0.8.5',
|
||||
description='Format agnostic tabular data library (XLS, JSON, YAML, CSV)',
|
||||
long_description=open('README.rst').read() + '\n\n' +
|
||||
open('HISTORY.rst').read(),
|
||||
author='Kenneth Reitz',
|
||||
author_email='me@kennethreitz.com',
|
||||
url='http://github.com/kennethreitz/tablib',
|
||||
packages= [
|
||||
'tablib', 'tablib.formats',
|
||||
'tablib.packages.simplejson'
|
||||
'tablib.packages.xlwt',
|
||||
'tablib.packages.yaml',
|
||||
],
|
||||
install_requires=required,
|
||||
license='MIT',
|
||||
classifiers=(
|
||||
'Development Status :: 5 - Production/Stable',
|
||||
'Intended Audience :: Developers',
|
||||
'Natural Language :: English',
|
||||
'License :: OSI Approved :: MIT License',
|
||||
'Programming Language :: Python',
|
||||
# 'Programming Language :: Python :: 2.5',
|
||||
'Programming Language :: Python :: 2.6',
|
||||
'Programming Language :: Python :: 2.7',
|
||||
# 'Programming Language :: Python :: 3.0',
|
||||
# 'Programming Language :: Python :: 3.1',
|
||||
),
|
||||
# entry_points={
|
||||
# 'console_scripts': [
|
||||
# 'tabbed = tablib.cli:start',
|
||||
# ],
|
||||
# }
|
||||
name='tablib',
|
||||
use_scm_version=True,
|
||||
setup_requires=['setuptools_scm'],
|
||||
description='Format agnostic tabular data library (XLS, JSON, YAML, CSV)',
|
||||
long_description=(open('README.md').read() + '\n\n' +
|
||||
open('HISTORY.md').read()),
|
||||
long_description_content_type="text/markdown",
|
||||
author='Kenneth Reitz',
|
||||
author_email='me@kennethreitz.org',
|
||||
maintainer='Jazzband',
|
||||
maintainer_email='roadies@jazzband.co',
|
||||
url='https://tablib.readthedocs.io',
|
||||
packages=find_packages(where="src"),
|
||||
package_dir={"": "src"},
|
||||
license='MIT',
|
||||
classifiers=[
|
||||
'Development Status :: 5 - Production/Stable',
|
||||
'Intended Audience :: Developers',
|
||||
'Natural Language :: English',
|
||||
'License :: OSI Approved :: MIT License',
|
||||
'Programming Language :: Python',
|
||||
'Programming Language :: Python :: 2',
|
||||
'Programming Language :: Python :: 2.7',
|
||||
'Programming Language :: Python :: 3',
|
||||
'Programming Language :: Python :: 3.5',
|
||||
'Programming Language :: Python :: 3.6',
|
||||
'Programming Language :: Python :: 3.7',
|
||||
'Programming Language :: Python :: 3.8',
|
||||
],
|
||||
python_requires='>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*',
|
||||
install_requires=install,
|
||||
extras_require={
|
||||
'pandas': ['pandas'],
|
||||
},
|
||||
)
|
||||
|
||||
@@ -0,0 +1,13 @@
|
||||
""" Tablib. """
|
||||
from pkg_resources import get_distribution, DistributionNotFound
|
||||
|
||||
from tablib.core import (
|
||||
Databook, Dataset, detect_format, import_set, import_book,
|
||||
InvalidDatasetType, InvalidDimensions, UnsupportedFormat
|
||||
)
|
||||
|
||||
try:
|
||||
__version__ = get_distribution(__name__).version
|
||||
except DistributionNotFound:
|
||||
# package is not installed
|
||||
__version__ = None
|
||||
@@ -0,0 +1,36 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
tablib.compat
|
||||
~~~~~~~~~~~~~
|
||||
|
||||
Tablib compatiblity module.
|
||||
|
||||
"""
|
||||
|
||||
import sys
|
||||
|
||||
is_py3 = (sys.version_info[0] > 2)
|
||||
|
||||
|
||||
if is_py3:
|
||||
from io import StringIO
|
||||
from statistics import median
|
||||
from itertools import zip_longest as izip_longest
|
||||
import csv
|
||||
import tablib.packages.dbfpy3 as dbfpy
|
||||
|
||||
unicode = str
|
||||
xrange = range
|
||||
|
||||
else:
|
||||
from StringIO import StringIO
|
||||
from tablib.packages.statistics import median
|
||||
from itertools import izip_longest
|
||||
from backports import csv
|
||||
import tablib.packages.dbfpy as dbfpy
|
||||
|
||||
unicode = unicode
|
||||
xrange = xrange
|
||||
|
||||
from MarkupPy import markup # Kept temporarily to avoid breaking existing imports
|
||||
+1160
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,21 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - formats
|
||||
"""
|
||||
|
||||
from . import _csv as csv
|
||||
from . import _json as json
|
||||
from . import _xls as xls
|
||||
from . import _yaml as yaml
|
||||
from . import _tsv as tsv
|
||||
from . import _html as html
|
||||
from . import _xlsx as xlsx
|
||||
from . import _ods as ods
|
||||
from . import _dbf as dbf
|
||||
from . import _latex as latex
|
||||
from . import _df as df
|
||||
from . import _rst as rst
|
||||
from . import _jira as jira
|
||||
|
||||
# xlsx before as xls (xlrd) can also read xlsx
|
||||
available = (json, xlsx, xls, yaml, csv, dbf, tsv, html, jira, latex, ods, df, rst)
|
||||
@@ -0,0 +1,59 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - *SV Support.
|
||||
"""
|
||||
|
||||
from tablib.compat import csv, StringIO, unicode
|
||||
|
||||
|
||||
title = 'csv'
|
||||
extensions = ('csv',)
|
||||
|
||||
|
||||
DEFAULT_DELIMITER = unicode(',')
|
||||
|
||||
|
||||
def export_stream_set(dataset, **kwargs):
|
||||
"""Returns CSV representation of Dataset as file-like."""
|
||||
stream = StringIO()
|
||||
|
||||
kwargs.setdefault('delimiter', DEFAULT_DELIMITER)
|
||||
|
||||
_csv = csv.writer(stream, **kwargs)
|
||||
|
||||
for row in dataset._package(dicts=False):
|
||||
_csv.writerow(row)
|
||||
|
||||
stream.seek(0)
|
||||
return stream
|
||||
|
||||
|
||||
def export_set(dataset, **kwargs):
|
||||
"""Returns CSV representation of Dataset."""
|
||||
stream = export_stream_set(dataset, **kwargs)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def import_set(dset, in_stream, headers=True, **kwargs):
|
||||
"""Returns dataset from CSV stream."""
|
||||
|
||||
dset.wipe()
|
||||
|
||||
kwargs.setdefault('delimiter', DEFAULT_DELIMITER)
|
||||
|
||||
rows = csv.reader(StringIO(in_stream), **kwargs)
|
||||
for i, row in enumerate(rows):
|
||||
|
||||
if (i == 0) and (headers):
|
||||
dset.headers = row
|
||||
elif row:
|
||||
dset.append(row)
|
||||
|
||||
|
||||
def detect(stream, delimiter=DEFAULT_DELIMITER):
|
||||
"""Returns True if given stream is valid CSV."""
|
||||
try:
|
||||
csv.Sniffer().sniff(stream, delimiters=delimiter)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
@@ -0,0 +1,87 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - DBF Support.
|
||||
"""
|
||||
import tempfile
|
||||
import struct
|
||||
import os
|
||||
|
||||
from tablib.compat import StringIO
|
||||
from tablib.compat import dbfpy
|
||||
from tablib.compat import is_py3
|
||||
|
||||
if is_py3:
|
||||
from tablib.packages.dbfpy3 import dbf
|
||||
from tablib.packages.dbfpy3 import dbfnew
|
||||
from tablib.packages.dbfpy3 import record as dbfrecord
|
||||
import io
|
||||
else:
|
||||
from tablib.packages.dbfpy import dbf
|
||||
from tablib.packages.dbfpy import dbfnew
|
||||
from tablib.packages.dbfpy import record as dbfrecord
|
||||
|
||||
|
||||
title = 'dbf'
|
||||
extensions = ('csv',)
|
||||
|
||||
DEFAULT_ENCODING = 'utf-8'
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns DBF representation of a Dataset"""
|
||||
new_dbf = dbfnew.dbf_new()
|
||||
temp_file, temp_uri = tempfile.mkstemp()
|
||||
|
||||
# create the appropriate fields based on the contents of the first row
|
||||
first_row = dataset[0]
|
||||
for fieldname, field_value in zip(dataset.headers, first_row):
|
||||
if type(field_value) in [int, float]:
|
||||
new_dbf.add_field(fieldname, 'N', 10, 8)
|
||||
else:
|
||||
new_dbf.add_field(fieldname, 'C', 80)
|
||||
|
||||
new_dbf.write(temp_uri)
|
||||
|
||||
dbf_file = dbf.Dbf(temp_uri, readOnly=0)
|
||||
for row in dataset:
|
||||
record = dbfrecord.DbfRecord(dbf_file)
|
||||
for fieldname, field_value in zip(dataset.headers, row):
|
||||
record[fieldname] = field_value
|
||||
record.store()
|
||||
|
||||
dbf_file.close()
|
||||
dbf_stream = open(temp_uri, 'rb')
|
||||
if is_py3:
|
||||
stream = io.BytesIO(dbf_stream.read())
|
||||
else:
|
||||
stream = StringIO(dbf_stream.read())
|
||||
dbf_stream.close()
|
||||
os.close(temp_file)
|
||||
os.remove(temp_uri)
|
||||
return stream.getvalue()
|
||||
|
||||
def import_set(dset, in_stream, headers=True):
|
||||
"""Returns a dataset from a DBF stream."""
|
||||
|
||||
dset.wipe()
|
||||
if is_py3:
|
||||
_dbf = dbf.Dbf(io.BytesIO(in_stream))
|
||||
else:
|
||||
_dbf = dbf.Dbf(StringIO(in_stream))
|
||||
dset.headers = _dbf.fieldNames
|
||||
for record in range(_dbf.recordCount):
|
||||
row = [_dbf[record][f] for f in _dbf.fieldNames]
|
||||
dset.append(row)
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if the given stream is valid DBF"""
|
||||
#_dbf = dbf.Table(StringIO(stream))
|
||||
try:
|
||||
if is_py3:
|
||||
if type(stream) is not bytes:
|
||||
stream = bytes(stream, 'utf-8')
|
||||
_dbf = dbf.Dbf(io.BytesIO(stream), readOnly=True)
|
||||
else:
|
||||
_dbf = dbf.Dbf(StringIO(stream), readOnly=True)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
@@ -0,0 +1,43 @@
|
||||
""" Tablib - DataFrame Support.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from io import BytesIO
|
||||
|
||||
try:
|
||||
from pandas import DataFrame
|
||||
except ImportError:
|
||||
DataFrame = None
|
||||
|
||||
import tablib
|
||||
|
||||
from tablib.compat import unicode
|
||||
|
||||
title = 'df'
|
||||
extensions = ('df', )
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is a DataFrame."""
|
||||
if DataFrame is None:
|
||||
return False
|
||||
try:
|
||||
DataFrame(stream)
|
||||
return True
|
||||
except ValueError:
|
||||
return False
|
||||
|
||||
|
||||
def export_set(dset, index=None):
|
||||
"""Returns DataFrame representation of DataBook."""
|
||||
if DataFrame is None:
|
||||
raise NotImplementedError(
|
||||
'DataFrame Format requires `pandas` to be installed.'
|
||||
' Try `pip install tablib[pandas]`.')
|
||||
dataframe = DataFrame(dset.dict, columns=dset.headers)
|
||||
return dataframe
|
||||
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
"""Returns dataset from DataFrame."""
|
||||
dset.wipe()
|
||||
dset.dict = in_stream.to_dict(orient='records')
|
||||
@@ -0,0 +1,65 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - HTML export support.
|
||||
"""
|
||||
|
||||
import codecs
|
||||
import sys
|
||||
from io import BytesIO
|
||||
|
||||
from MarkupPy import markup
|
||||
import tablib
|
||||
from tablib.compat import unicode
|
||||
|
||||
BOOK_ENDINGS = 'h3'
|
||||
|
||||
title = 'html'
|
||||
extensions = ('html', )
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""HTML representation of a Dataset."""
|
||||
|
||||
stream = BytesIO()
|
||||
|
||||
page = markup.page()
|
||||
page.table.open()
|
||||
|
||||
if dataset.headers is not None:
|
||||
new_header = [item if item is not None else '' for item in dataset.headers]
|
||||
|
||||
page.thead.open()
|
||||
headers = markup.oneliner.th(new_header)
|
||||
page.tr(headers)
|
||||
page.thead.close()
|
||||
|
||||
for row in dataset:
|
||||
new_row = [item if item is not None else '' for item in row]
|
||||
|
||||
html_row = markup.oneliner.td(new_row)
|
||||
page.tr(html_row)
|
||||
|
||||
page.table.close()
|
||||
|
||||
# Allow unicode characters in output
|
||||
wrapper = codecs.getwriter("utf8")(stream)
|
||||
wrapper.writelines(unicode(page))
|
||||
|
||||
return stream.getvalue().decode('utf-8')
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""HTML representation of a Databook."""
|
||||
|
||||
stream = BytesIO()
|
||||
|
||||
# Allow unicode characters in output
|
||||
wrapper = codecs.getwriter("utf8")(stream)
|
||||
|
||||
for i, dset in enumerate(databook._datasets):
|
||||
title = (dset.title if dset.title else 'Set %s' % (i))
|
||||
wrapper.write('<%s>%s</%s>\n' % (BOOK_ENDINGS, title, BOOK_ENDINGS))
|
||||
wrapper.write(dset.html)
|
||||
wrapper.write('\n')
|
||||
|
||||
return stream.getvalue().decode('utf-8')
|
||||
@@ -0,0 +1,39 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""Tablib - Jira table export support.
|
||||
|
||||
Generates a Jira table from the dataset.
|
||||
"""
|
||||
from tablib.compat import unicode
|
||||
|
||||
title = 'jira'
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Formats the dataset according to the Jira table syntax:
|
||||
|
||||
||heading 1||heading 2||heading 3||
|
||||
|col A1|col A2|col A3|
|
||||
|col B1|col B2|col B3|
|
||||
|
||||
:param dataset: dataset to serialize
|
||||
:type dataset: tablib.core.Dataset
|
||||
"""
|
||||
|
||||
header = _get_header(dataset.headers) if dataset.headers else ''
|
||||
body = _get_body(dataset)
|
||||
return '%s\n%s' % (header, body) if header else body
|
||||
|
||||
|
||||
def _get_body(dataset):
|
||||
return '\n'.join([_serialize_row(row) for row in dataset])
|
||||
|
||||
|
||||
def _get_header(headers):
|
||||
return _serialize_row(headers, delimiter='||')
|
||||
|
||||
|
||||
def _serialize_row(row, delimiter='|'):
|
||||
return '%s%s%s' % (delimiter,
|
||||
delimiter.join([unicode(item) if item else ' ' for item in row]),
|
||||
delimiter)
|
||||
@@ -0,0 +1,59 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - JSON Support
|
||||
"""
|
||||
import decimal
|
||||
import json
|
||||
from uuid import UUID
|
||||
|
||||
import tablib
|
||||
|
||||
|
||||
title = 'json'
|
||||
extensions = ('json', 'jsn')
|
||||
|
||||
|
||||
def serialize_objects_handler(obj):
|
||||
if isinstance(obj, (decimal.Decimal, UUID)):
|
||||
return str(obj)
|
||||
elif hasattr(obj, 'isoformat'):
|
||||
return obj.isoformat()
|
||||
else:
|
||||
return obj
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns JSON representation of Dataset."""
|
||||
return json.dumps(dataset.dict, default=serialize_objects_handler)
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns JSON representation of Databook."""
|
||||
return json.dumps(databook._package(), default=serialize_objects_handler)
|
||||
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
"""Returns dataset from JSON stream."""
|
||||
|
||||
dset.wipe()
|
||||
dset.dict = json.loads(in_stream)
|
||||
|
||||
|
||||
def import_book(dbook, in_stream):
|
||||
"""Returns databook from JSON stream."""
|
||||
|
||||
dbook.wipe()
|
||||
for sheet in json.loads(in_stream):
|
||||
data = tablib.Dataset()
|
||||
data.title = sheet['title']
|
||||
data.dict = sheet['data']
|
||||
dbook.add_sheet(data)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid JSON."""
|
||||
try:
|
||||
json.loads(stream)
|
||||
return True
|
||||
except (TypeError, ValueError):
|
||||
return False
|
||||
@@ -0,0 +1,134 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""Tablib - LaTeX table export support.
|
||||
|
||||
Generates a LaTeX booktabs-style table from the dataset.
|
||||
"""
|
||||
import re
|
||||
|
||||
from tablib.compat import unicode
|
||||
|
||||
title = 'latex'
|
||||
extensions = ('tex',)
|
||||
|
||||
TABLE_TEMPLATE = """\
|
||||
%% Note: add \\usepackage{booktabs} to your preamble
|
||||
%%
|
||||
\\begin{table}[!htbp]
|
||||
\\centering
|
||||
%(CAPTION)s
|
||||
\\begin{tabular}{%(COLSPEC)s}
|
||||
\\toprule
|
||||
%(HEADER)s
|
||||
%(MIDRULE)s
|
||||
%(BODY)s
|
||||
\\bottomrule
|
||||
\\end{tabular}
|
||||
\\end{table}
|
||||
"""
|
||||
|
||||
TEX_RESERVED_SYMBOLS_MAP = dict([
|
||||
('\\', '\\textbackslash{}'),
|
||||
('{', '\\{'),
|
||||
('}', '\\}'),
|
||||
('$', '\\$'),
|
||||
('&', '\\&'),
|
||||
('#', '\\#'),
|
||||
('^', '\\textasciicircum{}'),
|
||||
('_', '\\_'),
|
||||
('~', '\\textasciitilde{}'),
|
||||
('%', '\\%'),
|
||||
])
|
||||
|
||||
TEX_RESERVED_SYMBOLS_RE = re.compile(
|
||||
'(%s)' % '|'.join(map(re.escape, TEX_RESERVED_SYMBOLS_MAP.keys())))
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns LaTeX representation of dataset
|
||||
|
||||
:param dataset: dataset to serialize
|
||||
:type dataset: tablib.core.Dataset
|
||||
"""
|
||||
|
||||
caption = '\\caption{%s}' % dataset.title if dataset.title else '%'
|
||||
colspec = _colspec(dataset.width)
|
||||
header = _serialize_row(dataset.headers) if dataset.headers else ''
|
||||
midrule = _midrule(dataset.width)
|
||||
body = '\n'.join([_serialize_row(row) for row in dataset])
|
||||
return TABLE_TEMPLATE % dict(CAPTION=caption, COLSPEC=colspec,
|
||||
HEADER=header, MIDRULE=midrule, BODY=body)
|
||||
|
||||
|
||||
def _colspec(dataset_width):
|
||||
"""Generates the column specification for the LaTeX `tabular` environment
|
||||
based on the dataset width.
|
||||
|
||||
The first column is justified to the left, all further columns are aligned
|
||||
to the right.
|
||||
|
||||
.. note:: This is only a heuristic and most probably has to be fine-tuned
|
||||
post export. Column alignment should depend on the data type, e.g., textual
|
||||
content should usually be aligned to the left while numeric content almost
|
||||
always should be aligned to the right.
|
||||
|
||||
:param dataset_width: width of the dataset
|
||||
"""
|
||||
|
||||
spec = 'l'
|
||||
for _ in range(1, dataset_width):
|
||||
spec += 'r'
|
||||
return spec
|
||||
|
||||
|
||||
def _midrule(dataset_width):
|
||||
"""Generates the table `midrule`, which may be composed of several
|
||||
`cmidrules`.
|
||||
|
||||
:param dataset_width: width of the dataset to serialize
|
||||
"""
|
||||
|
||||
if not dataset_width or dataset_width == 1:
|
||||
return '\\midrule'
|
||||
return ' '.join([_cmidrule(colindex, dataset_width) for colindex in
|
||||
range(1, dataset_width + 1)])
|
||||
|
||||
|
||||
def _cmidrule(colindex, dataset_width):
|
||||
"""Generates the `cmidrule` for a single column with appropriate trimming
|
||||
based on the column position.
|
||||
|
||||
:param colindex: Column index
|
||||
:param dataset_width: width of the dataset
|
||||
"""
|
||||
|
||||
rule = '\\cmidrule(%s){%d-%d}'
|
||||
if colindex == 1:
|
||||
# Rule of first column is trimmed on the right
|
||||
return rule % ('r', colindex, colindex)
|
||||
if colindex == dataset_width:
|
||||
# Rule of last column is trimmed on the left
|
||||
return rule % ('l', colindex, colindex)
|
||||
# Inner columns are trimmed on the left and right
|
||||
return rule % ('lr', colindex, colindex)
|
||||
|
||||
|
||||
def _serialize_row(row):
|
||||
"""Returns string representation of a single row.
|
||||
|
||||
:param row: single dataset row
|
||||
"""
|
||||
|
||||
new_row = [_escape_tex_reserved_symbols(unicode(item)) if item else '' for
|
||||
item in row]
|
||||
return 6 * ' ' + ' & '.join(new_row) + ' \\\\'
|
||||
|
||||
|
||||
def _escape_tex_reserved_symbols(input):
|
||||
"""Escapes all TeX reserved symbols ('_', '~', etc.) in a string.
|
||||
|
||||
:param input: String to escape
|
||||
"""
|
||||
def replace(match):
|
||||
return TEX_RESERVED_SYMBOLS_MAP[match.group()]
|
||||
return TEX_RESERVED_SYMBOLS_RE.sub(replace, input)
|
||||
@@ -0,0 +1,104 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - ODF Support.
|
||||
"""
|
||||
|
||||
from io import BytesIO
|
||||
from odf import opendocument, style, table, text
|
||||
from tablib.compat import unicode
|
||||
|
||||
title = 'ods'
|
||||
extensions = ('ods',)
|
||||
|
||||
bold = style.Style(name="bold", family="paragraph")
|
||||
bold.addElement(style.TextProperties(fontweight="bold", fontweightasian="bold", fontweightcomplex="bold"))
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns ODF representation of Dataset."""
|
||||
|
||||
wb = opendocument.OpenDocumentSpreadsheet()
|
||||
wb.automaticstyles.addElement(bold)
|
||||
|
||||
ws = table.Table(name=dataset.title if dataset.title else 'Tablib Dataset')
|
||||
wb.spreadsheet.addElement(ws)
|
||||
dset_sheet(dataset, ws)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns ODF representation of DataBook."""
|
||||
|
||||
wb = opendocument.OpenDocumentSpreadsheet()
|
||||
wb.automaticstyles.addElement(bold)
|
||||
|
||||
for i, dset in enumerate(databook._datasets):
|
||||
ws = table.Table(name=dset.title if dset.title else 'Sheet%s' % (i))
|
||||
wb.spreadsheet.addElement(ws)
|
||||
dset_sheet(dset, ws)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def dset_sheet(dataset, ws):
|
||||
"""Completes given worksheet from given Dataset."""
|
||||
_package = dataset._package(dicts=False)
|
||||
|
||||
for i, sep in enumerate(dataset._separators):
|
||||
_offset = i
|
||||
_package.insert((sep[0] + _offset), (sep[1],))
|
||||
|
||||
for i, row in enumerate(_package):
|
||||
row_number = i + 1
|
||||
odf_row = table.TableRow(stylename=bold, defaultcellstylename='bold')
|
||||
for j, col in enumerate(row):
|
||||
try:
|
||||
col = unicode(col, errors='ignore')
|
||||
except TypeError:
|
||||
## col is already unicode
|
||||
pass
|
||||
ws.addElement(table.TableColumn())
|
||||
|
||||
# bold headers
|
||||
if (row_number == 1) and dataset.headers:
|
||||
odf_row.setAttribute('stylename', bold)
|
||||
ws.addElement(odf_row)
|
||||
cell = table.TableCell()
|
||||
p = text.P()
|
||||
p.addElement(text.Span(text=col, stylename=bold))
|
||||
cell.addElement(p)
|
||||
odf_row.addElement(cell)
|
||||
|
||||
# wrap the rest
|
||||
else:
|
||||
try:
|
||||
if '\n' in col:
|
||||
ws.addElement(odf_row)
|
||||
cell = table.TableCell()
|
||||
cell.addElement(text.P(text=col))
|
||||
odf_row.addElement(cell)
|
||||
else:
|
||||
ws.addElement(odf_row)
|
||||
cell = table.TableCell()
|
||||
cell.addElement(text.P(text=col))
|
||||
odf_row.addElement(cell)
|
||||
except TypeError:
|
||||
ws.addElement(odf_row)
|
||||
cell = table.TableCell()
|
||||
cell.addElement(text.P(text=col))
|
||||
odf_row.addElement(cell)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
if isinstance(stream, bytes):
|
||||
# load expects a file-like object.
|
||||
stream = BytesIO(stream)
|
||||
try:
|
||||
opendocument.load(stream)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
@@ -0,0 +1,273 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - reStructuredText Support
|
||||
"""
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
from __future__ import unicode_literals
|
||||
|
||||
from textwrap import TextWrapper
|
||||
|
||||
from tablib.compat import (
|
||||
median,
|
||||
unicode,
|
||||
izip_longest,
|
||||
)
|
||||
|
||||
|
||||
title = 'rst'
|
||||
extensions = ('rst',)
|
||||
|
||||
|
||||
MAX_TABLE_WIDTH = 80 # Roughly. It may be wider to avoid breaking words.
|
||||
|
||||
|
||||
JUSTIFY_LEFT = 'left'
|
||||
JUSTIFY_CENTER = 'center'
|
||||
JUSTIFY_RIGHT = 'right'
|
||||
JUSTIFY_VALUES = (JUSTIFY_LEFT, JUSTIFY_CENTER, JUSTIFY_RIGHT)
|
||||
|
||||
|
||||
def to_unicode(value):
|
||||
if isinstance(value, bytes):
|
||||
return value.decode('utf-8')
|
||||
return unicode(value)
|
||||
|
||||
|
||||
def _max_word_len(text):
|
||||
"""
|
||||
Return the length of the longest word in `text`.
|
||||
|
||||
|
||||
>>> _max_word_len('Python Module for Tabular Datasets')
|
||||
8
|
||||
|
||||
"""
|
||||
return max((len(word) for word in text.split()))
|
||||
|
||||
|
||||
def _get_column_string_lengths(dataset):
|
||||
"""
|
||||
Returns a list of string lengths of each column, and a list of
|
||||
maximum word lengths.
|
||||
"""
|
||||
if dataset.headers:
|
||||
column_lengths = [[len(h)] for h in dataset.headers]
|
||||
word_lens = [_max_word_len(h) for h in dataset.headers]
|
||||
else:
|
||||
column_lengths = [[] for _ in range(dataset.width)]
|
||||
word_lens = [0 for _ in range(dataset.width)]
|
||||
for row in dataset.dict:
|
||||
values = iter(row.values() if hasattr(row, 'values') else row)
|
||||
for i, val in enumerate(values):
|
||||
text = to_unicode(val)
|
||||
column_lengths[i].append(len(text))
|
||||
word_lens[i] = max(word_lens[i], _max_word_len(text))
|
||||
return column_lengths, word_lens
|
||||
|
||||
|
||||
def _row_to_lines(values, widths, wrapper, sep='|', justify=JUSTIFY_LEFT):
|
||||
"""
|
||||
Returns a table row of wrapped values as a list of lines
|
||||
"""
|
||||
if justify not in JUSTIFY_VALUES:
|
||||
raise ValueError('Value of "justify" must be one of "{}"'.format(
|
||||
'", "'.join(JUSTIFY_VALUES)
|
||||
))
|
||||
if justify == JUSTIFY_LEFT:
|
||||
just = lambda text, width: text.ljust(width)
|
||||
elif justify == JUSTIFY_CENTER:
|
||||
just = lambda text, width: text.center(width)
|
||||
else:
|
||||
just = lambda text, width: text.rjust(width)
|
||||
lpad = sep + ' ' if sep else ''
|
||||
rpad = ' ' + sep if sep else ''
|
||||
pad = ' ' + sep + ' '
|
||||
cells = []
|
||||
for value, width in zip(values, widths):
|
||||
wrapper.width = width
|
||||
text = to_unicode(value)
|
||||
cell = wrapper.wrap(text)
|
||||
cells.append(cell)
|
||||
lines = izip_longest(*cells, fillvalue='')
|
||||
lines = (
|
||||
(just(cell_line, widths[i]) for i, cell_line in enumerate(line))
|
||||
for line in lines
|
||||
)
|
||||
lines = [''.join((lpad, pad.join(line), rpad)) for line in lines]
|
||||
return lines
|
||||
|
||||
|
||||
def _get_column_widths(dataset, max_table_width=MAX_TABLE_WIDTH, pad_len=3):
|
||||
"""
|
||||
Returns a list of column widths proportional to the median length
|
||||
of the text in their cells.
|
||||
"""
|
||||
str_lens, word_lens = _get_column_string_lengths(dataset)
|
||||
median_lens = [int(median(lens)) for lens in str_lens]
|
||||
total = sum(median_lens)
|
||||
if total > max_table_width - (pad_len * len(median_lens)):
|
||||
column_widths = (max_table_width * l // total for l in median_lens)
|
||||
else:
|
||||
column_widths = (l for l in median_lens)
|
||||
# Allow for separator and padding:
|
||||
column_widths = (w - pad_len if w > pad_len else w for w in column_widths)
|
||||
# Rather widen table than break words:
|
||||
column_widths = [max(w, l) for w, l in zip(column_widths, word_lens)]
|
||||
return column_widths
|
||||
|
||||
|
||||
def export_set_as_simple_table(dataset, column_widths=None):
|
||||
"""
|
||||
Returns reStructuredText grid table representation of dataset.
|
||||
"""
|
||||
lines = []
|
||||
wrapper = TextWrapper()
|
||||
if column_widths is None:
|
||||
column_widths = _get_column_widths(dataset, pad_len=2)
|
||||
border = ' '.join(['=' * w for w in column_widths])
|
||||
|
||||
lines.append(border)
|
||||
if dataset.headers:
|
||||
lines.extend(_row_to_lines(
|
||||
dataset.headers,
|
||||
column_widths,
|
||||
wrapper,
|
||||
sep='',
|
||||
justify=JUSTIFY_CENTER,
|
||||
))
|
||||
lines.append(border)
|
||||
for row in dataset.dict:
|
||||
values = iter(row.values() if hasattr(row, 'values') else row)
|
||||
lines.extend(_row_to_lines(values, column_widths, wrapper, ''))
|
||||
lines.append(border)
|
||||
return '\n'.join(lines)
|
||||
|
||||
|
||||
def export_set_as_grid_table(dataset, column_widths=None):
|
||||
"""
|
||||
Returns reStructuredText grid table representation of dataset.
|
||||
|
||||
|
||||
>>> from tablib import Dataset
|
||||
>>> from tablib.formats import rst
|
||||
>>> bits = ((0, 0), (1, 0), (0, 1), (1, 1))
|
||||
>>> data = Dataset()
|
||||
>>> data.headers = ['A', 'B', 'A and B']
|
||||
>>> for a, b in bits:
|
||||
... data.append([bool(a), bool(b), bool(a * b)])
|
||||
>>> print(rst.export_set(data, force_grid=True))
|
||||
+-------+-------+-------+
|
||||
| A | B | A and |
|
||||
| | | B |
|
||||
+=======+=======+=======+
|
||||
| False | False | False |
|
||||
+-------+-------+-------+
|
||||
| True | False | False |
|
||||
+-------+-------+-------+
|
||||
| False | True | False |
|
||||
+-------+-------+-------+
|
||||
| True | True | True |
|
||||
+-------+-------+-------+
|
||||
|
||||
"""
|
||||
lines = []
|
||||
wrapper = TextWrapper()
|
||||
if column_widths is None:
|
||||
column_widths = _get_column_widths(dataset)
|
||||
header_sep = '+=' + '=+='.join(['=' * w for w in column_widths]) + '=+'
|
||||
row_sep = '+-' + '-+-'.join(['-' * w for w in column_widths]) + '-+'
|
||||
|
||||
lines.append(row_sep)
|
||||
if dataset.headers:
|
||||
lines.extend(_row_to_lines(
|
||||
dataset.headers,
|
||||
column_widths,
|
||||
wrapper,
|
||||
justify=JUSTIFY_CENTER,
|
||||
))
|
||||
lines.append(header_sep)
|
||||
for row in dataset.dict:
|
||||
values = iter(row.values() if hasattr(row, 'values') else row)
|
||||
lines.extend(_row_to_lines(values, column_widths, wrapper))
|
||||
lines.append(row_sep)
|
||||
return '\n'.join(lines)
|
||||
|
||||
|
||||
def _use_simple_table(head0, col0, width0):
|
||||
"""
|
||||
Use a simple table if the text in the first column is never wrapped
|
||||
|
||||
|
||||
>>> _use_simple_table('menu', ['egg', 'bacon'], 10)
|
||||
True
|
||||
>>> _use_simple_table(None, ['lobster thermidor', 'spam'], 10)
|
||||
False
|
||||
|
||||
"""
|
||||
if head0 is not None:
|
||||
head0 = to_unicode(head0)
|
||||
if len(head0) > width0:
|
||||
return False
|
||||
for cell in col0:
|
||||
cell = to_unicode(cell)
|
||||
if len(cell) > width0:
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def export_set(dataset, **kwargs):
|
||||
"""
|
||||
Returns reStructuredText table representation of dataset.
|
||||
|
||||
Returns a simple table if the text in the first column is never
|
||||
wrapped, otherwise returns a grid table.
|
||||
|
||||
|
||||
>>> from tablib import Dataset
|
||||
>>> bits = ((0, 0), (1, 0), (0, 1), (1, 1))
|
||||
>>> data = Dataset()
|
||||
>>> data.headers = ['A', 'B', 'A and B']
|
||||
>>> for a, b in bits:
|
||||
... data.append([bool(a), bool(b), bool(a * b)])
|
||||
>>> table = data.rst
|
||||
>>> table.split('\\n') == [
|
||||
... '===== ===== =====',
|
||||
... ' A B A and',
|
||||
... ' B ',
|
||||
... '===== ===== =====',
|
||||
... 'False False False',
|
||||
... 'True False False',
|
||||
... 'False True False',
|
||||
... 'True True True ',
|
||||
... '===== ===== =====',
|
||||
... ]
|
||||
True
|
||||
|
||||
"""
|
||||
if not dataset.dict:
|
||||
return ''
|
||||
force_grid = kwargs.get('force_grid', False)
|
||||
max_table_width = kwargs.get('max_table_width', MAX_TABLE_WIDTH)
|
||||
column_widths = _get_column_widths(dataset, max_table_width)
|
||||
|
||||
use_simple_table = _use_simple_table(
|
||||
dataset.headers[0] if dataset.headers else None,
|
||||
dataset.get_col(0),
|
||||
column_widths[0],
|
||||
)
|
||||
if use_simple_table and not force_grid:
|
||||
return export_set_as_simple_table(dataset, column_widths)
|
||||
else:
|
||||
return export_set_as_grid_table(dataset, column_widths)
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""
|
||||
reStructuredText representation of a Databook.
