awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
fluentpython avatar

fluentpython/example-codeArchived

0
View on GitHub↗
bit.ly/fluentpy↗

Example Code

This project is a collection of practical scripts and reference guides that demonstrate advanced Python language features and idioms. It provides code implementations for mastering concepts such as concurrency, metaprogramming, and data structure design.

The repository includes examples of the Python object model, covering custom attribute access, descriptor protocols, and special method overrides. It also features implementations of design patterns that utilize first-class functions and decorators to reduce object-oriented boilerplate.

The codebase covers a broad range of capabilities, including asynchronous programming with event loops and futures, the creation of custom sequences and generators, and the use of abstract base classes for interface enforcement. It further demonstrates resource management through context managers and the handling of text and byte sequences.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Features

  • Python Code Examples - A collection of practical scripts and patterns demonstrating advanced Python language features and idioms.
  • Python Programming Guides - Provides a comprehensive guide to advanced Python features, including asynchronous programming and concurrency.
  • Language Data Model Overrides - Python implements special methods to change how objects behave and integrate seamlessly with core language features.
  • Context Managers - Provides implementations of context managers to ensure consistent setup and teardown of external resources.
  • Pythonic Data Structures - Demonstrates the design of custom sequences and generators to optimize data access in Python.
  • Attribute Descriptors - Implements descriptor protocols to intercept and manage object attribute access and assignment.
  • Special Method Overrides - Python implements special methods to ensure custom objects behave like built-in types during common operations.
  • Class Inheritance - Python defines classes that derive attributes and methods from parent classes to reuse logic across a hierarchy.
  • Metaprogramming Patterns - Implements metaprogramming patterns using decorators, descriptors, and metaclasses to modify class behavior.
  • Context Managers - Python ensures proper setup and teardown of external resources through context managers to prevent memory leaks.
  • Dynamic Attribute Management - Python controls how attributes are accessed and assigned to objects by intercepting lookup and assignment operations.
  • Runtime Class Modifications - Demonstrates the use of metaclasses to intercept class creation and automate object construction.
  • First-Class Functions - Python treats functions as first-class citizens, allowing them to be passed as arguments and returned from other functions.
  • Function Decorators - Python wraps functions to extend their capabilities and encapsulate state without modifying the original source code.
  • Coroutines - Manages concurrent workflows using coroutines that can be paused and resumed by a scheduler.
  • Metaprogramming - Python manipulates class behavior and creation logic using metaprogramming techniques to automate object construction.
  • Object Oriented Class Design - Demonstrates advanced object-oriented design using the descriptor protocol, abstract base classes, and operator overloading.
  • Operator Overloading - Python defines custom behavior for standard operators to allow objects to interact using intuitive mathematical or logical syntax.
  • Abstract Base Classes - Demonstrates the use of abstract base classes to enforce consistent APIs across derived class implementations.
  • Special Method Overloads - Demonstrates dunder methods to integrate custom objects with built-in language operators and behaviors.
  • Concurrent Task Execution - Executes multiple I/O-bound operations concurrently using an event loop to maximize throughput.
  • Python - Examples of using first-class functions and decorators to replace traditional object-oriented boilerplate.
  • Non-Blocking Event Loops - Implements non-blocking event loops to coordinate concurrent I/O tasks and network requests.
  • Object Model Implementations - Code demonstrating custom attribute access, descriptor protocols, and special method overrides for Python objects.
  • Network I/O Examples - Implementations of non-blocking network requests and concurrent task management using event loops and futures.
  • Custom Collection Implementations - Provides implementations of dictionaries and sets using standard patterns for efficient data management.
  • Future-Based Result Handling - Implements parallel result retrieval from multiple functions using Python futures.
  • Iterable Class Implementation - Defines the iteration protocol for custom classes using generator methods to produce values on demand.
  • Generative Iterators - Implements generative iterators that produce sequence values on demand for efficient memory usage.
  • Sequence Slicing - Implements specialized indexing and slicing behaviors for custom Python sequences.
  • Unicode and Byte String Distinction - Manages the distinction and conversion between Unicode text strings and raw byte sequences.
  • Functional Design Patterns - Python uses first-class functions to replace traditional object-oriented patterns and reduce boilerplate in the code structure.
  • Context Managers - Handling the lifecycle of external resources and managing the transition between Unicode text and raw byte sequences.
5,569 stars·2,156 forks·Python·MIT·25 views

Star history

Star history chart for fluentpython/example-codeStar history chart for fluentpython/example-code

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does fluentpython/example-code do?

