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Python Guide
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Python Guide

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README 

        


 

  


  Python Guide




#### A guide covering the Python programming language including the applications and tools that will make you a better and more efficient Python developer.



 **Note: You can easily convert this markdown file to a PDF in [VSCode](https://code.visualstudio.com/) using this handy extension [Markdown PDF](https://marketplace.visualstudio.com/items?itemName=yzane.markdown-pdf).**

 

 


 

  





## Python Learning Resources



[Python](https://www.python.org) is an interpreted, high-level programming language. Python is used heavily in the fields of Data Science and Machine Learning. 



[Python Developer’s Guide](https://devguide.python.org) is a comprehensive resource for contributing to Python – for both new and experienced contributors. It is maintained by the same community that maintains Python. 



[Azure Functions Python developer guide](https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference-python) is an introduction to developing Azure Functions using Python. The content below assumes that you've already read the [Azure Functions developers guide](https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference).



[CheckiO](https://checkio.org/) is a programming learning platform and a gamified website that teaches Python through solving code challenges and competing for the most elegant and creative solutions.



[Python Institute](https://pythoninstitute.org)



[PCEP – Certified Entry-Level Python Programmer certification](https://pythoninstitute.org/pcep-certification-entry-level/)



[PCAP – Certified Associate in Python Programming certification](https://pythoninstitute.org/pcap-certification-associate/)



[PCPP – Certified Professional in Python Programming 1 certification](https://pythoninstitute.org/pcpp-certification-professional/)



[PCPP – Certified Professional in Python Programming 2](https://pythoninstitute.org/pcpp-certification-professional/)



[MTA: Introduction to Programming Using Python Certification](https://docs.microsoft.com/en-us/learn/certifications/mta-introduction-to-programming-using-python)



[Getting Started with Python in Visual Studio Code](https://code.visualstudio.com/docs/python/python-tutorial)



[Google's Python Style Guide](https://google.github.io/styleguide/pyguide.html)



[Google's Python Education Class](https://developers.google.com/edu/python/)



[Real Python](https://realpython.com)



[The Python Open Source Computer Science Degree by Forrest Knight](https://github.com/ForrestKnight/open-source-cs-python)



[Intro to Python for Data Science](https://www.datacamp.com/courses/intro-to-python-for-data-science)



[Intro to Python by W3schools](https://www.w3schools.com/python/python_intro.asp)



[Codecademy's Python 3 course](https://www.codecademy.com/learn/learn-python-3)



[Learn Python with Online Courses and Classes from edX](https://www.edx.org/learn/python)



[Python Courses Online from Coursera](https://www.coursera.org/courses?query=python)



## Python Frameworks, Libraries, and Tools



[Python Package Index (PyPI)](https://pypi.org/) is a repository of software for the Python programming language. PyPI helps you find and install software developed and shared by the Python community. 



[PyCharm](https://www.jetbrains.com/pycharm/) is the best IDE I've ever used. With PyCharm, you can access the command line, connect to a database, create a virtual environment, and manage your version control system all in one place, saving time by avoiding constantly switching between windows.



[Python Tools for Visual Studio(PTVS)](https://microsoft.github.io/PTVS/) is a free, open source plugin that turns Visual Studio into a Python IDE. It supports editing, browsing, IntelliSense, mixed Python/C++ debugging, remote Linux/MacOS debugging, profiling, IPython, and web development with Django and other frameworks.



[Django](https://www.djangoproject.com/) is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.



[Flask](https://flask.palletsprojects.com/) is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. 

 

[Web2py](http://web2py.com/) is an open-source web application framework written in Python allowing allows web developers to program dynamic web content. One web2py instance can run multiple web sites using different databases.



[AWS Chalice](https://github.com/aws/chalice) is a framework for writing serverless apps in python. It allows you to quickly create and deploy applications that use AWS Lambda. 



[Tornado](https://www.tornadoweb.org/) is a Python web framework and asynchronous networking library. Tornado uses a non-blocking network I/O, which can scale to tens of thousands of open connections.