|
||||
|
||||
Tables are separated by a blank line. All tables use the grid
|
||||
format.
|
||||
"""
|
||||
return '\n\n'.join(export_set(dataset, force_grid=True)
|
||||
for dataset in databook._datasets)
|
||||
@@ -0,0 +1,30 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - TSV (Tab Separated Values) Support.
|
||||
"""
|
||||
|
||||
from tablib.compat import unicode
|
||||
from tablib.formats._csv import (
|
||||
export_set as export_set_wrapper,
|
||||
import_set as import_set_wrapper,
|
||||
detect as detect_wrapper,
|
||||
)
|
||||
|
||||
title = 'tsv'
|
||||
extensions = ('tsv',)
|
||||
|
||||
DELIMITER = unicode('\t')
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns TSV representation of Dataset."""
|
||||
return export_set_wrapper(dataset, delimiter=DELIMITER)
|
||||
|
||||
|
||||
def import_set(dset, in_stream, headers=True):
|
||||
"""Returns dataset from TSV stream."""
|
||||
return import_set_wrapper(dset, in_stream, headers=headers, delimiter=DELIMITER)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid TSV."""
|
||||
return detect_wrapper(stream, delimiter=DELIMITER)
|
||||
@@ -0,0 +1,137 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - XLS Support.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from io import BytesIO
|
||||
|
||||
from tablib.compat import xrange
|
||||
import tablib
|
||||
import xlrd
|
||||
import xlwt
|
||||
from xlrd.biffh import XLRDError
|
||||
|
||||
title = 'xls'
|
||||
extensions = ('xls',)
|
||||
|
||||
# special styles
|
||||
wrap = xlwt.easyxf("alignment: wrap on")
|
||||
bold = xlwt.easyxf("font: bold on")
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is a readable excel file."""
|
||||
try:
|
||||
xlrd.open_workbook(file_contents=stream)
|
||||
return True
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
xlrd.open_workbook(file_contents=stream.read())
|
||||
return True
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
xlrd.open_workbook(filename=stream)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns XLS representation of Dataset."""
|
||||
|
||||
wb = xlwt.Workbook(encoding='utf8')
|
||||
ws = wb.add_sheet(dataset.title if dataset.title else 'Tablib Dataset')
|
||||
|
||||
dset_sheet(dataset, ws)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns XLS representation of DataBook."""
|
||||
|
||||
wb = xlwt.Workbook(encoding='utf8')
|
||||
|
||||
for i, dset in enumerate(databook._datasets):
|
||||
ws = wb.add_sheet(dset.title if dset.title else 'Sheet%s' % (i))
|
||||
|
||||
dset_sheet(dset, ws)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def import_set(dset, in_stream, headers=True):
|
||||
"""Returns databook from XLS stream."""
|
||||
|
||||
dset.wipe()
|
||||
|
||||
xls_book = xlrd.open_workbook(file_contents=in_stream)
|
||||
sheet = xls_book.sheet_by_index(0)
|
||||
|
||||
dset.title = sheet.name
|
||||
|
||||
for i in xrange(sheet.nrows):
|
||||
if (i == 0) and (headers):
|
||||
dset.headers = sheet.row_values(0)
|
||||
else:
|
||||
dset.append(sheet.row_values(i))
|
||||
|
||||
def import_book(dbook, in_stream, headers=True):
|
||||
"""Returns databook from XLS stream."""
|
||||
|
||||
dbook.wipe()
|
||||
|
||||
xls_book = xlrd.open_workbook(file_contents=in_stream)
|
||||
|
||||
for sheet in xls_book.sheets():
|
||||
data = tablib.Dataset()
|
||||
data.title = sheet.name
|
||||
|
||||
for i in xrange(sheet.nrows):
|
||||
if (i == 0) and (headers):
|
||||
data.headers = sheet.row_values(0)
|
||||
else:
|
||||
data.append(sheet.row_values(i))
|
||||
|
||||
dbook.add_sheet(data)
|
||||
|
||||
|
||||
def dset_sheet(dataset, ws):
|
||||
"""Completes given worksheet from given Dataset."""
|
||||
_package = dataset._package(dicts=False)
|
||||
|
||||
for i, sep in enumerate(dataset._separators):
|
||||
_offset = i
|
||||
_package.insert((sep[0] + _offset), (sep[1],))
|
||||
|
||||
for i, row in enumerate(_package):
|
||||
for j, col in enumerate(row):
|
||||
|
||||
# bold headers
|
||||
if (i == 0) and dataset.headers:
|
||||
ws.write(i, j, col, bold)
|
||||
|
||||
# frozen header row
|
||||
ws.panes_frozen = True
|
||||
ws.horz_split_pos = 1
|
||||
|
||||
# bold separators
|
||||
elif len(row) < dataset.width:
|
||||
ws.write(i, j, col, bold)
|
||||
|
||||
# wrap the rest
|
||||
else:
|
||||
try:
|
||||
if '\n' in col:
|
||||
ws.write(i, j, col, wrap)
|
||||
else:
|
||||
ws.write(i, j, col)
|
||||
except TypeError:
|
||||
ws.write(i, j, col)
|
||||
@@ -0,0 +1,144 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - XLSX Support.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from io import BytesIO
|
||||
|
||||
import openpyxl
|
||||
import tablib
|
||||
|
||||
Workbook = openpyxl.workbook.Workbook
|
||||
ExcelWriter = openpyxl.writer.excel.ExcelWriter
|
||||
get_column_letter = openpyxl.utils.get_column_letter
|
||||
|
||||
from tablib.compat import unicode
|
||||
|
||||
|
||||
title = 'xlsx'
|
||||
extensions = ('xlsx',)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is a readable excel file."""
|
||||
if isinstance(stream, bytes):
|
||||
# load_workbook expects a file-like object.
|
||||
stream = BytesIO(stream)
|
||||
try:
|
||||
openpyxl.reader.excel.load_workbook(stream, read_only=True)
|
||||
return True
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
def export_set(dataset, freeze_panes=True):
|
||||
"""Returns XLSX representation of Dataset."""
|
||||
|
||||
wb = Workbook()
|
||||
ws = wb.worksheets[0]
|
||||
ws.title = dataset.title if dataset.title else 'Tablib Dataset'
|
||||
|
||||
dset_sheet(dataset, ws, freeze_panes=freeze_panes)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def export_book(databook, freeze_panes=True):
|
||||
"""Returns XLSX representation of DataBook."""
|
||||
|
||||
wb = Workbook()
|
||||
for sheet in wb.worksheets:
|
||||
wb.remove(sheet)
|
||||
for i, dset in enumerate(databook._datasets):
|
||||
ws = wb.create_sheet()
|
||||
ws.title = dset.title if dset.title else 'Sheet%s' % (i)
|
||||
|
||||
dset_sheet(dset, ws, freeze_panes=freeze_panes)
|
||||
|
||||
stream = BytesIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def import_set(dset, in_stream, headers=True):
|
||||
"""Returns databook from XLS stream."""
|
||||
|
||||
dset.wipe()
|
||||
|
||||
xls_book = openpyxl.reader.excel.load_workbook(BytesIO(in_stream), read_only=True)
|
||||
sheet = xls_book.active
|
||||
|
||||
dset.title = sheet.title
|
||||
|
||||
for i, row in enumerate(sheet.rows):
|
||||
row_vals = [c.value for c in row]
|
||||
if (i == 0) and (headers):
|
||||
dset.headers = row_vals
|
||||
else:
|
||||
dset.append(row_vals)
|
||||
|
||||
|
||||
def import_book(dbook, in_stream, headers=True):
|
||||
"""Returns databook from XLS stream."""
|
||||
|
||||
dbook.wipe()
|
||||
|
||||
xls_book = openpyxl.reader.excel.load_workbook(BytesIO(in_stream), read_only=True)
|
||||
|
||||
for sheet in xls_book.worksheets:
|
||||
data = tablib.Dataset()
|
||||
data.title = sheet.title
|
||||
|
||||
for i, row in enumerate(sheet.rows):
|
||||
row_vals = [c.value for c in row]
|
||||
if (i == 0) and (headers):
|
||||
data.headers = row_vals
|
||||
else:
|
||||
data.append(row_vals)
|
||||
|
||||
dbook.add_sheet(data)
|
||||
|
||||
|
||||
def dset_sheet(dataset, ws, freeze_panes=True):
|
||||
"""Completes given worksheet from given Dataset."""
|
||||
_package = dataset._package(dicts=False)
|
||||
|
||||
for i, sep in enumerate(dataset._separators):
|
||||
_offset = i
|
||||
_package.insert((sep[0] + _offset), (sep[1],))
|
||||
|
||||
bold = openpyxl.styles.Font(bold=True)
|
||||
wrap_text = openpyxl.styles.Alignment(wrap_text=True)
|
||||
|
||||
for i, row in enumerate(_package):
|
||||
row_number = i + 1
|
||||
for j, col in enumerate(row):
|
||||
col_idx = get_column_letter(j + 1)
|
||||
cell = ws['%s%s' % (col_idx, row_number)]
|
||||
|
||||
# bold headers
|
||||
if (row_number == 1) and dataset.headers:
|
||||
cell.font = bold
|
||||
if freeze_panes:
|
||||
# Export Freeze only after first Line
|
||||
ws.freeze_panes = 'A2'
|
||||
|
||||
# bold separators
|
||||
elif len(row) < dataset.width:
|
||||
cell.font = bold
|
||||
|
||||
# wrap the rest
|
||||
else:
|
||||
try:
|
||||
str_col_value = unicode(col)
|
||||
except TypeError:
|
||||
str_col_value = ''
|
||||
if '\n' in str_col_value:
|
||||
cell.alignment = wrap_text
|
||||
|
||||
try:
|
||||
cell.value = col
|
||||
except (ValueError, TypeError):
|
||||
cell.value = unicode(col)
|
||||
@@ -0,0 +1,53 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - YAML Support.
|
||||
"""
|
||||
|
||||
import tablib
|
||||
import yaml
|
||||
|
||||
title = 'yaml'
|
||||
extensions = ('yaml', 'yml')
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns YAML representation of Dataset."""
|
||||
|
||||
return yaml.safe_dump(dataset._package(ordered=False))
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns YAML representation of Databook."""
|
||||
return yaml.safe_dump(databook._package(ordered=False))
|
||||
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
"""Returns dataset from YAML stream."""
|
||||
|
||||
dset.wipe()
|
||||
dset.dict = yaml.safe_load(in_stream)
|
||||
|
||||
|
||||
def import_book(dbook, in_stream):
|
||||
"""Returns databook from YAML stream."""
|
||||
|
||||
dbook.wipe()
|
||||
|
||||
for sheet in yaml.safe_load(in_stream):
|
||||
data = tablib.Dataset()
|
||||
data.title = sheet['title']
|
||||
data.dict = sheet['data']
|
||||
dbook.add_sheet(data)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid YAML."""
|
||||
try:
|
||||
_yaml = yaml.safe_load(stream)
|
||||
if isinstance(_yaml, (list, tuple, dict)):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
except (yaml.parser.ParserError, yaml.reader.ReaderError,
|
||||
yaml.scanner.ScannerError):
|
||||
return False
|
||||
@@ -0,0 +1,297 @@
|
||||
#! /usr/bin/env python
|
||||
"""DBF accessing helpers.
|
||||
|
||||
FIXME: more documentation needed
|
||||
|
||||
Examples:
|
||||
|
||||
Create new table, setup structure, add records:
|
||||
|
||||
dbf = Dbf(filename, new=True)
|
||||
dbf.addField(
|
||||
("NAME", "C", 15),
|
||||
("SURNAME", "C", 25),
|
||||
("INITIALS", "C", 10),
|
||||
("BIRTHDATE", "D"),
|
||||
)
|
||||
for (n, s, i, b) in (
|
||||
("John", "Miller", "YC", (1980, 10, 11)),
|
||||
("Andy", "Larkin", "", (1980, 4, 11)),
|
||||
):
|
||||
rec = dbf.newRecord()
|
||||
rec["NAME"] = n
|
||||
rec["SURNAME"] = s
|
||||
rec["INITIALS"] = i
|
||||
rec["BIRTHDATE"] = b
|
||||
rec.store()
|
||||
dbf.close()
|
||||
|
||||
Open existed dbf, read some data:
|
||||
|
||||
dbf = Dbf(filename, True)
|
||||
for rec in dbf:
|
||||
for fldName in dbf.fieldNames:
|
||||
print('%s:\t %s (%s)' % (fldName, rec[fldName],
|
||||
type(rec[fldName])))
|
||||
print()
|
||||
dbf.close()
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] export INVALID_VALUE;
|
||||
Dbf: added .ignoreErrors, .INVALID_VALUE
|
||||
04-jul-2006 [als] added export declaration
|
||||
20-dec-2005 [yc] removed fromStream and newDbf methods:
|
||||
use argument of __init__ call must be used instead;
|
||||
added class fields pointing to the header and
|
||||
record classes.
|
||||
17-dec-2005 [yc] split to several modules; reimplemented
|
||||
13-dec-2005 [yc] adapted to the changes of the `strutil` module.
|
||||
13-sep-2002 [als] support FoxPro Timestamp datatype
|
||||
15-nov-1999 [jjk] documentation updates, add demo
|
||||
24-aug-1998 [jjk] add some encodeValue methods (not tested), other tweaks
|
||||
08-jun-1998 [jjk] fix problems, add more features
|
||||
20-feb-1998 [jjk] fix problems, add more features
|
||||
19-feb-1998 [jjk] add create/write capabilities
|
||||
18-feb-1998 [jjk] from dbfload.py
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.7 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 09:23:13 $"[7:-2]
|
||||
__author__ = "Jeff Kunce <kuncej@mail.conservation.state.mo.us>"
|
||||
|
||||
__all__ = ["Dbf"]
|
||||
|
||||
from . import header
|
||||
from . import record
|
||||
from utils import INVALID_VALUE
|
||||
|
||||
|
||||
class Dbf(object):
|
||||
"""DBF accessor.
|
||||
|
||||
FIXME:
|
||||
docs and examples needed (dont' forget to tell
|
||||
about problems adding new fields on the fly)
|
||||
|
||||
Implementation notes:
|
||||
``_new`` field is used to indicate whether this is
|
||||
a new data table. `addField` could be used only for
|
||||
the new tables! If at least one record was appended
|
||||
to the table it's structure couldn't be changed.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("name", "header", "stream",
|
||||
"_changed", "_new", "_ignore_errors")
|
||||
|
||||
HeaderClass = header.DbfHeader
|
||||
RecordClass = record.DbfRecord
|
||||
INVALID_VALUE = INVALID_VALUE
|
||||
|
||||
# initialization and creation helpers
|
||||
|
||||
def __init__(self, f, readOnly=False, new=False, ignoreErrors=False):
|
||||
"""Initialize instance.
|
||||
|
||||
Arguments:
|
||||
f:
|
||||
Filename or file-like object.
|
||||
new:
|
||||
True if new data table must be created. Assume
|
||||
data table exists if this argument is False.
|
||||
readOnly:
|
||||
if ``f`` argument is a string file will
|
||||
be opend in read-only mode; in other cases
|
||||
this argument is ignored. This argument is ignored
|
||||
even if ``new`` argument is True.
|
||||
headerObj:
|
||||
`header.DbfHeader` instance or None. If this argument
|
||||
is None, new empty header will be used with the
|
||||
all fields set by default.
|
||||
ignoreErrors:
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
"""
|
||||
if isinstance(f, basestring):
|
||||
# a filename
|
||||
self.name = f
|
||||
if new:
|
||||
# new table (table file must be
|
||||
# created or opened and truncated)
|
||||
self.stream = file(f, "w+b")
|
||||
else:
|
||||
# tabe file must exist
|
||||
self.stream = file(f, ("r+b", "rb")[bool(readOnly)])
|
||||
else:
|
||||
# a stream
|
||||
self.name = getattr(f, "name", "")
|
||||
self.stream = f
|
||||
if new:
|
||||
# if this is a new table, header will be empty
|
||||
self.header = self.HeaderClass()
|
||||
else:
|
||||
# or instantiated using stream
|
||||
self.header = self.HeaderClass.fromStream(self.stream)
|
||||
self.ignoreErrors = ignoreErrors
|
||||
self._new = bool(new)
|
||||
self._changed = False
|
||||
|
||||
# properties
|
||||
|
||||
closed = property(lambda self: self.stream.closed)
|
||||
recordCount = property(lambda self: self.header.recordCount)
|
||||
fieldNames = property(
|
||||
lambda self: [_fld.name for _fld in self.header.fields])
|
||||
fieldDefs = property(lambda self: self.header.fields)
|
||||
changed = property(lambda self: self._changed or self.header.changed)
|
||||
|
||||
def ignoreErrors(self, value):
|
||||
"""Update `ignoreErrors` flag on the header object and self"""
|
||||
self.header.ignoreErrors = self._ignore_errors = bool(value)
|
||||
|
||||
ignoreErrors = property(
|
||||
lambda self: self._ignore_errors,
|
||||
ignoreErrors,
|
||||
doc="""Error processing mode for DBF field value conversion
|
||||
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
""")
|
||||
|
||||
# protected methods
|
||||
|
||||
def _fixIndex(self, index):
|
||||
"""Return fixed index.
|
||||
|
||||
This method fails if index isn't a numeric object
|
||||
(long or int). Or index isn't in a valid range
|
||||
(less or equal to the number of records in the db).
|
||||
|
||||
If ``index`` is a negative number, it will be
|
||||
treated as a negative indexes for list objects.
|
||||
|
||||
Return:
|
||||
Return value is numeric object maning valid index.
|
||||
|
||||
"""
|
||||
if not isinstance(index, (int, long)):
|
||||
raise TypeError("Index must be a numeric object")
|
||||
if index < 0:
|
||||
# index from the right side
|
||||
# fix it to the left-side index
|
||||
index += len(self) + 1
|
||||
if index >= len(self):
|
||||
raise IndexError("Record index out of range")
|
||||
return index
|
||||
|
||||
# iterface methods
|
||||
|
||||
def close(self):
|
||||
self.flush()
|
||||
self.stream.close()
|
||||
|
||||
def flush(self):
|
||||
"""Flush data to the associated stream."""
|
||||
if self.changed:
|
||||
self.header.setCurrentDate()
|
||||
self.header.write(self.stream)
|
||||
self.stream.flush()
|
||||
self._changed = False
|
||||
|
||||
def indexOfFieldName(self, name):
|
||||
"""Index of field named ``name``."""
|
||||
# FIXME: move this to header class
|
||||
return self.header.fields.index(name)
|
||||
|
||||
def newRecord(self):
|
||||
"""Return new record, which belong to this table."""
|
||||
return self.RecordClass(self)
|
||||
|
||||
def append(self, record):
|
||||
"""Append ``record`` to the database."""
|
||||
record.index = self.header.recordCount
|
||||
record._write()
|
||||
self.header.recordCount += 1
|
||||
self._changed = True
|
||||
self._new = False
|
||||
|
||||
def addField(self, *defs):
|
||||
"""Add field definitions.
|
||||
|
||||
For more information see `header.DbfHeader.addField`.
|
||||
|
||||
"""
|
||||
if self._new:
|
||||
self.header.addField(*defs)
|
||||
else:
|
||||
raise TypeError("At least one record was added, "
|
||||
"structure can't be changed")
|
||||
|
||||
# 'magic' methods (representation and sequence interface)
|
||||
|
||||
def __repr__(self):
|
||||
return "Dbf stream '%s'\n" % self.stream + repr(self.header)
|
||||
|
||||
def __len__(self):
|
||||
"""Return number of records."""
|
||||
return self.recordCount
|
||||
|
||||
def __getitem__(self, index):
|
||||
"""Return `DbfRecord` instance."""
|
||||
return self.RecordClass.fromStream(self, self._fixIndex(index))
|
||||
|
||||
def __setitem__(self, index, record):
|
||||
"""Write `DbfRecord` instance to the stream."""
|
||||
record.index = self._fixIndex(index)
|
||||
record._write()
|
||||
self._changed = True
|
||||
self._new = False
|
||||
|
||||
# def __del__(self):
|
||||
# """Flush stream upon deletion of the object."""
|
||||
# self.flush()
|
||||
|
||||
|
||||
def demo_read(filename):
|
||||
_dbf = Dbf(filename, True)
|
||||
for _rec in _dbf:
|
||||
print()
|
||||
print(repr(_rec))
|
||||
_dbf.close()
|
||||
|
||||
|
||||
def demo_create(filename):
|
||||
_dbf = Dbf(filename, new=True)
|
||||
_dbf.addField(
|
||||
("NAME", "C", 15),
|
||||
("SURNAME", "C", 25),
|
||||
("INITIALS", "C", 10),
|
||||
("BIRTHDATE", "D"),
|
||||
)
|
||||
for (_n, _s, _i, _b) in (
|
||||
("John", "Miller", "YC", (1981, 1, 2)),
|
||||
("Andy", "Larkin", "AL", (1982, 3, 4)),
|
||||
("Bill", "Clinth", "", (1983, 5, 6)),
|
||||
("Bobb", "McNail", "", (1984, 7, 8)),
|
||||
):
|
||||
_rec = _dbf.newRecord()
|
||||
_rec["NAME"] = _n
|
||||
_rec["SURNAME"] = _s
|
||||
_rec["INITIALS"] = _i
|
||||
_rec["BIRTHDATE"] = _b
|
||||
_rec.store()
|
||||
print(repr(_dbf))
|
||||
_dbf.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import sys
|
||||
|
||||
_name = len(sys.argv) > 1 and sys.argv[1] or "county.dbf"
|
||||
demo_create(_name)
|
||||
demo_read(_name)
|
||||
|
||||
# vim: set et sw=4 sts=4 :
|
||||
@@ -0,0 +1,189 @@
|
||||
#!/usr/bin/python
|
||||
""".DBF creation helpers.
|
||||
|
||||
Note: this is a legacy interface. New code should use Dbf class
|
||||
for table creation (see examples in dbf.py)
|
||||
|
||||
TODO:
|
||||
- handle Memo fields.
|
||||
- check length of the fields accoring to the
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
|
||||
"""
|
||||
"""History (most recent first)
|
||||
04-jul-2006 [als] added export declaration;
|
||||
updated for dbfpy 2.0
|
||||
15-dec-2005 [yc] define dbf_new.__slots__
|
||||
14-dec-2005 [yc] added vim modeline; retab'd; added doc-strings;
|
||||
dbf_new now is a new class (inherited from object)
|
||||
??-jun-2000 [--] added by Hans Fiby
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.4 $"[11:-2]
|
||||
__date__ = "$Date: 2006/07/04 08:18:18 $"[7:-2]
|
||||
|
||||
__all__ = ["dbf_new"]
|
||||
|
||||
from dbf import *
|
||||
from fields import *
|
||||
from header import *
|
||||
from record import *
|
||||
|
||||
|
||||
class _FieldDefinition(object):
|
||||
"""Field definition.
|
||||
|
||||
This is a simple structure, which contains ``name``, ``type``,
|
||||
``len``, ``dec`` and ``cls`` fields.
|
||||
|
||||
Objects also implement get/setitem magic functions, so fields
|
||||
could be accessed via sequence iterface, where 'name' has
|
||||
index 0, 'type' index 1, 'len' index 2, 'dec' index 3 and
|
||||
'cls' could be located at index 4.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = "name", "type", "len", "dec", "cls"
|
||||
|
||||
# WARNING: be attentive - dictionaries are mutable!
|
||||
FLD_TYPES = {
|
||||
# type: (cls, len)
|
||||
"C": (DbfCharacterFieldDef, None),
|
||||
"N": (DbfNumericFieldDef, None),
|
||||
"L": (DbfLogicalFieldDef, 1),
|
||||
# FIXME: support memos
|
||||
# "M": (DbfMemoFieldDef),
|
||||
"D": (DbfDateFieldDef, 8),
|
||||
# FIXME: I'm not sure length should be 14 characters!
|
||||
# but temporary I use it, cuz date is 8 characters
|
||||
# and time 6 (hhmmss)
|
||||
"T": (DbfDateTimeFieldDef, 14),
|
||||
}
|
||||
|
||||
def __init__(self, name, type, len=None, dec=0):
|
||||
_cls, _len = self.FLD_TYPES[type]
|
||||
if _len is None:
|
||||
if len is None:
|
||||
raise ValueError("Field length must be defined")
|
||||
_len = len
|
||||
self.name = name
|
||||
self.type = type
|
||||
self.len = _len
|
||||
self.dec = dec
|
||||
self.cls = _cls
|
||||
|
||||
def getDbfField(self):
|
||||
"Return `DbfFieldDef` instance from the current definition."
|
||||
return self.cls(self.name, self.len, self.dec)
|
||||
|
||||
def appendToHeader(self, dbfh):
|
||||
"""Create a `DbfFieldDef` instance and append it to the dbf header.
|
||||
|
||||
Arguments:
|
||||
dbfh: `DbfHeader` instance.
|
||||
|
||||
"""
|
||||
_dbff = self.getDbfField()
|
||||
dbfh.addField(_dbff)
|
||||
|
||||
|
||||
class dbf_new(object):
|
||||
"""New .DBF creation helper.
|
||||
|
||||
Example Usage:
|
||||
|
||||
dbfn = dbf_new()
|
||||
dbfn.add_field("name",'C',80)
|
||||
dbfn.add_field("price",'N',10,2)
|
||||
dbfn.add_field("date",'D',8)
|
||||
dbfn.write("tst.dbf")
|
||||
|
||||
Note:
|
||||
This module cannot handle Memo-fields,
|
||||
they are special.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("fields",)
|
||||
|
||||
FieldDefinitionClass = _FieldDefinition
|
||||
|
||||
def __init__(self):
|
||||
self.fields = []
|
||||
|
||||
def add_field(self, name, typ, len, dec=0):
|
||||
"""Add field definition.
|
||||
|
||||
Arguments:
|
||||
name:
|
||||
field name (str object). field name must not
|
||||
contain ASCII NULs and it's length shouldn't
|
||||
exceed 10 characters.
|
||||
typ:
|
||||
type of the field. this must be a single character
|
||||
from the "CNLMDT" set meaning character, numeric,
|
||||
logical, memo, date and date/time respectively.
|
||||
len:
|
||||
length of the field. this argument is used only for
|
||||
the character and numeric fields. all other fields
|
||||
have fixed length.
|
||||
FIXME: use None as a default for this argument?
|
||||
dec:
|
||||
decimal precision. used only for the numric fields.
|
||||
|
||||
"""
|
||||
self.fields.append(self.FieldDefinitionClass(name, typ, len, dec))
|
||||
|
||||
def write(self, filename):
|
||||
"""Create empty .DBF file using current structure."""
|
||||
_dbfh = DbfHeader()
|
||||
_dbfh.setCurrentDate()
|
||||
for _fldDef in self.fields:
|
||||
_fldDef.appendToHeader(_dbfh)
|
||||
_dbfStream = file(filename, "wb")
|
||||
_dbfh.write(_dbfStream)
|
||||
_dbfStream.close()
|
||||
|
||||
def write_stream(self, stream):
|
||||
_dbfh = DbfHeader()
|
||||
_dbfh.setCurrentDate()
|
||||
for _fldDef in self.fields:
|
||||
_fldDef.appendToHeader(_dbfh)
|
||||
_dbfh.write(stream)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# create a new DBF-File
|
||||
dbfn = dbf_new()
|
||||
dbfn.add_field("name", 'C', 80)
|
||||
dbfn.add_field("price", 'N', 10, 2)
|
||||
dbfn.add_field("date", 'D', 8)
|
||||
dbfn.write("tst.dbf")
|
||||
# test new dbf
|
||||
print("*** created tst.dbf: ***")
|
||||
dbft = Dbf('tst.dbf', readOnly=0)
|
||||
print(repr(dbft))
|
||||
# add a record
|
||||
rec = DbfRecord(dbft)
|
||||
rec['name'] = 'something'
|
||||
rec['price'] = 10.5
|
||||
rec['date'] = (2000, 1, 12)
|
||||
rec.store()
|
||||
# add another record
|
||||
rec = DbfRecord(dbft)
|
||||
rec['name'] = 'foo and bar'
|
||||
rec['price'] = 12234
|
||||
rec['date'] = (1992, 7, 15)
|
||||
rec.store()
|
||||
|
||||
# show the records
|
||||
print("*** inserted 2 records into tst.dbf: ***")
|
||||
print(repr(dbft))
|
||||
for i1 in range(len(dbft)):
|
||||
rec = dbft[i1]
|
||||
for fldName in dbft.fieldNames:
|
||||
print('%s:\t %s' % (fldName, rec[fldName]))
|
||||
print()
|
||||
dbft.close()
|
||||
|
||||
# vim: set et sts=4 sw=4 :
|
||||
@@ -0,0 +1,466 @@
|
||||
"""DBF fields definitions.
|
||||
|
||||
TODO:
|
||||
- make memos work
|
||||
"""
|
||||
"""History (most recent first):
|
||||
26-may-2009 [als] DbfNumericFieldDef.decodeValue: strip zero bytes
|
||||
05-feb-2009 [als] DbfDateFieldDef.encodeValue: empty arg produces empty date
|
||||
16-sep-2008 [als] DbfNumericFieldDef decoding looks for decimal point
|
||||
in the value to select float or integer return type
|
||||
13-mar-2008 [als] check field name length in constructor
|
||||
11-feb-2007 [als] handle value conversion errors
|
||||
10-feb-2007 [als] DbfFieldDef: added .rawFromRecord()
|
||||
01-dec-2006 [als] Timestamp columns use None for empty values
|
||||
31-oct-2006 [als] support field types 'F' (float), 'I' (integer)
|
||||
and 'Y' (currency);
|
||||
automate export and registration of field classes
|
||||
04-jul-2006 [als] added export declaration
|
||||
10-mar-2006 [als] decode empty values for Date and Logical fields;
|
||||
show field name in errors
|
||||
10-mar-2006 [als] fix Numeric value decoding: according to spec,
|
||||
value always is string representation of the number;
|
||||
ensure that encoded Numeric value fits into the field
|
||||
20-dec-2005 [yc] use field names in upper case
|
||||
15-dec-2005 [yc] field definitions moved from `dbf`.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.14 $"[11:-2]
|
||||
__date__ = "$Date: 2009/05/26 05:16:51 $"[7:-2]
|
||||
|
||||
__all__ = ["lookupFor",] # field classes added at the end of the module
|
||||
|
||||
import datetime
|
||||
import struct
|
||||
import sys
|
||||
|
||||
from . import utils
|
||||
|
||||
## abstract definitions
|
||||
|
||||
class DbfFieldDef(object):
|
||||
"""Abstract field definition.
|
||||
|
||||
Child classes must override ``type`` class attribute to provide datatype
|
||||
infromation of the field definition. For more info about types visit
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
|
||||
Also child classes must override ``defaultValue`` field to provide
|
||||
default value for the field value.
|
||||
|
||||
If child class has fixed length ``length`` class attribute must be
|
||||
overriden and set to the valid value. None value means, that field
|
||||
isn't of fixed length.
|
||||
|
||||
Note: ``name`` field must not be changed after instantiation.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("name", "length", "decimalCount",
|
||||
"start", "end", "ignoreErrors")
|
||||
|
||||
# length of the field, None in case of variable-length field,
|
||||
# or a number if this field is a fixed-length field
|
||||
length = None
|
||||
|
||||
# field type. for more information about fields types visit
|
||||
# `http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
# must be overriden in child classes
|
||||
typeCode = None
|
||||
|
||||
# default value for the field. this field must be
|
||||
# overriden in child classes
|
||||
defaultValue = None
|
||||
|
||||
def __init__(self, name, length=None, decimalCount=None,
|
||||
start=None, stop=None, ignoreErrors=False,
|
||||
):
|
||||
"""Initialize instance."""
|
||||
assert self.typeCode is not None, "Type code must be overriden"
|
||||
assert self.defaultValue is not None, "Default value must be overriden"
|
||||
## fix arguments
|
||||
if len(name) >10:
|
||||
raise ValueError("Field name \"%s\" is too long" % name)
|
||||
name = str(name).upper()
|
||||
if self.__class__.length is None:
|
||||
if length is None:
|
||||
raise ValueError("[%s] Length isn't specified" % name)
|
||||
length = int(length)
|
||||
if length <= 0:
|
||||
raise ValueError("[%s] Length must be a positive integer"
|
||||
% name)
|
||||
else:
|
||||
length = self.length
|
||||
if decimalCount is None:
|
||||
decimalCount = 0
|
||||
## set fields
|
||||
self.name = name
|
||||
# FIXME: validate length according to the specification at
|
||||
# http://www.clicketyclick.dk/databases/xbase/format/data_types.html
|
||||
self.length = length
|
||||
self.decimalCount = decimalCount
|
||||
self.ignoreErrors = ignoreErrors
|
||||
self.start = start
|
||||
self.end = stop
|
||||
|
||||
def __cmp__(self, other):
|
||||
return cmp(self.name, str(other).upper())
|
||||
|
||||
def __hash__(self):
|
||||
return hash(self.name)
|
||||
|
||||
def fromString(cls, string, start, ignoreErrors=False):
|
||||
"""Decode dbf field definition from the string data.
|
||||
|
||||
Arguments:
|
||||
string:
|
||||
a string, dbf definition is decoded from. length of
|
||||
the string must be 32 bytes.
|
||||
start:
|
||||
position in the database file.
|
||||
ignoreErrors:
|
||||
initial error processing mode for the new field (boolean)
|
||||
|
||||
"""
|
||||
assert len(string) == 32
|
||||
_length = ord(string[16])
|
||||
return cls(utils.unzfill(string)[:11], _length, ord(string[17]),
|
||||
start, start + _length, ignoreErrors=ignoreErrors)
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
def toString(self):
|
||||
"""Return encoded field definition.
|
||||
|
||||
Return:
|
||||
Return value is a string object containing encoded
|
||||
definition of this field.
|
||||
|
||||
"""
|
||||
if sys.version_info < (2, 4):
|
||||
# earlier versions did not support padding character
|
||||
_name = self.name[:11] + "\0" * (11 - len(self.name))
|
||||
else:
|
||||
_name = self.name.ljust(11, '\0')
|
||||
return (
|
||||
_name +
|
||||
self.typeCode +
|
||||
#data address
|
||||
chr(0) * 4 +
|
||||
chr(self.length) +
|
||||
chr(self.decimalCount) +
|
||||
chr(0) * 14
|
||||
)
|
||||
|
||||
def __repr__(self):
|
||||
return "%-10s %1s %3d %3d" % self.fieldInfo()
|
||||
|
||||
def fieldInfo(self):
|
||||
"""Return field information.
|
||||
|
||||
Return:
|
||||
Return value is a (name, type, length, decimals) tuple.
|
||||
|
||||
"""
|
||||
return (self.name, self.typeCode, self.length, self.decimalCount)
|
||||
|
||||
def rawFromRecord(self, record):
|
||||
"""Return a "raw" field value from the record string."""
|
||||
return record[self.start:self.end]
|
||||
|
||||
def decodeFromRecord(self, record):
|
||||
"""Return decoded field value from the record string."""
|
||||
try:
|
||||
return self.decodeValue(self.rawFromRecord(record))
|
||||
except:
|
||||
if self.ignoreErrors:
|
||||
return utils.INVALID_VALUE
|
||||
else:
|
||||
raise
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return decoded value from string value.
|
||||
|
||||
This method shouldn't be used publicly. It's called from the
|
||||
`decodeFromRecord` method.
|
||||
|
||||
This is an abstract method and it must be overridden in child classes.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return str object containing encoded field value.
|
||||
|
||||
This is an abstract method and it must be overriden in child classes.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
## real classes
|
||||
|
||||
class DbfCharacterFieldDef(DbfFieldDef):
|
||||
"""Definition of the character field."""
|
||||
|
||||
typeCode = "C"
|
||||
defaultValue = ""
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return string object.
|
||||
|
||||
Return value is a ``value`` argument with stripped right spaces.
|
||||
|
||||
"""
|
||||
return value.rstrip(" ")
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return raw data string encoded from a ``value``."""
|
||||
return str(value)[:self.length].ljust(self.length)
|
||||
|
||||
|
||||
class DbfNumericFieldDef(DbfFieldDef):
|
||||
"""Definition of the numeric field."""
|
||||
|
||||
typeCode = "N"
|
||||
# XXX: now I'm not sure it was a good idea to make a class field
|
||||
# `defaultValue` instead of a generic method as it was implemented
|
||||
# previously -- it's ok with all types except number, cuz
|
||||
# if self.decimalCount is 0, we should return 0 and 0.0 otherwise.
|
||||
defaultValue = 0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a number decoded from ``value``.
|
||||
|
||||
If decimals is zero, value will be decoded as an integer;
|
||||
or as a float otherwise.
|
||||
|
||||
Return:
|
||||
Return value is a int (long) or float instance.
|
||||
|
||||
"""
|
||||
value = value.strip(" \0")
|
||||
if "." in value:
|
||||
# a float (has decimal separator)
|
||||
return float(value)
|
||||
elif value:
|
||||
# must be an integer
|
||||
return int(value)
|
||||
else:
|
||||
return 0
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
_rv = ("%*.*f" % (self.length, self.decimalCount, value))
|
||||
if len(_rv) > self.length:
|
||||
_ppos = _rv.find(".")
|
||||
if 0 <= _ppos <= self.length:
|
||||
_rv = _rv[:self.length]
|
||||
else:
|
||||
raise ValueError("[%s] Numeric overflow: %s (field width: %i)"
|
||||
% (self.name, _rv, self.length))
|
||||
return _rv
|
||||
|
||||
class DbfFloatFieldDef(DbfNumericFieldDef):
|
||||
"""Definition of the float field - same as numeric."""
|
||||
|
||||
typeCode = "F"
|
||||
|
||||
class DbfIntegerFieldDef(DbfFieldDef):
|
||||
"""Definition of the integer field."""
|
||||
|
||||
typeCode = "I"
|
||||
length = 4
|
||||
defaultValue = 0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return an integer number decoded from ``value``."""
|
||||
return struct.unpack("<i", value)[0]
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
return struct.pack("<i", int(value))
|
||||
|
||||
class DbfCurrencyFieldDef(DbfFieldDef):
|
||||
"""Definition of the currency field."""
|
||||
|
||||
typeCode = "Y"
|
||||
length = 8
|
||||
defaultValue = 0.0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return float number decoded from ``value``."""
|
||||
return struct.unpack("<q", value)[0] / 10000.
