Python 3 - Overview

Last Updated: 2023-03-02

Why Python

• Easy to learn.
• Available everywhere: Linux, macOS, Windows.
• Super popular in machine learning / data science, competing with R.
• help() gets docstring for any module / method / function.
• Simple, compact and powerful.
  • list comprehensions.
  • class magic methods.
  • very powerful OOP.
  • built-in strings and array slicing.
  • huge and coherent standard library.

globals() vs locals() vs vars()

• globals(): returns the dictionary of the module namespace
• locals(): returns a dictionary of the current namespace
• vars(): returns either a dictionary of the current namespace (if called with no argument) or the dictionary of the argument.

Ecosystem

• Tensorflow / PyTorch: machine learning frameworks.
• Scikit Learn: ML.
• pandas: data analysis and manipulation. https://pandas.pydata.org/
• numpy: scientific computing. https://numpy.org/
• jupyter: notebook. https://jupyter.org/
• Django: web framework.
• Tornado: a Python web framework and asynchronous networking library. https://www.tornadoweb.org/
• Twisted: An event-driven networking engine. https://twisted.org/
• Pillow: For image processing

Python specific features

Swap

a, b = b, a

If You Forget Function Name

Use dir() to check the function names:

>>> dir([])
[... 'append', 'clear', 'copy', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort']

Or pretty print:

>>> import pprint; pprint.pprint(dir([]))
[ ...
  'append',
  'clear',
  'copy',
  'count',
  'extend',
  'index',
  'insert',
  'pop',
  'remove',
  'reverse',
  'sort']

All and ANY

ALL: if every one is truthy

>>> all([1, "abc", [False]])
True
>>> all([1, 0, 1])
False

ANY: if any one is truthy

>>> any([1, 0, 0])
True
>>> any(["", 0, 0])
False

Resources

• functional programming
  • http://docs.python.org/howto/functional.html
• performance
  • http://wiki.python.org/moin/PythonSpeed/PerformanceTips
• best practice
  • http://www.python.org/dev/peps/pep-0008/
  • http://www.fantascienza.net/leonardo/ar/python_best_practices.html