- Basics / Learning
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- Python Fundamentals
- Lists, Tuples, Dictionaries, Conditionals, Loops, etc...
- Data Structures & Algorithms
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- Introduction to Python
- Learn Python
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- Online Python REPLs & Editors
- Local machine: Interacting with Python
- Python by Chris Albon - topics covered: Basics • Data Wrangling • Data Visualization • Web Scraping • Testing • Logging • Other
- Regex resources by Chris Albon
- WTF Python repo
- Introduction to Python
- Introduction of Python Programming
- Writing your first program in Python (2019) - Brown University
- Numpy QUICK REFERENCE
- Python to Numpy
- 100 Exercises ✅ Numpy ✅
- Scientific Python
- Neural Networks Matrices exploration - Under the Hood Mathematical Operations
- Understand the use of *args and **kwargs
- Here are some great Python Resources to learn #DataScience and #MachineLearning
- 👉 🐍Machine Learning Projects with Python 🐍👈
- Python NumPy for Artificial Intelligence : 14. Array Comparison | Logical Operations
- The Ultimate NumPy Tutorial for Data Science Beginners
- Can machine learning help build a better stock portfolio?
- How to Develop Voting Ensembles With Python
- How to Develop Super Learner Ensembles in Python
- Python Machine Learning Mini-Course
- 5 free books for learning Python for DS
- 7 advanced tricks in pandas for data science
- Sqlite saving numpy serialised into the database
See Python: Best practices and Python: Testing under Courses
- Python Cheatsheet
- PySheee: Python Cheatsheet
- 7+ Python Cheat Sheets for Beginners and Experts
- Python for Data Science
- 30 seconds of python
- Comprehensive Python cheatsheet
- mccabe - check McCabe complexity
- mypy - a static type checker that aims to combine the benefits of duck typing and static typing, frequently used with MonkeyType
- py-find-injection - find SQL injection vulnerabilities in Python code
- pycodestyle - (formerly
pep8) check Python code against some of the style conventions in PEP 8 - pydocstyle - check compliance with Python docstring conventions
- pyflakes - check Python source files for errors
- pylint - looks for programming errors, helps enforcing a coding standard and sniffs for some code smells. It additionally includes
pyreverse(an UML diagram generator) andsymilar(a similarities checker). - pyre-check - A fast, scalable type checker for large Python codebases
- pyright - Static type checker for Python, created to address gaps in existing tools like mypy.
- pyroma - rate how well a Python project complies with the best practices of the Python packaging ecosystem, and list issues that could be improved
- PyT - Python Taint - A static analysis tool for detecting security vulnerabilities in Python web applications.
- pytype - A static type analyzer for Python code.
- Review of Python Static Analysis Tools
- Python Static Analysis Tools
- PANDAS 👉 Reading and Writing Data 👈
- See awesome-static-analysis for Python
- ciocheck - linter, formatter and test suite helper. As a linter, it is a wrapper around
pep8,pydocstyle,flake8, andpylint. - flake8 - a wrapper around
pyflakes,pycodestyleandmccabe - multilint - a wrapper around
flake8,isortandmodernize - prospector - a wrapper around
pylint,pep8,mccabeand others
- [The first real-time semantic code analysis - powered by AI](https://semmle.com/ - A code analysis platform for finding zero-days and automating variant analysis.](deepcode.ai) | GitHub
- Python Zero to Hero - Ep.12 - Python linting and auto-formating
- Nine simple steps for better-looking python code
- For Python projects
- For Data Science projects
- For Reproducible Data Science projects
- For Data Driven Journalism projects
- Rich is a Python library for writing rich text with color and style to the terminal and for displaying advanced content such as tables, markdown, and syntax highlighted code!