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
return struct.pack("<q", round(value * 10000))
|
||||
|
||||
class DbfLogicalFieldDef(DbfFieldDef):
|
||||
"""Definition of the logical field."""
|
||||
|
||||
typeCode = "L"
|
||||
defaultValue = -1
|
||||
length = 1
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return True, False or -1 decoded from ``value``."""
|
||||
# Note: value always is 1-char string
|
||||
if value == "?":
|
||||
return -1
|
||||
if value in "NnFf ":
|
||||
return False
|
||||
if value in "YyTt":
|
||||
return True
|
||||
raise ValueError("[%s] Invalid logical value %r" % (self.name, value))
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a character from the "TF?" set.
|
||||
|
||||
Return:
|
||||
Return value is "T" if ``value`` is True
|
||||
"?" if value is -1 or False otherwise.
|
||||
|
||||
"""
|
||||
if value is True:
|
||||
return "T"
|
||||
if value == -1:
|
||||
return "?"
|
||||
return "F"
|
||||
|
||||
|
||||
class DbfMemoFieldDef(DbfFieldDef):
|
||||
"""Definition of the memo field.
|
||||
|
||||
Note: memos aren't currenly completely supported.
|
||||
|
||||
"""
|
||||
|
||||
typeCode = "M"
|
||||
defaultValue = " " * 10
|
||||
length = 10
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return int .dbt block number decoded from the string object."""
|
||||
#return int(value)
|
||||
raise NotImplementedError
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return raw data string encoded from a ``value``.
|
||||
|
||||
Note: this is an internal method.
|
||||
|
||||
"""
|
||||
#return str(value)[:self.length].ljust(self.length)
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class DbfDateFieldDef(DbfFieldDef):
|
||||
"""Definition of the date field."""
|
||||
|
||||
typeCode = "D"
|
||||
defaultValue = utils.classproperty(lambda cls: datetime.date.today())
|
||||
# "yyyymmdd" gives us 8 characters
|
||||
length = 8
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a ``datetime.date`` instance decoded from ``value``."""
|
||||
if value.strip():
|
||||
return utils.getDate(value)
|
||||
else:
|
||||
return None
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a string-encoded value.
|
||||
|
||||
``value`` argument should be a value suitable for the
|
||||
`utils.getDate` call.
|
||||
|
||||
Return:
|
||||
Return value is a string in format "yyyymmdd".
|
||||
|
||||
"""
|
||||
if value:
|
||||
return utils.getDate(value).strftime("%Y%m%d")
|
||||
else:
|
||||
return " " * self.length
|
||||
|
||||
|
||||
class DbfDateTimeFieldDef(DbfFieldDef):
|
||||
"""Definition of the timestamp field."""
|
||||
|
||||
# a difference between JDN (Julian Day Number)
|
||||
# and GDN (Gregorian Day Number). note, that GDN < JDN
|
||||
JDN_GDN_DIFF = 1721425
|
||||
typeCode = "T"
|
||||
defaultValue = utils.classproperty(lambda cls: datetime.datetime.now())
|
||||
# two 32-bits integers representing JDN and amount of
|
||||
# milliseconds respectively gives us 8 bytes.
|
||||
# note, that values must be encoded in LE byteorder.
|
||||
length = 8
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a `datetime.datetime` instance."""
|
||||
assert len(value) == self.length
|
||||
# LE byteorder
|
||||
_jdn, _msecs = struct.unpack("<2I", value)
|
||||
if _jdn >= 1:
|
||||
_rv = datetime.datetime.fromordinal(_jdn - self.JDN_GDN_DIFF)
|
||||
_rv += datetime.timedelta(0, _msecs / 1000.0)
|
||||
else:
|
||||
# empty date
|
||||
_rv = None
|
||||
return _rv
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a string-encoded ``value``."""
|
||||
if value:
|
||||
value = utils.getDateTime(value)
|
||||
# LE byteorder
|
||||
_rv = struct.pack("<2I", value.toordinal() + self.JDN_GDN_DIFF,
|
||||
(value.hour * 3600 + value.minute * 60 + value.second) * 1000)
|
||||
else:
|
||||
_rv = "\0" * self.length
|
||||
assert len(_rv) == self.length
|
||||
return _rv
|
||||
|
||||
|
||||
_fieldsRegistry = {}
|
||||
|
||||
def registerField(fieldCls):
|
||||
"""Register field definition class.
|
||||
|
||||
``fieldCls`` should be subclass of the `DbfFieldDef`.
|
||||
|
||||
Use `lookupFor` to retrieve field definition class
|
||||
by the type code.
|
||||
|
||||
"""
|
||||
assert fieldCls.typeCode is not None, "Type code isn't defined"
|
||||
# XXX: use fieldCls.typeCode.upper()? in case of any decign
|
||||
# don't forget to look to the same comment in ``lookupFor`` method
|
||||
_fieldsRegistry[fieldCls.typeCode] = fieldCls
|
||||
|
||||
|
||||
def lookupFor(typeCode):
|
||||
"""Return field definition class for the given type code.
|
||||
|
||||
``typeCode`` must be a single character. That type should be
|
||||
previously registered.
|
||||
|
||||
Use `registerField` to register new field class.
|
||||
|
||||
Return:
|
||||
Return value is a subclass of the `DbfFieldDef`.
|
||||
|
||||
"""
|
||||
# XXX: use typeCode.upper()? in case of any decign don't
|
||||
# forget to look to the same comment in ``registerField``
|
||||
return _fieldsRegistry[typeCode]
|
||||
|
||||
## register generic types
|
||||
|
||||
for (_name, _val) in globals().items():
|
||||
if isinstance(_val, type) and issubclass(_val, DbfFieldDef) \
|
||||
and (_name != "DbfFieldDef"):
|
||||
__all__.append(_name)
|
||||
registerField(_val)
|
||||
del _name, _val
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,275 @@
|
||||
"""DBF header definition.
|
||||
|
||||
TODO:
|
||||
- handle encoding of the character fields
|
||||
(encoding information stored in the DBF header)
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
16-sep-2010 [als] fromStream: fix century of the last update field
|
||||
11-feb-2007 [als] added .ignoreErrors
|
||||
10-feb-2007 [als] added __getitem__: return field definitions
|
||||
by field name or field number (zero-based)
|
||||
04-jul-2006 [als] added export declaration
|
||||
15-dec-2005 [yc] created
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.6 $"[11:-2]
|
||||
__date__ = "$Date: 2010/09/16 05:06:39 $"[7:-2]
|
||||
|
||||
__all__ = ["DbfHeader"]
|
||||
|
||||
try:
|
||||
import cStringIO
|
||||
except ImportError:
|
||||
# when we're in python3, we cStringIO has been replaced by io.StringIO
|
||||
import io as cStringIO
|
||||
import datetime
|
||||
import struct
|
||||
import time
|
||||
|
||||
from . import fields
|
||||
from . import utils
|
||||
|
||||
|
||||
class DbfHeader(object):
|
||||
"""Dbf header definition.
|
||||
|
||||
For more information about dbf header format visit
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/dbf.html#DBF_STRUCT`
|
||||
|
||||
Examples:
|
||||
Create an empty dbf header and add some field definitions:
|
||||
dbfh = DbfHeader()
|
||||
dbfh.addField(("name", "C", 10))
|
||||
dbfh.addField(("date", "D"))
|
||||
dbfh.addField(DbfNumericFieldDef("price", 5, 2))
|
||||
Create a dbf header with field definitions:
|
||||
dbfh = DbfHeader([
|
||||
("name", "C", 10),
|
||||
("date", "D"),
|
||||
DbfNumericFieldDef("price", 5, 2),
|
||||
])
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("signature", "fields", "lastUpdate", "recordLength",
|
||||
"recordCount", "headerLength", "changed", "_ignore_errors")
|
||||
|
||||
## instance construction and initialization methods
|
||||
|
||||
def __init__(self, fields=None, headerLength=0, recordLength=0,
|
||||
recordCount=0, signature=0x03, lastUpdate=None, ignoreErrors=False,
|
||||
):
|
||||
"""Initialize instance.
|
||||
|
||||
Arguments:
|
||||
fields:
|
||||
a list of field definitions;
|
||||
recordLength:
|
||||
size of the records;
|
||||
headerLength:
|
||||
size of the header;
|
||||
recordCount:
|
||||
number of records stored in DBF;
|
||||
signature:
|
||||
version number (aka signature). using 0x03 as a default meaning
|
||||
"File without DBT". for more information about this field visit
|
||||
``http://www.clicketyclick.dk/databases/xbase/format/dbf.html#DBF_NOTE_1_TARGET``
|
||||
lastUpdate:
|
||||
date of the DBF's update. this could be a string ('yymmdd' or
|
||||
'yyyymmdd'), timestamp (int or float), datetime/date value,
|
||||
a sequence (assuming (yyyy, mm, dd, ...)) or an object having
|
||||
callable ``ticks`` field.
|
||||
ignoreErrors:
|
||||
error processing mode for DBF fields (boolean)
|
||||
|
||||
"""
|
||||
self.signature = signature
|
||||
if fields is None:
|
||||
self.fields = []
|
||||
else:
|
||||
self.fields = list(fields)
|
||||
self.lastUpdate = utils.getDate(lastUpdate)
|
||||
self.recordLength = recordLength
|
||||
self.headerLength = headerLength
|
||||
self.recordCount = recordCount
|
||||
self.ignoreErrors = ignoreErrors
|
||||
# XXX: I'm not sure this is safe to
|
||||
# initialize `self.changed` in this way
|
||||
self.changed = bool(self.fields)
|
||||
|
||||
# @classmethod
|
||||
def fromString(cls, string):
|
||||
"""Return header instance from the string object."""
|
||||
return cls.fromStream(cStringIO.StringIO(str(string)))
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
# @classmethod
|
||||
def fromStream(cls, stream):
|
||||
"""Return header object from the stream."""
|
||||
stream.seek(0)
|
||||
_data = stream.read(32)
|
||||
(_cnt, _hdrLen, _recLen) = struct.unpack("<I2H", _data[4:12])
|
||||
#reserved = _data[12:32]
|
||||
_year = ord(_data[1])
|
||||
if _year < 80:
|
||||
# dBase II started at 1980. It is quite unlikely
|
||||
# that actual last update date is before that year.
|
||||
_year += 2000
|
||||
else:
|
||||
_year += 1900
|
||||
## create header object
|
||||
_obj = cls(None, _hdrLen, _recLen, _cnt, ord(_data[0]),
|
||||
(_year, ord(_data[2]), ord(_data[3])))
|
||||
## append field definitions
|
||||
# position 0 is for the deletion flag
|
||||
_pos = 1
|
||||
_data = stream.read(1)
|
||||
|
||||
# The field definitions are ended either by \x0D OR a newline
|
||||
# character, so we need to handle both when reading from a stream.
|
||||
# When writing, dbfpy appears to write newlines instead of \x0D.
|
||||
while _data[0] not in ["\x0D", "\n"]:
|
||||
_data += stream.read(31)
|
||||
_fld = fields.lookupFor(_data[11]).fromString(_data, _pos)
|
||||
_obj._addField(_fld)
|
||||
_pos = _fld.end
|
||||
_data = stream.read(1)
|
||||
return _obj
|
||||
fromStream = classmethod(fromStream)
|
||||
|
||||
## properties
|
||||
|
||||
year = property(lambda self: self.lastUpdate.year)
|
||||
month = property(lambda self: self.lastUpdate.month)
|
||||
day = property(lambda self: self.lastUpdate.day)
|
||||
|
||||
def ignoreErrors(self, value):
|
||||
"""Update `ignoreErrors` flag on self and all fields"""
|
||||
self._ignore_errors = value = bool(value)
|
||||
for _field in self.fields:
|
||||
_field.ignoreErrors = value
|
||||
ignoreErrors = property(
|
||||
lambda self: self._ignore_errors,
|
||||
ignoreErrors,
|
||||
doc="""Error processing mode for DBF field value conversion
|
||||
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
""")
|
||||
|
||||
## object representation
|
||||
|
||||
def __repr__(self):
|
||||
_rv = """\
|
||||
Version (signature): 0x%02x
|
||||
Last update: %s
|
||||
Header length: %d
|
||||
Record length: %d
|
||||
Record count: %d
|
||||
FieldName Type Len Dec
|
||||
""" % (self.signature, self.lastUpdate, self.headerLength,
|
||||
self.recordLength, self.recordCount)
|
||||
_rv += "\n".join(
|
||||
["%10s %4s %3s %3s" % _fld.fieldInfo() for _fld in self.fields]
|
||||
)
|
||||
return _rv
|
||||
|
||||
## internal methods
|
||||
|
||||
def _addField(self, *defs):
|
||||
"""Internal variant of the `addField` method.
|
||||
|
||||
This method doesn't set `self.changed` field to True.
|
||||
|
||||
Return value is a length of the appended records.
|
||||
Note: this method doesn't modify ``recordLength`` and
|
||||
``headerLength`` fields. Use `addField` instead of this
|
||||
method if you don't exactly know what you're doing.
|
||||
|
||||
"""
|
||||
# insure we have dbf.DbfFieldDef instances first (instantiation
|
||||
# from the tuple could raise an error, in such a case I don't
|
||||
# wanna add any of the definitions -- all will be ignored)
|
||||
_defs = []
|
||||
_recordLength = 0
|
||||
for _def in defs:
|
||||
if isinstance(_def, fields.DbfFieldDef):
|
||||
_obj = _def
|
||||
else:
|
||||
(_name, _type, _len, _dec) = (tuple(_def) + (None,) * 4)[:4]
|
||||
_cls = fields.lookupFor(_type)
|
||||
_obj = _cls(_name, _len, _dec,
|
||||
ignoreErrors=self._ignore_errors)
|
||||
_recordLength += _obj.length
|
||||
_defs.append(_obj)
|
||||
# and now extend field definitions and
|
||||
# update record length
|
||||
self.fields += _defs
|
||||
return _recordLength
|
||||
|
||||
## interface methods
|
||||
|
||||
def addField(self, *defs):
|
||||
"""Add field definition to the header.
|
||||
|
||||
Examples:
|
||||
dbfh.addField(
|
||||
("name", "C", 20),
|
||||
dbf.DbfCharacterFieldDef("surname", 20),
|
||||
dbf.DbfDateFieldDef("birthdate"),
|
||||
("member", "L"),
|
||||
)
|
||||
dbfh.addField(("price", "N", 5, 2))
|
||||
dbfh.addField(dbf.DbfNumericFieldDef("origprice", 5, 2))
|
||||
|
||||
"""
|
||||
_oldLen = self.recordLength
|
||||
self.recordLength += self._addField(*defs)
|
||||
if not _oldLen:
|
||||
self.recordLength += 1
|
||||
# XXX: may be just use:
|
||||
# self.recordeLength += self._addField(*defs) + bool(not _oldLen)
|
||||
# recalculate headerLength
|
||||
self.headerLength = 32 + (32 * len(self.fields)) + 1
|
||||
self.changed = True
|
||||
|
||||
def write(self, stream):
|
||||
"""Encode and write header to the stream."""
|
||||
stream.seek(0)
|
||||
stream.write(self.toString())
|
||||
stream.write("".join([_fld.toString() for _fld in self.fields]))
|
||||
stream.write(chr(0x0D)) # cr at end of all hdr data
|
||||
self.changed = False
|
||||
|
||||
def toString(self):
|
||||
"""Returned 32 chars length string with encoded header."""
|
||||
return struct.pack("<4BI2H",
|
||||
self.signature,
|
||||
self.year - 1900,
|
||||
self.month,
|
||||
self.day,
|
||||
self.recordCount,
|
||||
self.headerLength,
|
||||
self.recordLength) + "\0" * 20
|
||||
|
||||
def setCurrentDate(self):
|
||||
"""Update ``self.lastUpdate`` field with current date value."""
|
||||
self.lastUpdate = datetime.date.today()
|
||||
|
||||
def __getitem__(self, item):
|
||||
"""Return a field definition by numeric index or name string"""
|
||||
if isinstance(item, basestring):
|
||||
_name = item.upper()
|
||||
for _field in self.fields:
|
||||
if _field.name == _name:
|
||||
return _field
|
||||
else:
|
||||
raise KeyError(item)
|
||||
else:
|
||||
# item must be field index
|
||||
return self.fields[item]
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,262 @@
|
||||
"""DBF record definition.
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] __repr__: added special case for invalid field values
|
||||
10-feb-2007 [als] added .rawFromStream()
|
||||
30-oct-2006 [als] fix record length in .fromStream()
|
||||
04-jul-2006 [als] added export declaration
|
||||
20-dec-2005 [yc] DbfRecord.write() -> DbfRecord._write();
|
||||
added delete() method.
|
||||
16-dec-2005 [yc] record definition moved from `dbf`.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.7 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 09:05:49 $"[7:-2]
|
||||
|
||||
__all__ = ["DbfRecord"]
|
||||
|
||||
from itertools import izip
|
||||
|
||||
import utils
|
||||
|
||||
class DbfRecord(object):
|
||||
"""DBF record.
|
||||
|
||||
Instances of this class shouldn't be created manualy,
|
||||
use `dbf.Dbf.newRecord` instead.
|
||||
|
||||
Class implements mapping/sequence interface, so
|
||||
fields could be accessed via their names or indexes
|
||||
(names is a preffered way to access fields).
|
||||
|
||||
Hint:
|
||||
Use `store` method to save modified record.
|
||||
|
||||
Examples:
|
||||
Add new record to the database:
|
||||
db = Dbf(filename)
|
||||
rec = db.newRecord()
|
||||
rec["FIELD1"] = value1
|
||||
rec["FIELD2"] = value2
|
||||
rec.store()
|
||||
Or the same, but modify existed
|
||||
(second in this case) record:
|
||||
db = Dbf(filename)
|
||||
rec = db[2]
|
||||
rec["FIELD1"] = value1
|
||||
rec["FIELD2"] = value2
|
||||
rec.store()
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = "dbf", "index", "deleted", "fieldData"
|
||||
|
||||
## creation and initialization
|
||||
|
||||
def __init__(self, dbf, index=None, deleted=False, data=None):
|
||||
"""Instance initialiation.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance this record belonogs to.
|
||||
index:
|
||||
An integer record index or None. If this value is
|
||||
None, record will be appended to the DBF.
|
||||
deleted:
|
||||
Boolean flag indicating whether this record
|
||||
is a deleted record.
|
||||
data:
|
||||
A sequence or None. This is a data of the fields.
|
||||
If this argument is None, default values will be used.
|
||||
|
||||
"""
|
||||
self.dbf = dbf
|
||||
# XXX: I'm not sure ``index`` is necessary
|
||||
self.index = index
|
||||
self.deleted = deleted
|
||||
if data is None:
|
||||
self.fieldData = [_fd.defaultValue for _fd in dbf.header.fields]
|
||||
else:
|
||||
self.fieldData = list(data)
|
||||
|
||||
# XXX: validate self.index before calculating position?
|
||||
position = property(lambda self: self.dbf.header.headerLength + \
|
||||
self.index * self.dbf.header.recordLength)
|
||||
|
||||
def rawFromStream(cls, dbf, index):
|
||||
"""Return raw record contents read from the stream.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance containing the record.
|
||||
index:
|
||||
Index of the record in the records' container.
|
||||
This argument can't be None in this call.
|
||||
|
||||
Return value is a string containing record data in DBF format.
|
||||
|
||||
"""
|
||||
# XXX: may be write smth assuming, that current stream
|
||||
# position is the required one? it could save some
|
||||
# time required to calculate where to seek in the file
|
||||
dbf.stream.seek(dbf.header.headerLength +
|
||||
index * dbf.header.recordLength)
|
||||
return dbf.stream.read(dbf.header.recordLength)
|
||||
rawFromStream = classmethod(rawFromStream)
|
||||
|
||||
def fromStream(cls, dbf, index):
|
||||
"""Return a record read from the stream.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance new record should belong to.
|
||||
index:
|
||||
Index of the record in the records' container.
|
||||
This argument can't be None in this call.
|
||||
|
||||
Return value is an instance of the current class.
|
||||
|
||||
"""
|
||||
return cls.fromString(dbf, cls.rawFromStream(dbf, index), index)
|
||||
fromStream = classmethod(fromStream)
|
||||
|
||||
def fromString(cls, dbf, string, index=None):
|
||||
"""Return record read from the string object.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance new record should belong to.
|
||||
string:
|
||||
A string new record should be created from.
|
||||
index:
|
||||
Index of the record in the container. If this
|
||||
argument is None, record will be appended.
|
||||
|
||||
Return value is an instance of the current class.
|
||||
|
||||
"""
|
||||
return cls(dbf, index, string[0]=="*",
|
||||
[_fd.decodeFromRecord(string) for _fd in dbf.header.fields])
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
## object representation
|
||||
|
||||
def __repr__(self):
|
||||
_template = "%%%ds: %%s (%%s)" % max([len(_fld)
|
||||
for _fld in self.dbf.fieldNames])
|
||||
_rv = []
|
||||
for _fld in self.dbf.fieldNames:
|
||||
_val = self[_fld]
|
||||
if _val is utils.INVALID_VALUE:
|
||||
_rv.append(_template %
|
||||
(_fld, "None", "value cannot be decoded"))
|
||||
else:
|
||||
_rv.append(_template % (_fld, _val, type(_val)))
|
||||
return "\n".join(_rv)
|
||||
|
||||
## protected methods
|
||||
|
||||
def _write(self):
|
||||
"""Write data to the dbf stream.
|
||||
|
||||
Note:
|
||||
This isn't a public method, it's better to
|
||||
use 'store' instead publically.
|
||||
Be design ``_write`` method should be called
|
||||
only from the `Dbf` instance.
|
||||
|
||||
|
||||
"""
|
||||
self._validateIndex(False)
|
||||
self.dbf.stream.seek(self.position)
|
||||
self.dbf.stream.write(self.toString())
|
||||
# FIXME: may be move this write somewhere else?
|
||||
# why we should check this condition for each record?
|
||||
if self.index == len(self.dbf):
|
||||
# this is the last record,
|
||||
# we should write SUB (ASCII 26)
|
||||
self.dbf.stream.write("\x1A")
|
||||
|
||||
## utility methods
|
||||
|
||||
def _validateIndex(self, allowUndefined=True, checkRange=False):
|
||||
"""Valid ``self.index`` value.
|
||||
|
||||
If ``allowUndefined`` argument is True functions does nothing
|
||||
in case of ``self.index`` pointing to None object.
|
||||
|
||||
"""
|
||||
if self.index is None:
|
||||
if not allowUndefined:
|
||||
raise ValueError("Index is undefined")
|
||||
elif self.index < 0:
|
||||
raise ValueError("Index can't be negative (%s)" % self.index)
|
||||
elif checkRange and self.index <= self.dbf.header.recordCount:
|
||||
raise ValueError("There are only %d records in the DBF" %
|
||||
self.dbf.header.recordCount)
|
||||
|
||||
## interface methods
|
||||
|
||||
def store(self):
|
||||
"""Store current record in the DBF.
|
||||
|
||||
If ``self.index`` is None, this record will be appended to the
|
||||
records of the DBF this records belongs to; or replaced otherwise.
|
||||
|
||||
"""
|
||||
self._validateIndex()
|
||||
if self.index is None:
|
||||
self.index = len(self.dbf)
|
||||
self.dbf.append(self)
|
||||
else:
|
||||
self.dbf[self.index] = self
|
||||
|
||||
def delete(self):
|
||||
"""Mark method as deleted."""
|
||||
self.deleted = True
|
||||
|
||||
def toString(self):
|
||||
"""Return string packed record values."""
|
||||
return "".join([" *"[self.deleted]] + [
|
||||
_def.encodeValue(_dat)
|
||||
for (_def, _dat) in izip(self.dbf.header.fields, self.fieldData)
|
||||
])
|
||||
|
||||
def asList(self):
|
||||
"""Return a flat list of fields.
|
||||
|
||||
Note:
|
||||
Change of the list's values won't change
|
||||
real values stored in this object.
|
||||
|
||||
"""
|
||||
return self.fieldData[:]
|
||||
|
||||
def asDict(self):
|
||||
"""Return a dictionary of fields.
|
||||
|
||||
Note:
|
||||
Change of the dicts's values won't change
|
||||
real values stored in this object.
|
||||
|
||||
"""
|
||||
return dict([_i for _i in izip(self.dbf.fieldNames, self.fieldData)])
|
||||
|
||||
def __getitem__(self, key):
|
||||
"""Return value by field name or field index."""
|
||||
if isinstance(key, (long, int)):
|
||||
# integer index of the field
|
||||
return self.fieldData[key]
|
||||
# assuming string field name
|
||||
return self.fieldData[self.dbf.indexOfFieldName(key)]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
"""Set field value by integer index of the field or string name."""
|
||||
if isinstance(key, (int, long)):
|
||||
# integer index of the field
|
||||
return self.fieldData[key]
|
||||
# assuming string field name
|
||||
self.fieldData[self.dbf.indexOfFieldName(key)] = value
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,170 @@
|
||||
"""String utilities.
|
||||
|
||||
TODO:
|
||||
- allow strings in getDateTime routine;
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] added INVALID_VALUE
|
||||
10-feb-2007 [als] allow date strings padded with spaces instead of zeroes
|
||||
20-dec-2005 [yc] handle long objects in getDate/getDateTime
|
||||
16-dec-2005 [yc] created from ``strutil`` module.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.4 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 08:57:17 $"[7:-2]
|
||||
|
||||
import datetime
|
||||
import time
|
||||
|
||||
|
||||
def unzfill(str):
|
||||
"""Return a string without ASCII NULs.
|
||||
|
||||
This function searchers for the first NUL (ASCII 0) occurance
|
||||
and truncates string till that position.
|
||||
|
||||
"""
|
||||
try:
|
||||
return str[:str.index('\0')]
|
||||
except ValueError:
|
||||
return str
|
||||
|
||||
|
||||
def getDate(date=None):
|
||||
"""Return `datetime.date` instance.
|
||||
|
||||
Type of the ``date`` argument could be one of the following:
|
||||
None:
|
||||
use current date value;
|
||||
datetime.date:
|
||||
this value will be returned;
|
||||
datetime.datetime:
|
||||
the result of the date.date() will be returned;
|
||||
string:
|
||||
assuming "%Y%m%d" or "%y%m%dd" format;
|
||||
number:
|
||||
assuming it's a timestamp (returned for example
|
||||
by the time.time() call;
|
||||
sequence:
|
||||
assuming (year, month, day, ...) sequence;
|
||||
|
||||
Additionaly, if ``date`` has callable ``ticks`` attribute,
|
||||
it will be used and result of the called would be treated
|
||||
as a timestamp value.
|
||||
|
||||
"""
|
||||
if date is None:
|
||||
# use current value
|
||||
return datetime.date.today()
|
||||
if isinstance(date, datetime.date):
|
||||
return date
|
||||
if isinstance(date, datetime.datetime):
|
||||
return date.date()
|
||||
if isinstance(date, (int, long, float)):
|
||||
# date is a timestamp
|
||||
return datetime.date.fromtimestamp(date)
|
||||
if isinstance(date, basestring):
|
||||
date = date.replace(" ", "0")
|
||||
if len(date) == 6:
|
||||
# yymmdd
|
||||
return datetime.date(*time.strptime(date, "%y%m%d")[:3])
|
||||
# yyyymmdd
|
||||
return datetime.date(*time.strptime(date, "%Y%m%d")[:3])
|
||||
if hasattr(date, "__getitem__"):
|
||||
# a sequence (assuming date/time tuple)
|
||||
return datetime.date(*date[:3])
|
||||
return datetime.date.fromtimestamp(date.ticks())
|
||||
|
||||
|
||||
def getDateTime(value=None):
|
||||
"""Return `datetime.datetime` instance.
|
||||
|
||||
Type of the ``value`` argument could be one of the following:
|
||||
None:
|
||||
use current date value;
|
||||
datetime.date:
|
||||
result will be converted to the `datetime.datetime` instance
|
||||
using midnight;
|
||||
datetime.datetime:
|
||||
``value`` will be returned as is;
|
||||
string:
|
||||
*** CURRENTLY NOT SUPPORTED ***;
|
||||
number:
|
||||
assuming it's a timestamp (returned for example
|
||||
by the time.time() call;
|
||||
sequence:
|
||||
assuming (year, month, day, ...) sequence;
|
||||
|
||||
Additionaly, if ``value`` has callable ``ticks`` attribute,
|
||||
it will be used and result of the called would be treated
|
||||
as a timestamp value.
|
||||
|
||||
"""
|
||||
if value is None:
|
||||
# use current value
|
||||
return datetime.datetime.today()
|
||||
if isinstance(value, datetime.datetime):
|
||||
return value
|
||||
if isinstance(value, datetime.date):
|
||||
return datetime.datetime.fromordinal(value.toordinal())
|
||||
if isinstance(value, (int, long, float)):
|
||||
# value is a timestamp
|
||||
return datetime.datetime.fromtimestamp(value)
|
||||
if isinstance(value, basestring):
|
||||
raise NotImplementedError("Strings aren't currently implemented")
|
||||
if hasattr(value, "__getitem__"):
|
||||
# a sequence (assuming date/time tuple)
|
||||
return datetime.datetime(*tuple(value)[:6])
|
||||
return datetime.datetime.fromtimestamp(value.ticks())
|
||||
|
||||
|
||||
class classproperty(property):
|
||||
"""Works in the same way as a ``property``, but for the classes."""
|
||||
|
||||
def __get__(self, obj, cls):
|
||||
return self.fget(cls)
|
||||
|
||||
|
||||
class _InvalidValue(object):
|
||||
|
||||
"""Value returned from DBF records when field validation fails
|
||||
|
||||
The value is not equal to anything except for itself
|
||||
and equal to all empty values: None, 0, empty string etc.
|
||||
In other words, invalid value is equal to None and not equal
|
||||
to None at the same time.
|
||||
|
||||
This value yields zero upon explicit conversion to a number type,
|
||||
empty string for string types, and False for boolean.
