| Core Library | Modules |
|---|---|
| Built-ins |
The principal built-in types are functions, constants, exceptions, numerics, sequences, mappings, classes and instances. Built-in Functions - Built-in Constants - Built-in Exceptions Built-in Types: int, float, complex, list, tuple, range, str bytes, bytearray, memoryview, set, frozenset, dict Type Annotations: Generic Alias, Union, Other built-in types |
| Specialized Data Types |
Specialized data types such as dates and times, fixed-type arrays, heap queues, double-ended queues, and enumerations. datetime, zoneinfo, calendar, array, heapq, enum, pprint collections — Specialized containers; alternatives to dict, list, set, and tuple. collections.abc — Test class interfaces; e.g. hashable or is a mapping. bisect — Maintaining a sorted list after each insertion using array bisection weakref — Weak object reference allowing garbage collection types — Dynamic type creation and names for built-in types copy — Shallow and deep copy operations reprlib — Object representations with string size limits graphlib — Functionality to topologically sort a graph 3rd party datetime libraries: arrow, pendulum |
| Text Processing |
String manipulation operations and other text processing services. string, re, difflib, textwrap, unicodedata, stringprep, readline, rlcompleter 3rd party text libraries: transformers, spacy, gensim, nltk |
| Binary Data |
Basic services operations for manipulation of binary data struct, codecs 3rd party binary libraries: h5py, pyarrow, avro, fastparquet |
| Numeric and Mathematical |
The numbers module defines an abstract hierarchy of numeric types. The math and cmath modules contain mathematical functions for floating-point and complex numbers. The decimal module supports exact representations of decimal numbers, using arbitrary precision arithmetic. numbers, math, cmath, decimal, fractions, random, statistics 3rd party math libraries: numpy, sympy, scipy, scikit-learn, tensorflow, pytorch |
| Functional Programming |
Classes that support a functional programming style, and general operations on callables. itertools — Functions creating iterators for efficient looping functools — Higher-order functions and operations on callable objects operator — Standard operators as functions 3rd party functional libraries: toolz, funcy, wrapt, more-itertools |
| Concurrent Execution |
Concurrent execution of code. threading — Thread-based parallelism multiprocessing — Process-based parallelism multiprocessing.shared_memory — Provides shared memory for direct access across processes concurrent.futures — Launching parallel tasks subprocess — Subprocess management sched — Event scheduler queue — A synchronized queue class contextvars — Context Variables _thread — Low-level threading API 3rd party (distributed) concurrency libraries: dask, dask.distributed, celery |
| Networking and Interprocess |
Networking and inter-processes communication. Some modules only work for two processes that are on the same machine, e.g. signal and mmap. Other modules support networking protocols that two or more processes can use to communicate across machines. asyncio — Asynchronous I/O socket — Low-level networking interface ssl — TLS/SSL wrapper for socket objects select — Waiting for I/O completion selectors — High-level I/O multiplexing signal — Set handlers for asynchronous events mmap — Memory-mapped file support 3rd party asyncio libraries: uvloop, trio, curio, anyio, asyncer |
| Data Serialization and Persistence |
Serialization and persisting data to disk. pickle, copyreg, shelve, marshal, dbm, sqlite3 3rd party serialization libraries: flatbuffers, dataclasses-json, marshmallow, pydantic, dacite, pyserde 3rd party data-storage libraries: aws-data-wrangler, pandas, modin, vaex, xarray, pytables 3rd party sql libraries: sqlalchemy, alembic, sqlmodel, sqlite-utils |
| Operating System Services | OS features, such as files, datetime, argument parsing, logging etc. os, io, time, argparse, getopt, logging, getpass, curses, platform, errno, ctypes 3rd party argparse libraries: click, python-fire, typer 3rd party logging/env/C++ libraries: loguru, python-dotenv, pybind11 |
| Graphical User Interfaces |
