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Converted README/HISTORY to Markdown format
This commit is contained in:
Hugo van Kemenade
committed by
Claude Paroz
Claude Paroz
parent
923711d99a
commit
e8838b5ce6
+58
-89
@@ -1,120 +1,105 @@
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History
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-------
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# History
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0.11.5 (2017-06-13)
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+++++++++++++++++++
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## 0.11.5 (2017-06-13)
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- Use ``yaml.safe_load`` for importing yaml.
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- Use `yaml.safe_load` for importing yaml.
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0.11.4 (2017-01-23)
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+++++++++++++++++++
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## 0.11.4 (2017-01-23)
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- Use built-in `json` package if available
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- Support Python 3.5+ in classifiers
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** Bugfixes **
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### Bugfixes
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- Fixed textual representation for Dataset with no headers
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- Handle decimal types
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0.11.3 (2016-02-16)
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+++++++++++++++++++
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## 0.11.3 (2016-02-16)
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- Release fix.
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0.11.2 (2016-02-16)
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+++++++++++++++++++
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## 0.11.2 (2016-02-16)
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**Bugfixes**
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### Bugfixes
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- Fix export only formats.
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- Fix for xlsx output.
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0.11.1 (2016-02-07)
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+++++++++++++++++++
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## 0.11.1 (2016-02-07)
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**Bugfixes**
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### Bugfixes
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- Fixed packaging error on Python 3.
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0.11.0 (2016-02-07)
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+++++++++++++++++++
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## 0.11.0 (2016-02-07)
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**New Formats!**
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### New Formats!
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- Added LaTeX table export format (``Dataset.latex``).
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- Support for dBase (DBF) files (``Dataset.dbf``).
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- Added LaTeX table export format (`Dataset.latex`).
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- Support for dBase (DBF) files (`Dataset.dbf`).
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**Improvements**
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### Improvements
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- New import/export interface (``Dataset.export()``, ``Dataset.load()``).
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- CSV custom delimiter support (``Dataset.export('csv', delimiter='$')``).
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- Adding ability to remove duplicates to all rows in a dataset (``Dataset.remove_duplicates()``).
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- Added a mechanism to avoid ``datetime.datetime`` issues when serializing data.
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- New ``detect_format()`` function (mostly for internal use).
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- Update the vendored unicodecsv to fix ``None`` handling.
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- New import/export interface (`Dataset.export()`, `Dataset.load()`).
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- CSV custom delimiter support (`Dataset.export('csv', delimiter='$')`).
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- Adding ability to remove duplicates to all rows in a dataset (`Dataset.remove_duplicates()`).
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- Added a mechanism to avoid `datetime.datetime` issues when serializing data.
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- New `detect_format()` function (mostly for internal use).
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- Update the vendored unicodecsv to fix `None` handling.
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- Only freeze the headers row, not the headers columns (xls).
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**Breaking Changes**
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### Breaking Changes
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- ``detect()`` function removed.
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- `detect()` function removed.
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**Bugfixes**
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### Bugfixes
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- Fix XLSX import.
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- Bugfix for ``Dataset.transpose().transpose()``.
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- Bugfix for `Dataset.transpose().transpose()`.
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0.10.0 (2014-05-27)
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+++++++++++++++++++
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## 0.10.0 (2014-05-27)
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* Unicode Column Headers
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* ALL the bugfixes!