|
||||
|
||||
"""
|
||||
|
||||
def __eq__(self, other):
|
||||
return not other
|
||||
|
||||
def __ne__(self, other):
|
||||
return not (other is self)
|
||||
|
||||
def __nonzero__(self):
|
||||
return False
|
||||
|
||||
def __int__(self):
|
||||
return 0
|
||||
__long__ = __int__
|
||||
|
||||
def __float__(self):
|
||||
return 0.0
|
||||
|
||||
def __str__(self):
|
||||
return ""
|
||||
|
||||
def __unicode__(self):
|
||||
return u""
|
||||
|
||||
def __repr__(self):
|
||||
return "<INVALID>"
|
||||
|
||||
# invalid value is a constant singleton
|
||||
INVALID_VALUE = _InvalidValue()
|
||||
|
||||
# vim: set et sts=4 sw=4 :
|
||||
@@ -0,0 +1,297 @@
|
||||
#! /usr/bin/env python
|
||||
"""DBF accessing helpers.
|
||||
|
||||
FIXME: more documentation needed
|
||||
|
||||
Examples:
|
||||
|
||||
Create new table, setup structure, add records:
|
||||
|
||||
dbf = Dbf(filename, new=True)
|
||||
dbf.addField(
|
||||
("NAME", "C", 15),
|
||||
("SURNAME", "C", 25),
|
||||
("INITIALS", "C", 10),
|
||||
("BIRTHDATE", "D"),
|
||||
)
|
||||
for (n, s, i, b) in (
|
||||
("John", "Miller", "YC", (1980, 10, 11)),
|
||||
("Andy", "Larkin", "", (1980, 4, 11)),
|
||||
):
|
||||
rec = dbf.newRecord()
|
||||
rec["NAME"] = n
|
||||
rec["SURNAME"] = s
|
||||
rec["INITIALS"] = i
|
||||
rec["BIRTHDATE"] = b
|
||||
rec.store()
|
||||
dbf.close()
|
||||
|
||||
Open existed dbf, read some data:
|
||||
|
||||
dbf = Dbf(filename, True)
|
||||
for rec in dbf:
|
||||
for fldName in dbf.fieldNames:
|
||||
print('%s:\t %s (%s)' % (fldName, rec[fldName],
|
||||
type(rec[fldName])))
|
||||
dbf.close()
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] export INVALID_VALUE;
|
||||
Dbf: added .ignoreErrors, .INVALID_VALUE
|
||||
04-jul-2006 [als] added export declaration
|
||||
20-dec-2005 [yc] removed fromStream and newDbf methods:
|
||||
use argument of __init__ call must be used instead;
|
||||
added class fields pointing to the header and
|
||||
record classes.
|
||||
17-dec-2005 [yc] split to several modules; reimplemented
|
||||
13-dec-2005 [yc] adapted to the changes of the `strutil` module.
|
||||
13-sep-2002 [als] support FoxPro Timestamp datatype
|
||||
15-nov-1999 [jjk] documentation updates, add demo
|
||||
24-aug-1998 [jjk] add some encodeValue methods (not tested), other tweaks
|
||||
08-jun-1998 [jjk] fix problems, add more features
|
||||
20-feb-1998 [jjk] fix problems, add more features
|
||||
19-feb-1998 [jjk] add create/write capabilities
|
||||
18-feb-1998 [jjk] from dbfload.py
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.7 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 09:23:13 $"[7:-2]
|
||||
__author__ = "Jeff Kunce <kuncej@mail.conservation.state.mo.us>"
|
||||
|
||||
__all__ = ["Dbf"]
|
||||
|
||||
from . import header
|
||||
from . import record
|
||||
from .utils import INVALID_VALUE
|
||||
|
||||
|
||||
class Dbf(object):
|
||||
"""DBF accessor.
|
||||
|
||||
FIXME:
|
||||
docs and examples needed (dont' forget to tell
|
||||
about problems adding new fields on the fly)
|
||||
|
||||
Implementation notes:
|
||||
``_new`` field is used to indicate whether this is
|
||||
a new data table. `addField` could be used only for
|
||||
the new tables! If at least one record was appended
|
||||
to the table it's structure couldn't be changed.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("name", "header", "stream",
|
||||
"_changed", "_new", "_ignore_errors")
|
||||
|
||||
HeaderClass = header.DbfHeader
|
||||
RecordClass = record.DbfRecord
|
||||
INVALID_VALUE = INVALID_VALUE
|
||||
|
||||
# initialization and creation helpers
|
||||
|
||||
def __init__(self, f, readOnly=False, new=False, ignoreErrors=False):
|
||||
"""Initialize instance.
|
||||
|
||||
Arguments:
|
||||
f:
|
||||
Filename or file-like object.
|
||||
new:
|
||||
True if new data table must be created. Assume
|
||||
data table exists if this argument is False.
|
||||
readOnly:
|
||||
if ``f`` argument is a string file will
|
||||
be opend in read-only mode; in other cases
|
||||
this argument is ignored. This argument is ignored
|
||||
even if ``new`` argument is True.
|
||||
headerObj:
|
||||
`header.DbfHeader` instance or None. If this argument
|
||||
is None, new empty header will be used with the
|
||||
all fields set by default.
|
||||
ignoreErrors:
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
"""
|
||||
if isinstance(f, str):
|
||||
# a filename
|
||||
self.name = f
|
||||
if new:
|
||||
# new table (table file must be
|
||||
# created or opened and truncated)
|
||||
self.stream = open(f, "w+b")
|
||||
else:
|
||||
# tabe file must exist
|
||||
self.stream = open(f, ("r+b", "rb")[bool(readOnly)])
|
||||
else:
|
||||
# a stream
|
||||
self.name = getattr(f, "name", "")
|
||||
self.stream = f
|
||||
if new:
|
||||
# if this is a new table, header will be empty
|
||||
self.header = self.HeaderClass()
|
||||
else:
|
||||
# or instantiated using stream
|
||||
self.header = self.HeaderClass.fromStream(self.stream)
|
||||
self.ignoreErrors = ignoreErrors
|
||||
self._new = bool(new)
|
||||
self._changed = False
|
||||
|
||||
# properties
|
||||
|
||||
closed = property(lambda self: self.stream.closed)
|
||||
recordCount = property(lambda self: self.header.recordCount)
|
||||
fieldNames = property(
|
||||
lambda self: [_fld.name for _fld in self.header.fields])
|
||||
fieldDefs = property(lambda self: self.header.fields)
|
||||
changed = property(lambda self: self._changed or self.header.changed)
|
||||
|
||||
def ignoreErrors(self, value):
|
||||
"""Update `ignoreErrors` flag on the header object and self"""
|
||||
self.header.ignoreErrors = self._ignore_errors = bool(value)
|
||||
|
||||
ignoreErrors = property(
|
||||
lambda self: self._ignore_errors,
|
||||
ignoreErrors,
|
||||
doc="""Error processing mode for DBF field value conversion
|
||||
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
""")
|
||||
|
||||
# protected methods
|
||||
|
||||
def _fixIndex(self, index):
|
||||
"""Return fixed index.
|
||||
|
||||
This method fails if index isn't a numeric object
|
||||
(long or int). Or index isn't in a valid range
|
||||
(less or equal to the number of records in the db).
|
||||
|
||||
If ``index`` is a negative number, it will be
|
||||
treated as a negative indexes for list objects.
|
||||
|
||||
Return:
|
||||
Return value is numeric object maning valid index.
|
||||
|
||||
"""
|
||||
if not isinstance(index, int):
|
||||
raise TypeError("Index must be a numeric object")
|
||||
if index < 0:
|
||||
# index from the right side
|
||||
# fix it to the left-side index
|
||||
index += len(self) + 1
|
||||
if index >= len(self):
|
||||
raise IndexError("Record index out of range")
|
||||
return index
|
||||
|
||||
# iterface methods
|
||||
|
||||
def close(self):
|
||||
self.flush()
|
||||
self.stream.close()
|
||||
|
||||
def flush(self):
|
||||
"""Flush data to the associated stream."""
|
||||
if self.changed:
|
||||
self.header.setCurrentDate()
|
||||
self.header.write(self.stream)
|
||||
self.stream.flush()
|
||||
self._changed = False
|
||||
|
||||
def indexOfFieldName(self, name):
|
||||
"""Index of field named ``name``."""
|
||||
# FIXME: move this to header class
|
||||
names = [f.name for f in self.header.fields]
|
||||
return names.index(name.upper())
|
||||
|
||||
def newRecord(self):
|
||||
"""Return new record, which belong to this table."""
|
||||
return self.RecordClass(self)
|
||||
|
||||
def append(self, record):
|
||||
"""Append ``record`` to the database."""
|
||||
record.index = self.header.recordCount
|
||||
record._write()
|
||||
self.header.recordCount += 1
|
||||
self._changed = True
|
||||
self._new = False
|
||||
|
||||
def addField(self, *defs):
|
||||
"""Add field definitions.
|
||||
|
||||
For more information see `header.DbfHeader.addField`.
|
||||
|
||||
"""
|
||||
if self._new:
|
||||
self.header.addField(*defs)
|
||||
else:
|
||||
raise TypeError("At least one record was added, "
|
||||
"structure can't be changed")
|
||||
|
||||
# 'magic' methods (representation and sequence interface)
|
||||
|
||||
def __repr__(self):
|
||||
return "Dbf stream '%s'\n" % self.stream + repr(self.header)
|
||||
|
||||
def __len__(self):
|
||||
"""Return number of records."""
|
||||
return self.recordCount
|
||||
|
||||
def __getitem__(self, index):
|
||||
"""Return `DbfRecord` instance."""
|
||||
return self.RecordClass.fromStream(self, self._fixIndex(index))
|
||||
|
||||
def __setitem__(self, index, record):
|
||||
"""Write `DbfRecord` instance to the stream."""
|
||||
record.index = self._fixIndex(index)
|
||||
record._write()
|
||||
self._changed = True
|
||||
self._new = False
|
||||
|
||||
# def __del__(self):
|
||||
# """Flush stream upon deletion of the object."""
|
||||
# self.flush()
|
||||
|
||||
|
||||
def demo_read(filename):
|
||||
_dbf = Dbf(filename, True)
|
||||
for _rec in _dbf:
|
||||
print()
|
||||
print(repr(_rec))
|
||||
_dbf.close()
|
||||
|
||||
|
||||
def demo_create(filename):
|
||||
_dbf = Dbf(filename, new=True)
|
||||
_dbf.addField(
|
||||
("NAME", "C", 15),
|
||||
("SURNAME", "C", 25),
|
||||
("INITIALS", "C", 10),
|
||||
("BIRTHDATE", "D"),
|
||||
)
|
||||
for (_n, _s, _i, _b) in (
|
||||
("John", "Miller", "YC", (1981, 1, 2)),
|
||||
("Andy", "Larkin", "AL", (1982, 3, 4)),
|
||||
("Bill", "Clinth", "", (1983, 5, 6)),
|
||||
("Bobb", "McNail", "", (1984, 7, 8)),
|
||||
):
|
||||
_rec = _dbf.newRecord()
|
||||
_rec["NAME"] = _n
|
||||
_rec["SURNAME"] = _s
|
||||
_rec["INITIALS"] = _i
|
||||
_rec["BIRTHDATE"] = _b
|
||||
_rec.store()
|
||||
print(repr(_dbf))
|
||||
_dbf.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import sys
|
||||
|
||||
_name = len(sys.argv) > 1 and sys.argv[1] or "county.dbf"
|
||||
demo_create(_name)
|
||||
demo_read(_name)
|
||||
|
||||
# vim: set et sw=4 sts=4 :
|
||||
@@ -0,0 +1,183 @@
|
||||
#!/usr/bin/python
|
||||
""".DBF creation helpers.
|
||||
|
||||
Note: this is a legacy interface. New code should use Dbf class
|
||||
for table creation (see examples in dbf.py)
|
||||
|
||||
TODO:
|
||||
- handle Memo fields.
|
||||
- check length of the fields accoring to the
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
|
||||
"""
|
||||
"""History (most recent first)
|
||||
04-jul-2006 [als] added export declaration;
|
||||
updated for dbfpy 2.0
|
||||
15-dec-2005 [yc] define dbf_new.__slots__
|
||||
14-dec-2005 [yc] added vim modeline; retab'd; added doc-strings;
|
||||
dbf_new now is a new class (inherited from object)
|
||||
??-jun-2000 [--] added by Hans Fiby
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.4 $"[11:-2]
|
||||
__date__ = "$Date: 2006/07/04 08:18:18 $"[7:-2]
|
||||
|
||||
__all__ = ["dbf_new"]
|
||||
|
||||
from .dbf import *
|
||||
from .fields import *
|
||||
from .header import *
|
||||
from .record import *
|
||||
|
||||
|
||||
class _FieldDefinition(object):
|
||||
"""Field definition.
|
||||
|
||||
This is a simple structure, which contains ``name``, ``type``,
|
||||
``len``, ``dec`` and ``cls`` fields.
|
||||
|
||||
Objects also implement get/setitem magic functions, so fields
|
||||
could be accessed via sequence iterface, where 'name' has
|
||||
index 0, 'type' index 1, 'len' index 2, 'dec' index 3 and
|
||||
'cls' could be located at index 4.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = "name", "type", "len", "dec", "cls"
|
||||
|
||||
# WARNING: be attentive - dictionaries are mutable!
|
||||
FLD_TYPES = {
|
||||
# type: (cls, len)
|
||||
"C": (DbfCharacterFieldDef, None),
|
||||
"N": (DbfNumericFieldDef, None),
|
||||
"L": (DbfLogicalFieldDef, 1),
|
||||
# FIXME: support memos
|
||||
# "M": (DbfMemoFieldDef),
|
||||
"D": (DbfDateFieldDef, 8),
|
||||
# FIXME: I'm not sure length should be 14 characters!
|
||||
# but temporary I use it, cuz date is 8 characters
|
||||
# and time 6 (hhmmss)
|
||||
"T": (DbfDateTimeFieldDef, 14),
|
||||
}
|
||||
|
||||
def __init__(self, name, type, len=None, dec=0):
|
||||
_cls, _len = self.FLD_TYPES[type]
|
||||
if _len is None:
|
||||
if len is None:
|
||||
raise ValueError("Field length must be defined")
|
||||
_len = len
|
||||
self.name = name
|
||||
self.type = type
|
||||
self.len = _len
|
||||
self.dec = dec
|
||||
self.cls = _cls
|
||||
|
||||
def getDbfField(self):
|
||||
"Return `DbfFieldDef` instance from the current definition."
|
||||
return self.cls(self.name, self.len, self.dec)
|
||||
|
||||
def appendToHeader(self, dbfh):
|
||||
"""Create a `DbfFieldDef` instance and append it to the dbf header.
|
||||
|
||||
Arguments:
|
||||
dbfh: `DbfHeader` instance.
|
||||
|
||||
"""
|
||||
_dbff = self.getDbfField()
|
||||
dbfh.addField(_dbff)
|
||||
|
||||
|
||||
class dbf_new(object):
|
||||
"""New .DBF creation helper.
|
||||
|
||||
Example Usage:
|
||||
|
||||
dbfn = dbf_new()
|
||||
dbfn.add_field("name",'C',80)
|
||||
dbfn.add_field("price",'N',10,2)
|
||||
dbfn.add_field("date",'D',8)
|
||||
dbfn.write("tst.dbf")
|
||||
|
||||
Note:
|
||||
This module cannot handle Memo-fields,
|
||||
they are special.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("fields",)
|
||||
|
||||
FieldDefinitionClass = _FieldDefinition
|
||||
|
||||
def __init__(self):
|
||||
self.fields = []
|
||||
|
||||
def add_field(self, name, typ, len, dec=0):
|
||||
"""Add field definition.
|
||||
|
||||
Arguments:
|
||||
name:
|
||||
field name (str object). field name must not
|
||||
contain ASCII NULs and it's length shouldn't
|
||||
exceed 10 characters.
|
||||
typ:
|
||||
type of the field. this must be a single character
|
||||
from the "CNLMDT" set meaning character, numeric,
|
||||
logical, memo, date and date/time respectively.
|
||||
len:
|
||||
length of the field. this argument is used only for
|
||||
the character and numeric fields. all other fields
|
||||
have fixed length.
|
||||
FIXME: use None as a default for this argument?
|
||||
dec:
|
||||
decimal precision. used only for the numric fields.
|
||||
|
||||
"""
|
||||
self.fields.append(self.FieldDefinitionClass(name, typ, len, dec))
|
||||
|
||||
def write(self, filename):
|
||||
"""Create empty .DBF file using current structure."""
|
||||
_dbfh = DbfHeader()
|
||||
_dbfh.setCurrentDate()
|
||||
for _fldDef in self.fields:
|
||||
_fldDef.appendToHeader(_dbfh)
|
||||
|
||||
_dbfStream = open(filename, "wb")
|
||||
_dbfh.write(_dbfStream)
|
||||
_dbfStream.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# create a new DBF-File
|
||||
dbfn = dbf_new()
|
||||
dbfn.add_field("name", 'C', 80)
|
||||
dbfn.add_field("price", 'N', 10, 2)
|
||||
dbfn.add_field("date", 'D', 8)
|
||||
dbfn.write("tst.dbf")
|
||||
# test new dbf
|
||||
print("*** created tst.dbf: ***")
|
||||
dbft = Dbf('tst.dbf', readOnly=0)
|
||||
print(repr(dbft))
|
||||
# add a record
|
||||
rec = DbfRecord(dbft)
|
||||
rec['name'] = 'something'
|
||||
rec['price'] = 10.5
|
||||
rec['date'] = (2000, 1, 12)
|
||||
rec.store()
|
||||
# add another record
|
||||
rec = DbfRecord(dbft)
|
||||
rec['name'] = 'foo and bar'
|
||||
rec['price'] = 12234
|
||||
rec['date'] = (1992, 7, 15)
|
||||
rec.store()
|
||||
|
||||
# show the records
|
||||
print("*** inserted 2 records into tst.dbf: ***")
|
||||
print(repr(dbft))
|
||||
for i1 in range(len(dbft)):
|
||||
rec = dbft[i1]
|
||||
for fldName in dbft.fieldNames:
|
||||
print('%s:\t %s' % (fldName, rec[fldName]))
|
||||
print()
|
||||
dbft.close()
|
||||
|
||||
# vim: set et sts=4 sw=4 :
|
||||
@@ -0,0 +1,466 @@
|
||||
"""DBF fields definitions.
|
||||
|
||||
TODO:
|
||||
- make memos work
|
||||
"""
|
||||
"""History (most recent first):
|
||||
26-may-2009 [als] DbfNumericFieldDef.decodeValue: strip zero bytes
|
||||
05-feb-2009 [als] DbfDateFieldDef.encodeValue: empty arg produces empty date
|
||||
16-sep-2008 [als] DbfNumericFieldDef decoding looks for decimal point
|
||||
in the value to select float or integer return type
|
||||
13-mar-2008 [als] check field name length in constructor
|
||||
11-feb-2007 [als] handle value conversion errors
|
||||
10-feb-2007 [als] DbfFieldDef: added .rawFromRecord()
|
||||
01-dec-2006 [als] Timestamp columns use None for empty values
|
||||
31-oct-2006 [als] support field types 'F' (float), 'I' (integer)
|
||||
and 'Y' (currency);
|
||||
automate export and registration of field classes
|
||||
04-jul-2006 [als] added export declaration
|
||||
10-mar-2006 [als] decode empty values for Date and Logical fields;
|
||||
show field name in errors
|
||||
10-mar-2006 [als] fix Numeric value decoding: according to spec,
|
||||
value always is string representation of the number;
|
||||
ensure that encoded Numeric value fits into the field
|
||||
20-dec-2005 [yc] use field names in upper case
|
||||
15-dec-2005 [yc] field definitions moved from `dbf`.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.14 $"[11:-2]
|
||||
__date__ = "$Date: 2009/05/26 05:16:51 $"[7:-2]
|
||||
|
||||
__all__ = ["lookupFor",] # field classes added at the end of the module
|
||||
|
||||
import datetime
|
||||
import struct
|
||||
import sys
|
||||
|
||||
from . import utils
|
||||
|
||||
## abstract definitions
|
||||
|
||||
class DbfFieldDef(object):
|
||||
"""Abstract field definition.
|
||||
|
||||
Child classes must override ``type`` class attribute to provide datatype
|
||||
infromation of the field definition. For more info about types visit
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
|
||||
Also child classes must override ``defaultValue`` field to provide
|
||||
default value for the field value.
|
||||
|
||||
If child class has fixed length ``length`` class attribute must be
|
||||
overriden and set to the valid value. None value means, that field
|
||||
isn't of fixed length.
|
||||
|
||||
Note: ``name`` field must not be changed after instantiation.
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("name", "decimalCount",
|
||||
"start", "end", "ignoreErrors")
|
||||
|
||||
# length of the field, None in case of variable-length field,
|
||||
# or a number if this field is a fixed-length field
|
||||
length = None
|
||||
|
||||
# field type. for more information about fields types visit
|
||||
# `http://www.clicketyclick.dk/databases/xbase/format/data_types.html`
|
||||
# must be overriden in child classes
|
||||
typeCode = None
|
||||
|
||||
# default value for the field. this field must be
|
||||
# overriden in child classes
|
||||
defaultValue = None
|
||||
|
||||
def __init__(self, name, length=None, decimalCount=None,
|
||||
start=None, stop=None, ignoreErrors=False,
|
||||
):
|
||||
"""Initialize instance."""
|
||||
assert self.typeCode is not None, "Type code must be overriden"
|
||||
assert self.defaultValue is not None, "Default value must be overriden"
|
||||
## fix arguments
|
||||
if len(name) >10:
|
||||
raise ValueError("Field name \"%s\" is too long" % name)
|
||||
name = str(name).upper()
|
||||
if self.__class__.length is None:
|
||||
if length is None:
|
||||
raise ValueError("[%s] Length isn't specified" % name)
|
||||
length = int(length)
|
||||
if length <= 0:
|
||||
raise ValueError("[%s] Length must be a positive integer"
|
||||
% name)
|
||||
else:
|
||||
length = self.length
|
||||
if decimalCount is None:
|
||||
decimalCount = 0
|
||||
## set fields
|
||||
self.name = name
|
||||
# FIXME: validate length according to the specification at
|
||||
# http://www.clicketyclick.dk/databases/xbase/format/data_types.html
|
||||
self.length = length
|
||||
self.decimalCount = decimalCount
|
||||
self.ignoreErrors = ignoreErrors
|
||||
self.start = start
|
||||
self.end = stop
|
||||
|
||||
def __cmp__(self, other):
|
||||
return cmp(self.name, str(other).upper())
|
||||
|
||||
def __hash__(self):
|
||||
return hash(self.name)
|
||||
|
||||
def fromString(cls, string, start, ignoreErrors=False):
|
||||
"""Decode dbf field definition from the string data.
|
||||
|
||||
Arguments:
|
||||
string:
|
||||
a string, dbf definition is decoded from. length of
|
||||
the string must be 32 bytes.
|
||||
start:
|
||||
position in the database file.
|
||||
ignoreErrors:
|
||||
initial error processing mode for the new field (boolean)
|
||||
|
||||
"""
|
||||
assert len(string) == 32
|
||||
_length = string[16]
|
||||
return cls(utils.unzfill(string)[:11].decode('utf-8'), _length,
|
||||
string[17], start, start + _length, ignoreErrors=ignoreErrors)
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
def toString(self):
|
||||
"""Return encoded field definition.
|
||||
|
||||
Return:
|
||||
Return value is a string object containing encoded
|
||||
definition of this field.
|
||||
|
||||
"""
|
||||
if sys.version_info < (2, 4):
|
||||
# earlier versions did not support padding character
|
||||
_name = self.name[:11] + "\0" * (11 - len(self.name))
|
||||
else:
|
||||
_name = self.name.ljust(11, '\0')
|
||||
return (
|
||||
_name +
|
||||
self.typeCode +
|
||||
#data address
|
||||
chr(0) * 4 +
|
||||
chr(self.length) +
|
||||
chr(self.decimalCount) +
|
||||
chr(0) * 14
|
||||
)
|
||||
|
||||
def __repr__(self):
|
||||
return "%-10s %1s %3d %3d" % self.fieldInfo()
|
||||
|
||||
def fieldInfo(self):
|
||||
"""Return field information.
|
||||
|
||||
Return:
|
||||
Return value is a (name, type, length, decimals) tuple.
|
||||
|
||||
"""
|
||||
return (self.name, self.typeCode, self.length, self.decimalCount)
|
||||
|
||||
def rawFromRecord(self, record):
|
||||
"""Return a "raw" field value from the record string."""
|
||||
return record[self.start:self.end]
|
||||
|
||||
def decodeFromRecord(self, record):
|
||||
"""Return decoded field value from the record string."""
|
||||
try:
|
||||
return self.decodeValue(self.rawFromRecord(record))
|
||||
except:
|
||||
if self.ignoreErrors:
|
||||
return utils.INVALID_VALUE
|
||||
else:
|
||||
raise
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return decoded value from string value.
|
||||
|
||||
This method shouldn't be used publicly. It's called from the
|
||||
`decodeFromRecord` method.
|
||||
|
||||
This is an abstract method and it must be overridden in child classes.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return str object containing encoded field value.
|
||||
|
||||
This is an abstract method and it must be overriden in child classes.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
## real classes
|
||||
|
||||
class DbfCharacterFieldDef(DbfFieldDef):
|
||||
"""Definition of the character field."""
|
||||
|
||||
typeCode = "C"
|
||||
defaultValue = b''
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return string object.
|
||||
|
||||
Return value is a ``value`` argument with stripped right spaces.
|
||||
|
||||
"""
|
||||
return value.rstrip(b' ').decode('utf-8')
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return raw data string encoded from a ``value``."""
|
||||
return str(value)[:self.length].ljust(self.length)
|
||||
|
||||
|
||||
class DbfNumericFieldDef(DbfFieldDef):
|
||||
"""Definition of the numeric field."""
|
||||
|
||||
typeCode = "N"
|
||||
# XXX: now I'm not sure it was a good idea to make a class field
|
||||
# `defaultValue` instead of a generic method as it was implemented
|
||||
# previously -- it's ok with all types except number, cuz
|
||||
# if self.decimalCount is 0, we should return 0 and 0.0 otherwise.
|
||||
defaultValue = 0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a number decoded from ``value``.
|
||||
|
||||
If decimals is zero, value will be decoded as an integer;
|
||||
or as a float otherwise.
|
||||
|
||||
Return:
|
||||
Return value is a int (long) or float instance.
|
||||
|
||||
"""
|
||||
value = value.strip(b' \0')
|
||||
if b'.' in value:
|
||||
# a float (has decimal separator)
|
||||
return float(value)
|
||||
elif value:
|
||||
# must be an integer
|
||||
return int(value)
|
||||
else:
|
||||
return 0
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
_rv = ("%*.*f" % (self.length, self.decimalCount, value))
|
||||
if len(_rv) > self.length:
|
||||
_ppos = _rv.find(".")
|
||||
if 0 <= _ppos <= self.length:
|
||||
_rv = _rv[:self.length]
|
||||
else:
|
||||
raise ValueError("[%s] Numeric overflow: %s (field width: %i)"
|
||||
% (self.name, _rv, self.length))
|
||||
return _rv
|
||||
|
||||
class DbfFloatFieldDef(DbfNumericFieldDef):
|
||||
"""Definition of the float field - same as numeric."""
|
||||
|
||||
typeCode = "F"
|
||||
|
||||
class DbfIntegerFieldDef(DbfFieldDef):
|
||||
"""Definition of the integer field."""
|
||||
|
||||
typeCode = "I"
|
||||
length = 4
|
||||
defaultValue = 0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return an integer number decoded from ``value``."""
|
||||
return struct.unpack("<i", value)[0]
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
return struct.pack("<i", int(value))
|
||||
|
||||
class DbfCurrencyFieldDef(DbfFieldDef):
|
||||
"""Definition of the currency field."""
|
||||
|
||||
typeCode = "Y"
|
||||
length = 8
|
||||
defaultValue = 0.0
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return float number decoded from ``value``."""
|
||||
return struct.unpack("<q", value)[0] / 10000.
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return string containing encoded ``value``."""
|
||||
return struct.pack("<q", round(value * 10000))
|
||||
|
||||
class DbfLogicalFieldDef(DbfFieldDef):
|
||||
"""Definition of the logical field."""
|
||||
|
||||
typeCode = "L"
|
||||
defaultValue = -1
|
||||
length = 1
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return True, False or -1 decoded from ``value``."""
|
||||
# Note: value always is 1-char string
|
||||
if value == "?":
|
||||
return -1
|
||||
if value in "NnFf ":
|
||||
return False
|
||||
if value in "YyTt":
|
||||
return True
|
||||
raise ValueError("[%s] Invalid logical value %r" % (self.name, value))
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a character from the "TF?" set.
|
||||
|
||||
Return:
|
||||
Return value is "T" if ``value`` is True
|
||||
"?" if value is -1 or False otherwise.
|
||||
|
||||
"""
|
||||
if value is True:
|
||||
return "T"
|
||||
if value == -1:
|
||||
return "?"
|
||||
return "F"
|
||||
|
||||
|
||||
class DbfMemoFieldDef(DbfFieldDef):
|
||||
"""Definition of the memo field.
|
||||
|
||||
Note: memos aren't currenly completely supported.
|
||||
|
||||
"""
|
||||
|
||||
typeCode = "M"
|
||||
defaultValue = " " * 10
|
||||
length = 10
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return int .dbt block number decoded from the string object."""
|
||||
#return int(value)
|
||||
raise NotImplementedError
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return raw data string encoded from a ``value``.
|
||||
|
||||
Note: this is an internal method.
|
||||
|
||||
"""
|
||||
#return str(value)[:self.length].ljust(self.length)
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class DbfDateFieldDef(DbfFieldDef):
|
||||
"""Definition of the date field."""
|
||||
|
||||
typeCode = "D"
|
||||
defaultValue = utils.classproperty(lambda cls: datetime.date.today())
|
||||
# "yyyymmdd" gives us 8 characters
|
||||
length = 8
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a ``datetime.date`` instance decoded from ``value``."""
|
||||
if value.strip():
|
||||
return utils.getDate(value)
|
||||
else:
|
||||
return None
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a string-encoded value.
|
||||
|
||||
``value`` argument should be a value suitable for the
|
||||
`utils.getDate` call.
|
||||
|
||||
Return:
|
||||
Return value is a string in format "yyyymmdd".
|
||||
|
||||
"""
|
||||
if value:
|
||||
return utils.getDate(value).strftime("%Y%m%d")
|
||||
else:
|
||||
return " " * self.length
|
||||
|
||||
|
||||
class DbfDateTimeFieldDef(DbfFieldDef):
|
||||
"""Definition of the timestamp field."""
|
||||
|
||||
# a difference between JDN (Julian Day Number)
|
||||
# and GDN (Gregorian Day Number). note, that GDN < JDN
|
||||
JDN_GDN_DIFF = 1721425
|
||||
typeCode = "T"
|
||||
defaultValue = utils.classproperty(lambda cls: datetime.datetime.now())
|
||||
# two 32-bits integers representing JDN and amount of
|
||||
# milliseconds respectively gives us 8 bytes.
|
||||
# note, that values must be encoded in LE byteorder.
|
||||
length = 8
|
||||
|
||||
def decodeValue(self, value):
|
||||
"""Return a `datetime.datetime` instance."""
|
||||
assert len(value) == self.length
|
||||
# LE byteorder
|
||||
_jdn, _msecs = struct.unpack("<2I", value)
|
||||
if _jdn >= 1:
|
||||
_rv = datetime.datetime.fromordinal(_jdn - self.JDN_GDN_DIFF)
|
||||
_rv += datetime.timedelta(0, _msecs / 1000.0)
|
||||
else:
|
||||
# empty date
|
||||
_rv = None
|
||||
return _rv
|
||||
|
||||
def encodeValue(self, value):
|
||||
"""Return a string-encoded ``value``."""
|
||||
if value:
|
||||
value = utils.getDateTime(value)
|
||||
# LE byteorder
|
||||
_rv = struct.pack("<2I", value.toordinal() + self.JDN_GDN_DIFF,
|
||||
(value.hour * 3600 + value.minute * 60 + value.second) * 1000)
|
||||
else:
|
||||
_rv = "\0" * self.length
|
||||
assert len(_rv) == self.length
|
||||
return _rv
|
||||
|
||||
|
||||
_fieldsRegistry = {}
|
||||
|
||||
def registerField(fieldCls):
|
||||
"""Register field definition class.
|
||||
|
||||
``fieldCls`` should be subclass of the `DbfFieldDef`.
|
||||
|
||||
Use `lookupFor` to retrieve field definition class
|
||||
by the type code.
|
||||
|
||||
"""
|
||||
assert fieldCls.typeCode is not None, "Type code isn't defined"
|
||||
# XXX: use fieldCls.typeCode.upper()? in case of any decign
|
||||
# don't forget to look to the same comment in ``lookupFor`` method
|
||||
_fieldsRegistry[fieldCls.typeCode] = fieldCls
|
||||
|
||||
|
||||
def lookupFor(typeCode):
|
||||
"""Return field definition class for the given type code.
|
||||
|
||||
``typeCode`` must be a single character. That type should be
|
||||
previously registered.
|
||||
|
||||
Use `registerField` to register new field class.
|
||||
|
||||
Return:
|
||||
Return value is a subclass of the `DbfFieldDef`.
|
||||
|
||||
"""
|
||||
# XXX: use typeCode.upper()? in case of any decign don't
|
||||
# forget to look to the same comment in ``registerField``
|
||||
return _fieldsRegistry[chr(typeCode)]
|
||||
|
||||
## register generic types
|
||||
|
||||
for (_name, _val) in list(globals().items()):
|
||||
if isinstance(_val, type) and issubclass(_val, DbfFieldDef) \
|
||||
and (_name != "DbfFieldDef"):
|
||||
__all__.append(_name)
|
||||
registerField(_val)
|
||||
del _name, _val
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,273 @@
|
||||
"""DBF header definition.
|
||||
|
||||
TODO:
|
||||
- handle encoding of the character fields
|
||||
(encoding information stored in the DBF header)
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
16-sep-2010 [als] fromStream: fix century of the last update field
|
||||
11-feb-2007 [als] added .ignoreErrors
|
||||
10-feb-2007 [als] added __getitem__: return field definitions
|
||||
by field name or field number (zero-based)
|
||||
04-jul-2006 [als] added export declaration
|
||||
15-dec-2005 [yc] created
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.6 $"[11:-2]
|
||||
__date__ = "$Date: 2010/09/16 05:06:39 $"[7:-2]
|
||||
|
||||
__all__ = ["DbfHeader"]
|
||||
|
||||
import io
|
||||
import datetime
|
||||
import struct
|
||||
import time
|
||||
import sys
|
||||
|
||||
from . import fields
|
||||
from .utils import getDate
|
||||
|
||||
|
||||
class DbfHeader(object):
|
||||
"""Dbf header definition.
