Python - from None to AI
  • License
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  • References

Basics

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

Intermediate

  • 1. About
  • 2. String
  • 3. Syntax
  • 4. Star
  • 5. Enum
  • 6. Match
  • 7. Regex
  • 8. Datetime
  • 9. Generators
  • 10. Iterator
  • 11. Pathlib
  • 12. Logging
  • 13. Modules
  • 14. Locale
  • 15. Serialization
  • 16. Pickle
  • 17. TOML
  • 18. CSV
  • 19. JSON
  • 20. Typing
  • 21. Dataclass

Advanced

  • 1. About
  • 2. Syntax
  • 3. OOP Paradigm
  • 4. OOP Inheritance
  • 5. OOP Polymorphism
  • 6. OOP Encapsulation
  • 7. OOP Metaprogramming
  • 8. OOP Operator
  • 9. FP Paradigm
  • 10. FP Apply
  • 11. Decorators
  • 12. Async Paradigm
  • 13. Async AsyncIO

Concurrency

  • 1. About
  • 2. Multiprocessing
  • 3. Threading
  • 4. Async Paradigm
  • 5. Async AsyncIO

Performance

  • 1. About
  • 2. Introduction
    • 2.1. Introduction Faster CPython
    • 2.2. Introduction Hardware
    • 2.3. Optimization Compilers and Interpreters
    • 2.4. Optimization Disassembler
    • 2.5. Optimization Interpreter
    • 2.6. Optimization Transpiler
  • 3. Transpilation
  • 4. Tools
  • 5. Profiling
  • 6. Optimization
  • 7. Extensions

Testing

  • 1. About
  • 2. Introduction
  • 3. Random
  • 4. Syntax
  • 5. Doctest
  • 6. Unittest
  • 7. Recap

CI/CD

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

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. Introduction
  • 3. UML
  • 4. Creational
  • 5. Behavioral
  • 6. Structural
  • 7. Functional

Numpy

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

Pandas

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

Matplotlib

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

Stdlib

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

Network

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

webapp

  • 1. About
  • 2. HTTP
  • 3. REST
  • 4. Architecture
  • 5. Auth

Django

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

FastAPI

  • 1. About
  • 2. Introduction
  • 3. FastAPI
  • 4. Pydantic
  • 5. Database
  • 6. Auth
  • 7. DevOps
  • 8. 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
  • 2. Introduction

OOP

  • 1. Paradigm
  • 2. Python

Dragon

  • 1. English
  • 2. Polish
  • 3. ADR
Python - from None to AI
  • 1. About
  • 2.1. Introduction Faster CPython

2.1. Introduction Faster CPython

  • https://github.com/faster-cpython/ideas

  • Shannon M. (2025) Performance improvements in 3.14 and maybe 3.15 — Mark Shannon

  • Shannon M. (2023) Talks - Mark Shannon: How we are making CPython faster. Past, present and future.

  • Shannon M., van Rossum G. (2022) Making Python 5x FASTER with Guido van Rossum and Mark Shannon - Talk Python To Me Ep.339

  • Shannon M. (2022) How we are making Python 3.11 faster - presented by Mark Shannon

  • Shannon M. (2023) How we are making CPython faster. Past, present and future — Mark Shannon

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© Copyright 2026, Matt Harasymczuk <matt@python3.info>, last update: 2026-06-09.