tkinter is fast and usually comes bundled with Python. 3rd party GUI libraries: PySimpleGUI, DearPyGui, remi, pygame, panda3d, arcade |
| File and Directory Access |
Disk files and directories. pathlib, os.path, fileinput, stat, filecmp, tempfile, glob, fnmatch, linecache, shutil 3rd party functional libraries: pyfilesystem2 |
| Data Compression |
Data compression with the zlib, gzip, bzip2 and lzma algorithms, and the creation of zip and tar archives. zlib, gzip, bz2, lzma, zipfile, tarfile |
| File Formats |
Miscellaneous file formats that aren't markup languages and are not related to e-mail. csv, configparser, netrc, plistlib 3rd party file-format libraries: XlsxWriter, imageio, markdown (see also 3rd party binary libraries) |
| Cryptographic Services |
Cryptographic algorithms; available at the discretion of the installation. hashlib, hmac, secrets 3rd party cryptographic libraries: cryptography, pynacl, bcrypt |
| Internet Data Handling |
email, json, mailbox, mimetypes, base64, binhex, binascii, quopri. |
| Structured Markup |
html and xml. |
| Internet Protocols and Support |
webbrowser, wsgiref, urllib, http, ftplib, poplib, imaplib, smtplib, uuid, socketserver, xmlrpc, ipaddress etc. 3rd party internet libraries: requests, TODO: more |
| Dev, Packaging and Runtime | |
| Development Tools |
Modules to help you write software typing — Support for type hints pydoc — Documentation generator and online help system doctest — Test interactive Python examples unittest — Unit testing framework unittest.mock — mock object library unittest.mock — getting started test — Regression tests package for Python (internal) Python Development Mode 3rd party typing libraries: mypy, pyright, pyre-check, pytype, monkeytype 3rd party testing libraries: pytest, parameterized, hypothesis, behave 3rd party coverage libraries: coveragepy, pytest-cov 3rd party style/linting libraries: black, ruff, pylint, flake8, autoflake, isort, pycodestyle, pyflakes, pydocstyle 3rd party doc libraries: mkdocs-material, sphinx, readthedocs |
| Debugging and Profiling |
The debugger enables you to step through code, analyze stack frames and set breakpoints etc Profilers run code and give you a detailed breakdown of execution times, allowing you to identify bottlenecks Auditing events provide visibility into runtime behaviors that would otherwise require intrusive debugging or patching bdb — Debugger framework faulthandler — Dump the Python traceback pdb — The Python Debugger timeit — Measure execution time of small code snippets trace — Trace or track Python statement execution tracemalloc — Trace memory allocations Audit events table The Python Profilers 3rd party debugging libraries: PySnooper, icecream, snoop, birdseye 3rd party profiling libraries: memray, viztracer, pyheat |
| Software Packaging and Distribution |
These libraries help you with publishing and installing Python software. setuptools, distutils, ensurepip, venv, zipapp 3rd party packaging tools: poetry, pdm, hatch, flit 3rd party standalone executables: pyinstaller, pyOxidizer, py2exe 3rd party venv libraries: pipenv, pipx, pipx comparisons 3rd party package managers: conda, miniconda, mamba, micromamba Read more: Python Packaging User Guide (PyPUG), Python packaging in 2023 |
| Python Runtime |
Services related to the Python interpreter and its interaction with its environment. __main__ — Top-level code environment __future__ — Future statement definitions sys — System-specific parameters and functions sysconfig — Provide access to Python’s configuration information builtins — Built-in objects warnings — Warning control dataclasses — Data Classes: mutable namedtuples with defaults contextlib — Utilities for with-statement contexts abc — Abstract Base Classes atexit — Exit handlers traceback — Print or retrieve a stack traceback gc — Garbage Collector interface inspect — Inspect live objects site — Site-specific configuration hook 3rd party libraries: pydantic Runtime/compilation alternatives: CPython, Cython, PyPy, CPython without the GIL, numba |
| Importing Modules | Modules that provide new ways to import Python modules and hooks for customizing the import process. |
| Python Language | These modules support tokenizing, parsing, syntax analysis, bytecode disassembly etc. |