|
||||
|
||||
For more information about dbf header format visit
|
||||
`http://www.clicketyclick.dk/databases/xbase/format/dbf.html#DBF_STRUCT`
|
||||
|
||||
Examples:
|
||||
Create an empty dbf header and add some field definitions:
|
||||
dbfh = DbfHeader()
|
||||
dbfh.addField(("name", "C", 10))
|
||||
dbfh.addField(("date", "D"))
|
||||
dbfh.addField(DbfNumericFieldDef("price", 5, 2))
|
||||
Create a dbf header with field definitions:
|
||||
dbfh = DbfHeader([
|
||||
("name", "C", 10),
|
||||
("date", "D"),
|
||||
DbfNumericFieldDef("price", 5, 2),
|
||||
])
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = ("signature", "fields", "lastUpdate", "recordLength",
|
||||
"recordCount", "headerLength", "changed", "_ignore_errors")
|
||||
|
||||
## instance construction and initialization methods
|
||||
|
||||
def __init__(self, fields=None, headerLength=0, recordLength=0,
|
||||
recordCount=0, signature=0x03, lastUpdate=None, ignoreErrors=False,
|
||||
):
|
||||
"""Initialize instance.
|
||||
|
||||
Arguments:
|
||||
fields:
|
||||
a list of field definitions;
|
||||
recordLength:
|
||||
size of the records;
|
||||
headerLength:
|
||||
size of the header;
|
||||
recordCount:
|
||||
number of records stored in DBF;
|
||||
signature:
|
||||
version number (aka signature). using 0x03 as a default meaning
|
||||
"File without DBT". for more information about this field visit
|
||||
``http://www.clicketyclick.dk/databases/xbase/format/dbf.html#DBF_NOTE_1_TARGET``
|
||||
lastUpdate:
|
||||
date of the DBF's update. this could be a string ('yymmdd' or
|
||||
'yyyymmdd'), timestamp (int or float), datetime/date value,
|
||||
a sequence (assuming (yyyy, mm, dd, ...)) or an object having
|
||||
callable ``ticks`` field.
|
||||
ignoreErrors:
|
||||
error processing mode for DBF fields (boolean)
|
||||
|
||||
"""
|
||||
self.signature = signature
|
||||
if fields is None:
|
||||
self.fields = []
|
||||
else:
|
||||
self.fields = list(fields)
|
||||
self.lastUpdate = getDate(lastUpdate)
|
||||
self.recordLength = recordLength
|
||||
self.headerLength = headerLength
|
||||
self.recordCount = recordCount
|
||||
self.ignoreErrors = ignoreErrors
|
||||
# XXX: I'm not sure this is safe to
|
||||
# initialize `self.changed` in this way
|
||||
self.changed = bool(self.fields)
|
||||
|
||||
# @classmethod
|
||||
def fromString(cls, string):
|
||||
"""Return header instance from the string object."""
|
||||
return cls.fromStream(io.StringIO(str(string)))
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
# @classmethod
|
||||
def fromStream(cls, stream):
|
||||
"""Return header object from the stream."""
|
||||
stream.seek(0)
|
||||
first_32 = stream.read(32)
|
||||
if type(first_32) != bytes:
|
||||
_data = bytes(first_32, sys.getfilesystemencoding())
|
||||
_data = first_32
|
||||
(_cnt, _hdrLen, _recLen) = struct.unpack("<I2H", _data[4:12])
|
||||
#reserved = _data[12:32]
|
||||
_year = _data[1]
|
||||
if _year < 80:
|
||||
# dBase II started at 1980. It is quite unlikely
|
||||
# that actual last update date is before that year.
|
||||
_year += 2000
|
||||
else:
|
||||
_year += 1900
|
||||
## create header object
|
||||
_obj = cls(None, _hdrLen, _recLen, _cnt, _data[0],
|
||||
(_year, _data[2], _data[3]))
|
||||
## append field definitions
|
||||
# position 0 is for the deletion flag
|
||||
_pos = 1
|
||||
_data = stream.read(1)
|
||||
while _data != b'\r':
|
||||
_data += stream.read(31)
|
||||
_fld = fields.lookupFor(_data[11]).fromString(_data, _pos)
|
||||
_obj._addField(_fld)
|
||||
_pos = _fld.end
|
||||
_data = stream.read(1)
|
||||
return _obj
|
||||
fromStream = classmethod(fromStream)
|
||||
|
||||
## properties
|
||||
|
||||
year = property(lambda self: self.lastUpdate.year)
|
||||
month = property(lambda self: self.lastUpdate.month)
|
||||
day = property(lambda self: self.lastUpdate.day)
|
||||
|
||||
def ignoreErrors(self, value):
|
||||
"""Update `ignoreErrors` flag on self and all fields"""
|
||||
self._ignore_errors = value = bool(value)
|
||||
for _field in self.fields:
|
||||
_field.ignoreErrors = value
|
||||
ignoreErrors = property(
|
||||
lambda self: self._ignore_errors,
|
||||
ignoreErrors,
|
||||
doc="""Error processing mode for DBF field value conversion
|
||||
|
||||
if set, failing field value conversion will return
|
||||
``INVALID_VALUE`` instead of raising conversion error.
|
||||
|
||||
""")
|
||||
|
||||
## object representation
|
||||
|
||||
def __repr__(self):
|
||||
_rv = """\
|
||||
Version (signature): 0x%02x
|
||||
Last update: %s
|
||||
Header length: %d
|
||||
Record length: %d
|
||||
Record count: %d
|
||||
FieldName Type Len Dec
|
||||
""" % (self.signature, self.lastUpdate, self.headerLength,
|
||||
self.recordLength, self.recordCount)
|
||||
_rv += "\n".join(
|
||||
["%10s %4s %3s %3s" % _fld.fieldInfo() for _fld in self.fields]
|
||||
)
|
||||
return _rv
|
||||
|
||||
## internal methods
|
||||
|
||||
def _addField(self, *defs):
|
||||
"""Internal variant of the `addField` method.
|
||||
|
||||
This method doesn't set `self.changed` field to True.
|
||||
|
||||
Return value is a length of the appended records.
|
||||
Note: this method doesn't modify ``recordLength`` and
|
||||
``headerLength`` fields. Use `addField` instead of this
|
||||
method if you don't exactly know what you're doing.
|
||||
|
||||
"""
|
||||
# insure we have dbf.DbfFieldDef instances first (instantiation
|
||||
# from the tuple could raise an error, in such a case I don't
|
||||
# wanna add any of the definitions -- all will be ignored)
|
||||
_defs = []
|
||||
_recordLength = 0
|
||||
for _def in defs:
|
||||
if isinstance(_def, fields.DbfFieldDef):
|
||||
_obj = _def
|
||||
else:
|
||||
(_name, _type, _len, _dec) = (tuple(_def) + (None,) * 4)[:4]
|
||||
_cls = fields.lookupFor(_type)
|
||||
_obj = _cls(_name, _len, _dec,
|
||||
ignoreErrors=self._ignore_errors)
|
||||
_recordLength += _obj.length
|
||||
_defs.append(_obj)
|
||||
# and now extend field definitions and
|
||||
# update record length
|
||||
self.fields += _defs
|
||||
return _recordLength
|
||||
|
||||
## interface methods
|
||||
|
||||
def addField(self, *defs):
|
||||
"""Add field definition to the header.
|
||||
|
||||
Examples:
|
||||
dbfh.addField(
|
||||
("name", "C", 20),
|
||||
dbf.DbfCharacterFieldDef("surname", 20),
|
||||
dbf.DbfDateFieldDef("birthdate"),
|
||||
("member", "L"),
|
||||
)
|
||||
dbfh.addField(("price", "N", 5, 2))
|
||||
dbfh.addField(dbf.DbfNumericFieldDef("origprice", 5, 2))
|
||||
|
||||
"""
|
||||
_oldLen = self.recordLength
|
||||
self.recordLength += self._addField(*defs)
|
||||
if not _oldLen:
|
||||
self.recordLength += 1
|
||||
# XXX: may be just use:
|
||||
# self.recordeLength += self._addField(*defs) + bool(not _oldLen)
|
||||
# recalculate headerLength
|
||||
self.headerLength = 32 + (32 * len(self.fields)) + 1
|
||||
self.changed = True
|
||||
|
||||
def write(self, stream):
|
||||
"""Encode and write header to the stream."""
|
||||
stream.seek(0)
|
||||
stream.write(self.toString())
|
||||
fields = [_fld.toString() for _fld in self.fields]
|
||||
stream.write(''.join(fields).encode(sys.getfilesystemencoding()))
|
||||
stream.write(b'\x0D') # cr at end of all header data
|
||||
self.changed = False
|
||||
|
||||
def toString(self):
|
||||
"""Returned 32 chars length string with encoded header."""
|
||||
return struct.pack("<4BI2H",
|
||||
self.signature,
|
||||
self.year - 1900,
|
||||
self.month,
|
||||
self.day,
|
||||
self.recordCount,
|
||||
self.headerLength,
|
||||
self.recordLength) + (b'\x00' * 20)
|
||||
#TODO: figure out if bytes(utf-8) is correct here.
|
||||
|
||||
def setCurrentDate(self):
|
||||
"""Update ``self.lastUpdate`` field with current date value."""
|
||||
self.lastUpdate = datetime.date.today()
|
||||
|
||||
def __getitem__(self, item):
|
||||
"""Return a field definition by numeric index or name string"""
|
||||
if isinstance(item, str):
|
||||
_name = item.upper()
|
||||
for _field in self.fields:
|
||||
if _field.name == _name:
|
||||
return _field
|
||||
else:
|
||||
raise KeyError(item)
|
||||
else:
|
||||
# item must be field index
|
||||
return self.fields[item]
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,266 @@
|
||||
"""DBF record definition.
|
||||
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] __repr__: added special case for invalid field values
|
||||
10-feb-2007 [als] added .rawFromStream()
|
||||
30-oct-2006 [als] fix record length in .fromStream()
|
||||
04-jul-2006 [als] added export declaration
|
||||
20-dec-2005 [yc] DbfRecord.write() -> DbfRecord._write();
|
||||
added delete() method.
|
||||
16-dec-2005 [yc] record definition moved from `dbf`.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.7 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 09:05:49 $"[7:-2]
|
||||
|
||||
__all__ = ["DbfRecord"]
|
||||
|
||||
import sys
|
||||
|
||||
from . import utils
|
||||
|
||||
class DbfRecord(object):
|
||||
"""DBF record.
|
||||
|
||||
Instances of this class shouldn't be created manualy,
|
||||
use `dbf.Dbf.newRecord` instead.
|
||||
|
||||
Class implements mapping/sequence interface, so
|
||||
fields could be accessed via their names or indexes
|
||||
(names is a preffered way to access fields).
|
||||
|
||||
Hint:
|
||||
Use `store` method to save modified record.
|
||||
|
||||
Examples:
|
||||
Add new record to the database:
|
||||
db = Dbf(filename)
|
||||
rec = db.newRecord()
|
||||
rec["FIELD1"] = value1
|
||||
rec["FIELD2"] = value2
|
||||
rec.store()
|
||||
Or the same, but modify existed
|
||||
(second in this case) record:
|
||||
db = Dbf(filename)
|
||||
rec = db[2]
|
||||
rec["FIELD1"] = value1
|
||||
rec["FIELD2"] = value2
|
||||
rec.store()
|
||||
|
||||
"""
|
||||
|
||||
__slots__ = "dbf", "index", "deleted", "fieldData"
|
||||
|
||||
## creation and initialization
|
||||
|
||||
def __init__(self, dbf, index=None, deleted=False, data=None):
|
||||
"""Instance initialiation.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance this record belonogs to.
|
||||
index:
|
||||
An integer record index or None. If this value is
|
||||
None, record will be appended to the DBF.
|
||||
deleted:
|
||||
Boolean flag indicating whether this record
|
||||
is a deleted record.
|
||||
data:
|
||||
A sequence or None. This is a data of the fields.
|
||||
If this argument is None, default values will be used.
|
||||
|
||||
"""
|
||||
self.dbf = dbf
|
||||
# XXX: I'm not sure ``index`` is necessary
|
||||
self.index = index
|
||||
self.deleted = deleted
|
||||
if data is None:
|
||||
self.fieldData = [_fd.defaultValue for _fd in dbf.header.fields]
|
||||
else:
|
||||
self.fieldData = list(data)
|
||||
|
||||
# XXX: validate self.index before calculating position?
|
||||
position = property(lambda self: self.dbf.header.headerLength + \
|
||||
self.index * self.dbf.header.recordLength)
|
||||
|
||||
def rawFromStream(cls, dbf, index):
|
||||
"""Return raw record contents read from the stream.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance containing the record.
|
||||
index:
|
||||
Index of the record in the records' container.
|
||||
This argument can't be None in this call.
|
||||
|
||||
Return value is a string containing record data in DBF format.
|
||||
|
||||
"""
|
||||
# XXX: may be write smth assuming, that current stream
|
||||
# position is the required one? it could save some
|
||||
# time required to calculate where to seek in the file
|
||||
dbf.stream.seek(dbf.header.headerLength +
|
||||
index * dbf.header.recordLength)
|
||||
return dbf.stream.read(dbf.header.recordLength)
|
||||
rawFromStream = classmethod(rawFromStream)
|
||||
|
||||
def fromStream(cls, dbf, index):
|
||||
"""Return a record read from the stream.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance new record should belong to.
|
||||
index:
|
||||
Index of the record in the records' container.
|
||||
This argument can't be None in this call.
|
||||
|
||||
Return value is an instance of the current class.
|
||||
|
||||
"""
|
||||
return cls.fromString(dbf, cls.rawFromStream(dbf, index), index)
|
||||
fromStream = classmethod(fromStream)
|
||||
|
||||
def fromString(cls, dbf, string, index=None):
|
||||
"""Return record read from the string object.
|
||||
|
||||
Arguments:
|
||||
dbf:
|
||||
A `Dbf.Dbf` instance new record should belong to.
|
||||
string:
|
||||
A string new record should be created from.
|
||||
index:
|
||||
Index of the record in the container. If this
|
||||
argument is None, record will be appended.
|
||||
|
||||
Return value is an instance of the current class.
|
||||
|
||||
"""
|
||||
return cls(dbf, index, string[0]=="*",
|
||||
[_fd.decodeFromRecord(string) for _fd in dbf.header.fields])
|
||||
fromString = classmethod(fromString)
|
||||
|
||||
## object representation
|
||||
|
||||
def __repr__(self):
|
||||
_template = "%%%ds: %%s (%%s)" % max([len(_fld)
|
||||
for _fld in self.dbf.fieldNames])
|
||||
_rv = []
|
||||
for _fld in self.dbf.fieldNames:
|
||||
_val = self[_fld]
|
||||
if _val is utils.INVALID_VALUE:
|
||||
_rv.append(_template %
|
||||
(_fld, "None", "value cannot be decoded"))
|
||||
else:
|
||||
_rv.append(_template % (_fld, _val, type(_val)))
|
||||
return "\n".join(_rv)
|
||||
|
||||
## protected methods
|
||||
|
||||
def _write(self):
|
||||
"""Write data to the dbf stream.
|
||||
|
||||
Note:
|
||||
This isn't a public method, it's better to
|
||||
use 'store' instead publically.
|
||||
Be design ``_write`` method should be called
|
||||
only from the `Dbf` instance.
|
||||
|
||||
|
||||
"""
|
||||
self._validateIndex(False)
|
||||
self.dbf.stream.seek(self.position)
|
||||
self.dbf.stream.write(bytes(self.toString(),
|
||||
sys.getfilesystemencoding()))
|
||||
# FIXME: may be move this write somewhere else?
|
||||
# why we should check this condition for each record?
|
||||
if self.index == len(self.dbf):
|
||||
# this is the last record,
|
||||
# we should write SUB (ASCII 26)
|
||||
self.dbf.stream.write(b"\x1A")
|
||||
|
||||
## utility methods
|
||||
|
||||
def _validateIndex(self, allowUndefined=True, checkRange=False):
|
||||
"""Valid ``self.index`` value.
|
||||
|
||||
If ``allowUndefined`` argument is True functions does nothing
|
||||
in case of ``self.index`` pointing to None object.
|
||||
|
||||
"""
|
||||
if self.index is None:
|
||||
if not allowUndefined:
|
||||
raise ValueError("Index is undefined")
|
||||
elif self.index < 0:
|
||||
raise ValueError("Index can't be negative (%s)" % self.index)
|
||||
elif checkRange and self.index <= self.dbf.header.recordCount:
|
||||
raise ValueError("There are only %d records in the DBF" %
|
||||
self.dbf.header.recordCount)
|
||||
|
||||
## interface methods
|
||||
|
||||
def store(self):
|
||||
"""Store current record in the DBF.
|
||||
|
||||
If ``self.index`` is None, this record will be appended to the
|
||||
records of the DBF this records belongs to; or replaced otherwise.
|
||||
|
||||
"""
|
||||
self._validateIndex()
|
||||
if self.index is None:
|
||||
self.index = len(self.dbf)
|
||||
self.dbf.append(self)
|
||||
else:
|
||||
self.dbf[self.index] = self
|
||||
|
||||
def delete(self):
|
||||
"""Mark method as deleted."""
|
||||
self.deleted = True
|
||||
|
||||
def toString(self):
|
||||
"""Return string packed record values."""
|
||||
# for (_def, _dat) in zip(self.dbf.header.fields, self.fieldData):
|
||||
#
|
||||
|
||||
return "".join([" *"[self.deleted]] + [
|
||||
_def.encodeValue(_dat)
|
||||
for (_def, _dat) in zip(self.dbf.header.fields, self.fieldData)
|
||||
])
|
||||
|
||||
def asList(self):
|
||||
"""Return a flat list of fields.
|
||||
|
||||
Note:
|
||||
Change of the list's values won't change
|
||||
real values stored in this object.
|
||||
|
||||
"""
|
||||
return self.fieldData[:]
|
||||
|
||||
def asDict(self):
|
||||
"""Return a dictionary of fields.
|
||||
|
||||
Note:
|
||||
Change of the dicts's values won't change
|
||||
real values stored in this object.
|
||||
|
||||
"""
|
||||
return dict([_i for _i in zip(self.dbf.fieldNames, self.fieldData)])
|
||||
|
||||
def __getitem__(self, key):
|
||||
"""Return value by field name or field index."""
|
||||
if isinstance(key, int):
|
||||
# integer index of the field
|
||||
return self.fieldData[key]
|
||||
# assuming string field name
|
||||
return self.fieldData[self.dbf.indexOfFieldName(key)]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
"""Set field value by integer index of the field or string name."""
|
||||
if isinstance(key, int):
|
||||
# integer index of the field
|
||||
return self.fieldData[key]
|
||||
# assuming string field name
|
||||
self.fieldData[self.dbf.indexOfFieldName(key)] = value
|
||||
|
||||
# vim: et sts=4 sw=4 :
|
||||
@@ -0,0 +1,170 @@
|
||||
"""String utilities.
|
||||
|
||||
TODO:
|
||||
- allow strings in getDateTime routine;
|
||||
"""
|
||||
"""History (most recent first):
|
||||
11-feb-2007 [als] added INVALID_VALUE
|
||||
10-feb-2007 [als] allow date strings padded with spaces instead of zeroes
|
||||
20-dec-2005 [yc] handle long objects in getDate/getDateTime
|
||||
16-dec-2005 [yc] created from ``strutil`` module.
|
||||
"""
|
||||
|
||||
__version__ = "$Revision: 1.4 $"[11:-2]
|
||||
__date__ = "$Date: 2007/02/11 08:57:17 $"[7:-2]
|
||||
|
||||
import datetime
|
||||
import time
|
||||
|
||||
|
||||
def unzfill(str):
|
||||
"""Return a string without ASCII NULs.
|
||||
|
||||
This function searchers for the first NUL (ASCII 0) occurance
|
||||
and truncates string till that position.
|
||||
|
||||
"""
|
||||
try:
|
||||
return str[:str.index(b'\0')]
|
||||
except ValueError:
|
||||
return str
|
||||
|
||||
|
||||
def getDate(date=None):
|
||||
"""Return `datetime.date` instance.
|
||||
|
||||
Type of the ``date`` argument could be one of the following:
|
||||
None:
|
||||
use current date value;
|
||||
datetime.date:
|
||||
this value will be returned;
|
||||
datetime.datetime:
|
||||
the result of the date.date() will be returned;
|
||||
string:
|
||||
assuming "%Y%m%d" or "%y%m%dd" format;
|
||||
number:
|
||||
assuming it's a timestamp (returned for example
|
||||
by the time.time() call;
|
||||
sequence:
|
||||
assuming (year, month, day, ...) sequence;
|
||||
|
||||
Additionaly, if ``date`` has callable ``ticks`` attribute,
|
||||
it will be used and result of the called would be treated
|
||||
as a timestamp value.
|
||||
|
||||
"""
|
||||
if date is None:
|
||||
# use current value
|
||||
return datetime.date.today()
|
||||
if isinstance(date, datetime.date):
|
||||
return date
|
||||
if isinstance(date, datetime.datetime):
|
||||
return date.date()
|
||||
if isinstance(date, (int, float)):
|
||||
# date is a timestamp
|
||||
return datetime.date.fromtimestamp(date)
|
||||
if isinstance(date, str):
|
||||
date = date.replace(" ", "0")
|
||||
if len(date) == 6:
|
||||
# yymmdd
|
||||
return datetime.date(*time.strptime(date, "%y%m%d")[:3])
|
||||
# yyyymmdd
|
||||
return datetime.date(*time.strptime(date, "%Y%m%d")[:3])
|
||||
if hasattr(date, "__getitem__"):
|
||||
# a sequence (assuming date/time tuple)
|
||||
return datetime.date(*date[:3])
|
||||
return datetime.date.fromtimestamp(date.ticks())
|
||||
|
||||
|
||||
def getDateTime(value=None):
|
||||
"""Return `datetime.datetime` instance.
|
||||
|
||||
Type of the ``value`` argument could be one of the following:
|
||||
None:
|
||||
use current date value;
|
||||
datetime.date:
|
||||
result will be converted to the `datetime.datetime` instance
|
||||
using midnight;
|
||||
datetime.datetime:
|
||||
``value`` will be returned as is;
|
||||
string:
|
||||
*** CURRENTLY NOT SUPPORTED ***;
|
||||
number:
|
||||
assuming it's a timestamp (returned for example
|
||||
by the time.time() call;
|
||||
sequence:
|
||||
assuming (year, month, day, ...) sequence;
|
||||
|
||||
Additionaly, if ``value`` has callable ``ticks`` attribute,
|
||||
it will be used and result of the called would be treated
|
||||
as a timestamp value.
|
||||
|
||||
"""
|
||||
if value is None:
|
||||
# use current value
|
||||
return datetime.datetime.today()
|
||||
if isinstance(value, datetime.datetime):
|
||||
return value
|
||||
if isinstance(value, datetime.date):
|
||||
return datetime.datetime.fromordinal(value.toordinal())
|
||||
if isinstance(value, (int, float)):
|
||||
# value is a timestamp
|
||||
return datetime.datetime.fromtimestamp(value)
|
||||
if isinstance(value, str):
|
||||
raise NotImplementedError("Strings aren't currently implemented")
|
||||
if hasattr(value, "__getitem__"):
|
||||
# a sequence (assuming date/time tuple)
|
||||
return datetime.datetime(*tuple(value)[:6])
|
||||
return datetime.datetime.fromtimestamp(value.ticks())
|
||||
|
||||
|
||||
class classproperty(property):
|
||||
"""Works in the same way as a ``property``, but for the classes."""
|
||||
|
||||
def __get__(self, obj, cls):
|
||||
return self.fget(cls)
|
||||
|
||||
|
||||
class _InvalidValue(object):
|
||||
|
||||
"""Value returned from DBF records when field validation fails
|
||||
|
||||
The value is not equal to anything except for itself
|
||||
and equal to all empty values: None, 0, empty string etc.
|
||||
In other words, invalid value is equal to None and not equal
|
||||
to None at the same time.
|
||||
|
||||
This value yields zero upon explicit conversion to a number type,
|
||||
empty string for string types, and False for boolean.
|
||||
|
||||
"""
|
||||
|
||||
def __eq__(self, other):
|
||||
return not other
|
||||
|
||||
def __ne__(self, other):
|
||||
return not (other is self)
|
||||
|
||||
def __bool__(self):
|
||||
return False
|
||||
|
||||
def __int__(self):
|
||||
return 0
|
||||
__long__ = __int__
|
||||
|
||||
def __float__(self):
|
||||
return 0.0
|
||||
|
||||
def __str__(self):
|
||||
return ""
|
||||
|
||||
def __unicode__(self):
|
||||
return ""
|
||||
|
||||
def __repr__(self):
|
||||
return "<INVALID>"
|
||||
|
||||
# invalid value is a constant singleton
|
||||
INVALID_VALUE = _InvalidValue()
|
||||
|
||||
# vim: set et sts=4 sw=4 :
|
||||
@@ -0,0 +1,24 @@
|
||||
from __future__ import division
|
||||
|
||||
|
||||
def median(data):
|
||||
"""
|
||||
Return the median (middle value) of numeric data, using the common
|
||||
"mean of middle two" method. If data is empty, ValueError is raised.
|
||||
|
||||
Mimics the behaviour of Python3's statistics.median
|
||||
|
||||
>>> median([1, 3, 5])
|
||||
3
|
||||
>>> median([1, 3, 5, 7])
|
||||
4.0
|
||||
|
||||
"""
|
||||
data = sorted(data)
|
||||
n = len(data)
|
||||
if not n:
|
||||
raise ValueError("No median for empty data")
|
||||
i = n // 2
|
||||
if n % 2:
|
||||
return data[i]
|
||||
return (data[i - 1] + data[i]) / 2
|
||||
@@ -1,14 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
Tabbed -- CLI for Tablib
|
||||
Copyright (c) 2010 Kenneth Reitz. MIT License.
|
||||
"""
|
||||
|
||||
import tablib.cli
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
tablib.cli.start()
|
||||
@@ -1,8 +0,0 @@
|
||||
""" Tablib.
|
||||
"""
|
||||
|
||||
from tablib.core import (
|
||||
Databook, Dataset, detect, import_set,
|
||||
InvalidDatasetType, InvalidDimensions, UnsupportedFormat
|
||||
)
|
||||
|
||||
@@ -1,84 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
# encoding: utf-8
|
||||
|
||||
""" Tabbed CLI Inteface Application
|
||||
"""
|
||||
|
||||
import io
|
||||
import sys
|
||||
|
||||
import argue
|
||||
|
||||
import tablib
|
||||
from helpers import Struct, piped
|
||||
|
||||
|
||||
|
||||
FORMATS = [fmt.title for fmt in tablib.formats.FORMATS]
|
||||
|
||||
opts = []
|
||||
|
||||
opts.append(('v', 'version', False, 'Report tabbed version'))
|
||||
|
||||
for format in FORMATS:
|
||||
opts.append(('', format, False, 'Output to %s' % (format.upper())))
|
||||
|
||||
|
||||
|
||||
@argue.command(options=opts, usage='[FILE] [--FORMAT | FILE]')
|
||||
def start(in_file=None, out_file=None, **opts):
|
||||
"""Covertly convert dataset formats"""
|
||||
|
||||
opts = Struct(**opts)
|
||||
|
||||
if opts.version:
|
||||
print('Tabbed, Ver. %s' % tablib.core.__version__)
|
||||
sys.exit(0)
|
||||
|
||||
stdin = piped()
|
||||
|
||||
if stdin:
|
||||
data = tablib.import_set(stdin)
|
||||
|
||||
elif in_file:
|
||||
|
||||
try:
|
||||
in_stream =- io.open(in_file, 'r').read()
|
||||
except Exception, e:
|
||||
print(' %s cannot be read.' % in_file)
|
||||
sys.exit(65)
|
||||
|
||||
try:
|
||||
tablib.import_set(in_stream)
|
||||
except Exception, e:
|
||||
raise e
|
||||
print('Import format not supported.')
|
||||
sys.exit(65)
|
||||
else:
|
||||
print('Please provide input.')
|
||||
sys.exit(65)
|
||||
|
||||
|
||||
_formats_sum = sum(opts[f] for f in FORMATS)
|
||||
|
||||
# Multiple output formats given
|
||||
if _formats_sum > 1:
|
||||
print('Please specify a single output format.')
|
||||
sys.exit(64)
|
||||
|
||||
# No output formats given
|
||||
elif _formats_sum < 1:
|
||||
print('Please specify an output format.')
|
||||
sys.exit(64)
|
||||
|
||||
|
||||
# fetch options.formats list
|
||||
# if sum(()) > 1
|
||||
# log only one data format please
|
||||
# if sum of formats == 0, specity format
|
||||
|
||||
# look for filename
|
||||
|
||||
# print opts.__dict__
|
||||
# print in_file
|
||||
# print out_file
|
||||
-440
@@ -1,440 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
tablib.core
|
||||
~~~~~~~~~~~
|
||||
|
||||
This module implements the central tablib objects.
|
||||
|
||||
:copyright: (c) 2010 by Kenneth Reitz.
|
||||
:license: MIT, see LICENSE for more details.
|
||||
"""
|
||||
|
||||
from tablib.formats import FORMATS as formats
|
||||
|
||||
|
||||
__title__ = 'tablib'
|
||||
__version__ = '0.8.5'
|
||||
__build__ = 0x000805
|
||||
__author__ = 'Kenneth Reitz'
|
||||
__license__ = 'MIT'
|
||||
__copyright__ = 'Copyright 2010 Kenneth Reitz'
|
||||
|
||||
|
||||
class Dataset(object):
|
||||
"""The tablib Dataset object is the heart of tablib. It provides all core
|
||||
functionality.
|
||||
|
||||
Usually you create a :class:`Dataset` instance in your main module, and append
|
||||
rows and columns as you collect data. ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.headers = ('name', 'age')
|
||||
|
||||
for (name, age) in some_collector():
|
||||
data.append((name, age))
|
||||
|
||||
You can also set rows and headers upon instantiation. This is useful if dealing
|
||||
with dozens or hundres of :class:`Dataset` objects. ::
|
||||
|
||||
headers = ('first_name', 'last_name')
|
||||
data = [('John', 'Adams'), ('George', 'Washington')]
|
||||
|
||||
data = tablib.Dataset(*data, headers=headers)
|
||||
|
||||
|
||||
:param \*args: (optional) list of rows to populate Dataset
|
||||
:param headers: (optional) list strings for Dataset header row
|
||||
|
||||
|
||||
.. admonition:: About the Format Attributes
|
||||
|
||||
If you look at the code, the various output/import formats are not
|
||||
defined within the itself. To add support for a new format, see
|
||||
:ref:`Adding New Formats`.
|
||||
|
||||
.. attribute:: csv
|
||||
|
||||
A CSV representation of the Dataset object. The top row will contain
|
||||
headers, if they have been set. Otherwise, the top row will contain
|
||||
the first row of the dataset.
|
||||
|
||||
A dataset object can also be imported by setting the `Dataset.csv` attribute: ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.csv = 'age, first_name, last_name\\n90, John, Adams'
|
||||
|
||||
Import assumes (for now) that headers exist.
|
||||
|
||||
|
||||
.. attribute:: dict
|
||||
|
||||
An native Python representation of the Dataset object. If headers have been
|
||||
set, a list of Python dictionaries will be returned. If no headers have been
|
||||
set, a list of tuples (rows) will be returned instead.
|
||||
|
||||
A dataset object can also be imported by setting the `Dataset.dict` attribute: ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.dict = [{'age': 90, 'first_name': 'Kenneth', 'last_name': 'Reitz'}]
|
||||
|
||||
|
||||
.. attribute:: xls
|
||||
|
||||
An Excel Spreadsheet representation of the Dataset object, including
|
||||
:ref:`seperators`.
|
||||
|
||||
*Note:* `Dataset.xls` contains binary data, so make sure to write in binary
|
||||
mode::
|
||||
|
||||
with open('output.xls', 'wb') as f:
|
||||
f.write(data.xls)
|
||||
|
||||
|
||||
.. attribute:: yaml
|
||||
|
||||
A YAML representation of the Dataset object. If headers have been
|
||||
set, a YAML list of objects will be returned. If no headers have
|
||||
been set, a YAML list of lists (rows) will be returned instead.
|
||||
|
||||
A dataset object can also be imported by setting the `Dataset.json` attribute: ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.yaml = '- {age: 90, first_name: John, last_name: Adams}'
|
||||
|
||||
Import assumes (for now) that headers exist.
|
||||
"""
|
||||
|
||||
def __init__(self, *args, **kwargs):
|
||||
self._data = list(args)
|
||||
self.__headers = None
|
||||
|
||||
# ('title', index) tuples
|
||||
self._separators = []
|
||||
|
||||
try:
|
||||
self.headers = kwargs['headers']
|
||||
except KeyError:
|
||||
self.headers = None
|
||||
|
||||
try:
|
||||
self.title = kwargs['title']
|
||||
except KeyError:
|
||||
self.title = None
|
||||
|
||||
self._register_formats()
|
||||
|
||||
|
||||
def __len__(self):
|
||||
return self.height
|
||||
|
||||
|
||||
def __getitem__(self, key):
|
||||
if isinstance(key, basestring):
|
||||
if key in self.headers:
|
||||
pos = self.headers.index(key) # get 'key' index from each data
|
||||
return [row[pos] for row in self._data]
|
||||
else:
|
||||
raise KeyError
|
||||
else:
|
||||
return self._data[key]
|
||||
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
self._validate(value)
|
||||
self._data[key] = tuple(value)
|
||||
|
||||
|
||||
def __delitem__(self, key):
|
||||
del self._data[key]
|
||||
|
||||
|
||||
def __repr__(self):
|
||||
try:
|
||||
return '<%s dataset>' % (self.title.lower())
|
||||
except AttributeError:
|
||||
return '<dataset object>'
|
||||
|
||||
|
||||
@classmethod
|
||||
def _register_formats(cls):
|
||||
"""Adds format properties."""
|
||||
for fmt in formats:
|
||||
try:
|
||||
try:
|
||||
setattr(cls, fmt.title, property(fmt.export_set, fmt.import_set))
|
||||
except AttributeError:
|
||||
setattr(cls, fmt.title, property(fmt.export_set))
|
||||
|
||||
except AttributeError:
|
||||
pass
|
||||
|
||||
|
||||
def _validate(self, row=None, col=None, safety=False):
|
||||
"""Assures size of every row in dataset is of proper proportions."""