[HTTPie](https://github.com/httpie/httpie) is a command line HTTP client that makes CLI interaction with web services as easy as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. 



[Scrapy](https://scrapy.org/) is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing.



[Sentry](https://sentry.io/) is a service that helps you monitor and fix crashes in realtime. The server is in Python, but it contains a full API for sending events from any language, in any application.



[Pipenv](https://github.com/pypa/pipenv) is a tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world.



[Python Fire](https://github.com/google/python-fire) is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.



[Bottle](https://github.com/bottlepy/bottle) is a fast, simple and lightweight [WSGI](https://www.wsgi.org/) micro web-framework for Python. It is distributed as a single file module and has no dependencies other than the [Python Standard Library](https://docs.python.org/library/).



[CherryPy](https://cherrypy.org) is a minimalist Python object-oriented HTTP web framework.



[Sanic](https://github.com/huge-success/sanic) is a Python 3.6+ web server and web framework that's written to go fast. 



[Pyramid](https://trypyramid.com) is a small and fast open source Python web framework. It makes real-world web application development and deployment more fun and more productive.



[TurboGears](https://turbogears.org) is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. 



[Falcon](https://falconframework.org/) is a reliable, high-performance Python web framework for building large-scale app backends and microservices with support for MongoDB, Pluggable Applications and autogenerated Admin.



[Neural Network Intelligence(NNI)](https://github.com/microsoft/nni) is an open source AutoML toolkit for automate machine learning lifecycle, including [Feature Engineering](https://github.com/microsoft/nni/blob/master/docs/en_US/FeatureEngineering/Overview.md), [Neural Architecture Search](https://github.com/microsoft/nni/blob/master/docs/en_US/NAS/Overview.md), [Model Compression](https://github.com/microsoft/nni/blob/master/docs/en_US/Compressor/Overview.md) and [Hyperparameter Tuning](https://github.com/microsoft/nni/blob/master/docs/en_US/Tuner/BuiltinTuner.md).



[Dash](https://plotly.com/dash) is a popular Python framework for building ML & data science web apps for Python, R, Julia, and Jupyter.



[Luigi](https://github.com/spotify/luigi) is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built-in.



[Locust](https://github.com/locustio/locust) is an easy to use, scriptable and scalable performance testing tool. 



[spaCy](https://github.com/explosion/spaCy) is a library for advanced Natural Language Processing in Python and Cython. 



[NumPy](https://www.numpy.org/) is the fundamental package needed for scientific computing with Python.



[Pillow](https://python-pillow.org/) is a friendly PIL(Python Imaging Library) fork.



[IPython](https://ipython.org/) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers enhanced introspection, rich media, additional shell syntax, tab completion, and rich history.



[GraphLab Create](https://turi.com/) is a Python library, backed by a C++ engine, for quickly building large-scale, high-performance machine learning models.



[Pandas](https://pandas.pydata.org/) is a fast, powerful, and easy to use open source data structrures, data analysis and manipulation tool, built on top of the Python programming language.



[PuLP](https://coin-or.github.io/pulp/) is an Linear Programming modeler written in python. PuLP can generate LP files and call on use highly optimized solvers, GLPK, COIN CLP/CBC, CPLEX, and GUROBI, to solve these linear problems.



[Matplotlib](https://matplotlib.org/) is a 2D plotting library for creating static, animated, and interactive visualizations in Python. Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.



[Scikit-Learn](https://scikit-learn.org/stable/index.html) is a simple and efficient tool for data mining and data analysis. It is built on NumPy,SciPy, and mathplotlib.



## Contribute



- [x] If would you like to contribute to this guide simply make a [Pull Request](https://github.com/mikeroyal/Python-Guide/pulls).



## License



Distributed under the [Creative Commons Attribution 4.0 International (CC BY 4.0) Public License](https://creativecommons.org/licenses/by/4.0/).