DEV Community: Python Trending Weekly

Python Trending Weekly #175 (with Issue 125 full text): AI Writes 610K Lines of Lean Proofs for CPython

Python Trending Weekly — Sat, 14 Nov 2026 14:56:21 +0000

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Shared 12 articles, 12 open-source projects, 1 audio/video, 2 hot discussions

Here are the title summaries for this issue:

🦄Articles & Tutorials

① PEP 852: Asynchronous functions in the C API

② Adopting Python 3.15's lazy imports: a 4× faster CLI, and where they didn't help

③ Catch the import. Name the culprit. Keep threads free: Introducing gilguard

④ Adapting CPython for yk

⑤ Muru: import once, fork many

⑥ Portable Python scripts with dependencies

⑦ mizu: thread-speed parallel R and Python over shared memory

⑧ Building an Agent Sandbox from Scratch in Python

⑨ Michigan prof creates Python-like Jac language for AI agents

⑩ What makes uv slow?

⑪ Django in Space with Loes Crama

⑫ Formalizing CPython

🐿️Projects & Resources

① paperclip: The open-source app everyone uses to manage agents at work

② LangGraph: Build resilient agents

③ agent-desktop: Computer use CLI for AI agents

④ vllm: A high-throughput and memory-efficient inference and serving engine for LLMs

⑤ indra: Fast CPU OCR

⑥ artcraft: An Intentional Crafting Engine for Artists, Designers, and Filmmakers

⑦ sqlfluff: The SQL Linter for Humans

⑧ linkding-cn: A self-hosted bookmark manager with highlights and read-later

⑨ Mailu: Mail server as Docker images

⑩ ioe: One-Stop Retail Inventory Solution

⑪ android-ad-cleaner: Turn off ads on Chinese Android phones without root

⑫ cn-math-taxonomy: Chinese K-12 Math Knowledge Graph and Prerequisite Diagnostics

🐢Podcasts & Videos

① DjangoCon Europe 2026

🥂Discussions & Questions

① Google Adopts Pyrefly for Faster, More Accurate Python Type Checking

② PEP 840: Name Resolution in Class Namespaces

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📖 Full text of a past issue, now free

Paid issues of this newsletter become free to read one year after publication,
so every new issue comes with one past issue's full text.

Below is the issue published one year ago (Issue 125, 2025-11-01) —
much of it is still worth reading today.

🦄Articles & Tutorials

1、The PSF has withdrawn a $1.5 million proposal to US government grant program

The Python Software Foundation proactively withdrew a $1.5 million grant application to the U.S. National Science Foundation because the grant terms required the PSF to commit to not carrying out any projects advancing diversity, equity, and inclusion, but the PSF board unanimously decided to uphold its values and refused to betray its mission of supporting a diverse Python community.

2、CPython Core Dev Sprint 2025 at Arm Cambridge: The biggest one yet

Arm's Cambridge headquarters hosted the largest-ever CPython core developer sprint, with 48 developers gathering for in-depth technical exchange. The event covered core topics including the JIT compiler, performance optimization, package management, and language design, and advanced important progress such as free-threading and documentation improvements.

3、Why is Python's OrderedDict ordered?

Why can OrderedDict remember insertion order while ordinary dictionaries cannot? The author dives into the internal implementation of the OrderedDict type and reveals the root cause of its ordering: adding a doubly linked list on top of a dictionary to maintain order information, combined with an index dictionary for fast lookup. The author also shares interesting details, such as cleverly resolving "circular references" through weakref, and the design of using object() as a default value.

4、Exploring & Improving the Thread Safety of NumPy's Test Suite

The author deeply analyzes the thread-safety issues in the NumPy test suite during parallel execution. By introducing the pytest-run-parallel plugin, the author identified and fixed key defects such as global state pollution and random number seed conflicts, increasing test execution speed several times over.

5、Reliable Django Signals

Django signals seem simple but hide traps—when signal handling fails, it causes the entire transaction to roll back. The author reveals the fundamental flaws of the signal mechanism and proposes a practical solution of replacing synchronous signals with background task queues such as Celery, effectively avoiding signal exceptions affecting the main business flow.

6、uv is the best thing to happen to the Python ecosystem in a decade

uv rewrote the entire toolchain in Rust, and it is astonishingly fast from version installation to dependency resolution. The author compares in detail the performance differences between uv and traditional tools, showing how it turns complex environment configuration into a one-command task.

7、Understanding Docker Internals: Building a Container Runtime in Python

The author reproduces the core mechanisms of containers with less than 200 lines of Python code, from Linux namespaces to cgroups resource limits, with detailed code examples for each step.

8、PEP 686 – Make UTF-8 mode default

Python 3.15, currently in development, has implemented PEP-686 and will enable UTF-8 mode by default, unifying the encoding of files, standard input/output, and pipes as UTF-8, solving cross-platform encoding inconsistency issues and improving interoperability with other languages.