|
||||
if row:
|
||||
is_valid = (len(row) == self.width) if self.width else True
|
||||
elif col:
|
||||
if self.headers:
|
||||
is_valid = (len(col) - 1) == self.height
|
||||
else:
|
||||
is_valid = (len(col) == self.height) if self.height else True
|
||||
else:
|
||||
is_valid = all((len(x)== self.width for x in self._data))
|
||||
|
||||
if is_valid:
|
||||
return True
|
||||
else:
|
||||
if not safety:
|
||||
raise InvalidDimensions
|
||||
return False
|
||||
|
||||
|
||||
def _package(self, dicts=True):
|
||||
"""Packages Dataset into lists of dictionaries for transmission."""
|
||||
|
||||
if self.headers:
|
||||
if dicts:
|
||||
data = [dict(zip(self.headers, data_row)) for data_row in self ._data]
|
||||
else:
|
||||
data = [list(self.headers)] + list(self._data)
|
||||
else:
|
||||
data = [list(row) for row in self._data]
|
||||
|
||||
return data
|
||||
|
||||
|
||||
@property
|
||||
def height(self):
|
||||
"""Returns the height of the Dataset."""
|
||||
return len(self._data)
|
||||
|
||||
|
||||
@property
|
||||
def width(self):
|
||||
"""Returns the width of the Dataset."""
|
||||
try:
|
||||
return len(self._data[0])
|
||||
except IndexError:
|
||||
try:
|
||||
return len(self.headers)
|
||||
except TypeError:
|
||||
return 0
|
||||
|
||||
|
||||
@property
|
||||
def headers(self):
|
||||
"""Headers property."""
|
||||
return self.__headers
|
||||
|
||||
|
||||
@headers.setter
|
||||
def headers(self, collection):
|
||||
"""Validating headers setter."""
|
||||
self._validate(collection)
|
||||
if collection:
|
||||
try:
|
||||
self.__headers = list(collection)
|
||||
except TypeError:
|
||||
raise TypeError
|
||||
else:
|
||||
self.__headers = None
|
||||
|
||||
|
||||
@property
|
||||
def dict(self):
|
||||
"""A JSON representation of the Dataset object. If headers have been
|
||||
set, a JSON list of objects will be returned. If no headers have
|
||||
been set, a JSON list of lists (rows) will be returned instead.
|
||||
|
||||
A dataset object can also be imported by setting the `Dataset.json` attribute: ::
|
||||
|
||||
data = tablib.Dataset()
|
||||
data.json = '[{"last_name": "Adams","age": 90,"first_name": "John"}]'
|
||||
|
||||
"""
|
||||
return self._package()
|
||||
|
||||
|
||||
@dict.setter
|
||||
def dict(self, pickle):
|
||||
|
||||
if not len(pickle):
|
||||
return
|
||||
|
||||
# if list of rows
|
||||
if isinstance(pickle[0], list):
|
||||
self.wipe()
|
||||
for row in pickle:
|
||||
self.append(row)
|
||||
|
||||
# if list of objects
|
||||
elif isinstance(pickle[0], dict):
|
||||
self.wipe()
|
||||
self.headers = pickle[0].keys()
|
||||
for row in pickle:
|
||||
self.append(row.values())
|
||||
else:
|
||||
raise UnsupportedFormat
|
||||
|
||||
|
||||
def append(self, row=None, col=None):
|
||||
"""Adds a row to the end of Dataset"""
|
||||
if row is not None:
|
||||
self._validate(row)
|
||||
self._data.append(tuple(row))
|
||||
elif col is not None:
|
||||
col = list(col)
|
||||
if self.headers:
|
||||
header = [col.pop(0)]
|
||||
else:
|
||||
header = []
|
||||
if len(col) == 1 and callable(col[0]):
|
||||
col = map(col[0], self._data)
|
||||
col = tuple(header + col)
|
||||
|
||||
self._validate(col=col)
|
||||
|
||||
if self.headers:
|
||||
# pop the first item off, add to headers
|
||||
self.headers.append(col[0])
|
||||
col = col[1:]
|
||||
|
||||
if self.height and self.width:
|
||||
|
||||
for i, row in enumerate(self._data):
|
||||
_row = list(row)
|
||||
_row.append(col[i])
|
||||
self._data[i] = tuple(_row)
|
||||
else:
|
||||
self._data = [tuple([row]) for row in col]
|
||||
|
||||
|
||||
def insert_separator(self, index, text='-'):
|
||||
"""Adds a separator to Dataset at given index."""
|
||||
|
||||
sep = (index, text)
|
||||
self._separators.append(sep)
|
||||
|
||||
|
||||
def append_separator(self, text='-'):
|
||||
"""Adds a separator to Dataset."""
|
||||
|
||||
# change offsets if headers are or aren't defined
|
||||
if not self.headers:
|
||||
index = self.height if self.height else 0
|
||||
else:
|
||||
index = (self.height + 1) if self.height else 1
|
||||
|
||||
self.insert_separator(index, text)
|
||||
|
||||
|
||||
def insert(self, i, row=None):
|
||||
"""Inserts a row at given position in Dataset"""
|
||||
if row:
|
||||
self._validate(row)
|
||||
self._data.insert(i, tuple(row))
|
||||
elif col:
|
||||
pass
|
||||
|
||||
|
||||
def wipe(self):
|
||||
"""Erases all data from Dataset."""
|
||||
self._data = list()
|
||||
self.__headers = None
|
||||
|
||||
|
||||
class Databook(object):
|
||||
"""A book of Dataset objects.
|
||||
Currently, this exists only for XLS workbook support.
|
||||
"""
|
||||
|
||||
def __init__(self, sets=[]):
|
||||
self._datasets = sets
|
||||
self._register_formats()
|
||||
|
||||
|
||||
def __repr__(self):
|
||||
try:
|
||||
return '<%s databook>' % (self.title.lower())
|
||||
except AttributeError:
|
||||
return '<databook object>'
|
||||
|
||||
|
||||
def wipe(self):
|
||||
"""Wipe book clean."""
|
||||
self._datasets = []
|
||||
|
||||
|
||||
@classmethod
|
||||
def _register_formats(cls):
|
||||
"""Adds format properties."""
|
||||
for fmt in formats:
|
||||
try:
|
||||
try:
|
||||
setattr(cls, fmt.title, property(fmt.export_book, fmt.import_book))
|
||||
except AttributeError:
|
||||
setattr(cls, fmt.title, property(fmt.export_book))
|
||||
|
||||
except AttributeError:
|
||||
pass
|
||||
|
||||
|
||||
def add_sheet(self, dataset):
|
||||
"""Adds given dataset."""
|
||||
if type(dataset) is Dataset:
|
||||
self._datasets.append(dataset)
|
||||
else:
|
||||
raise InvalidDatasetType
|
||||
|
||||
|
||||
def _package(self):
|
||||
"""Packages Databook for delivery."""
|
||||
collector = []
|
||||
for dset in self._datasets:
|
||||
collector.append(dict(
|
||||
title = dset.title,
|
||||
data = dset.dict
|
||||
))
|
||||
return collector
|
||||
|
||||
|
||||
@property
|
||||
def size(self):
|
||||
"""The number of the Datasets within DataBook."""
|
||||
return len(self._datasets)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Return (format, stream) of given stream."""
|
||||
for fmt in formats:
|
||||
try:
|
||||
if fmt.detect(stream):
|
||||
return (fmt, stream)
|
||||
except AttributeError:
|
||||
pass
|
||||
return (None, stream)
|
||||
|
||||
|
||||
def import_set(stream):
|
||||
"""Return dataset of given stream."""
|
||||
(format, stream) = detect(stream)
|
||||
|
||||
try:
|
||||
data = Dataset()
|
||||
format.import_set(data, stream)
|
||||
return data
|
||||
|
||||
except AttributeError, e:
|
||||
return None
|
||||
|
||||
|
||||
class InvalidDatasetType(Exception):
|
||||
"Only Datasets can be added to a DataBook"
|
||||
|
||||
|
||||
class InvalidDimensions(Exception):
|
||||
"Invalid size"
|
||||
|
||||
|
||||
class UnsupportedFormat(NotImplementedError):
|
||||
"Format is not supported"
|
||||
@@ -1,11 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - formats
|
||||
"""
|
||||
|
||||
import _csv as csv
|
||||
import _json as json
|
||||
import _xls as xls
|
||||
import _yaml as yaml
|
||||
|
||||
FORMATS = (json, xls, yaml, csv)
|
||||
@@ -1,49 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - CSV Support.
|
||||
"""
|
||||
|
||||
import cStringIO
|
||||
import csv
|
||||
import os
|
||||
|
||||
import tablib
|
||||
|
||||
|
||||
title = 'csv'
|
||||
extentions = ('csv',)
|
||||
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns CSV representation of Dataset."""
|
||||
stream = cStringIO.StringIO()
|
||||
_csv = csv.writer(stream)
|
||||
|
||||
for row in dataset._package(dicts=False):
|
||||
_csv.writerow(row)
|
||||
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def import_set(dset, in_stream, headers=True):
|
||||
"""Returns dataset from CSV stream."""
|
||||
|
||||
dset.wipe()
|
||||
|
||||
rows = csv.reader(in_stream.split())
|
||||
for i, row in enumerate(rows):
|
||||
|
||||
if (i == 0) and (headers):
|
||||
dset.headers = row
|
||||
else:
|
||||
dset.append(row)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid CSV."""
|
||||
try:
|
||||
rows = dialect = csv.Sniffer().sniff(stream)
|
||||
return True
|
||||
except csv.Error:
|
||||
return False
|
||||
@@ -1,55 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - JSON Support
|
||||
"""
|
||||
|
||||
try:
|
||||
import json # load system JSON (Python >= 2.6)
|
||||
except ImportError:
|
||||
try:
|
||||
import simplejson as json
|
||||
except ImportError:
|
||||
import tablib.packages.simplejson as json # use the vendorized copy
|
||||
|
||||
import tablib.core
|
||||
|
||||
|
||||
title = 'json'
|
||||
extentions = ('json', 'jsn')
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns JSON representation of Dataset."""
|
||||
return json.dumps(dataset.dict)
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns JSON representation of Databook."""
|
||||
return json.dumps(databook._package())
|
||||
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
"""Returns dataset from JSON stream."""
|
||||
|
||||
dset.wipe()
|
||||
dset.dict = json.loads(in_stream)
|
||||
|
||||
|
||||
def import_book(dbook, in_stream):
|
||||
"""Returns databook from JSON stream."""
|
||||
|
||||
dbook.wipe()
|
||||
for sheet in json.loads(in_stream):
|
||||
data = tablib.core.Dataset()
|
||||
data.title = sheet['title']
|
||||
data.dict = sheet['data']
|
||||
dbook.add_sheet(data)
|
||||
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid JSON."""
|
||||
try:
|
||||
json.loads(stream)
|
||||
return True
|
||||
except ValueError:
|
||||
return False
|
||||
@@ -1,80 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - XLS Support.
|
||||
"""
|
||||
|
||||
import cStringIO
|
||||
|
||||
try:
|
||||
import xlwt
|
||||
except ImportError:
|
||||
import tablib.packages.xlwt as xlwt
|
||||
|
||||
|
||||
title = 'xls'
|
||||
extentions = ('xls',)
|
||||
|
||||
# special styles
|
||||
wrap = xlwt.easyxf("alignment: wrap on")
|
||||
bold = xlwt.easyxf("font: bold on")
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns XLS representation of Dataset."""
|
||||
|
||||
wb = xlwt.Workbook(encoding='utf8')
|
||||
ws = wb.add_sheet(dataset.title if dataset.title else 'Tabbed Dataset')
|
||||
|
||||
dset_sheet(dataset, ws)
|
||||
|
||||
stream = cStringIO.StringIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns XLS representation of DataBook."""
|
||||
|
||||
wb = xlwt.Workbook(encoding='utf8')
|
||||
|
||||
for i, dset in enumerate(databook._datasets):
|
||||
ws = wb.add_sheet(dset.title if dset.title else 'Sheet%s' % (i))
|
||||
|
||||
dset_sheet(dset, ws)
|
||||
|
||||
|
||||
stream = cStringIO.StringIO()
|
||||
wb.save(stream)
|
||||
return stream.getvalue()
|
||||
|
||||
|
||||
def dset_sheet(dataset, ws):
|
||||
"""Completes given worksheet from given Dataset."""
|
||||
_package = dataset._package(dicts=False)
|
||||
|
||||
for i, sep in enumerate(dataset._separators):
|
||||
_offset = i
|
||||
_package.insert((sep[0] + _offset), (sep[1],))
|
||||
|
||||
for i, row in enumerate(_package):
|
||||
for j, col in enumerate(row):
|
||||
|
||||
# bold headers
|
||||
if (i == 0) and dataset.headers:
|
||||
ws.write(i, j, col, bold)
|
||||
|
||||
# bold separators
|
||||
elif len(row) < dataset.width:
|
||||
ws.write(i, j, col, bold)
|
||||
|
||||
# wrap the rest
|
||||
else:
|
||||
try:
|
||||
if '\n' in col:
|
||||
ws.write(i, j, col, wrap)
|
||||
else:
|
||||
ws.write(i, j, col)
|
||||
except TypeError:
|
||||
ws.write(i, j, col)
|
||||
|
||||
|
||||
@@ -1,57 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - YAML Support.
|
||||
"""
|
||||
|
||||
try:
|
||||
import yaml
|
||||
except ImportError:
|
||||
import tablib.packages.yaml as yaml
|
||||
|
||||
import tablib
|
||||
|
||||
|
||||
|
||||
title = 'yaml'
|
||||
extentions = ('yaml', 'yml')
|
||||
|
||||
|
||||
|
||||
def export_set(dataset):
|
||||
"""Returns YAML representation of Dataset."""
|
||||
return yaml.dump(dataset.dict)
|
||||
|
||||
|
||||
def export_book(databook):
|
||||
"""Returns YAML representation of Databook."""
|
||||
return yaml.dump(databook._package())
|
||||
|
||||
|
||||
def import_set(dset, in_stream):
|
||||
"""Returns dataset from YAML stream."""
|
||||
|
||||
dset.wipe()
|
||||
dset.dict = yaml.load(in_stream)
|
||||
|
||||
|
||||
def import_book(dbook, in_stream):
|
||||
"""Returns databook from YAML stream."""
|
||||
|
||||
dbook.wipe()
|
||||
|
||||
for sheet in yaml.load(in_stream):
|
||||
data = tablib.core.Dataset()
|
||||
data.title = sheet['title']
|
||||
data.dict = sheet['data']
|
||||
dbook.add_sheet(data)
|
||||
|
||||
def detect(stream):
|
||||
"""Returns True if given stream is valid YAML."""
|
||||
try:
|
||||
_yaml = yaml.load(stream)
|
||||
if isinstance(_yaml, (list, tuple, dict)):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
except yaml.parser.ParserError:
|
||||
return False
|
||||
@@ -1,37 +0,0 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" Tablib - General Helpers.
|
||||
"""
|
||||
|
||||
import sys
|
||||
|
||||
|
||||
class Struct(object):
|
||||
"""Your attributes are belong to us."""
|
||||
|
||||
def __init__(self, **entries):
|
||||
self.__dict__.update(entries)
|
||||
|
||||
def __getitem__(self, key):
|
||||
return getattr(self, key, None)
|
||||
|
||||
def dictionary(self):
|
||||
"""Returns dictionary representation of object."""
|
||||
return self.__dict__
|
||||
|
||||
def items(self):
|
||||
"""Returns items within object."""
|
||||
return self.__dict__.items()
|
||||
|
||||
def keys(self):
|
||||
"""Returns keys within object."""
|
||||
return self.__dict__.keys()
|
||||
|
||||
|
||||
|
||||
def piped():
|
||||
"""Returns piped input via stdin, else False."""
|
||||
with sys.stdin as stdin:
|
||||
# TTY is only way to detect if stdin contains data
|
||||
return stdin.read() if not stdin.isatty() else None
|
||||
|
||||
@@ -1,437 +0,0 @@
|
||||
r"""JSON (JavaScript Object Notation) <http://json.org> is a subset of
|
||||
JavaScript syntax (ECMA-262 3rd edition) used as a lightweight data
|
||||
interchange format.
|
||||
|
||||
:mod:`simplejson` exposes an API familiar to users of the standard library
|
||||
:mod:`marshal` and :mod:`pickle` modules. It is the externally maintained
|
||||
version of the :mod:`json` library contained in Python 2.6, but maintains
|
||||
compatibility with Python 2.4 and Python 2.5 and (currently) has
|
||||
significant performance advantages, even without using the optional C
|
||||
extension for speedups.
|
||||
|
||||
Encoding basic Python object hierarchies::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> json.dumps(['foo', {'bar': ('baz', None, 1.0, 2)}])
|
||||
'["foo", {"bar": ["baz", null, 1.0, 2]}]'
|
||||
>>> print json.dumps("\"foo\bar")
|
||||
"\"foo\bar"
|
||||
>>> print json.dumps(u'\u1234')
|
||||
"\u1234"
|
||||
>>> print json.dumps('\\')
|
||||
"\\"
|
||||
>>> print json.dumps({"c": 0, "b": 0, "a": 0}, sort_keys=True)
|
||||
{"a": 0, "b": 0, "c": 0}
|
||||
>>> from StringIO import StringIO
|
||||
>>> io = StringIO()
|
||||
>>> json.dump(['streaming API'], io)
|
||||
>>> io.getvalue()
|
||||
'["streaming API"]'
|
||||
|
||||
Compact encoding::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> json.dumps([1,2,3,{'4': 5, '6': 7}], separators=(',',':'))
|
||||
'[1,2,3,{"4":5,"6":7}]'
|
||||
|
||||
Pretty printing::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> s = json.dumps({'4': 5, '6': 7}, sort_keys=True, indent=' ')
|
||||
>>> print '\n'.join([l.rstrip() for l in s.splitlines()])
|
||||
{
|
||||
"4": 5,
|
||||
"6": 7
|
||||
}
|
||||
|
||||
Decoding JSON::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> obj = [u'foo', {u'bar': [u'baz', None, 1.0, 2]}]
|
||||
>>> json.loads('["foo", {"bar":["baz", null, 1.0, 2]}]') == obj
|
||||
True
|
||||
>>> json.loads('"\\"foo\\bar"') == u'"foo\x08ar'
|
||||
True
|
||||
>>> from StringIO import StringIO
|
||||
>>> io = StringIO('["streaming API"]')
|
||||
>>> json.load(io)[0] == 'streaming API'
|
||||
True
|
||||
|
||||
Specializing JSON object decoding::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> def as_complex(dct):
|
||||
... if '__complex__' in dct:
|
||||
... return complex(dct['real'], dct['imag'])
|
||||
... return dct
|
||||
...
|
||||
>>> json.loads('{"__complex__": true, "real": 1, "imag": 2}',
|
||||
... object_hook=as_complex)
|
||||
(1+2j)
|
||||
>>> from decimal import Decimal
|
||||
>>> json.loads('1.1', parse_float=Decimal) == Decimal('1.1')
|
||||
True
|
||||
|
||||
Specializing JSON object encoding::
|
||||
|
||||
>>> import simplejson as json
|
||||
>>> def encode_complex(obj):
|
||||
... if isinstance(obj, complex):
|
||||
... return [obj.real, obj.imag]
|
||||
... raise TypeError(repr(o) + " is not JSON serializable")
|
||||
...
|
||||
>>> json.dumps(2 + 1j, default=encode_complex)
|
||||
'[2.0, 1.0]'
|
||||
>>> json.JSONEncoder(default=encode_complex).encode(2 + 1j)
|
||||
'[2.0, 1.0]'
|
||||
>>> ''.join(json.JSONEncoder(default=encode_complex).iterencode(2 + 1j))
|
||||
'[2.0, 1.0]'
|
||||
|
||||
|
||||
Using simplejson.tool from the shell to validate and pretty-print::
|
||||
|
||||
$ echo '{"json":"obj"}' | python -m simplejson.tool
|
||||
{
|
||||
"json": "obj"
|
||||
}
|
||||
$ echo '{ 1.2:3.4}' | python -m simplejson.tool
|
||||
Expecting property name: line 1 column 2 (char 2)
|
||||
"""
|
||||
__version__ = '2.1.1'
|
||||
__all__ = [
|
||||
'dump', 'dumps', 'load', 'loads',
|
||||
'JSONDecoder', 'JSONDecodeError', 'JSONEncoder',
|
||||
'OrderedDict',
|
||||
]
|
||||
|
||||
__author__ = 'Bob Ippolito <bob@redivi.com>'
|
||||
|
||||
from decimal import Decimal
|
||||
|
||||
from decoder import JSONDecoder, JSONDecodeError
|
||||
from encoder import JSONEncoder
|
||||
def _import_OrderedDict():
|
||||
import collections
|
||||
try:
|
||||
return collections.OrderedDict
|
||||
except AttributeError:
|
||||
import ordered_dict
|
||||
return ordered_dict.OrderedDict
|
||||
OrderedDict = _import_OrderedDict()
|
||||
|
||||
def _import_c_make_encoder():
|
||||
try:
|
||||
from simplejson._speedups import make_encoder
|
||||
return make_encoder
|
||||
except ImportError:
|
||||
return None
|
||||
|
||||
_default_encoder = JSONEncoder(
|
||||
skipkeys=False,
|
||||
ensure_ascii=True,
|
||||
check_circular=True,
|
||||
allow_nan=True,
|
||||
indent=None,
|
||||
separators=None,
|
||||
encoding='utf-8',
|
||||
default=None,
|
||||
use_decimal=False,
|
||||
)
|
||||
|
||||
def dump(obj, fp, skipkeys=False, ensure_ascii=True, check_circular=True,
|
||||
allow_nan=True, cls=None, indent=None, separators=None,
|
||||
encoding='utf-8', default=None, use_decimal=False, **kw):
|
||||
"""Serialize ``obj`` as a JSON formatted stream to ``fp`` (a
|
||||
``.write()``-supporting file-like object).
|
||||
|
||||
If ``skipkeys`` is true then ``dict`` keys that are not basic types
|
||||
(``str``, ``unicode``, ``int``, ``long``, ``float``, ``bool``, ``None``)
|
||||
will be skipped instead of raising a ``TypeError``.
|
||||
|
||||
If ``ensure_ascii`` is false, then the some chunks written to ``fp``
|
||||
may be ``unicode`` instances, subject to normal Python ``str`` to
|
||||
``unicode`` coercion rules. Unless ``fp.write()`` explicitly
|
||||
understands ``unicode`` (as in ``codecs.getwriter()``) this is likely
|
||||
to cause an error.
|
||||
|
||||
If ``check_circular`` is false, then the circular reference check
|
||||
for container types will be skipped and a circular reference will
|
||||
result in an ``OverflowError`` (or worse).
|
||||
|
||||
If ``allow_nan`` is false, then it will be a ``ValueError`` to
|
||||
serialize out of range ``float`` values (``nan``, ``inf``, ``-inf``)
|
||||
in strict compliance of the JSON specification, instead of using the
|
||||
JavaScript equivalents (``NaN``, ``Infinity``, ``-Infinity``).
|
||||
|
||||
If *indent* is a string, then JSON array elements and object members
|
||||
will be pretty-printed with a newline followed by that string repeated
|
||||
for each level of nesting. ``None`` (the default) selects the most compact
|
||||
representation without any newlines. For backwards compatibility with
|
||||
versions of simplejson earlier than 2.1.0, an integer is also accepted
|
||||
and is converted to a string with that many spaces.
|
||||
|
||||
If ``separators`` is an ``(item_separator, dict_separator)`` tuple
|
||||
then it will be used instead of the default ``(', ', ': ')`` separators.
|
||||
``(',', ':')`` is the most compact JSON representation.
|
||||
|
||||
``encoding`` is the character encoding for str instances, default is UTF-8.
|
||||
|
||||
``default(obj)`` is a function that should return a serializable version
|
||||
of obj or raise TypeError. The default simply raises TypeError.
|
||||
|
||||
If *use_decimal* is true (default: ``False``) then decimal.Decimal
|
||||
will be natively serialized to JSON with full precision.
|
||||
|
||||
To use a custom ``JSONEncoder`` subclass (e.g. one that overrides the
|
||||
``.default()`` method to serialize additional types), specify it with
|
||||
the ``cls`` kwarg.
|
||||
|
||||
"""
|
||||
# cached encoder
|
||||
if (not skipkeys and ensure_ascii and
|
||||
check_circular and allow_nan and
|
||||
cls is None and indent is None and separators is None and
|
||||
encoding == 'utf-8' and default is None and not kw):
|
||||
iterable = _default_encoder.iterencode(obj)
|
||||
else:
|
||||
if cls is None:
|
||||
cls = JSONEncoder
|
||||
iterable = cls(skipkeys=skipkeys, ensure_ascii=ensure_ascii,
|
||||
check_circular=check_circular, allow_nan=allow_nan, indent=indent,
|
||||
separators=separators, encoding=encoding,
|
||||
default=default, use_decimal=use_decimal, **kw).iterencode(obj)
|
||||
# could accelerate with writelines in some versions of Python, at
|
||||
# a debuggability cost
|
||||
for chunk in iterable:
|
||||
fp.write(chunk)
|
||||
|
||||
|
||||
def dumps(obj, skipkeys=False, ensure_ascii=True, check_circular=True,
|
||||
allow_nan=True, cls=None, indent=None, separators=None,
|
||||
encoding='utf-8', default=None, use_decimal=False, **kw):
|
||||
"""Serialize ``obj`` to a JSON formatted ``str``.
|
||||
|
||||
If ``skipkeys`` is false then ``dict`` keys that are not basic types
|
||||
(``str``, ``unicode``, ``int``, ``long``, ``float``, ``bool``, ``None``)
|
||||
will be skipped instead of raising a ``TypeError``.
|
||||
|
||||
If ``ensure_ascii`` is false, then the return value will be a
|
||||
``unicode`` instance subject to normal Python ``str`` to ``unicode``
|
||||
coercion rules instead of being escaped to an ASCII ``str``.
|
||||
|
||||
If ``check_circular`` is false, then the circular reference check
|
||||
for container types will be skipped and a circular reference will
|
||||
result in an ``OverflowError`` (or worse).
|
||||
|
||||
If ``allow_nan`` is false, then it will be a ``ValueError`` to
|
||||
serialize out of range ``float`` values (``nan``, ``inf``, ``-inf``) in
|
||||
strict compliance of the JSON specification, instead of using the
|
||||
JavaScript equivalents (``NaN``, ``Infinity``, ``-Infinity``).
|
||||
|
||||
If ``indent`` is a string, then JSON array elements and object members
|
||||
will be pretty-printed with a newline followed by that string repeated
|
||||
for each level of nesting. ``None`` (the default) selects the most compact
|
||||
representation without any newlines. For backwards compatibility with
|
||||
versions of simplejson earlier than 2.1.0, an integer is also accepted
|
||||
and is converted to a string with that many spaces.
|
||||
|
||||
If ``separators`` is an ``(item_separator, dict_separator)`` tuple
|
||||
then it will be used instead of the default ``(', ', ': ')`` separators.
|
||||
``(',', ':')`` is the most compact JSON representation.
|
||||
|
||||
``encoding`` is the character encoding for str instances, default is UTF-8.
|
||||
|
||||
``default(obj)`` is a function that should return a serializable version
|
||||
of obj or raise TypeError. The default simply raises TypeError.
|
||||
|
||||
If *use_decimal* is true (default: ``False``) then decimal.Decimal
|
||||
will be natively serialized to JSON with full precision.
|
||||
|
||||
To use a custom ``JSONEncoder`` subclass (e.g. one that overrides the
|
||||
``.default()`` method to serialize additional types), specify it with
|
||||
the ``cls`` kwarg.
|
||||
|
||||
"""
|
||||
# cached encoder
|
||||
if (not skipkeys and ensure_ascii and
|
||||
check_circular and allow_nan and
|
||||
cls is None and indent is None and separators is None and
|
||||
encoding == 'utf-8' and default is None and not use_decimal
|
||||
and not kw):
|
||||
return _default_encoder.encode(obj)
|
||||
if cls is None:
|
||||
cls = JSONEncoder
|
||||
return cls(
|
||||
skipkeys=skipkeys, ensure_ascii=ensure_ascii,
|
||||
check_circular=check_circular, allow_nan=allow_nan, indent=indent,
|
||||
separators=separators, encoding=encoding, default=default,
|
||||
use_decimal=use_decimal, **kw).encode(obj)
|
||||
|
||||
|
||||
_default_decoder = JSONDecoder(encoding=None, object_hook=None,
|
||||
object_pairs_hook=None)
|
||||
|
||||
|
||||
def load(fp, encoding=None, cls=None, object_hook=None, parse_float=None,
|
||||
parse_int=None, parse_constant=None, object_pairs_hook=None,
|
||||
use_decimal=False, **kw):
|
||||
"""Deserialize ``fp`` (a ``.read()``-supporting file-like object containing
|
||||
a JSON document) to a Python object.
|
||||
|
||||
*encoding* determines the encoding used to interpret any
|
||||
:class:`str` objects decoded by this instance (``'utf-8'`` by
|
||||
default). It has no effect when decoding :class:`unicode` objects.
|
||||
|
||||
Note that currently only encodings that are a superset of ASCII work,
|
||||
strings of other encodings should be passed in as :class:`unicode`.
|
||||
|
||||
*object_hook*, if specified, will be called with the result of every
|
||||
JSON object decoded and its return value will be used in place of the
|
||||
given :class:`dict`. This can be used to provide custom
|
||||
deserializations (e.g. to support JSON-RPC class hinting).
|
||||
|
||||
*object_pairs_hook* is an optional function that will be called with
|
||||
the result of any object literal decode with an ordered list of pairs.
|
||||
The return value of *object_pairs_hook* will be used instead of the
|
||||
:class:`dict`. This feature can be used to implement custom decoders
|
||||
that rely on the order that the key and value pairs are decoded (for
|
||||
example, :func:`collections.OrderedDict` will remember the order of
|
||||
insertion). If *object_hook* is also defined, the *object_pairs_hook*
|
||||
takes priority.
|
||||
|
||||
*parse_float*, if specified, will be called with the string of every
|
||||
JSON float to be decoded. By default, this is equivalent to
|
||||
``float(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON floats (e.g. :class:`decimal.Decimal`).
|
||||
|
||||
*parse_int*, if specified, will be called with the string of every
|
||||
JSON int to be decoded. By default, this is equivalent to
|
||||
``int(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON integers (e.g. :class:`float`).
|
||||
|
||||
*parse_constant*, if specified, will be called with one of the
|
||||
following strings: ``'-Infinity'``, ``'Infinity'``, ``'NaN'``. This
|
||||
can be used to raise an exception if invalid JSON numbers are
|
||||
encountered.
|
||||
|
||||
If *use_decimal* is true (default: ``False``) then it implies
|
||||
parse_float=decimal.Decimal for parity with ``dump``.
|
||||
|
||||
To use a custom ``JSONDecoder`` subclass, specify it with the ``cls``
|
||||
kwarg.
|
||||
|
||||
"""
|
||||
return loads(fp.read(),
|
||||
encoding=encoding, cls=cls, object_hook=object_hook,
|
||||
parse_float=parse_float, parse_int=parse_int,
|
||||
parse_constant=parse_constant, object_pairs_hook=object_pairs_hook,
|
||||
use_decimal=use_decimal, **kw)
|
||||
|
||||
|
||||
def loads(s, encoding=None, cls=None, object_hook=None, parse_float=None,
|
||||
parse_int=None, parse_constant=None, object_pairs_hook=None,
|
||||
use_decimal=False, **kw):
|
||||
"""Deserialize ``s`` (a ``str`` or ``unicode`` instance containing a JSON
|
||||
document) to a Python object.
|
||||
|
||||
*encoding* determines the encoding used to interpret any
|
||||
:class:`str` objects decoded by this instance (``'utf-8'`` by
|
||||
default). It has no effect when decoding :class:`unicode` objects.
|
||||
|
||||
Note that currently only encodings that are a superset of ASCII work,
|
||||
strings of other encodings should be passed in as :class:`unicode`.
|
||||
|
||||
*object_hook*, if specified, will be called with the result of every
|
||||
JSON object decoded and its return value will be used in place of the
|
||||
given :class:`dict`. This can be used to provide custom
|
||||
deserializations (e.g. to support JSON-RPC class hinting).
|
||||
|
||||
*object_pairs_hook* is an optional function that will be called with
|
||||
the result of any object literal decode with an ordered list of pairs.
|
||||
The return value of *object_pairs_hook* will be used instead of the
|
||||
:class:`dict`. This feature can be used to implement custom decoders
|
||||
that rely on the order that the key and value pairs are decoded (for
|
||||
example, :func:`collections.OrderedDict` will remember the order of
|
||||
insertion). If *object_hook* is also defined, the *object_pairs_hook*
|
||||
takes priority.
|
||||
|
||||
*parse_float*, if specified, will be called with the string of every
|
||||
JSON float to be decoded. By default, this is equivalent to
|
||||
``float(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON floats (e.g. :class:`decimal.Decimal`).
|
||||
|
||||
*parse_int*, if specified, will be called with the string of every
|
||||
JSON int to be decoded. By default, this is equivalent to
|
||||
``int(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON integers (e.g. :class:`float`).
|
||||
|
||||
*parse_constant*, if specified, will be called with one of the
|
||||
following strings: ``'-Infinity'``, ``'Infinity'``, ``'NaN'``. This
|
||||
can be used to raise an exception if invalid JSON numbers are
|
||||
encountered.
|
||||
|
||||
If *use_decimal* is true (default: ``False``) then it implies
|
||||
parse_float=decimal.Decimal for parity with ``dump``.
|
||||
|
||||
To use a custom ``JSONDecoder`` subclass, specify it with the ``cls``
|
||||
kwarg.
