ReviseAlgo Logo

Modules & Packages

Standard Library Overview

Python's batteries-included standard library modules

Interview: Knowing key modules saves time in interviews — demonstrates practical Python knowledge

Last Updated: June 12, 2026 9 min read

Python's standard library is famously described as "batteries included" — it provides modules for virtually every common programming task. Knowing the key modules and when to use them is a significant productivity advantage and demonstrates practical Python knowledge in interviews.

Essential Modules

  • collections: Counter, defaultdict, namedtuple, OrderedDict, deque — enhanced data structures
  • itertools: Infinite iterators, combinatoric iterators, chaining, grouping — functional iteration tools
  • functools: lru_cache, partial, reduce, wraps — higher-order function utilities
  • os/pathlib: File system operations, path manipulation — prefer pathlib for new code
  • json: JSON encoding/decoding — essential for API work
  • re: Regular expressions — powerful text pattern matching

Data and Math

  • math: Mathematical functions — sqrt, ceil, floor, factorial, gcd
  • random: Random number generation — choice, shuffle, randint, sample
  • statistics: Statistical functions — mean, median, stdev, mode
  • decimal: Precise decimal arithmetic — essential for financial calculations
  • fractions: Exact rational number arithmetic

System and I/O

  • sys: System parameters, argv, path, modules, exit
  • subprocess: Running external commands and processes
  • logging: Flexible logging framework — preferred over print()
  • argparse: Command-line argument parsing
  • typing: Type hints for static analysis and IDE support

Know Your Itertools

itertools is one of the most powerful standard library modules. Key functions: chain (concatenate), product (Cartesian product), combinations, permutations, groupby, islice. These often solve interview problems in one line.

Use Cases

Solving coding interview problems with collections, itertools, and functools

Building data processing pipelines with standard library modules

Implementing logging and monitoring in production applications

Working with JSON APIs using the json module

File system operations with pathlib for modern Python

Common Mistakes

Reinventing functionality that already exists in the standard library

Using print() instead of logging — print is for debugging, logging is for production

Not knowing itertools — many combinatoric problems have one-line itertools solutions

Using os.path instead of pathlib — pathlib is the modern, more Pythonic approach

Forgetting about lru_cache — it turns O(2^n) recursive solutions into O(n) with one line