- Python for MicroControllers
- streamlit.io - the fastest way to build custom ML tools | Docs | GitHub | Blog | Community
- Flask alternatives
- anvil.works - Full stack web apps with nothing but Python
- Assembly - A Pythonic Object-Oriented Web Framework built on Flask
- A curated list of awesome Python frameworks, libraries, software and resources
- Explanation of most popular Data Science Library (in Python)
- 50 most popular Python libraries and frameworks used in data science
- Python for 9 Purposes: The graphics miss Scikit-Learn and of course "Pandas"
- Free python tools
- Tips N Tricks: 3 Simple and Easy Ways to Cache Functions in Python
- HPy
- 🗽 𝙂𝙧𝙖𝙙𝙞𝙤 𝙥𝙮𝙩𝙝𝙤𝙣 𝙡𝙞𝙗𝙧𝙖𝙧𝙮 : 𝙃𝙖𝙨𝙨𝙡𝙚-𝙁𝙧𝙚𝙚 𝙎𝙝𝙖𝙧𝙞𝙣𝙜 𝙖𝙣𝙙 𝙏𝙚𝙨𝙩𝙞𝙣𝙜 𝙤𝙛 𝙈𝙇 𝙈𝙤𝙙𝙚𝙡𝙨 𝙞𝙣 𝙩𝙝𝙚 𝙒𝙞𝙡𝙙
- The Python scientific stack, compiled to WebAssembly. GitHub
- A simple video that explains in a very simple way how you can use joblib to speed up almost any function
- PEP 8 -- Style Guide for Python Code
- Python Best Practices and Tips by Toptal Developers
- Python Best Practices for More Pythonic Code
- Python String Formatting Best Practices
- The Best of the Best Practices (BOBP) Guide for Python
- Dmitry Mugtasimov's Python software development practices
- SO: Python coding standards/best practices
- Python Best Practices: 5 Tips For Better Code - Airbrake Blog
- Python tutorial: Best practices and common mistakes to avoid
- Common mistakes beginnners make in python
- Six steps to more professional data science code notebook on Kaggle by Rachael Tateman | Video: 6 Steps for More Professional Data Science Code | Kaggle | Import scripts into notebook kernels | Kaggle Live Coding: Making code modular | Kaggle | Documentation on Python modules | DocStrings | Don't Repeat Yourself (DRY) | PEP 8 | Joy of Functional programming for Data Science | Method Chaining in Python using pyjanitor | pyjanitor docs | Code reviewing Data Science work | Python built-in method: assert | Code Smells | Kaggle Coffee Chat: Joel Grus | Kaggle: software engineering best practices | Scripting-your-data-validation notebook: Automating Data Pipelines | Dashboarding with Notebooks: Day 5 | Kaggle Scripts | Regular Expressions
- Packages & Libraries: Cerberus module | missingno package | python-magic module | Python Flashtext | Flashtext github | Forum post embeddings + clustering
- Jason Gormans' Python Code Craft series:
- "Stop writing classes"
- How to package Python apps with BeeWare Briefcase
- Python Developer's Guide » Running & Writing Tests
- Hitchhickers Guide to Python: Testing Your Code
- SO: Writing unit tests in Python: How do I start?
- Testing Python Applications with Pytest
- An Introduction to Mocking in Python
- PyCharm: Testing Your First Python Application
- unittest — Unit testing framework
- Python Zero to Hero - Ep.10 - More Pytest and Mock
- Python Zero to Hero - Ep.7 - Unit testing with Pytest
- Python Zero to Hero - Ep.11 - Python property-based testing
- Backtest Trading Strategies with Pandas — Vectorized Backtesting
- PyCharm: Refactoring code
- PyCharm refactoring tip
- PyCharm Refactoring Tutorial
- Learning Python with PyCharm: Refactoring
- What refactoring tools do you use for Python?
- Bowler: Safe code refactoring for modern Python projects - Bowler is a refactoring tool for manipulating Python at the syntax tree level. It enables safe, large scale code modifications while guaranteeing that the resulting code compiles and runs.
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