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0.9.11 (2011-06-30)
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+++++++++++++++++++
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## 0.9.11 (2011-06-30)
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* Bugfixes
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0.9.10 (2011-06-22)
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+++++++++++++++++++
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## 0.9.10 (2011-06-22)
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* Bugfixes
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0.9.9 (2011-06-21)
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++++++++++++++++++
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## 0.9.9 (2011-06-21)
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* Dataset API Changes
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* ``stack_rows`` => ``stack``, ``stack_columns`` => ``stack_cols``
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* column operations have their own methods now (``append_col``, ``insert_col``)
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* List-style ``pop()``
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* Redis-style ``rpush``, ``lpush``, ``rpop``, ``lpop``, ``rpush_col``, and ``lpush_col``
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* `stack_rows` => `stack`, `stack_columns` => `stack_cols`
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* column operations have their own methods now (`append_col`, `insert_col`)
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* List-style `pop()`
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* Redis-style `rpush`, `lpush`, `rpop`, `lpop`, `rpush_col`, and `lpush_col`
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0.9.8 (2011-05-22)
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++++++++++++++++++
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## 0.9.8 (2011-05-22)
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* OpenDocument Spreadsheet support (.ods)
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* Full Unicode TSV support
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0.9.7 (2011-05-12)
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++++++++++++++++++
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## 0.9.7 (2011-05-12)
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* Full XLSX Support!
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* Pickling Bugfix
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* Compat Module
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0.9.6 (2011-05-12)
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++++++++++++++++++
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## 0.9.6 (2011-05-12)
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* ``seperators`` renamed to ``separators``
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* `seperators` renamed to `separators`
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* Full unicode CSV support
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0.9.5 (2011-03-24)
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++++++++++++++++++
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## 0.9.5 (2011-03-24)
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* Python 3.1, Python 3.2 Support (same code base!)
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* Formatter callback support
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@@ -122,8 +107,7 @@ History
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0.9.4 (2011-02-18)
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++++++++++++++++++
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## 0.9.4 (2011-02-18)
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* Python 2.5 Support!
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* Tox Testing for 2.5, 2.6, 2.7
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@@ -132,16 +116,14 @@ History
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* Caved to community pressure (spaces)
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0.9.3 (2011-01-31)
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++++++++++++++++++
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## 0.9.3 (2011-01-31)
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* Databook duplication leak fix.
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* HTML Table output.
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* Added column sorting.
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0.9.2 (2010-11-17)
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++++++++++++++++++
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## 0.9.2 (2010-11-17)
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* Transpose method added to Datasets.
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* New frozen top row in Excel output.
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@@ -149,14 +131,12 @@ History
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* Support for row/column stacking.
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0.9.1 (2010-11-04)
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++++++++++++++++++
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## 0.9.1 (2010-11-04)
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* Minor reference shadowing bugfix.
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0.9.0 (2010-11-04)
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++++++++++++++++++
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## 0.9.0 (2010-11-04)
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* Massive documentation update!
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* Tablib.org!
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@@ -166,56 +146,48 @@ History
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* Internal Changes (Row object and use thereof)
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0.8.5 (2010-10-06)
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++++++++++++++++++
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## 0.8.5 (2010-10-06)
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* New import system. All dependencies attempt to load from site-packages,
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then fallback on tenderized modules.
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0.8.4 (2010-10-04)
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++++++++++++++++++
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## 0.8.4 (2010-10-04)
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* Updated XLS output: Only wrap if '\\n' in cell.
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0.8.3 (2010-10-04)
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++++++++++++++++++
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## 0.8.3 (2010-10-04)
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* Ability to append new column passing a callable
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as the value that will be applied to every row.
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0.8.2 (2010-10-04)
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++++++++++++++++++
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## 0.8.2 (2010-10-04)
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* Added alignment wrapping to written cells.
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* Added separator support to XLS.
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0.8.1 (2010-09-28)
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++++++++++++++++++
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## 0.8.1 (2010-09-28)
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* Packaging Fix
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0.8.0 (2010-09-25)
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++++++++++++++++++
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## 0.8.0 (2010-09-25)
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* New format plugin system!
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* Imports! ELEGANT Imports!
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* Tests. Lots of tests.
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0.7.1 (2010-09-20)
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++++++++++++++++++
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## 0.7.1 (2010-09-20)
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* Reverting methods back to properties.
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* Windows bug compensated in documentation.
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0.7.0 (2010-09-20)
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++++++++++++++++++
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## 0.7.0 (2010-09-20)
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* Renamed DataBook Databook for consistency.
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* Export properties changed to methods (XLS filename / StringIO bug).
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@@ -223,32 +195,29 @@ History
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* Added utf-8 on the worksheet level.