|
||||
|
||||
"""
|
||||
if (cls is None and encoding is None and object_hook is None and
|
||||
parse_int is None and parse_float is None and
|
||||
parse_constant is None and object_pairs_hook is None
|
||||
and not use_decimal and not kw):
|
||||
return _default_decoder.decode(s)
|
||||
if cls is None:
|
||||
cls = JSONDecoder
|
||||
if object_hook is not None:
|
||||
kw['object_hook'] = object_hook
|
||||
if object_pairs_hook is not None:
|
||||
kw['object_pairs_hook'] = object_pairs_hook
|
||||
if parse_float is not None:
|
||||
kw['parse_float'] = parse_float
|
||||
if parse_int is not None:
|
||||
kw['parse_int'] = parse_int
|
||||
if parse_constant is not None:
|
||||
kw['parse_constant'] = parse_constant
|
||||
if use_decimal:
|
||||
if parse_float is not None:
|
||||
raise TypeError("use_decimal=True implies parse_float=Decimal")
|
||||
kw['parse_float'] = Decimal
|
||||
return cls(encoding=encoding, **kw).decode(s)
|
||||
|
||||
|
||||
def _toggle_speedups(enabled):
|
||||
import simplejson.decoder as dec
|
||||
import simplejson.encoder as enc
|
||||
import simplejson.scanner as scan
|
||||
c_make_encoder = _import_c_make_encoder()
|
||||
if enabled:
|
||||
dec.scanstring = dec.c_scanstring or dec.py_scanstring
|
||||
enc.c_make_encoder = c_make_encoder
|
||||
enc.encode_basestring_ascii = (enc.c_encode_basestring_ascii or
|
||||
enc.py_encode_basestring_ascii)
|
||||
scan.make_scanner = scan.c_make_scanner or scan.py_make_scanner
|
||||
else:
|
||||
dec.scanstring = dec.py_scanstring
|
||||
enc.c_make_encoder = None
|
||||
enc.encode_basestring_ascii = enc.py_encode_basestring_ascii
|
||||
scan.make_scanner = scan.py_make_scanner
|
||||
dec.make_scanner = scan.make_scanner
|
||||
global _default_decoder
|
||||
_default_decoder = JSONDecoder(
|
||||
encoding=None,
|
||||
object_hook=None,
|
||||
object_pairs_hook=None,
|
||||
)
|
||||
global _default_encoder
|
||||
_default_encoder = JSONEncoder(
|
||||
skipkeys=False,
|
||||
ensure_ascii=True,
|
||||
check_circular=True,
|
||||
allow_nan=True,
|
||||
indent=None,
|
||||
separators=None,
|
||||
encoding='utf-8',
|
||||
default=None,
|
||||
)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,421 +0,0 @@
|
||||
"""Implementation of JSONDecoder
|
||||
"""
|
||||
import re
|
||||
import sys
|
||||
import struct
|
||||
|
||||
from simplejson.scanner import make_scanner
|
||||
def _import_c_scanstring():
|
||||
try:
|
||||
from simplejson._speedups import scanstring
|
||||
return scanstring
|
||||
except ImportError:
|
||||
return None
|
||||
c_scanstring = _import_c_scanstring()
|
||||
|
||||
__all__ = ['JSONDecoder']
|
||||
|
||||
FLAGS = re.VERBOSE | re.MULTILINE | re.DOTALL
|
||||
|
||||
def _floatconstants():
|
||||
_BYTES = '7FF80000000000007FF0000000000000'.decode('hex')
|
||||
# The struct module in Python 2.4 would get frexp() out of range here
|
||||
# when an endian is specified in the format string. Fixed in Python 2.5+
|
||||
if sys.byteorder != 'big':
|
||||
_BYTES = _BYTES[:8][::-1] + _BYTES[8:][::-1]
|
||||
nan, inf = struct.unpack('dd', _BYTES)
|
||||
return nan, inf, -inf
|
||||
|
||||
NaN, PosInf, NegInf = _floatconstants()
|
||||
|
||||
|
||||
class JSONDecodeError(ValueError):
|
||||
"""Subclass of ValueError with the following additional properties:
|
||||
|
||||
msg: The unformatted error message
|
||||
doc: The JSON document being parsed
|
||||
pos: The start index of doc where parsing failed
|
||||
end: The end index of doc where parsing failed (may be None)
|
||||
lineno: The line corresponding to pos
|
||||
colno: The column corresponding to pos
|
||||
endlineno: The line corresponding to end (may be None)
|
||||
endcolno: The column corresponding to end (may be None)
|
||||
|
||||
"""
|
||||
def __init__(self, msg, doc, pos, end=None):
|
||||
ValueError.__init__(self, errmsg(msg, doc, pos, end=end))
|
||||
self.msg = msg
|
||||
self.doc = doc
|
||||
self.pos = pos
|
||||
self.end = end
|
||||
self.lineno, self.colno = linecol(doc, pos)
|
||||
if end is not None:
|
||||
self.endlineno, self.endcolno = linecol(doc, pos)
|
||||
else:
|
||||
self.endlineno, self.endcolno = None, None
|
||||
|
||||
|
||||
def linecol(doc, pos):
|
||||
lineno = doc.count('\n', 0, pos) + 1
|
||||
if lineno == 1:
|
||||
colno = pos
|
||||
else:
|
||||
colno = pos - doc.rindex('\n', 0, pos)
|
||||
return lineno, colno
|
||||
|
||||
|
||||
def errmsg(msg, doc, pos, end=None):
|
||||
# Note that this function is called from _speedups
|
||||
lineno, colno = linecol(doc, pos)
|
||||
if end is None:
|
||||
#fmt = '{0}: line {1} column {2} (char {3})'
|
||||
#return fmt.format(msg, lineno, colno, pos)
|
||||
fmt = '%s: line %d column %d (char %d)'
|
||||
return fmt % (msg, lineno, colno, pos)
|
||||
endlineno, endcolno = linecol(doc, end)
|
||||
#fmt = '{0}: line {1} column {2} - line {3} column {4} (char {5} - {6})'
|
||||
#return fmt.format(msg, lineno, colno, endlineno, endcolno, pos, end)
|
||||
fmt = '%s: line %d column %d - line %d column %d (char %d - %d)'
|
||||
return fmt % (msg, lineno, colno, endlineno, endcolno, pos, end)
|
||||
|
||||
|
||||
_CONSTANTS = {
|
||||
'-Infinity': NegInf,
|
||||
'Infinity': PosInf,
|
||||
'NaN': NaN,
|
||||
}
|
||||
|
||||
STRINGCHUNK = re.compile(r'(.*?)(["\\\x00-\x1f])', FLAGS)
|
||||
BACKSLASH = {
|
||||
'"': u'"', '\\': u'\\', '/': u'/',
|
||||
'b': u'\b', 'f': u'\f', 'n': u'\n', 'r': u'\r', 't': u'\t',
|
||||
}
|
||||
|
||||
DEFAULT_ENCODING = "utf-8"
|
||||
|
||||
def py_scanstring(s, end, encoding=None, strict=True,
|
||||
_b=BACKSLASH, _m=STRINGCHUNK.match):
|
||||
"""Scan the string s for a JSON string. End is the index of the
|
||||
character in s after the quote that started the JSON string.
|
||||
Unescapes all valid JSON string escape sequences and raises ValueError
|
||||
on attempt to decode an invalid string. If strict is False then literal
|
||||
control characters are allowed in the string.
|
||||
|
||||
Returns a tuple of the decoded string and the index of the character in s
|
||||
after the end quote."""
|
||||
if encoding is None:
|
||||
encoding = DEFAULT_ENCODING
|
||||
chunks = []
|
||||
_append = chunks.append
|
||||
begin = end - 1
|
||||
while 1:
|
||||
chunk = _m(s, end)
|
||||
if chunk is None:
|
||||
raise JSONDecodeError(
|
||||
"Unterminated string starting at", s, begin)
|
||||
end = chunk.end()
|
||||
content, terminator = chunk.groups()
|
||||
# Content is contains zero or more unescaped string characters
|
||||
if content:
|
||||
if not isinstance(content, unicode):
|
||||
content = unicode(content, encoding)
|
||||
_append(content)
|
||||
# Terminator is the end of string, a literal control character,
|
||||
# or a backslash denoting that an escape sequence follows
|
||||
if terminator == '"':
|
||||
break
|
||||
elif terminator != '\\':
|
||||
if strict:
|
||||
msg = "Invalid control character %r at" % (terminator,)
|
||||
#msg = "Invalid control character {0!r} at".format(terminator)
|
||||
raise JSONDecodeError(msg, s, end)
|
||||
else:
|
||||
_append(terminator)
|
||||
continue
|
||||
try:
|
||||
esc = s[end]
|
||||
except IndexError:
|
||||
raise JSONDecodeError(
|
||||
"Unterminated string starting at", s, begin)
|
||||
# If not a unicode escape sequence, must be in the lookup table
|
||||
if esc != 'u':
|
||||
try:
|
||||
char = _b[esc]
|
||||
except KeyError:
|
||||
msg = "Invalid \\escape: " + repr(esc)
|
||||
raise JSONDecodeError(msg, s, end)
|
||||
end += 1
|
||||
else:
|
||||
# Unicode escape sequence
|
||||
esc = s[end + 1:end + 5]
|
||||
next_end = end + 5
|
||||
if len(esc) != 4:
|
||||
msg = "Invalid \\uXXXX escape"
|
||||
raise JSONDecodeError(msg, s, end)
|
||||
uni = int(esc, 16)
|
||||
# Check for surrogate pair on UCS-4 systems
|
||||
if 0xd800 <= uni <= 0xdbff and sys.maxunicode > 65535:
|
||||
msg = "Invalid \\uXXXX\\uXXXX surrogate pair"
|
||||
if not s[end + 5:end + 7] == '\\u':
|
||||
raise JSONDecodeError(msg, s, end)
|
||||
esc2 = s[end + 7:end + 11]
|
||||
if len(esc2) != 4:
|
||||
raise JSONDecodeError(msg, s, end)
|
||||
uni2 = int(esc2, 16)
|
||||
uni = 0x10000 + (((uni - 0xd800) << 10) | (uni2 - 0xdc00))
|
||||
next_end += 6
|
||||
char = unichr(uni)
|
||||
end = next_end
|
||||
# Append the unescaped character
|
||||
_append(char)
|
||||
return u''.join(chunks), end
|
||||
|
||||
|
||||
# Use speedup if available
|
||||
scanstring = c_scanstring or py_scanstring
|
||||
|
||||
WHITESPACE = re.compile(r'[ \t\n\r]*', FLAGS)
|
||||
WHITESPACE_STR = ' \t\n\r'
|
||||
|
||||
def JSONObject((s, end), encoding, strict, scan_once, object_hook,
|
||||
object_pairs_hook, memo=None,
|
||||
_w=WHITESPACE.match, _ws=WHITESPACE_STR):
|
||||
# Backwards compatibility
|
||||
if memo is None:
|
||||
memo = {}
|
||||
memo_get = memo.setdefault
|
||||
pairs = []
|
||||
# Use a slice to prevent IndexError from being raised, the following
|
||||
# check will raise a more specific ValueError if the string is empty
|
||||
nextchar = s[end:end + 1]
|
||||
# Normally we expect nextchar == '"'
|
||||
if nextchar != '"':
|
||||
if nextchar in _ws:
|
||||
end = _w(s, end).end()
|
||||
nextchar = s[end:end + 1]
|
||||
# Trivial empty object
|
||||
if nextchar == '}':
|
||||
if object_pairs_hook is not None:
|
||||
result = object_pairs_hook(pairs)
|
||||
return result, end
|
||||
pairs = {}
|
||||
if object_hook is not None:
|
||||
pairs = object_hook(pairs)
|
||||
return pairs, end + 1
|
||||
elif nextchar != '"':
|
||||
raise JSONDecodeError("Expecting property name", s, end)
|
||||
end += 1
|
||||
while True:
|
||||
key, end = scanstring(s, end, encoding, strict)
|
||||
key = memo_get(key, key)
|
||||
|
||||
# To skip some function call overhead we optimize the fast paths where
|
||||
# the JSON key separator is ": " or just ":".
|
||||
if s[end:end + 1] != ':':
|
||||
end = _w(s, end).end()
|
||||
if s[end:end + 1] != ':':
|
||||
raise JSONDecodeError("Expecting : delimiter", s, end)
|
||||
|
||||
end += 1
|
||||
|
||||
try:
|
||||
if s[end] in _ws:
|
||||
end += 1
|
||||
if s[end] in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
except IndexError:
|
||||
pass
|
||||
|
||||
try:
|
||||
value, end = scan_once(s, end)
|
||||
except StopIteration:
|
||||
raise JSONDecodeError("Expecting object", s, end)
|
||||
pairs.append((key, value))
|
||||
|
||||
try:
|
||||
nextchar = s[end]
|
||||
if nextchar in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
nextchar = s[end]
|
||||
except IndexError:
|
||||
nextchar = ''
|
||||
end += 1
|
||||
|
||||
if nextchar == '}':
|
||||
break
|
||||
elif nextchar != ',':
|
||||
raise JSONDecodeError("Expecting , delimiter", s, end - 1)
|
||||
|
||||
try:
|
||||
nextchar = s[end]
|
||||
if nextchar in _ws:
|
||||
end += 1
|
||||
nextchar = s[end]
|
||||
if nextchar in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
nextchar = s[end]
|
||||
except IndexError:
|
||||
nextchar = ''
|
||||
|
||||
end += 1
|
||||
if nextchar != '"':
|
||||
raise JSONDecodeError("Expecting property name", s, end - 1)
|
||||
|
||||
if object_pairs_hook is not None:
|
||||
result = object_pairs_hook(pairs)
|
||||
return result, end
|
||||
pairs = dict(pairs)
|
||||
if object_hook is not None:
|
||||
pairs = object_hook(pairs)
|
||||
return pairs, end
|
||||
|
||||
def JSONArray((s, end), scan_once, _w=WHITESPACE.match, _ws=WHITESPACE_STR):
|
||||
values = []
|
||||
nextchar = s[end:end + 1]
|
||||
if nextchar in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
nextchar = s[end:end + 1]
|
||||
# Look-ahead for trivial empty array
|
||||
if nextchar == ']':
|
||||
return values, end + 1
|
||||
_append = values.append
|
||||
while True:
|
||||
try:
|
||||
value, end = scan_once(s, end)
|
||||
except StopIteration:
|
||||
raise JSONDecodeError("Expecting object", s, end)
|
||||
_append(value)
|
||||
nextchar = s[end:end + 1]
|
||||
if nextchar in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
nextchar = s[end:end + 1]
|
||||
end += 1
|
||||
if nextchar == ']':
|
||||
break
|
||||
elif nextchar != ',':
|
||||
raise JSONDecodeError("Expecting , delimiter", s, end)
|
||||
|
||||
try:
|
||||
if s[end] in _ws:
|
||||
end += 1
|
||||
if s[end] in _ws:
|
||||
end = _w(s, end + 1).end()
|
||||
except IndexError:
|
||||
pass
|
||||
|
||||
return values, end
|
||||
|
||||
class JSONDecoder(object):
|
||||
"""Simple JSON <http://json.org> decoder
|
||||
|
||||
Performs the following translations in decoding by default:
|
||||
|
||||
+---------------+-------------------+
|
||||
| JSON | Python |
|
||||
+===============+===================+
|
||||
| object | dict |
|
||||
+---------------+-------------------+
|
||||
| array | list |
|
||||
+---------------+-------------------+
|
||||
| string | unicode |
|
||||
+---------------+-------------------+
|
||||
| number (int) | int, long |
|
||||
+---------------+-------------------+
|
||||
| number (real) | float |
|
||||
+---------------+-------------------+
|
||||
| true | True |
|
||||
+---------------+-------------------+
|
||||
| false | False |
|
||||
+---------------+-------------------+
|
||||
| null | None |
|
||||
+---------------+-------------------+
|
||||
|
||||
It also understands ``NaN``, ``Infinity``, and ``-Infinity`` as
|
||||
their corresponding ``float`` values, which is outside the JSON spec.
|
||||
|
||||
"""
|
||||
|
||||
def __init__(self, encoding=None, object_hook=None, parse_float=None,
|
||||
parse_int=None, parse_constant=None, strict=True,
|
||||
object_pairs_hook=None):
|
||||
"""
|
||||
*encoding* determines the encoding used to interpret any
|
||||
:class:`str` objects decoded by this instance (``'utf-8'`` by
|
||||
default). It has no effect when decoding :class:`unicode` objects.
|
||||
|
||||
Note that currently only encodings that are a superset of ASCII work,
|
||||
strings of other encodings should be passed in as :class:`unicode`.
|
||||
|
||||
*object_hook*, if specified, will be called with the result of every
|
||||
JSON object decoded and its return value will be used in place of the
|
||||
given :class:`dict`. This can be used to provide custom
|
||||
deserializations (e.g. to support JSON-RPC class hinting).
|
||||
|
||||
*object_pairs_hook* is an optional function that will be called with
|
||||
the result of any object literal decode with an ordered list of pairs.
|
||||
The return value of *object_pairs_hook* will be used instead of the
|
||||
:class:`dict`. This feature can be used to implement custom decoders
|
||||
that rely on the order that the key and value pairs are decoded (for
|
||||
example, :func:`collections.OrderedDict` will remember the order of
|
||||
insertion). If *object_hook* is also defined, the *object_pairs_hook*
|
||||
takes priority.
|
||||
|
||||
*parse_float*, if specified, will be called with the string of every
|
||||
JSON float to be decoded. By default, this is equivalent to
|
||||
``float(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON floats (e.g. :class:`decimal.Decimal`).
|
||||
|
||||
*parse_int*, if specified, will be called with the string of every
|
||||
JSON int to be decoded. By default, this is equivalent to
|
||||
``int(num_str)``. This can be used to use another datatype or parser
|
||||
for JSON integers (e.g. :class:`float`).
|
||||
|
||||
*parse_constant*, if specified, will be called with one of the
|
||||
following strings: ``'-Infinity'``, ``'Infinity'``, ``'NaN'``. This
|
||||
can be used to raise an exception if invalid JSON numbers are
|
||||
encountered.
|
||||
|
||||
*strict* controls the parser's behavior when it encounters an
|
||||
invalid control character in a string. The default setting of
|
||||
``True`` means that unescaped control characters are parse errors, if
|
||||
``False`` then control characters will be allowed in strings.
|
||||
|
||||
"""
|
||||
self.encoding = encoding
|
||||
self.object_hook = object_hook
|
||||
self.object_pairs_hook = object_pairs_hook
|
||||
self.parse_float = parse_float or float
|
||||
self.parse_int = parse_int or int
|
||||
self.parse_constant = parse_constant or _CONSTANTS.__getitem__
|
||||
self.strict = strict
|
||||
self.parse_object = JSONObject
|
||||
self.parse_array = JSONArray
|
||||
self.parse_string = scanstring
|
||||
self.memo = {}
|
||||
self.scan_once = make_scanner(self)
|
||||
|
||||
def decode(self, s, _w=WHITESPACE.match):
|
||||
"""Return the Python representation of ``s`` (a ``str`` or ``unicode``
|
||||
instance containing a JSON document)
|
||||
|
||||
"""
|
||||
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
|
||||
end = _w(s, end).end()
|
||||
if end != len(s):
|
||||
raise JSONDecodeError("Extra data", s, end, len(s))
|
||||
return obj
|
||||
|
||||
def raw_decode(self, s, idx=0):
|
||||
"""Decode a JSON document from ``s`` (a ``str`` or ``unicode``
|
||||
beginning with a JSON document) and return a 2-tuple of the Python
|
||||
representation and the index in ``s`` where the document ended.
|
||||
|
||||
This can be used to decode a JSON document from a string that may
|
||||
have extraneous data at the end.
|
||||
|
||||
"""
|
||||
try:
|
||||
obj, end = self.scan_once(s, idx)
|
||||
except StopIteration:
|
||||
raise JSONDecodeError("No JSON object could be decoded", s, idx)
|
||||
return obj, end
|
||||
@@ -1,501 +0,0 @@
|
||||
"""Implementation of JSONEncoder
|
||||
"""
|
||||
import re
|
||||
from decimal import Decimal
|
||||
|
||||
def _import_speedups():
|
||||
try:
|
||||
from simplejson import _speedups
|
||||
return _speedups.encode_basestring_ascii, _speedups.make_encoder
|
||||
except ImportError:
|
||||
return None, None
|
||||
c_encode_basestring_ascii, c_make_encoder = _import_speedups()
|
||||
|
||||
from simplejson.decoder import PosInf
|
||||
|
||||
ESCAPE = re.compile(r'[\x00-\x1f\\"\b\f\n\r\t]')
|
||||
ESCAPE_ASCII = re.compile(r'([\\"]|[^\ -~])')
|
||||
HAS_UTF8 = re.compile(r'[\x80-\xff]')
|
||||
ESCAPE_DCT = {
|
||||
'\\': '\\\\',
|
||||
'"': '\\"',
|
||||
'\b': '\\b',
|
||||
'\f': '\\f',
|
||||
'\n': '\\n',
|
||||
'\r': '\\r',
|
||||
'\t': '\\t',
|
||||
}
|
||||
for i in range(0x20):
|
||||
#ESCAPE_DCT.setdefault(chr(i), '\\u{0:04x}'.format(i))
|
||||
ESCAPE_DCT.setdefault(chr(i), '\\u%04x' % (i,))
|
||||
|
||||
FLOAT_REPR = repr
|
||||
|
||||
def encode_basestring(s):
|
||||
"""Return a JSON representation of a Python string
|
||||
|
||||
"""
|
||||
if isinstance(s, str) and HAS_UTF8.search(s) is not None:
|
||||
s = s.decode('utf-8')
|
||||
def replace(match):
|
||||
return ESCAPE_DCT[match.group(0)]
|
||||
return u'"' + ESCAPE.sub(replace, s) + u'"'
|
||||
|
||||
|
||||
def py_encode_basestring_ascii(s):
|
||||
"""Return an ASCII-only JSON representation of a Python string
|
||||
|
||||
"""
|
||||
if isinstance(s, str) and HAS_UTF8.search(s) is not None:
|
||||
s = s.decode('utf-8')
|
||||
def replace(match):
|
||||
s = match.group(0)
|
||||
try:
|
||||
return ESCAPE_DCT[s]
|
||||
except KeyError:
|
||||
n = ord(s)
|
||||
if n < 0x10000:
|
||||
#return '\\u{0:04x}'.format(n)
|
||||
return '\\u%04x' % (n,)
|
||||
else:
|
||||
# surrogate pair
|
||||
n -= 0x10000
|
||||
s1 = 0xd800 | ((n >> 10) & 0x3ff)
|
||||
s2 = 0xdc00 | (n & 0x3ff)
|
||||
#return '\\u{0:04x}\\u{1:04x}'.format(s1, s2)
|
||||
return '\\u%04x\\u%04x' % (s1, s2)
|
||||
return '"' + str(ESCAPE_ASCII.sub(replace, s)) + '"'
|
||||
|
||||
|
||||
encode_basestring_ascii = (
|
||||
c_encode_basestring_ascii or py_encode_basestring_ascii)
|
||||
|
||||
class JSONEncoder(object):
|
||||
"""Extensible JSON <http://json.org> encoder for Python data structures.
|
||||
|
||||
Supports the following objects and types by default:
|
||||
|
||||
+-------------------+---------------+
|
||||
| Python | JSON |
|
||||
+===================+===============+
|
||||
| dict | object |
|
||||
+-------------------+---------------+
|
||||
| list, tuple | array |
|
||||
+-------------------+---------------+
|
||||
| str, unicode | string |
|
||||
+-------------------+---------------+
|
||||
| int, long, float | number |
|
||||
+-------------------+---------------+
|
||||
| True | true |
|
||||
+-------------------+---------------+
|
||||
| False | false |
|
||||
+-------------------+---------------+
|
||||
| None | null |
|
||||
+-------------------+---------------+
|
||||
|
||||
To extend this to recognize other objects, subclass and implement a
|
||||
``.default()`` method with another method that returns a serializable
|
||||
object for ``o`` if possible, otherwise it should call the superclass
|
||||
implementation (to raise ``TypeError``).
|
||||
|
||||
"""
|
||||
item_separator = ', '
|
||||
key_separator = ': '
|
||||
def __init__(self, skipkeys=False, ensure_ascii=True,
|
||||
check_circular=True, allow_nan=True, sort_keys=False,
|
||||
indent=None, separators=None, encoding='utf-8', default=None,
|
||||
use_decimal=False):
|
||||
"""Constructor for JSONEncoder, with sensible defaults.
|
||||
|
||||
If skipkeys is false, then it is a TypeError to attempt
|
||||
encoding of keys that are not str, int, long, float or None. If
|
||||
skipkeys is True, such items are simply skipped.
|
||||
|
||||
If ensure_ascii is true, the output is guaranteed to be str
|
||||
objects with all incoming unicode characters escaped. If
|
||||
ensure_ascii is false, the output will be unicode object.
|
||||
|
||||
If check_circular is true, then lists, dicts, and custom encoded
|
||||
objects will be checked for circular references during encoding to
|
||||
prevent an infinite recursion (which would cause an OverflowError).
|
||||
Otherwise, no such check takes place.
|
||||
|
||||
If allow_nan is true, then NaN, Infinity, and -Infinity will be
|
||||
encoded as such. This behavior is not JSON specification compliant,
|
||||
but is consistent with most JavaScript based encoders and decoders.
|
||||
Otherwise, it will be a ValueError to encode such floats.
|
||||
|
||||
If sort_keys is true, then the output of dictionaries will be
|
||||
sorted by key; this is useful for regression tests to ensure
|
||||
that JSON serializations can be compared on a day-to-day basis.
|
||||
|
||||
If indent is a string, then JSON array elements and object members
|
||||
will be pretty-printed with a newline followed by that string repeated
|
||||
for each level of nesting. ``None`` (the default) selects the most compact
|
||||
representation without any newlines. For backwards compatibility with
|
||||
versions of simplejson earlier than 2.1.0, an integer is also accepted
|
||||
and is converted to a string with that many spaces.
|
||||
|
||||
If specified, separators should be a (item_separator, key_separator)
|
||||
tuple. The default is (', ', ': '). To get the most compact JSON
|
||||
representation you should specify (',', ':') to eliminate whitespace.
|
||||
|
||||
If specified, default is a function that gets called for objects
|
||||
that can't otherwise be serialized. It should return a JSON encodable
|
||||
version of the object or raise a ``TypeError``.
|
||||
|
||||
If encoding is not None, then all input strings will be
|
||||
transformed into unicode using that encoding prior to JSON-encoding.
|
||||
The default is UTF-8.
|
||||
|
||||
If use_decimal is true (not the default), ``decimal.Decimal`` will
|
||||
be supported directly by the encoder. For the inverse, decode JSON
|
||||
with ``parse_float=decimal.Decimal``.
|
||||
|
||||
"""
|
||||
|
||||
self.skipkeys = skipkeys
|
||||
self.ensure_ascii = ensure_ascii
|
||||
self.check_circular = check_circular
|
||||
self.allow_nan = allow_nan
|
||||
self.sort_keys = sort_keys
|
||||
self.use_decimal = use_decimal
|
||||
if isinstance(indent, (int, long)):
|
||||
indent = ' ' * indent
|
||||
self.indent = indent
|
||||
if separators is not None:
|
||||
self.item_separator, self.key_separator = separators
|
||||
if default is not None:
|
||||
self.default = default
|
||||
self.encoding = encoding
|
||||
|
||||
def default(self, o):
|
||||
"""Implement this method in a subclass such that it returns
|
||||
a serializable object for ``o``, or calls the base implementation
|
||||
(to raise a ``TypeError``).
|
||||
|
||||
For example, to support arbitrary iterators, you could
|
||||
implement default like this::
|
||||
|
||||
def default(self, o):
|
||||
try:
|
||||
iterable = iter(o)
|
||||
except TypeError:
|
||||
pass
|
||||
else:
|
||||
return list(iterable)
|
||||
return JSONEncoder.default(self, o)
|
||||
|
||||
"""
|
||||
raise TypeError(repr(o) + " is not JSON serializable")
|
||||
|
||||
def encode(self, o):
|
||||
"""Return a JSON string representation of a Python data structure.
|
||||
|
||||
>>> from simplejson import JSONEncoder
|
||||
>>> JSONEncoder().encode({"foo": ["bar", "baz"]})
|
||||
'{"foo": ["bar", "baz"]}'
|
||||
|
||||
"""
|
||||
# This is for extremely simple cases and benchmarks.
|
||||
if isinstance(o, basestring):
|
||||
if isinstance(o, str):
|
||||
_encoding = self.encoding
|
||||
if (_encoding is not None
|
||||
and not (_encoding == 'utf-8')):
|
||||
o = o.decode(_encoding)
|
||||
if self.ensure_ascii:
|
||||
return encode_basestring_ascii(o)
|
||||
else:
|
||||
return encode_basestring(o)
|
||||
# This doesn't pass the iterator directly to ''.join() because the
|
||||
# exceptions aren't as detailed. The list call should be roughly
|
||||
# equivalent to the PySequence_Fast that ''.join() would do.
|
||||
chunks = self.iterencode(o, _one_shot=True)
|
||||
if not isinstance(chunks, (list, tuple)):
|
||||
chunks = list(chunks)
|
||||
if self.ensure_ascii:
|
||||
return ''.join(chunks)
|
||||
else:
|
||||
return u''.join(chunks)
|
||||
|
||||
def iterencode(self, o, _one_shot=False):
|
||||
"""Encode the given object and yield each string
|
||||
representation as available.
|
||||
|
||||
For example::
|
||||
|
||||
for chunk in JSONEncoder().iterencode(bigobject):
|
||||
mysocket.write(chunk)
|
||||
|
||||
"""
|
||||
if self.check_circular:
|
||||
markers = {}
|
||||
else:
|
||||
markers = None
|
||||
if self.ensure_ascii:
|
||||
_encoder = encode_basestring_ascii
|
||||
else:
|
||||
_encoder = encode_basestring
|
||||
if self.encoding != 'utf-8':
|
||||
def _encoder(o, _orig_encoder=_encoder, _encoding=self.encoding):
|
||||
if isinstance(o, str):
|
||||
o = o.decode(_encoding)
|
||||
return _orig_encoder(o)
|
||||
|
||||
def floatstr(o, allow_nan=self.allow_nan,
|
||||
_repr=FLOAT_REPR, _inf=PosInf, _neginf=-PosInf):
|
||||
# Check for specials. Note that this type of test is processor
|
||||
# and/or platform-specific, so do tests which don't depend on
|
||||
# the internals.
|
||||
|
||||
if o != o:
|
||||
text = 'NaN'
|
||||
elif o == _inf:
|
||||
text = 'Infinity'
|
||||
elif o == _neginf:
|
||||
text = '-Infinity'
|
||||
else:
|
||||
return _repr(o)
|
||||
|
||||
if not allow_nan:
|
||||
raise ValueError(
|
||||
"Out of range float values are not JSON compliant: " +
|
||||
repr(o))
|
||||
|
||||
return text
|
||||
|
||||
|
||||
key_memo = {}
|
||||
if (_one_shot and c_make_encoder is not None
|
||||
and not self.indent and not self.sort_keys):
|
||||
_iterencode = c_make_encoder(
|
||||
markers, self.default, _encoder, self.indent,
|
||||
self.key_separator, self.item_separator, self.sort_keys,
|
||||
self.skipkeys, self.allow_nan, key_memo, self.use_decimal)
|
||||
else:
|
||||
_iterencode = _make_iterencode(
|
||||
markers, self.default, _encoder, self.indent, floatstr,
|
||||
self.key_separator, self.item_separator, self.sort_keys,
|
||||
self.skipkeys, _one_shot, self.use_decimal)
|
||||
try:
|
||||
return _iterencode(o, 0)
|
||||
finally:
|
||||
key_memo.clear()
|
||||
|
||||
|
||||
class JSONEncoderForHTML(JSONEncoder):
|
||||
"""An encoder that produces JSON safe to embed in HTML.
|
||||
|
||||
To embed JSON content in, say, a script tag on a web page, the
|
||||
characters &, < and > should be escaped. They cannot be escaped
|
||||
with the usual entities (e.g. &) because they are not expanded
|
||||
within <script> tags.
