Python libs

Below is a list of Python packages, their documentation links, and the corresponding installation commands. The packages are arranged alphabetically.

TOC

  1. allure-pytest
  2. cheat
  3. colorama
  4. faker
  5. graphviz
  6. hypothesis
  7. jsonschema
  8. loguru
  9. numpy
  10. openpyxl
  11. pandas
  12. pipdeptree
  13. pytest
  14. pytest-html
  15. pytest-lazy-f
  16. pytest-xdist
  17. pydocstyle
  18. random
  19. rich
  20. regex
  21. requests
  22. semopy
  23. scikit
  24. selenium
  25. sphinx
  26. tabulate
  27. tach
  28. tqdm
  29. typing
  30. requests-mock

allure-pytest

A Python library for integrating Allure reporting with pytest, enabling enhanced test reporting with visualizations and detailed logs.


cheat

A command-line tool that provides instant cheat sheets for numerous programming languages, frameworks, and tools.


colorama

A cross-platform library that allows for colored terminal text in Python, making it easier to style terminal output.


faker

A Python package that generates fake data for testing and development, including names, addresses, dates, and more.


graphviz

A Python interface to the Graphviz graph-drawing software, used for creating, rendering, and visualizing graphs and networks.


hypothesis

A property-based testing tool for Python that generates test cases based on your code’s specifications and properties.


jsonschema

A library for validating JSON data against a specified schema, ensuring data conforms to a defined structure.


loguru

A simple and flexible logging library for Python that aims to make logging easy and fun.


numpy

A fundamental package for scientific computing with Python, providing support for arrays, matrices, and large data sets.


openpyxl

A Python library for reading and writing Excel (xlsx) files, making it easy to manipulate spreadsheets.


pandas

A powerful library for data analysis and manipulation, providing data structures like DataFrames for handling large datasets.


pipdeptree

A command-line tool for showing the dependency tree of installed Python packages, helping you to manage dependencies.


pytest

A testing framework for Python that makes it easy to write simple and scalable test cases.


pytest-html

A plugin for pytest that generates HTML reports, making it easier to share test results.


pytest-lazy-fixture

A pytest plugin that allows for lazy loading of fixtures to improve test performance by evaluating fixtures only when needed.


pytest-xdist

A plugin for pytest that allows parallel test execution, speeding up test runs by distributing them across multiple CPUs or machines.


pydocstyle

A Python docstring style checker that enforces PEP 257 conventions for writing docstrings.


random

A built-in Python module for generating random numbers and performing random operations, such as selecting random items from a list.


rich

A Python library for rich text and beautiful formatting in the terminal, offering features like syntax highlighting, progress bars, tables, and more. It helps developers create visually appealing and interactive terminal applications.

1
pip install rich

regex

A library for handling regular expressions with more advanced features than the built-in re module.


requests

A simple and elegant HTTP library for Python, making it easy to send HTTP requests and handle responses.


semopy

A Python library for Structural Equation Modeling (SEM) that helps users estimate and analyze path models. It provides a convenient interface for building and fitting models, along with tools for model evaluation and visualization.

1
pip install semopy

scikit

A popular machine learning library for Python that provides simple and efficient tools for data mining and data analysis.


selenium

A powerful tool for automating web browsers, used for testing web applications and scraping web data.


sphinx

A documentation generator for Python projects, commonly used for creating beautiful, readable, and structured documentation.


tabulate

Pretty-print tabular data in Python, a library and a command-line utility.
The main use cases of the library are:

  • printing small tables without hassle: just one function call, formatting is guided by the data itself

  • authoring tabular data for lightweight plain-text markup: multiple output formats suitable for further editing or transformation

  • readable presentation of mixed textual and numeric data: smart column alignment, configurable number formatting, alignment by a decimal point

  • pypi.org docs: https://pypi.org/project/tabulate/

  • Home page: https://github.com/astanin/python-tabulate

    1
    pip install tabulate

tach

A lightweight tool for running multiple tests in parallel, useful for speeding up the testing process.


tqdm

A fast, extensible progress bar library for Python, useful for visualizing the progress of loops and long-running operations.


typing

A module that provides support for type hints in Python, enhancing code readability and maintainability.


requests-mock

A library that helps in mocking out requests during testing, useful for simulating API responses without making real network calls.