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0.6.4 (2010-09-19)
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++++++++++++++++++
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## 0.6.4 (2010-09-19)
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* Updated unicode export for XLS.
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* More exhaustive unit tests.
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0.6.3 (2010-09-14)
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++++++++++++++++++
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## 0.6.3 (2010-09-14)
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* Added Dataset.append() support for columns.
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0.6.2 (2010-09-13)
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++++++++++++++++++
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## 0.6.2 (2010-09-13)
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* Fixed Dataset.append() error on empty dataset.
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* Updated Dataset.headers property w/ validation.
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* Added Testing Fixtures.
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0.6.1 (2010-09-12)
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++++++++++++++++++
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## 0.6.1 (2010-09-12)
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* Packaging hotfixes.
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0.6.0 (2010-09-11)
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++++++++++++++++++
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## 0.6.0 (2010-09-11)
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* Public Release.
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* Export Support for XLS, JSON, YAML, and CSV.
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@@ -0,0 +1,180 @@
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# Tablib: format-agnostic tabular dataset library
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[](https://jazzband.co/)
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[](https://travis-ci.org/jazzband/tablib)
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|
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_____ ______ ___________ ______
|
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__ /_______ ____ /_ ___ /___(_)___ /_
|
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_ __/_ __ `/__ __ \__ / __ / __ __ \
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/ /_ / /_/ / _ /_/ /_ / _ / _ /_/ /
|
||||
\__/ \__,_/ /_.___/ /_/ /_/ /_.___/
|
||||
|
||||
|
||||
Tablib is a format-agnostic tabular dataset library, written in Python.
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||||
|
||||
Output formats supported:
|
||||
|
||||
- Excel (Sets + Books)
|
||||
- JSON (Sets + Books)
|
||||
- YAML (Sets + Books)
|
||||
- Pandas DataFrames (Sets)
|
||||
- HTML (Sets)
|
||||
- Jira (Sets)
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||||
- TSV (Sets)
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- ODS (Sets)
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- CSV (Sets)
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- DBF (Sets)
|
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|
||||
Note that tablib *purposefully* excludes XML support. It always will. (Note: This is a
|
||||
joke. Pull requests are welcome.)
|
||||
|
||||
If you're interested in financially supporting Kenneth Reitz open source, consider
|
||||
[visiting this link](https://cash.me/$KennethReitz>). Your support helps tremendously
|
||||
with sustainability of motivation, as Open Source is no longer part of my day job.
|
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|
||||
|
||||
## Overview
|
||||
|
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`tablib.Dataset()`
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A Dataset is a table of tabular data.
|
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It may or may not have a header row.
|
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They can be build and manipulated as raw Python datatypes (Lists of tuples|dictionaries).
|
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Datasets can be imported from JSON, YAML, DBF, and CSV;
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they can be exported to XLSX, XLS, ODS, JSON, YAML, DBF, CSV, TSV, and HTML.
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|
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`tablib.Databook()`
|
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|
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A Databook is a set of Datasets.
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The most common form of a Databook is an Excel file with multiple spreadsheets.
|
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Databooks can be imported from JSON and YAML;
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they can be exported to XLSX, XLS, ODS, JSON, and YAML.
|
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|
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|
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## Usage
|
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|
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Populate fresh data files:
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|
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```python
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headers = ('first_name', 'last_name')
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data = [
|
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('John', 'Adams'),
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('George', 'Washington')
|
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]
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|
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data = tablib.Dataset(*data, headers=headers)
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```
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|
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Intelligently add new rows:
|
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|
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```python
|
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>>> data.append(('Henry', 'Ford'))
|
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```
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|
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Intelligently add new columns:
|
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|
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```python
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>>> data.append_col((90, 67, 83), header='age')
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```
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|
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Slice rows:
|
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```python
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>>> print(data[:2])
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[('John', 'Adams', 90), ('George', 'Washington', 67)]
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```
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|
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Slice columns by header:
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|
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```python
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>>> print(data['first_name'])
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['John', 'George', 'Henry']
|
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```
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|
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Easily delete rows:
|
||||
|
||||
```python
|
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>>> del data[1]
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```
|
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|
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|
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## Exports
|
||||
|
||||
Drumroll please...........
