Python - from None to AI
  • License
  • Install
  • Python Versions
  • Python History
  • Links
    • Video
    • Roadmap
    • RSS
    • Podcast
    • CI/CD
    • Trends
    • Survey
    • Experiments
    • Documentation
    • Python Development
    • History
    • Conferences
    • Speakers
    • Talks
    • Django
    • FastAPI
    • Async
    • Multiprocessing
    • Http
    • Database
    • Online Courses
    • Community
    • Testing
    • Books
    • Useful libs
    • Fun
    • Data Sets
  • References

Basics

  • 1. About
  • 2. Syntax
  • 3. Numeric
  • 4. Logic
  • 5. Strings
  • 6. Iterables
  • 7. Mappings
  • 8. Unpack
  • 9. Conditional
  • 10. While
  • 11. For
  • 12. Comprehensions
  • 13. Files
  • 14. Functions
  • 15. Exceptions
  • 16. OOP
  • 17. Recap

Intermediate

  • 1. About
  • 2. Syntax
  • 3. Star
  • 4. Match
  • 5. Encoding
  • 6. Regex
  • 7. Datetime
  • 8. Idiom
  • 9. Iterator
  • 10. Enum
  • 11. Pathlib
  • 12. Modules
  • 13. Logging
  • 14. Serialization
  • 15. Pickle
  • 16. TOML
  • 17. CSV
  • 18. JSON
  • 19. OOP

Advanced

  • 1. About
  • 2. Syntax
  • 3. Typing
  • 4. OOP Dataclass
  • 5. OOP Paradigm
  • 6. OOP Inheritance
  • 7. OOP Metaprogramming
  • 8. OOP Operator
  • 9. OOP Accessors
  • 10. FP Paradigm
  • 11. FP Apply
  • 12. FP Patterns
  • 13. Generators
  • 14. Async Paradigm
  • 15. Async AsyncIO

Performance

  • 1. About
  • 2. Multiprocessing
  • 3. Threading
  • 4. Optimization
  • 5. Case Study
  • 6. Extensions

Testing

  • 1. About
  • 2. Random
  • 3. Syntax
  • 4. Doctest
  • 5. Unittest

CI/CD

  • 1. DevTools
  • 2. Distribute
  • 3. Lint
  • 4. Quality
  • 5. Security
  • 6. Webdev

DevOps

  • 1. About
  • 2. Quality
  • 3. Tests
  • 4. Debugging

Database

  • 1. About
  • 2. Theory
  • 3. ORM
  • 4. Normalization
  • 5. NoSQL
  • 6. SQL
  • 7. SQLite3
  • 8. SQLAlchemy
  • 9. Case Study

Design Patterns

  • 1. About
  • 2. UML
  • 3. OOP
  • 4. Inheritance
  • 5. Abstract
  • 6. Decorators
  • 7. Creational
  • 8. Behavioral
  • 9. Structural

Numpy

  • 1. About
  • 2. Array
  • 3. Attributes
  • 4. Random
  • 5. Indexing
  • 6. Operations
  • 7. Methods
  • 8. Statistics
  • 9. Math
  • 10. Polynomial

Pandas

  • 1. About
  • 2. Read
  • 3. To
  • 4. Series
  • 5. DataFrame
  • 6. Date
  • 7. Case Study

Matplotlib

  • 1. About
  • 2. Figure
  • 3. Style
  • 4. Chart
  • 5. Case Study

Stdlib

  • 1. Modules
  • 2. Collections
  • 3. Math
  • 4. Locale
  • 5. XML
  • 6. Operating System
  • 7. String
  • 8. Builtin
  • 9. Type
  • 10. Loop
  • 11. TkInter

Network

  • 1. About
  • 2. Protocol
  • 3. Web
  • 4. Transport
  • 5. Case Study

Microservices

  • 1. About
  • 2. HTTP
  • 3. Microservices
  • 4. Auth

Django

  • 1. About
  • 2. Setup
  • 3. Settings
  • 4. Models
  • 5. Admin
  • 6. ORM
  • 7. Views
  • 8. Templates
  • 9. Templatetags
  • 10. Forms
  • 11. Manage
  • 12. Locale
  • 13. Middleware
  • 14. Utils
  • 15. Auth
  • 16. API
  • 17. Ninja
  • 18. Tests
  • 19. Apps
  • 20. Deploy

FastAPI

  • 1. About
  • 2. FastAPI
  • 3. Pydantic
  • 4. Database
  • 5. Auth
  • 6. DevOps
  • 7. Case Study

Data Science

  • 1. About
  • 2. Jupyter
  • 3. Python
  • 4. Visualization
  • 5. Scipy
  • 6. Geopandas

