Final commit

This commit is contained in:
Harish Kesava Rao
2018-12-17 21:02:21 -06:00
parent 8a6b1c73bf
commit fd2a8f3e8f
+53 -5
View File
@@ -74,8 +74,9 @@ The repr method in Python takes a single object parameter and returns a printabl
# write content to files using repr
with open('/tmp/file.py') as f:f.write(repr(a))
ast.literal_eval
________________
----------------
The literal_eval method safely parses and evaluates an expression for a Python datatype.
Supported data types are: strings, numbers, tuples, lists, dicts, booleans and None.
@@ -95,6 +96,7 @@ Simple example for reading:
.. code-block:: python
# Reading CSV content from a file
import csv
with open('/tmp/file.csv', newline='') as f:
reader = csv.reader(f)
@@ -105,6 +107,7 @@ Simple example for writing:
.. code-block:: python
# Writing CSV content to a file
import csv
with open('/temp/file.csv', 'w', newline='') as f:
writer = csv.writer(f)
@@ -123,6 +126,7 @@ structures in Python. One such example is below.
.. code-block:: python
# Reading YAML content from a file using the load method
import yaml
with open('/tmp/file.yaml', 'r', newline='') as f:
try:
@@ -144,22 +148,66 @@ Reading:
.. code-block:: python
# Reading JSON content from a file
import json
with open('/tmp/file.json', 'r') as f:
data = json.dump(f)
data = json.load(f)
Writing:
.. code-block:: python
# writing JSON content to a file using the dump method
import json
with open('/tmp/file.json', 'w') as f:
json.dump(data, f, sort_keys=True)
=================
XML (nested data)
=================
******
Pickle
******
XML parsing in Python is possible using the `xml` package.
Example:
.. code-block:: python
# reading XML content from a file
import xml.etree.ElementTree as ET
tree = ET.parse('country_data.xml')
root = tree.getroot()
More documentation on using the `xml.dom` and `xml.sax` packages can be found
`here <https://docs.python.org/3/library/xml.html>`__.
*******
Binary
*******
=======================
Numpy Array (flat data)
=======================
Python's Numpy array can be used to serialize and deserialize data to and from byte representation.
Example:
.. code-block:: python
import numpy as np
# Converting Numpy array to byte format
byte_output = np.array([ [1, 2, 3], [4, 5, 6], [7, 8, 9] ]).tobytes()
# Converting byte format back to Numpy array
array_format = np.frombuffer(byte_output)
====================
Pickle (nested data)
====================
The native data serialization module for Python is called `Pickle
<https://docs.python.org/2/library/pickle.html>`_.