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Implemented feedback and suggestions from code review
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@@ -10,9 +10,9 @@ Data Serialization
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What is data serialization?
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***************************
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Data serialization is the concept of converting structured data into a format
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Data serialization is the process of converting structured data into a format
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that allows it to be shared or stored in such a way that its original
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structure can be recovered or reconstructed. In some cases, the secondary intention of data
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structure should be recovered or reconstructed. In some cases, the secondary intention of data
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serialization is to minimize the size of the serialized data which then
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minimizes disk space or bandwidth requirements.
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@@ -21,7 +21,7 @@ Flat vs. Nested data
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********************
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Before beginning to serialize data, it is important to identify or decide how the
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data should to be structured during data serialization - flat or nested.
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data should be structured during data serialization - flat or nested.
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The differences in the two styles are shown in the below examples.
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Flat style:
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@@ -65,7 +65,7 @@ The repr method in Python takes a single object parameter and returns a printabl
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a = { "Type" : "A", "field1": "value1", "field2": "value2", "field3": "value3" }
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# the same input can also be read from a file
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a =
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a = open('/tmp/file.py', 'r')
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# returns a printable representation of the input;
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# the output can be written to a file as well
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@@ -135,7 +135,7 @@ structures in Python. One such example is below.
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print(ymlexcp)
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Documentation on the third party module can be found
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`here <https://pyyaml.org/wiki/PyYAMLDocumentation>`__.
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`in the PyYAML Documentation <https://pyyaml.org/wiki/PyYAMLDocumentation>`__.
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=======================
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JSON file (nested data)
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@@ -157,7 +157,7 @@ Writing:
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.. code-block:: python
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# writing JSON content to a file using the dump method
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# Writing JSON content to a file using the dump method
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import json
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with open('/tmp/file.json', 'w') as f:
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json.dump(data, f, sort_keys=True)
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