Skip to content

Python Standard Library

Free code when using Python for analytics.

Since they are built into Python they don't need to be added to pyproject.toml dependencies like we do with external libraries such as pandas or polars.

Data Formats and Files

  • json - For handling JSON data
  • csv - For reading/writing CSV files
  • sqlite3 - For working with SQLite databases (built into Python)
  • pathlib - For working with filesystem paths
  • os - For interacting with the OS (e.g., file paths, env vars)
  • sys - For system-specific parameters and functions
  • urllib - For basic URL handling and data fetching (useful with or without requests)

Math and Analysis

  • math - For mathematical functions (sqrt, log, etc.)
  • statistics - For statistical analysis (mean, median, stdev, etc.)
  • random - For generating random numbers
  • time - For time-based functions
  • datetime - For date and time manipulation

Quality, Structure, and Maintenance

  • collections - For specialized containers like Counter, defaultdict
  • typing - For type hints and static type checking
  • unittest - For writing and running unit tests
  • logging - For structured logging in Python
  • re - For regular expressions and pattern matching
  • pprint - For pretty-printing complex or nested data structures
  • collections - For specialized containers like Counter, defaultdict
  • typing - For type hints and static type checking
  • unittest - For writing and running unit tests

Save time by knowing what is available in case a project needs these capabilities. Python can be learned in weeks or months, it's familarity with all the available tools and packages where experience is measured in years.