built-in python modules and their uses
1. abc - This tiny module delivers the environment you need for creating abstract base classes
2. argparse - This module contains tools that make it easier to create user-friendly interfaces from the level of the command line
3. asyncio - This is a very large module that delivers the framework and environment for asynchronous programming
4. base64 - This well-known module delivers a tool for coding and decoding binary code into a format that can be displayed – and
the other way round
5. collections - This module offers specialized container data types that work as an alternative to basic contained types for general
purposes such as dict, list, set, and tuple.
6. copy - Everyone uses this tiny module that contains tools for deep copying of container type data. Its most famous function is `deepcopy` – if not for this function, copying lists and dictionaries would become a torture for developers.
7. csv - Delivers functionalities for exporting and importing tabular data in CSV format. The module allows developers to say “load data” or “save data” from to a CSV file.
8. datetime - It delivers tools that make it easier to work with dates and times
9. decimal - The module delivers a data type called Decimal. Its main advantage is correct rounding of decimal numbers which is extremely important in billing systems– even
a slight distortion with several hundred thousand operations can change the final result significantly
10. functools - The functools module comes in handy for higher-order functions, ie. the functions that act on or return other functions. You can treat any callable
object as a function for the purposes of this module.
11. hashlib - his handy module implements a common interface to numerous secure hash and message digest algorithms like the FIPS
secure hash algorithms SHA1, SHA224, SHA256, SHA384, and SHA512
12. http - his package collects several modules for working with the HyperText Transfer Protocol
13. importlib - The package provides the implementation of the import statement (and the __import__() function) in Python source code
14. itertools - This useful module implements iterator building blocks inspired by constructs
from APL, Haskell, and SML (all in a form that matches Python programs)
15. inspect - The module offers several useful functions that help developers get information about live objects such as
modules, classes, methods, functions, tracebacks, frame objects, and code objects in Python code
16. json - Helps to work with json data
17. logging - This module defines functions and classes that provide a flexible event logging system for applications and libraries
18. math - This module gives developers access to the mathematical functions defined by the C standard
19. multiprocessing - This handy package supports spawning processes with the help of an API similar to the threading module
20. os - Offers a portable method of using operating system dependent functionality.
21. pdb - This module defines an interactive source code debugger
22. random - pseudo-random number generators for various distributions
23. re - Provides regular expression matching operations similar to those you get in Perl
24. shutil - Provides a number of high-level operations on files and collections of files, especially functions that
support file copying and removal
25. sys - offers access to variables used or maintained by the interpreter and functions that interact strongly
with the interpreter
26. threading - This useful module builds higher-level threading interfaces on top of the lower level _thread module
27. types - It defines names for object types used by the standard Python interpreter but not exposed as builtins
28. unittest - Works similarly to major unit testing frameworks in other programming languages
29. urllib - This handy package collects several modules for working with URLs
30. uuid - The module provides immutable UUID objects, as well as the following functions for generating version 1, 3, 4, and 5 UUIDs