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Libraries

nose packages

Pypy​

PyPy is a fast, compliant alternative implementation of the Python language (2.7.13 and 3.5.3). It has several advantages and distinct features:

  • Speed: thanks to its Just-in-Time compiler, Python programs often run faster on PyPy.(What is a JIT compiler?) "If you want your code to run faster, you should probably just use PyPy." - Guido van Rossum (creator of Python)
  • Memory usage: memory-hungry Python programs (several hundreds of MBs or more) might end up taking less space than they do in CPython.
  • Compatibility: PyPy is highly compatible with existing python code. It supports cffi and can run popular python libraries like twisted and django.
  • Stackless: PyPy comes by default with support for stackless mode, providing micro-threads for massive concurrency.

Django-model-utils​

  • Django model mixins and utilities.
  • Fields
    • StatusField
    • MonitorField
    • SplitField
  • Models
    • TimeFramedModel
    • TimeStampedModel
    • StatusModel
    • SoftDeletableModel
  • Model Managers
    • InheritanceManager

This manager should be attached to a base model class in a model-inheritance tree. It allows queries on that base model to return heterogenous results of the actual proper subtypes, without any additional queries.

PyFlame​

py-spy​

py-spy is a sampling profiler for Python programs. It lets you visualize what your Python program is spending time on without restarting the program or modifying the code in any way. py-spy is extremely low overhead: it is written in Rust for speed and doesn't run in the same process as the profiled Python program. This means py-spy is safe to use against production Python code.

https://github.com/benfred/py-spy

FII Memory profiler​

https://gitlab.com/pythonspeed/filprofiler

https://pythonspeed.com/articles/memory-profiler-data-scientists

HorusLP​

HorusLP is a Python optimization library designed to help you architect algorithm development workflows. It has a simple, declarative API and very little boilerplate.

https://www.toptal.com/algorithms/horuslp-python-optimization-library

https://www.toptal.com/python/horuslp-gurobi-optimization

tqdm​

A Fast, Extensible Progress Bar for Python and CLI

https://github.com/tqdm/tqdm

Pendulum​

Nativedatetimeinstances are enough for basic cases but when you face more complex use-cases they often show limitations and are not so intuitive to work with.Pendulumprovides a cleaner and more easy to use API while still relying on the standard library. So it's stilldatetimebut better.

https://github.com/sdispater/pendulum

https://pendulum.eustace.io

pyqt​

PyQt is one of the most popular Python bindings for the Qt cross-platform C++ framework

https://wiki.python.org/moin/PyQt

https://www.tutorialspoint.com/pyqt/index.htm

Pyro​

Pyro is a library that enables you to build applications in which objects can talk to each other over the network, with minimal programming effort. You can just use normal Python method calls, with almost every possible parameter and return value type, and Pyro takes care of locating the right object on the right computer to execute the method. It is designed to be very easy to use, and to generally stay out of your way. But it also provides a set of powerful features that enables you to build distributed applications rapidly and effortlessly. Pyro is a pure Python library and runs on many different platforms and Python versions.

https://github.com/irmen/Pyro4

CookieCutter​

A command-line utility that creates projects fromcookiecutters(project templates), e.g. creating a Python package project from a Python package project template.

https://cookiecutter.readthedocs.io/en/1.7.2/first_steps.html

https://github.com/cookiecutter/cookiecutter

Python-magic​

python-magic is a Python interface to the libmagic file type identification library. libmagic identifies file types by checking their headers according to a predefined list of file types. This functionality is exposed to the command line by the Unix commandfile.

https://pypi.org/project/python-magic

schedule​

Python job scheduling for humans.

An in-process scheduler for periodic jobs that uses the builder pattern for configuration. Schedule lets you run Python functions (or any other callable) periodically at pre-determined intervals using a simple, human-friendly syntax.

https://github.com/dbader/schedule

https://schedule.readthedocs.io/en/stable

pyglet​

3d animation and game creation engine

http://pyglet.org

pygame​

https://www.pygame.org

image

image

https://humberto.io/blog/exploring-pygame-5-movement-and-collision

Pong with Python & Pygame - Tutorial - YouTube

pygal​

image

image

jinja2​

Jinja2 is a full-featured template engine for Python. It has full unicode support, an optional integrated sandboxed execution environment, widely used and BSD licensed.

https://palletsprojects.com/p/jinja

Tenacity​

Tenacity is an Apache 2.0 licensed general-purpose retrying library, written in Python, to simplify the task of adding retry behavior to just about anything. It originates from a fork of retrying ⭐ 1.9k which is sadly no longer maintained. Tenacity isn’t api compatible with retrying but adds significant new functionality and fixes a number of longstanding bugs.

Serializers​

  • ujson ⭐ 4.5k (UltraJSON) is an ultra fast JSON encoder and decoder written in pure C with bindings for Python 3.7+.
  • orjson ⭐ 8.1k is a fast, correct JSON library for Python. It is the fastest python library for json encoding & decoding. It serializes dataclass, datetime, numpy, and UUID instances natively.

Benchmarking​

# Python 12.502133846282959
# ujson 4.428200960159302
# orjson 2.3136467933654785
  • ujson ⭐ 4.5k is 3 times faster than the standard json library
  • orjson ⭐ 8.1k is over 6 times faster than the standard json library

Conclusion​

For most cases, you would want to go with python’s standard json library which removes dependencies on other libraries. On other hand you could try out ujson ⭐ 4.5k which is simple replacement for python’s json library. If you want more speed and also want dataclass, datetime, numpy, and UUID instances and you are ready to deal with more complex code, then you can try your hands on orjson ⭐ 8.1k

Benchmarking Python JSON serializers - json vs ujson vs orjson - Dollar Dhingra’s Blog

GitHub - ultrajson/ultrajson: Ultra fast JSON decoder and encoder written in C with Python bindings ⭐ 4.5k

Visualization​

Others​

GUI​

Others​