This project is a collection of practical scripts and reference guides that demonstrate advanced Python language features and idioms. It provides code implementations for mastering concepts such as concurrency, metaprogramming, and data structure design.

What are the main features of fluentpython/example-code?

The main features of fluentpython/example-code are: Python Code Examples, Python Programming Guides, Language Data Model Overrides, Context Managers, Pythonic Data Structures, Attribute Descriptors, Special Method Overrides, Class Inheritance.

Which projects share features with fluentpython/example-code?

Projects with overlapping indexed features include: crazyguitar/pysheeet — pysheeet is a technical reference library providing a curated collection of code snippets and implementation patterns… realpython/materials — This project is a comprehensive collection of Python programming education materials, including tutorials, exercises,… jackzhenguo/python-small-examples — This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of… krishnaik06/complete-python-bootcamp — This is a comprehensive Python programming course and technical curriculum designed to take users from foundational… trekhleb/learn-python — This project is an educational resource designed for learning the Python programming language. It serves as a tutorial… micheles/decorator — The project is a Python metaprogramming toolkit designed to build signature-preserving function decorators, generic…

Projects sharing features with Example Code

These projects share indexed features with Example Code. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • crazyguitar/pysheeetcrazyguitar avatar

    crazyguitar/pysheeet

    8,150View on GitHub↗

    pysheeet is a technical reference library providing a curated collection of code snippets and implementation patterns for advanced Python development, system integration, and high-performance computing. It serves as a comprehensive guide for implementing low-level network programming, native C extensions, and asynchronous and concurrent programming. The project provides specialized frameworks for the development and deployment of large language models, including tools for distributed GPU inference and high-performance serving. It also includes detailed patterns for high-performance computing

    Python
    View on GitHub↗8,150
  • realpython/materialsrealpython avatar

    realpython/materials

    5,173View on GitHub↗

    This project is a comprehensive collection of Python programming education materials, including tutorials, exercises, and curated code samples. It serves as a learning curriculum and software engineering toolkit, utilizing Jupyter Notebooks to combine executable code with descriptive educational text. The repository provides practical implementation guides for building large language model applications, such as retrieval-augmented generation systems, stateful AI agents, and machine learning workflows. It distinguishes itself by offering a structured approach to agentic coding workflows, cover

    Jupyter Notebook
    View on GitHub↗5,173
  • jackzhenguo/python-small-examplesjackzhenguo avatar

    jackzhenguo/python-small-examples

    8,132View on GitHub↗

    This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of scripts and snippets designed to demonstrate a wide range of programming tasks, from basic syntax to advanced implementation patterns. The repository focuses on several core domains, including the implementation of concurrency and multithreading examples, data analysis snippets for cleaning and manipulating tabular data, and various data visualization examples. It also covers automation scripts for file system management and a variety of general programming patterns. Additional

    Pythondata-sciencemachine-learningpython
    View on GitHub↗8,132
  • krishnaik06/complete-python-bootcampkrishnaik06 avatar

    krishnaik06/Complete-Python-Bootcamp

    2,550View on GitHub↗

    This is a comprehensive Python programming course and technical curriculum designed to take users from foundational syntax to advanced development patterns. It serves as a multi-disciplinary educational suite covering programming fundamentals, object-oriented design, and data analysis. The project provides specialized guides on professional development techniques, including the use of decorators, generators for memory management, and dunder-method operator overloading. It also includes instructional material on executing parallel tasks through concurrency and multiprocessing to reduce executi

    Jupyter Notebook
    View on GitHub↗2,550
  • Compare all 30 related projects→