9、The Terrible Technical Architecture of my First Startup

How does technical debt accumulate in startups? The author candidly reviews his own "dark history"—from a simple Django + React architecture to an over-engineered microservices hell pursued for the sake of "scalability." When should simplicity be upheld, and when is complexity needed?

10、Python 3.14 - What didn't make the headlines

The author shares underappreciated practical improvements in Python 3.14: the PDB debugger supports remote debugging and better breakpoint strategies, asyncio simplifies event loop management, argparse enhances help information and error prompts, and multiprocessing switches to a safer forkserver strategy on Linux.

11、Helion: A High-Level DSL for Performant and Portable ML Kernels

An advanced domain-specific language introduced by PyTorch that compiles PyTorch-like syntax into optimized Triton code. Through an auto-tuning engine and implicit search space, it lets developers focus on algorithm logic rather than hardware details, achieving performance portability across hardware architectures.

12、Caching: The Most Elegant Innovation in Computing

An exquisite interactive caching tutorial that demonstrates caching principles through visual animations, from CPU multi-level caches to database caching strategies, using dynamic charts to illustrate core concepts such as hit rate changes, temporal locality, and spatial locality, making abstract caching mechanisms intuitive and easy to understand.

🐿️Projects & Resources

1、surf: Personal AI Notebooks

An AI notebook tool that integrates files and web pages directly into the thinking process, supporting multimedia resource management, intelligent note generation, @mentions, web search integration, interactive app development, and more. Built with Svelte, TypeScript, and Rust, it supports cross-platform operation and local data storage. (star 2.3K)

2、quark-auto-save: Quark Cloud Drive Auto-Save

An all-in-one tool for Quark cloud drive check-in, automatic transfer, name organization, push notifications, and media library refresh, supporting shared link subdirectories, intelligent file filtering, regex filename organization, multi-task management, Emby media library integration, and more. It offers Docker deployment and a WebUI configuration interface, supports multi-account management and plugin extensions, and can work with SmartStrm and Emby to achieve automatic episode updates. (star 2.1K)

3、AI-Trader: Can AI Beat the Market?

An experimental platform where five AI agents trade fully autonomously in the Nasdaq 100 stock market, supporting a multi-model arena, zero-human-intervention decision-making, real-time performance analysis, historical replay, and more. Based on an MCP toolchain architecture, it integrates Jina search to obtain market intelligence, provides complete trading records and profit analysis, and explores AI's autonomous decision-making capabilities in financial markets. (star 7.9K)

4、httptap: HTTP Request Analysis Tool

A powerful CLI tool that breaks down HTTP requests into stages such as DNS, TCP connection, TLS handshake, server wait, and transfer, and presents results as waterfall charts, compact summaries, or metric output. It supports IPv4/IPv6 identification, TLS certificate analysis, multiple output modes, JSON export, proxy support, and more. Built in Python with no system dependencies, it is suitable for interactive troubleshooting, regression analysis, and performance benchmark recording.

5、kanchi: A realtime celery task monitoring and management system

A real-time Celery task monitoring and management system with a friendly user interface. It supports WebSocket real-time monitoring, task filtering and search, retry tracking, orphan detection, daily statistics, worker health monitoring, and more. It offers quick deployment via Docker Compose, supports basic authentication and OAuth login, is compatible with RabbitMQ and Redis brokers, and can replace Flower as a more modern Celery monitoring solution.

6、IsaacSim: NVIDIA Isaac Sim for AI-driven robots

An open-source AI-driven robot simulation platform from NVIDIA, built on Omniverse. It supports GPU-accelerated physics simulation, RTX sensor rendering, import of multiple robot formats, reinforcement learning training, ROS integration, synthetic data generation, and more. It provides the Isaac Lab framework for robot learning, supports digital twin simulation, and offers complete infrastructure for every stage of robot development. (star 1.8K)

7、scikit-opt: Swarm Intelligence in Python

A Python swarm intelligence algorithm library that integrates genetic algorithms, particle swarm optimization, simulated annealing, ant colony optimization, immune algorithms, artificial fish swarm algorithms, differential evolution, and other heuristic optimization algorithms. It supports user-defined functions, GPU computing, multiple acceleration strategies (vectorization, multithreading, multiprocessing, caching), constrained optimization, TSP problem solving, and more. It provides rich examples and visualization tools, suitable for various complex optimization problems. (star 6.2K)

8、BettaFish: Multi-Agent Public Opinion Analysis Assistant

A multi-AI-agent public opinion analysis system developed from scratch that analyzes millions of comments from 30+ mainstream social media platforms at home and abroad through conversational interaction. It features six major advantages including AI-driven monitoring, a composite analysis engine, multimodal capabilities, an agent forum collaboration mechanism, and public-private data fusion, helping users break out of information cocoons and predict public opinion trends. (star 2.1K)