Machine Learning

  • 1. About
  • 2. Introduction
  • 3. Sklearn
  • 4. Model Quality
  • 5. Decision Trees
  • 6. Regressions
  • 7. K-Nearest Neighbors
  • 8. Bayes
  • 9. Support Vector Machines
  • 10. Clustering
  • 11. Neural Networks
  • 12. References
  • 13. Articles

Artificial Intelligence

  • 1. About

OOP

  • 1. Paradigm
  • 2. Python

Dragon

  • 1. English
  • 2. Polish
  • 3. ADR
Python - from None to AI
  • Links

Links

Video

  • Matt Harasymczuk's Webinars

  • PyVideo

  • InfoQ

  • Making Python 5x FASTER with Guido van Rossum and Mark Shannon

Roadmap

  • https://roadmap.sh/python

RSS

  • http://feeds.feedburner.com/PythonInsider

  • http://www.python.org/dev/peps/peps.rss

Podcast

  • https://podcasters.spotify.com/pod/show/corepy

  • https://patoarchitekci.io/

  • https://djangochat.com/

  • https://www.youtube.com/playlist?list=PLQ176FUIyIUbnCPB4WgLmTuv-Zc2juqa1

CI/CD

  • https://python3.info/devops/ci-cd/ecosystem.html#setup

  • https://github.com/sages-pl/src-python/blob/main/.solution/project.sh

  • https://www.youtube.com/watch?v=YnIfjzbfBEI

Trends

Programming Language:

  • Tiobe Index

  • PYPL

Technology:

  • Technology Radar

  • PatoArchitekci

  • InfoQ AI/ML/DS

Survey

Newest:

  • https://lp.jetbrains.com/python-developers-survey-2023/

  • https://lp.jetbrains.com/django-developer-survey-2022/

  • https://www.jetbrains.com/lp/devecosystem-2023/python/

  • https://www.jetbrains.com/lp/devecosystem-2023/

  • https://survey.stackoverflow.co/2024

Python Developers Survey (by Jetbrains and PSF):

  • https://lp.jetbrains.com/python-developers-survey-2023/

  • https://lp.jetbrains.com/python-developers-survey-2022/

  • https://lp.jetbrains.com/python-developers-survey-2021/

  • https://www.jetbrains.com/lp/python-developers-survey-2020/

  • https://www.jetbrains.com/lp/python-developers-survey-2019/

  • https://www.jetbrains.com/research/python-developers-survey-2018/

  • https://www.jetbrains.com/research/python-developers-survey-2017/

State of Developer Ecosystem for Python (by Jetbrains):

  • https://www.jetbrains.com/lp/devecosystem-2023/python/

  • https://www.jetbrains.com/lp/devecosystem-2022/python/

  • https://www.jetbrains.com/lp/devecosystem-2021/python/

  • https://www.jetbrains.com/lp/devecosystem-2020/python/

State of Developer Ecosystem for any Technology (by Jetbrains):

  • https://www.jetbrains.com/lp/devecosystem-2024/

  • https://www.jetbrains.com/lp/devecosystem-2023/

  • https://www.jetbrains.com/lp/devecosystem-2022/

  • https://www.jetbrains.com/lp/devecosystem-2021/

  • https://www.jetbrains.com/lp/devecosystem-2020/

StackOverflow Survey:

  • https://survey.stackoverflow.co/2024

  • https://survey.stackoverflow.co/2023

  • https://survey.stackoverflow.co/2022

  • https://insights.stackoverflow.com/survey

  • https://insights.stackoverflow.com/survey/2021

  • https://insights.stackoverflow.com/survey/2020

  • https://insights.stackoverflow.com/survey/2019

  • https://insights.stackoverflow.com/survey/2018

  • https://insights.stackoverflow.com/survey/2017

  • https://insights.stackoverflow.com/survey/2016

  • https://insights.stackoverflow.com/survey/2015

  • https://stackoverflow.blog/2014/02/2013-stack-overflow-user-survey-results/

  • https://stackoverflow.blog/2013/01/2012-stack-overflow-user-survey-results/

  • https://stackoverflow.blog/2012/02/survey-results/

  • https://stackoverflow.blog/2011/01/11/survey-says/

Django Survey:

  • https://lp.jetbrains.com/django-developer-survey-2023/

  • https://lp.jetbrains.com/django-developer-survey-2022/

  • https://lp.jetbrains.com/django-developer-survey-2021-486/

Web Frameworks:

  • https://insights.stackoverflow.com/survey/2021#section-most-loved-dreaded-and-wanted-web-frameworks

Experiments

  • https://blog.jetbrains.com/datalore/2020/12/17/we-downloaded-10-000-000-jupyter-notebooks-from-github-this-is-what-we-learned/