|
||||
|
||||
### JSON!
|
||||
|
||||
```python
|
||||
>>> print(data.export('json'))
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[
|
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{
|
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"last_name": "Adams",
|
||||
"age": 90,
|
||||
"first_name": "John"
|
||||
},
|
||||
{
|
||||
"last_name": "Ford",
|
||||
"age": 83,
|
||||
"first_name": "Henry"
|
||||
}
|
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]
|
||||
```
|
||||
|
||||
### 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.python.org/pypi/tablib/)!
|
||||
|
||||
|
||||
## Contribute
|
||||
|
||||
Please see the [contributing guide](https://github.com/jazzband/tablib/blob/master/.github/CONTRIBUTING.md).
|
||||
-182
@@ -1,182 +0,0 @@
|
||||
Tablib: format-agnostic tabular dataset library
|
||||
===============================================
|
||||
|
||||
.. image:: https://jazzband.co/static/img/badge.svg
|
||||
:target: https://jazzband.co/
|
||||
:alt: Jazzband
|
||||
|
||||
.. image:: https://travis-ci.org/jazzband/tablib.svg?branch=master
|
||||
:target: https://travis-ci.org/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.)
|
||||
|
||||
If you're interested in financially supporting Kenneth Reitz open source, consider `visiting this link <https://cash.me/$KennethReitz>`_. Your support helps tremendously with sustainability of motivation, as Open Source is no longer part of my day job.
|
||||
|
||||
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: ::
|
||||
|
||||
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((90, 67, 83), header='age')
|
||||
|
||||
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.export('json'))
|
||||
[
|
||||
{
|
||||
"last_name": "Adams",
|
||||
"age": 90,
|
||||
"first_name": "John"
|
||||
},
|
||||
{
|
||||
"last_name": "Ford",
|
||||
"age": 83,
|
||||
"first_name": "Henry"
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
YAML!
|
||||
+++++
|
||||
::
|
||||
|
||||
>>> print(data.export('yaml'))
|
||||
- {age: 90, first_name: John, last_name: Adams}
|
||||
- {age: 83, first_name: Henry, last_name: Ford}
|
||||
|
||||
CSV...
|
||||
++++++
|
||||
::
|
||||
|
||||
>>> print(data.export('csv'))
|
||||
first_name,last_name,age
|
||||
John,Adams,90
|
||||
Henry,Ford,83
|
||||
|
||||
EXCEL!
|
||||
++++++
|
||||
::
|
||||
|
||||
>>> with open('people.xls', 'wb') as f:
|
||||
... f.write(data.export('xls'))
|
||||
|
||||
DBF!
|
||||
++++
|
||||
::
|
||||
|
||||
>>> with open('people.dbf', 'wb') as f:
|
||||
... f.write(data.export('dbf'))
|
||||
|
||||
Pandas DataFrame!
|
||||
+++++++++++++++++
|
||||
::
|
||||
|
||||
>>> 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: ::
|
||||
|
||||
$ pip install tablib[pandas]
|
||||
|
||||
Make sure to check out `Tablib on PyPi <https://pypi.python.org/pypi/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_.
|
||||
|
||||
|
||||
|
||||
.. _`the repository`: http://github.com/jazzband/tablib
|
||||
.. _AUTHORS: http://github.com/jazzband/tablib/blob/master/AUTHORS
|
||||
@@ -48,8 +48,9 @@ setup(
|
||||
name='tablib',
|
||||
version=version,
|
||||
description='Format agnostic tabular data library (XLS, JSON, YAML, CSV)',
|
||||
long_description=(open('README.rst').read() + '\n\n' +
|
||||
open('HISTORY.rst').read()),
|
||||
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',
|
||||
url='http://python-tablib.org',
|
||||
|
||||
Reference in New Issue
Block a user