|
||||
"""
|
||||
|
||||
def encode(self, o):
|
||||
# Override JSONEncoder.encode because it has hacks for
|
||||
# performance that make things more complicated.
|
||||
chunks = self.iterencode(o, True)
|
||||
if self.ensure_ascii:
|
||||
return ''.join(chunks)
|
||||
else:
|
||||
return u''.join(chunks)
|
||||
|
||||
def iterencode(self, o, _one_shot=False):
|
||||
chunks = super(JSONEncoderForHTML, self).iterencode(o, _one_shot)
|
||||
for chunk in chunks:
|
||||
chunk = chunk.replace('&', '\\u0026')
|
||||
chunk = chunk.replace('<', '\\u003c')
|
||||
chunk = chunk.replace('>', '\\u003e')
|
||||
yield chunk
|
||||
|
||||
|
||||
def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
|
||||
_key_separator, _item_separator, _sort_keys, _skipkeys, _one_shot,
|
||||
_use_decimal,
|
||||
## HACK: hand-optimized bytecode; turn globals into locals
|
||||
False=False,
|
||||
True=True,
|
||||
ValueError=ValueError,
|
||||
basestring=basestring,
|
||||
Decimal=Decimal,
|
||||
dict=dict,
|
||||
float=float,
|
||||
id=id,
|
||||
int=int,
|
||||
isinstance=isinstance,
|
||||
list=list,
|
||||
long=long,
|
||||
str=str,
|
||||
tuple=tuple,
|
||||
):
|
||||
|
||||
def _iterencode_list(lst, _current_indent_level):
|
||||
if not lst:
|
||||
yield '[]'
|
||||
return
|
||||
if markers is not None:
|
||||
markerid = id(lst)
|
||||
if markerid in markers:
|
||||
raise ValueError("Circular reference detected")
|
||||
markers[markerid] = lst
|
||||
buf = '['
|
||||
if _indent is not None:
|
||||
_current_indent_level += 1
|
||||
newline_indent = '\n' + (_indent * _current_indent_level)
|
||||
separator = _item_separator + newline_indent
|
||||
buf += newline_indent
|
||||
else:
|
||||
newline_indent = None
|
||||
separator = _item_separator
|
||||
first = True
|
||||
for value in lst:
|
||||
if first:
|
||||
first = False
|
||||
else:
|
||||
buf = separator
|
||||
if isinstance(value, basestring):
|
||||
yield buf + _encoder(value)
|
||||
elif value is None:
|
||||
yield buf + 'null'
|
||||
elif value is True:
|
||||
yield buf + 'true'
|
||||
elif value is False:
|
||||
yield buf + 'false'
|
||||
elif isinstance(value, (int, long)):
|
||||
yield buf + str(value)
|
||||
elif isinstance(value, float):
|
||||
yield buf + _floatstr(value)
|
||||
elif _use_decimal and isinstance(value, Decimal):
|
||||
yield buf + str(value)
|
||||
else:
|
||||
yield buf
|
||||
if isinstance(value, (list, tuple)):
|
||||
chunks = _iterencode_list(value, _current_indent_level)
|
||||
elif isinstance(value, dict):
|
||||
chunks = _iterencode_dict(value, _current_indent_level)
|
||||
else:
|
||||
chunks = _iterencode(value, _current_indent_level)
|
||||
for chunk in chunks:
|
||||
yield chunk
|
||||
if newline_indent is not None:
|
||||
_current_indent_level -= 1
|
||||
yield '\n' + (_indent * _current_indent_level)
|
||||
yield ']'
|
||||
if markers is not None:
|
||||
del markers[markerid]
|
||||
|
||||
def _iterencode_dict(dct, _current_indent_level):
|
||||
if not dct:
|
||||
yield '{}'
|
||||
return
|
||||
if markers is not None:
|
||||
markerid = id(dct)
|
||||
if markerid in markers:
|
||||
raise ValueError("Circular reference detected")
|
||||
markers[markerid] = dct
|
||||
yield '{'
|
||||
if _indent is not None:
|
||||
_current_indent_level += 1
|
||||
newline_indent = '\n' + (_indent * _current_indent_level)
|
||||
item_separator = _item_separator + newline_indent
|
||||
yield newline_indent
|
||||
else:
|
||||
newline_indent = None
|
||||
item_separator = _item_separator
|
||||
first = True
|
||||
if _sort_keys:
|
||||
items = dct.items()
|
||||
items.sort(key=lambda kv: kv[0])
|
||||
else:
|
||||
items = dct.iteritems()
|
||||
for key, value in items:
|
||||
if isinstance(key, basestring):
|
||||
pass
|
||||
# JavaScript is weakly typed for these, so it makes sense to
|
||||
# also allow them. Many encoders seem to do something like this.
|
||||
elif isinstance(key, float):
|
||||
key = _floatstr(key)
|
||||
elif key is True:
|
||||
key = 'true'
|
||||
elif key is False:
|
||||
key = 'false'
|
||||
elif key is None:
|
||||
key = 'null'
|
||||
elif isinstance(key, (int, long)):
|
||||
key = str(key)
|
||||
elif _skipkeys:
|
||||
continue
|
||||
else:
|
||||
raise TypeError("key " + repr(key) + " is not a string")
|
||||
if first:
|
||||
first = False
|
||||
else:
|
||||
yield item_separator
|
||||
yield _encoder(key)
|
||||
yield _key_separator
|
||||
if isinstance(value, basestring):
|
||||
yield _encoder(value)
|
||||
elif value is None:
|
||||
yield 'null'
|
||||
elif value is True:
|
||||
yield 'true'
|
||||
elif value is False:
|
||||
yield 'false'
|
||||
elif isinstance(value, (int, long)):
|
||||
yield str(value)
|
||||
elif isinstance(value, float):
|
||||
yield _floatstr(value)
|
||||
elif _use_decimal and isinstance(value, Decimal):
|
||||
yield str(value)
|
||||
else:
|
||||
if isinstance(value, (list, tuple)):
|
||||
chunks = _iterencode_list(value, _current_indent_level)
|
||||
elif isinstance(value, dict):
|
||||
chunks = _iterencode_dict(value, _current_indent_level)
|
||||
else:
|
||||
chunks = _iterencode(value, _current_indent_level)
|
||||
for chunk in chunks:
|
||||
yield chunk
|
||||
if newline_indent is not None:
|
||||
_current_indent_level -= 1
|
||||
yield '\n' + (_indent * _current_indent_level)
|
||||
yield '}'
|
||||
if markers is not None:
|
||||
del markers[markerid]
|
||||
|
||||
def _iterencode(o, _current_indent_level):
|
||||
if isinstance(o, basestring):
|
||||
yield _encoder(o)
|
||||
elif o is None:
|
||||
yield 'null'
|
||||
elif o is True:
|
||||
yield 'true'
|
||||
elif o is False:
|
||||
yield 'false'
|
||||
elif isinstance(o, (int, long)):
|
||||
yield str(o)
|
||||
elif isinstance(o, float):
|
||||
yield _floatstr(o)
|
||||
elif isinstance(o, (list, tuple)):
|
||||
for chunk in _iterencode_list(o, _current_indent_level):
|
||||
yield chunk
|
||||
elif isinstance(o, dict):
|
||||
for chunk in _iterencode_dict(o, _current_indent_level):
|
||||
yield chunk
|
||||
elif _use_decimal and isinstance(o, Decimal):
|
||||
yield str(o)
|
||||
else:
|
||||
if markers is not None:
|
||||
markerid = id(o)
|
||||
if markerid in markers:
|
||||
raise ValueError("Circular reference detected")
|
||||
markers[markerid] = o
|
||||
o = _default(o)
|
||||
for chunk in _iterencode(o, _current_indent_level):
|
||||
yield chunk
|
||||
if markers is not None:
|
||||
del markers[markerid]
|
||||
|
||||
return _iterencode
|
||||
@@ -1,119 +0,0 @@
|
||||
"""Drop-in replacement for collections.OrderedDict by Raymond Hettinger
|
||||
|
||||
http://code.activestate.com/recipes/576693/
|
||||
|
||||
"""
|
||||
from UserDict import DictMixin
|
||||
|
||||
# Modified from original to support Python 2.4, see
|
||||
# http://code.google.com/p/simplejson/issues/detail?id=53
|
||||
try:
|
||||
all
|
||||
except NameError:
|
||||
def all(seq):
|
||||
for elem in seq:
|
||||
if not elem:
|
||||
return False
|
||||
return True
|
||||
|
||||
class OrderedDict(dict, DictMixin):
|
||||
|
||||
def __init__(self, *args, **kwds):
|
||||
if len(args) > 1:
|
||||
raise TypeError('expected at most 1 arguments, got %d' % len(args))
|
||||
try:
|
||||
self.__end
|
||||
except AttributeError:
|
||||
self.clear()
|
||||
self.update(*args, **kwds)
|
||||
|
||||
def clear(self):
|
||||
self.__end = end = []
|
||||
end += [None, end, end] # sentinel node for doubly linked list
|
||||
self.__map = {} # key --> [key, prev, next]
|
||||
dict.clear(self)
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
if key not in self:
|
||||
end = self.__end
|
||||
curr = end[1]
|
||||
curr[2] = end[1] = self.__map[key] = [key, curr, end]
|
||||
dict.__setitem__(self, key, value)
|
||||
|
||||
def __delitem__(self, key):
|
||||
dict.__delitem__(self, key)
|
||||
key, prev, next = self.__map.pop(key)
|
||||
prev[2] = next
|
||||
next[1] = prev
|
||||
|
||||
def __iter__(self):
|
||||
end = self.__end
|
||||
curr = end[2]
|
||||
while curr is not end:
|
||||
yield curr[0]
|
||||
curr = curr[2]
|
||||
|
||||
def __reversed__(self):
|
||||
end = self.__end
|
||||
curr = end[1]
|
||||
while curr is not end:
|
||||
yield curr[0]
|
||||
curr = curr[1]
|
||||
|
||||
def popitem(self, last=True):
|
||||
if not self:
|
||||
raise KeyError('dictionary is empty')
|
||||
# Modified from original to support Python 2.4, see
|
||||
# http://code.google.com/p/simplejson/issues/detail?id=53
|
||||
if last:
|
||||
key = reversed(self).next()
|
||||
else:
|
||||
key = iter(self).next()
|
||||
value = self.pop(key)
|
||||
return key, value
|
||||
|
||||
def __reduce__(self):
|
||||
items = [[k, self[k]] for k in self]
|
||||
tmp = self.__map, self.__end
|
||||
del self.__map, self.__end
|
||||
inst_dict = vars(self).copy()
|
||||
self.__map, self.__end = tmp
|
||||
if inst_dict:
|
||||
return (self.__class__, (items,), inst_dict)
|
||||
return self.__class__, (items,)
|
||||
|
||||
def keys(self):
|
||||
return list(self)
|
||||
|
||||
setdefault = DictMixin.setdefault
|
||||
update = DictMixin.update
|
||||
pop = DictMixin.pop
|
||||
values = DictMixin.values
|
||||
items = DictMixin.items
|
||||
iterkeys = DictMixin.iterkeys
|
||||
itervalues = DictMixin.itervalues
|
||||
iteritems = DictMixin.iteritems
|
||||
|
||||
def __repr__(self):
|
||||
if not self:
|
||||
return '%s()' % (self.__class__.__name__,)
|
||||
return '%s(%r)' % (self.__class__.__name__, self.items())
|
||||
|
||||
def copy(self):
|
||||
return self.__class__(self)
|
||||
|
||||
@classmethod
|
||||
def fromkeys(cls, iterable, value=None):
|
||||
d = cls()
|
||||
for key in iterable:
|
||||
d[key] = value
|
||||
return d
|
||||
|
||||
def __eq__(self, other):
|
||||
if isinstance(other, OrderedDict):
|
||||
return len(self)==len(other) and \
|
||||
all(p==q for p, q in zip(self.items(), other.items()))
|
||||
return dict.__eq__(self, other)
|
||||
|
||||
def __ne__(self, other):
|
||||
return not self == other
|
||||
@@ -1,77 +0,0 @@
|
||||
"""JSON token scanner
|
||||
"""
|
||||
import re
|
||||
def _import_c_make_scanner():
|
||||
try:
|
||||
from simplejson._speedups import make_scanner
|
||||
return make_scanner
|
||||
except ImportError:
|
||||
return None
|
||||
c_make_scanner = _import_c_make_scanner()
|
||||
|
||||
__all__ = ['make_scanner']
|
||||
|
||||
NUMBER_RE = re.compile(
|
||||
r'(-?(?:0|[1-9]\d*))(\.\d+)?([eE][-+]?\d+)?',
|
||||
(re.VERBOSE | re.MULTILINE | re.DOTALL))
|
||||
|
||||
def py_make_scanner(context):
|
||||
parse_object = context.parse_object
|
||||
parse_array = context.parse_array
|
||||
parse_string = context.parse_string
|
||||
match_number = NUMBER_RE.match
|
||||
encoding = context.encoding
|
||||
strict = context.strict
|
||||
parse_float = context.parse_float
|
||||
parse_int = context.parse_int
|
||||
parse_constant = context.parse_constant
|
||||
object_hook = context.object_hook
|
||||
object_pairs_hook = context.object_pairs_hook
|
||||
memo = context.memo
|
||||
|
||||
def _scan_once(string, idx):
|
||||
try:
|
||||
nextchar = string[idx]
|
||||
except IndexError:
|
||||
raise StopIteration
|
||||
|
||||
if nextchar == '"':
|
||||
return parse_string(string, idx + 1, encoding, strict)
|
||||
elif nextchar == '{':
|
||||
return parse_object((string, idx + 1), encoding, strict,
|
||||
_scan_once, object_hook, object_pairs_hook, memo)
|
||||
elif nextchar == '[':
|
||||
return parse_array((string, idx + 1), _scan_once)
|
||||
elif nextchar == 'n' and string[idx:idx + 4] == 'null':
|
||||
return None, idx + 4
|
||||
elif nextchar == 't' and string[idx:idx + 4] == 'true':
|
||||
return True, idx + 4
|
||||
elif nextchar == 'f' and string[idx:idx + 5] == 'false':
|
||||
return False, idx + 5
|
||||
|
||||
m = match_number(string, idx)
|
||||
if m is not None:
|
||||
integer, frac, exp = m.groups()
|
||||
if frac or exp:
|
||||
res = parse_float(integer + (frac or '') + (exp or ''))
|
||||
else:
|
||||
res = parse_int(integer)
|
||||
return res, m.end()
|
||||
elif nextchar == 'N' and string[idx:idx + 3] == 'NaN':
|
||||
return parse_constant('NaN'), idx + 3
|
||||
elif nextchar == 'I' and string[idx:idx + 8] == 'Infinity':
|
||||
return parse_constant('Infinity'), idx + 8
|
||||
elif nextchar == '-' and string[idx:idx + 9] == '-Infinity':
|
||||
return parse_constant('-Infinity'), idx + 9
|
||||
else:
|
||||
raise StopIteration
|
||||
|
||||
def scan_once(string, idx):
|
||||
try:
|
||||
return _scan_once(string, idx)
|
||||
finally:
|
||||
memo.clear()
|
||||
|
||||
return scan_once
|
||||
|
||||
make_scanner = c_make_scanner or py_make_scanner
|
||||
@@ -1,63 +0,0 @@
|
||||
import unittest
|
||||
import doctest
|
||||
|
||||
|
||||
class OptionalExtensionTestSuite(unittest.TestSuite):
|
||||
def run(self, result):
|
||||
import simplejson
|
||||
run = unittest.TestSuite.run
|
||||
run(self, result)
|
||||
simplejson._toggle_speedups(False)
|
||||
run(self, result)
|
||||
simplejson._toggle_speedups(True)
|
||||
return result
|
||||
|
||||
|
||||
def additional_tests(suite=None):
|
||||
import simplejson
|
||||
import simplejson.encoder
|
||||
import simplejson.decoder
|
||||
if suite is None:
|
||||
suite = unittest.TestSuite()
|
||||
for mod in (simplejson, simplejson.encoder, simplejson.decoder):
|
||||
suite.addTest(doctest.DocTestSuite(mod))
|
||||
suite.addTest(doctest.DocFileSuite('../../index.rst'))
|
||||
return suite
|
||||
|
||||
|
||||
def all_tests_suite():
|
||||
suite = unittest.TestLoader().loadTestsFromNames([
|
||||
'simplejson.tests.test_check_circular',
|
||||
'simplejson.tests.test_decode',
|
||||
'simplejson.tests.test_default',
|
||||
'simplejson.tests.test_dump',
|
||||
'simplejson.tests.test_encode_basestring_ascii',
|
||||
'simplejson.tests.test_encode_for_html',
|
||||
'simplejson.tests.test_fail',
|
||||
'simplejson.tests.test_float',
|
||||
'simplejson.tests.test_indent',
|
||||
'simplejson.tests.test_pass1',
|
||||
'simplejson.tests.test_pass2',
|
||||
'simplejson.tests.test_pass3',
|
||||
'simplejson.tests.test_recursion',
|
||||
'simplejson.tests.test_scanstring',
|
||||
'simplejson.tests.test_separators',
|
||||
'simplejson.tests.test_speedups',
|
||||
'simplejson.tests.test_unicode',
|
||||
'simplejson.tests.test_decimal',
|
||||
])
|
||||
suite = additional_tests(suite)
|
||||
return OptionalExtensionTestSuite([suite])
|
||||
|
||||
|
||||
def main():
|
||||
runner = unittest.TextTestRunner()
|
||||
suite = all_tests_suite()
|
||||
runner.run(suite)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
import os
|
||||
import sys
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
|
||||
main()
|
||||
@@ -1,30 +0,0 @@
|
||||
from unittest import TestCase
|
||||
import simplejson as json
|
||||
|
||||
def default_iterable(obj):
|
||||
return list(obj)
|
||||
|
||||
class TestCheckCircular(TestCase):
|
||||
def test_circular_dict(self):
|
||||
dct = {}
|
||||
dct['a'] = dct
|
||||
self.assertRaises(ValueError, json.dumps, dct)
|
||||
|
||||
def test_circular_list(self):
|
||||
lst = []
|
||||
lst.append(lst)
|
||||
self.assertRaises(ValueError, json.dumps, lst)
|
||||
|
||||
def test_circular_composite(self):
|
||||
dct2 = {}
|
||||
dct2['a'] = []
|
||||
dct2['a'].append(dct2)
|
||||
self.assertRaises(ValueError, json.dumps, dct2)
|
||||
|
||||
def test_circular_default(self):
|
||||
json.dumps([set()], default=default_iterable)
|
||||
self.assertRaises(TypeError, json.dumps, [set()])
|
||||
|
||||
def test_circular_off_default(self):
|
||||
json.dumps([set()], default=default_iterable, check_circular=False)
|
||||
self.assertRaises(TypeError, json.dumps, [set()], check_circular=False)
|
||||
@@ -1,33 +0,0 @@
|
||||
from decimal import Decimal
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson as json
|
||||
|
||||
class TestDecimal(TestCase):
|
||||
NUMS = "1.0", "10.00", "1.1", "1234567890.1234567890", "500"
|
||||
def test_decimal_encode(self):
|
||||
for d in map(Decimal, self.NUMS):
|
||||
self.assertEquals(json.dumps(d, use_decimal=True), str(d))
|
||||
|
||||
def test_decimal_decode(self):
|
||||
for s in self.NUMS:
|
||||
self.assertEquals(json.loads(s, parse_float=Decimal), Decimal(s))
|
||||
|
||||
def test_decimal_roundtrip(self):
|
||||
for d in map(Decimal, self.NUMS):
|
||||
# The type might not be the same (int and Decimal) but they
|
||||
# should still compare equal.
|
||||
self.assertEquals(
|
||||
json.loads(
|
||||
json.dumps(d, use_decimal=True), parse_float=Decimal),
|
||||
d)
|
||||
self.assertEquals(
|
||||
json.loads(
|
||||
json.dumps([d], use_decimal=True), parse_float=Decimal),
|
||||
[d])
|
||||
|
||||
def test_decimal_defaults(self):
|
||||
d = Decimal(1)
|
||||
# use_decimal=False is the default
|
||||
self.assertRaises(TypeError, json.dumps, d, use_decimal=False)
|
||||
self.assertRaises(TypeError, json.dumps, d)
|
||||
@@ -1,73 +0,0 @@
|
||||
import decimal
|
||||
from unittest import TestCase
|
||||
from StringIO import StringIO
|
||||
|
||||
import simplejson as json
|
||||
from simplejson import OrderedDict
|
||||
|
||||
class TestDecode(TestCase):
|
||||
if not hasattr(TestCase, 'assertIs'):
|
||||
def assertIs(self, a, b):
|
||||
self.assertTrue(a is b, '%r is %r' % (a, b))
|
||||
|
||||
def test_decimal(self):
|
||||
rval = json.loads('1.1', parse_float=decimal.Decimal)
|
||||
self.assertTrue(isinstance(rval, decimal.Decimal))
|
||||
self.assertEquals(rval, decimal.Decimal('1.1'))
|
||||
|
||||
def test_float(self):
|
||||
rval = json.loads('1', parse_int=float)
|
||||
self.assertTrue(isinstance(rval, float))
|
||||
self.assertEquals(rval, 1.0)
|
||||
|
||||
def test_decoder_optimizations(self):
|
||||
# Several optimizations were made that skip over calls to
|
||||
# the whitespace regex, so this test is designed to try and
|
||||
# exercise the uncommon cases. The array cases are already covered.
|
||||
rval = json.loads('{ "key" : "value" , "k":"v" }')
|
||||
self.assertEquals(rval, {"key":"value", "k":"v"})
|
||||
|
||||
def test_empty_objects(self):
|
||||
s = '{}'
|
||||
self.assertEqual(json.loads(s), eval(s))
|
||||
s = '[]'
|
||||
self.assertEqual(json.loads(s), eval(s))
|
||||
s = '""'
|
||||
self.assertEqual(json.loads(s), eval(s))
|
||||
|
||||
def test_object_pairs_hook(self):
|
||||
s = '{"xkd":1, "kcw":2, "art":3, "hxm":4, "qrt":5, "pad":6, "hoy":7}'
|
||||
p = [("xkd", 1), ("kcw", 2), ("art", 3), ("hxm", 4),
|
||||
("qrt", 5), ("pad", 6), ("hoy", 7)]
|
||||
self.assertEqual(json.loads(s), eval(s))
|
||||
self.assertEqual(json.loads(s, object_pairs_hook=lambda x: x), p)
|
||||
self.assertEqual(json.load(StringIO(s),
|
||||
object_pairs_hook=lambda x: x), p)
|
||||
od = json.loads(s, object_pairs_hook=OrderedDict)
|
||||
self.assertEqual(od, OrderedDict(p))
|
||||
self.assertEqual(type(od), OrderedDict)
|
||||
# the object_pairs_hook takes priority over the object_hook
|
||||
self.assertEqual(json.loads(s,
|
||||
object_pairs_hook=OrderedDict,
|
||||
object_hook=lambda x: None),
|
||||
OrderedDict(p))
|
||||
|
||||
def check_keys_reuse(self, source, loads):
|
||||
rval = loads(source)
|
||||
(a, b), (c, d) = sorted(rval[0]), sorted(rval[1])
|
||||
self.assertIs(a, c)
|
||||
self.assertIs(b, d)
|
||||
|
||||
def test_keys_reuse_str(self):
|
||||
s = u'[{"a_key": 1, "b_\xe9": 2}, {"a_key": 3, "b_\xe9": 4}]'.encode('utf8')
|
||||
self.check_keys_reuse(s, json.loads)
|
||||
|
||||
def test_keys_reuse_unicode(self):
|
||||
s = u'[{"a_key": 1, "b_\xe9": 2}, {"a_key": 3, "b_\xe9": 4}]'
|
||||
self.check_keys_reuse(s, json.loads)
|
||||
|
||||
def test_empty_strings(self):
|
||||
self.assertEqual(json.loads('""'), "")
|
||||
self.assertEqual(json.loads(u'""'), u"")
|
||||
self.assertEqual(json.loads('[""]'), [""])
|
||||
self.assertEqual(json.loads(u'[""]'), [u""])
|
||||
@@ -1,9 +0,0 @@
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson as json
|
||||
|
||||
class TestDefault(TestCase):
|
||||
def test_default(self):
|
||||
self.assertEquals(
|
||||
json.dumps(type, default=repr),
|
||||
json.dumps(repr(type)))
|
||||
@@ -1,27 +0,0 @@
|
||||
from unittest import TestCase
|
||||
from cStringIO import StringIO
|
||||
|
||||
import simplejson as json
|
||||
|
||||
class TestDump(TestCase):
|
||||
def test_dump(self):
|
||||
sio = StringIO()
|
||||
json.dump({}, sio)
|
||||
self.assertEquals(sio.getvalue(), '{}')
|
||||
|
||||
def test_dumps(self):
|
||||
self.assertEquals(json.dumps({}), '{}')
|
||||
|
||||
def test_encode_truefalse(self):
|
||||
self.assertEquals(json.dumps(
|
||||
{True: False, False: True}, sort_keys=True),
|
||||
'{"false": true, "true": false}')
|
||||
self.assertEquals(json.dumps(
|
||||
{2: 3.0, 4.0: 5L, False: 1, 6L: True, "7": 0}, sort_keys=True),
|
||||
'{"false": 1, "2": 3.0, "4.0": 5, "6": true, "7": 0}')
|
||||
|
||||
def test_ordered_dict(self):
|
||||
# http://bugs.python.org/issue6105
|
||||
items = [('one', 1), ('two', 2), ('three', 3), ('four', 4), ('five', 5)]
|
||||
s = json.dumps(json.OrderedDict(items))
|
||||
self.assertEqual(s, '{"one": 1, "two": 2, "three": 3, "four": 4, "five": 5}')
|
||||
@@ -1,41 +0,0 @@
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson.encoder
|
||||
|
||||
CASES = [
|
||||
(u'/\\"\ucafe\ubabe\uab98\ufcde\ubcda\uef4a\x08\x0c\n\r\t`1~!@#$%^&*()_+-=[]{}|;:\',./<>?', '"/\\\\\\"\\ucafe\\ubabe\\uab98\\ufcde\\ubcda\\uef4a\\b\\f\\n\\r\\t`1~!@#$%^&*()_+-=[]{}|;:\',./<>?"'),
|
||||
(u'\u0123\u4567\u89ab\ucdef\uabcd\uef4a', '"\\u0123\\u4567\\u89ab\\ucdef\\uabcd\\uef4a"'),
|
||||
(u'controls', '"controls"'),
|
||||
(u'\x08\x0c\n\r\t', '"\\b\\f\\n\\r\\t"'),
|
||||
(u'{"object with 1 member":["array with 1 element"]}', '"{\\"object with 1 member\\":[\\"array with 1 element\\"]}"'),
|
||||
(u' s p a c e d ', '" s p a c e d "'),
|
||||
(u'\U0001d120', '"\\ud834\\udd20"'),
|
||||
(u'\u03b1\u03a9', '"\\u03b1\\u03a9"'),
|
||||
('\xce\xb1\xce\xa9', '"\\u03b1\\u03a9"'),
|
||||
(u'\u03b1\u03a9', '"\\u03b1\\u03a9"'),
|
||||
('\xce\xb1\xce\xa9', '"\\u03b1\\u03a9"'),
|
||||
(u'\u03b1\u03a9', '"\\u03b1\\u03a9"'),
|
||||
(u'\u03b1\u03a9', '"\\u03b1\\u03a9"'),
|
||||
(u"`1~!@#$%^&*()_+-={':[,]}|;.</>?", '"`1~!@#$%^&*()_+-={\':[,]}|;.</>?"'),
|
||||
(u'\x08\x0c\n\r\t', '"\\b\\f\\n\\r\\t"'),
|
||||
(u'\u0123\u4567\u89ab\ucdef\uabcd\uef4a', '"\\u0123\\u4567\\u89ab\\ucdef\\uabcd\\uef4a"'),
|
||||
]
|
||||
|
||||
class TestEncodeBaseStringAscii(TestCase):
|
||||
def test_py_encode_basestring_ascii(self):
|
||||
self._test_encode_basestring_ascii(simplejson.encoder.py_encode_basestring_ascii)
|
||||
|
||||
def test_c_encode_basestring_ascii(self):
|
||||
if not simplejson.encoder.c_encode_basestring_ascii:
|
||||
return
|
||||
self._test_encode_basestring_ascii(simplejson.encoder.c_encode_basestring_ascii)
|
||||
|
||||
def _test_encode_basestring_ascii(self, encode_basestring_ascii):
|
||||
fname = encode_basestring_ascii.__name__
|
||||
for input_string, expect in CASES:
|
||||
result = encode_basestring_ascii(input_string)
|
||||
#self.assertEquals(result, expect,
|
||||
# '{0!r} != {1!r} for {2}({3!r})'.format(
|
||||
# result, expect, fname, input_string))
|
||||
self.assertEquals(result, expect,
|
||||
'%r != %r for %s(%r)' % (result, expect, fname, input_string))
|
||||
@@ -1,32 +0,0 @@
|
||||
import unittest
|
||||
|
||||
import simplejson.decoder
|
||||
import simplejson.encoder
|
||||
|
||||
|
||||
class TestEncodeForHTML(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.decoder = simplejson.decoder.JSONDecoder()
|
||||
self.encoder = simplejson.encoder.JSONEncoderForHTML()
|
||||
|
||||
def test_basic_encode(self):
|
||||
self.assertEqual(r'"\u0026"', self.encoder.encode('&'))
|
||||
self.assertEqual(r'"\u003c"', self.encoder.encode('<'))
|
||||
self.assertEqual(r'"\u003e"', self.encoder.encode('>'))
|
||||
|
||||
def test_basic_roundtrip(self):
|
||||
for char in '&<>':
|
||||
self.assertEqual(
|
||||
char, self.decoder.decode(
|
||||
self.encoder.encode(char)))
|
||||
|
||||
def test_prevent_script_breakout(self):
|
||||
bad_string = '</script><script>alert("gotcha")</script>'
|
||||
self.assertEqual(
|
||||
r'"\u003c/script\u003e\u003cscript\u003e'
|
||||
r'alert(\"gotcha\")\u003c/script\u003e"',
|
||||
self.encoder.encode(bad_string))
|
||||
self.assertEqual(
|
||||
bad_string, self.decoder.decode(
|
||||
self.encoder.encode(bad_string)))
|
||||
@@ -1,91 +0,0 @@
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson as json
|
||||
|
||||
# Fri Dec 30 18:57:26 2005
|
||||
JSONDOCS = [
|
||||
# http://json.org/JSON_checker/test/fail1.json
|
||||
'"A JSON payload should be an object or array, not a string."',
|
||||
# http://json.org/JSON_checker/test/fail2.json
|
||||
'["Unclosed array"',
|
||||
# http://json.org/JSON_checker/test/fail3.json
|
||||
'{unquoted_key: "keys must be quoted}',
|
||||
# http://json.org/JSON_checker/test/fail4.json
|
||||
'["extra comma",]',
|
||||
# http://json.org/JSON_checker/test/fail5.json
|
||||
'["double extra comma",,]',
|
||||
# http://json.org/JSON_checker/test/fail6.json
|
||||
'[ , "<-- missing value"]',
|
||||
# http://json.org/JSON_checker/test/fail7.json
|
||||
'["Comma after the close"],',
|
||||
# http://json.org/JSON_checker/test/fail8.json
|
||||
'["Extra close"]]',
|
||||
# http://json.org/JSON_checker/test/fail9.json
|
||||
'{"Extra comma": true,}',
|
||||
# http://json.org/JSON_checker/test/fail10.json
|
||||
'{"Extra value after close": true} "misplaced quoted value"',
|
||||
# http://json.org/JSON_checker/test/fail11.json
|
||||
'{"Illegal expression": 1 + 2}',
|
||||
# http://json.org/JSON_checker/test/fail12.json
|
||||
'{"Illegal invocation": alert()}',
|
||||
# http://json.org/JSON_checker/test/fail13.json
|
||||
'{"Numbers cannot have leading zeroes": 013}',
|
||||
# http://json.org/JSON_checker/test/fail14.json
|
||||
'{"Numbers cannot be hex": 0x14}',
|
||||
# http://json.org/JSON_checker/test/fail15.json
|
||||
'["Illegal backslash escape: \\x15"]',
|
||||
# http://json.org/JSON_checker/test/fail16.json
|
||||
'["Illegal backslash escape: \\\'"]',
|
||||
# http://json.org/JSON_checker/test/fail17.json
|
||||
'["Illegal backslash escape: \\017"]',
|
||||
# http://json.org/JSON_checker/test/fail18.json
|
||||
'[[[[[[[[[[[[[[[[[[[["Too deep"]]]]]]]]]]]]]]]]]]]]',
|
||||
# http://json.org/JSON_checker/test/fail19.json
|
||||
'{"Missing colon" null}',
|
||||
# http://json.org/JSON_checker/test/fail20.json
|
||||
'{"Double colon":: null}',
|
||||
# http://json.org/JSON_checker/test/fail21.json
|
||||
'{"Comma instead of colon", null}',
|
||||
# http://json.org/JSON_checker/test/fail22.json
|
||||
'["Colon instead of comma": false]',
|
||||
# http://json.org/JSON_checker/test/fail23.json
|
||||
'["Bad value", truth]',
|
||||
# http://json.org/JSON_checker/test/fail24.json
|
||||
"['single quote']",
|
||||
# http://code.google.com/p/simplejson/issues/detail?id=3
|
||||
u'["A\u001FZ control characters in string"]',
|
||||
]
|
||||
|
||||
SKIPS = {
|
||||
1: "why not have a string payload?",
|
||||
18: "spec doesn't specify any nesting limitations",
|
||||
}
|
||||
|
||||
class TestFail(TestCase):
|
||||
def test_failures(self):
|
||||
for idx, doc in enumerate(JSONDOCS):
|
||||
idx = idx + 1
|
||||
if idx in SKIPS:
|
||||
json.loads(doc)
|
||||
continue
|
||||
try:
|
||||
json.loads(doc)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
else:
|
||||
#self.fail("Expected failure for fail{0}.json: {1!r}".format(idx, doc))
|
||||
self.fail("Expected failure for fail%d.json: %r" % (idx, doc))
|
||||
|
||||
def test_array_decoder_issue46(self):
|
||||
# http://code.google.com/p/simplejson/issues/detail?id=46
|
||||
for doc in [u'[,]', '[,]']:
|
||||
try:
|
||||
json.loads(doc)
|
||||
except json.JSONDecodeError, e:
|
||||
self.assertEquals(e.pos, 1)
|
||||
self.assertEquals(e.lineno, 1)
|
||||
self.assertEquals(e.colno, 1)
|
||||
except Exception, e:
|
||||
self.fail("Unexpected exception raised %r %s" % (e, e))
|
||||
else:
|
||||
self.fail("Unexpected success parsing '[,]'")
|
||||
@@ -1,19 +0,0 @@
|
||||
import math
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson as json
|
||||
|
||||
class TestFloat(TestCase):
|
||||
def test_floats(self):
|
||||
for num in [1617161771.7650001, math.pi, math.pi**100,
|
||||
math.pi**-100, 3.1]:
|
||||
self.assertEquals(float(json.dumps(num)), num)
|
||||
self.assertEquals(json.loads(json.dumps(num)), num)
|
||||
self.assertEquals(json.loads(unicode(json.dumps(num))), num)
|
||||
|
||||
def test_ints(self):
|
||||
for num in [1, 1L, 1<<32, 1<<64]:
|
||||
self.assertEquals(json.dumps(num), str(num))
|
||||
self.assertEquals(int(json.dumps(num)), num)
|
||||
self.assertEquals(json.loads(json.dumps(num)), num)
|
||||
self.assertEquals(json.loads(unicode(json.dumps(num))), num)
|
||||
@@ -1,53 +0,0 @@
|
||||
from unittest import TestCase
|
||||
|
||||
import simplejson as json
|
||||
import textwrap
|
||||
|
||||
class TestIndent(TestCase):
|
||||
def test_indent(self):
|
||||
h = [['blorpie'], ['whoops'], [], 'd-shtaeou', 'd-nthiouh',
|
||||
'i-vhbjkhnth',
|
||||
{'nifty': 87}, {'field': 'yes', 'morefield': False} ]
|
||||
|
||||
expect = textwrap.dedent("""\
|
||||
[
|
||||
\t[
|
||||
\t\t"blorpie"
|
||||
\t],
|
||||
\t[
|
||||
\t\t"whoops"
|
||||
\t],
|
||||
\t[],
|
||||
\t"d-shtaeou",
|
||||
\t"d-nthiouh",
|
||||
\t"i-vhbjkhnth",
|
||||
\t{
|
||||
\t\t"nifty": 87
|
||||
\t},
|
||||
\t{
|
||||
\t\t"field": "yes",
|
||||
\t\t"morefield": false
|
||||
\t}
|
||||
]""")
|
||||
|
||||
|
||||
d1 = json.dumps(h)
|
||||
d2 = json.dumps(h, indent='\t', sort_keys=True, separators=(',', ': '))
|
||||
d3 = json.dumps(h, indent=' ', sort_keys=True, separators=(',', ': '))
|
||||
d4 = json.dumps(h, indent=2, sort_keys=True, separators=(',', ': '))
|
||||
|
||||
h1 = json.loads(d1)
|
||||
h2 = json.loads(d2)
|
||||
h3 = json.loads(d3)
|
||||
h4 = json.loads(d4)
|
||||
|
||||
self.assertEquals(h1, h)
|
||||
self.assertEquals(h2, h)
|
||||
self.assertEquals(h3, h)
|
||||
self.assertEquals(h4, h)
|
||||
self.assertEquals(d3, expect.replace('\t', ' '))
|
||||
self.assertEquals(d4, expect.replace('\t', ' '))
|
||||
# NOTE: Python 2.4 textwrap.dedent converts tabs to spaces,
|
||||
# so the following is expected to fail. Python 2.4 is not a
|
||||
# supported platform in simplejson 2.1.0+.
|
||||
self.assertEquals(d2, expect)
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user