Documentation

  • Python Module Index

  • Python string formatting

  • TimeComplexity

  • Multiple APIs documentation

  • Tests

Python Development

  • Python Insider

  • Newest PEPs RSS

  • Python Releases

  • CPython compiler

  • Python core development

  • Index of Python Enhancement Proposals (PEPs)

  • Python Enhancement Proposals repository

  • News from the Python Software Foundation

  • Future of Python

History

  • http://python-history.blogspot.com/

  • https://www.wefearchange.org/2010/06/import-this-and-zen-of-python.html

Conferences

  • World Python Events Calendar

  • Polish Python Events Calendar

Python:

  • EuroPython 2019

  • EuroPython 2020

  • Kiwi PyCon

  • PyCon

  • PyCon AU 2021

  • PyCon AU

  • PyCon PL 2016

  • PyCon US 2021

  • PyCon US 2020

  • PyGotham 2019

  • PyGotham

  • PyOhio 2019

Data Science / Machine Learning:

  • EuroSciPy 2019

  • PyData Berlin 2019

  • PyData Warsaw 2019

  • SciPy 2020

Django:

  • DjangoCon

Speakers

Łukasz Langa:

  • https://pyvideo.org/speaker/lukasz-langa.html

  • https://www.youtube.com/results?search_query=Łukasz+Langa

  • https://www.youtube.com/watch?v=fOdCxum-qLA

Pablo Galindo:

  • https://pyvideo.org/speaker/pablo-galindo.html

Raymond Hettinger:

  • https://pyvideo.org/speaker/raymond-hettinger.html

  • https://www.youtube.com/results?search_query=Raymond+Hettinger

Dustin Ingram:

  • https://pyvideo.org/speaker/dustin-ingram.html

Guido van Rossum:

  • https://pyvideo.org/speaker/guido-van-rossum.html

Larry Hastings:

  • https://pyvideo.org/speaker/larry-hastings.html

Russell Keith-Magee:

  • https://pyvideo.org/speaker/russell-keith-magee.html

Andrew Godwin:

  • https://pyvideo.org/speaker/andrew-godwin.html

Talks

  • Łukasz Langa - import asyncio: Learn Python's AsyncIO #1 - The Async Ecosystem

  • Łukasz Langa - Life Is Better Painted Black, or: How to Stop Worrying and Embrace Auto-Formatting. PyCon 2019

  • Raymond Hettinger - Beyond PEP 8 -- Best practices for beautiful intelligible code - PyCon 2015

  • Raymond Hettinger - Transforming Code Into Beautiful, Idiomatic Python

  • Raymond Hettinger - Modern Dictionaries

  • Raymond Hettinger - Keynote on Concurrency

  • Raymond Hettinger - Thinking about Concurrency

Django

Class-Based Views:

  • http://ccbv.co.uk

Conferences:

  • DjangoCon US: https://pyvideo.org/events/djangocon-us-2019.html

  • DjangoCon EU: https://pyvideo.org/events/djangocon-europe-2019.html

  • Russell Keith-Magee:

    • https://pyvideo.org/speaker/russell-keith-magee.html

    • https://www.youtube.com/results?search_query=Russel+Keith-Magee

  • Andrew Godwin:

    • https://pyvideo.org/speaker/andrew-godwin.html

    • https://www.youtube.com/results?search_query=andrew+goodwin+django+async

FastAPI

  • https://www.youtube.com/watch?v=0sOvCWFmrtA

  • https://fastapi.tiangolo.com/tutorial/security/oauth2-jwt/

  • https://jwt.io/

Async

  • https://www.youtube.com/watch?v=Xbl7XjFYsN4&list=PLhNSoGM2ik6SIkVGXWBwerucXjgP1rHmB

  • https://www.youtube.com/results?search_query=langa+asyncio

  • https://docs.djangoproject.com/en/dev/topics/db/queries/#async-queries

  • https://www.youtube.com/results?search_query=andrew+goodwin+async+django

  • https://www.youtube.com/watch?v=F19R_M4Nay4

  • https://www.youtube.com/watch?v=Pe3b9bdRtiE

  • https://www.youtube.com/watch?v=19Uh_PA_8Rc

  • https://www.youtube.com/watch?v=oMHrDy62kgE

Multiprocessing

  • https://dask.org/

Http

  • https://httpbin.org

  • https://12factor.net/

  • https://docs.djangoproject.com/en/dev/howto/deployment/checklist/

Database

  • https://prometheus.io/docs/introduction/overview/

  • https://www.influxdata.com/

Online Courses

Python:

  • Codecademy: http://www.codecademy.com/en/tracks/python

  • University of Michigan: https://www.coursera.org/learn/python

  • University of Toronto: https://www.coursera.org/learn/learn-to-program

  • University of Michigan: https://www.coursera.org/learn/python-databases

  • Rice University: https://www.coursera.org/learn/python-programming

  • OReilly: http://shop.oreilly.com/product/110000448.do

Machine Learning and Data Science:

  • https://www.youtube.com/user/sentdex

  • https://www.youtube.com/watch?v=OGxgnH8y2NM&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v

  • https://www.youtube.com/watch?v=wQ8BIBpya2k&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN

  • https://www.youtube.com/watch?v=nLw1RNvfElg&list=PLQVvvaa0QuDfSfqQuee6K8opKtZsh7sA9

  • https://www.youtube.com/watch?v=Wo5dMEP_BbI&list=PLQVvvaa0QuDcjD5BAw2DxE6OF2tius3V3

  • https://www.youtube.com/watch?v=mA5nwGoRAOo (+ cała playlista)

  • (UC San Diego) https://www.edx.org/course/python-for-data-science

  • (UC San Diego) https://www.edx.org/course/statistics-and-probability-in-data-science-using-python

  • (MIT) https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-11

  • (University of Michigan) https://www.coursera.org/learn/python-data

  • (University of Michigan) https://www.coursera.org/learn/python-data-analysis

  • (deeplearning.ai) https://www.coursera.org/learn/neural-networks-deep-learning

  • (deeplearning.ai) https://www.coursera.org/specializations/deep-learning

  • (University of Michigan) https://www.coursera.org/learn/python-machine-learning

  • (University of Michigan) https://www.coursera.org/learn/python-text-mining

  • (IBM) https://www.coursera.org/learn/python-for-applied-data-science

  • (IBM) https://www.coursera.org/learn/data-analysis-with-python

Community

  • https://www.reddit.com/r/learnpython

  • https://www.reddit.com/r/python

  • https://www.reddit.com/r/learnprogramming

  • https://www.reddit.com/r/programming

Testing

  • https://martinfowler.com/articles/microservice-testing/#testing-component-in-process-diagram

Books

Algorithms:

  • https://www.amazon.com/Introduction-Algorithms-Edition-Thomas-Cormen/dp/0262033844/

  • https://www.amazon.com/Algorithms-4th-Edition-Robert-Sedgewick/dp/032157351X/

Databases:

  • https://www.amazon.com/Database-Design-Mere-Mortals-Hands-/dp/0321884493/

  • https://www.amazon.com/SQL-Antipatterns-Programming-Pragmatic-Programmers/dp/1934356557/

  • https://www.amazon.com/C.-J.-Date/e/B000AQ6OJA/

Software Engineering Practises:

  • https://www.amazon.com/Pragmatic-Programmer-Journeyman-Master/dp/020161622X/

  • https://www.amazon.com/Code-Complete-Practical-Handbook-Construction/dp/0735619670/

  • https://www.amazon.com/The-Mythical-Man-Month-Engineering-Anniversary/dp/0201835959/

Design pattern:

  • Design Patterns: Elements of Reusable Object-Oriented Software

  • https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612/

  • https://helion.pl/ksiazki/wzorce-projektowe-elementy-oprogramowania-obiektowego-wielokrotnego-uzytku-erich-gamma-richard-helm-ralph-johnson-john-vli,wzoelv.htm

Refactoring:

  • Working effectively with legacy code - Michael Feathers

  • https://www.amazon.com/Working-Effectively-Legacy-Michael-Feathers/dp/0131177052

Clean Code by Uncle Bob:

  • https://helion.pl/ksiazki/czysty-kod-podrecznik-dobrego-programisty-robert-c-martin,czykov.htm

  • http://www.amazon.co.uk/Clean-Code-Handbook-Software-Craftsmanship/dp/0132350882/

Python:

  • https://www.amazon.com/Learning-Python-Edition-Mark-Lutz/dp/1449355730/

  • https://www.amazon.com/Python-Programming-Introduction-Computer-Science/dp/1590282418/

  • http://inventwithpython.com/

  • https://www.amazon.com/Python-Cookbook-David-Beazley/dp/1449340377/

  • https://www.jeffknupp.com/writing-idiomatic-python-ebook/

  • https://www.amazon.com/Python-Practice-Concurrency-Libraries-Developers/dp/0321905636/

  • http://learnpythonthehardway.org/book/

  • http://anandology.com/python-practice-book/index.html

  • https://www.amazon.com/Python-3-Object-Oriented-Programming/dp/1849511268/

  • http://shop.oreilly.com/product/0636920032519.do

Useful libs

  • FastAPI

  • SQL Model

  • Pydantic

Fun

  • PEP8 song

  • Silicon Valley: Tabs vs. Spaces

Data Sets

  • https://www.kaggle.com/datasets

  • https://www.airlines.org/dataset/

  • https://www.kaggle.com/datasets/mczielinski/bitcoin-historical-data

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© Copyright 2025, Matt Harasymczuk <matt@python3.info>, last update: 2025-01-14.