9、moon-dev-ai-agents: autonomous ai agents for trading in python

A collection of autonomous AI agents designed specifically for algorithmic trading, including backtesting research, live trading, market analysis, content creation, and other agents. It supports multi-model consensus decision-making, parallel backtesting, risk management, whale monitoring, sentiment analysis, funding rate arbitrage, and more. It integrates multiple trading platforms such as HyperLiquid and Solana, providing a complete automated solution from strategy research to live trading. (star 1.9K)

10、wove: Beautiful Python async

A library that improves the Python asynchronous programming experience, offering a more intuitive user experience than asyncio and supporting top-down code declaration, implicit parallel execution, mixing sync and async, automatic task scheduling, dependency graph construction, zero boilerplate, and more. Built on the pure Python standard library with no external dependencies and compatible with free-threading mode, it can be easily integrated into any Python project to achieve efficient concurrent processing.

11、agent-framework: A framework for building, orchestrating and deploying AI agents

An open-source multilingual AI agent development framework from Microsoft, supporting both Python and .NET implementations. It provides a complete solution from simple chat agents to complex multi-agent workflows, with advanced features such as graphical workflow orchestration, streaming, checkpoints, human-in-the-loop, and time travel. It integrates the DevUI interactive development interface and OpenTelemetry observability. (star 4.5K)

12、ViMax: Agentic Video Generation

A multi-agent video creation framework that combines director, screenwriter, producer, and video generator in one, supporting an end-to-end automated process from idea to finished film, including script writing, storyboard design, character creation, and scene consistency maintenance. It offers multiple creation modes such as idea-to-video, novel adaptation, script generation, and personal customization, solving core issues in traditional video production such as character consistency, scene coherence, and production efficiency.

Python Trending Weekly #174 (with Issue 124 full text): CPython Experimental JIT to Be Removed; PEP 836 Withdrawn

Python Trending Weekly — Thu, 12 Nov 2026 05:09:40 +0000

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Shared 12 articles, 12 open-source projects, 2 hot discussions

Here are the title summaries for this issue:

🦄Articles & Tutorials

① CPython to remove experimental JIT

② The state of Python profiling tools in 2026

③ Why DuckDB 2.0 is faster

④ UUIDv7 doesn't have the properties you think it does

⑤ Build a coding agent in 306 lines of Python

⑥ Orchestrating disposable browsers with Python

⑦ Production practices for caching in Django at scale

⑧ Storing Django static and media files on Cloudflare R2

⑨ From loops to vectorization: 7 key mindsets for speeding up NumPy

⑩ pyinfra: server automation with Python code

⑪ A 3D game built entirely by AI: the full production process revealed

⑫ PyScript enters maintenance mode: what's left of Python in the browser

🐿️Projects & Resources

① taste-skill: making coding agents settle on an art direction first

② mcode-stack: the MiniMax team's AI coding workflow and skill set

③ BMAD-METHOD: an AI-driven agile development methodology

④ artemis: a natural-language-driven agent for Android automation

⑤ ego-lite: handing an already-logged-in browser to an AI agent

⑥ agent-zero: giving an agent a Linux computer

⑦ Hy-Memory: a multi-scenario memory library for agents

⑧ jeff: a 0.8B small model for fast decisions with local LLMs

⑨ KittenTTS: an open-source speech synthesis model that runs on CPU

⑩ Open-Source-Face-Recognition-SDK: local offline face recognition

⑪ TalkLikeYou-Streaming-RealTime-Demo: real-time digital human generation in the browser

⑫ deepopen-3d-webs: generating explorable 3D scenes from a single image

🥂Discussions & Questions

① PEP 845: leading-dot value patterns

② PEP 851 proposes adding discard() to list

Cut through the noise with our premium subscription at $4.99/month. Get hand-picked, cutting-edge Python content delivered weekly. Join 350+ professionals who trust us to filter the best from 400+ sources for technical vision expansion and career development. Subscribe at: Patreon

After subscribing, you can view the full text of Issue 174 for free: https://www.patreon.com/PythonCat666/posts/python-trending-175077008

📖 Full text of a past issue, now free

Paid issues of this newsletter become free to read one year after publication,
so every new issue comes with one past issue's full text.

Below is the issue published one year ago (Issue 124, 2025-10-25) —
much of it is still worth reading today.

Issue 124 shared 12 articles, 12 open-source projects, 2 audio/videos.

🦄Articles & Tutorials

1、Beyond the AI hype: Guido van Rossum on Python philosophy, simplicity, and the future of programming

Guido van Rossum interview: emphasizes that code still requires human review; Python's "humanist" philosophy makes it easy for LLMs to understand; holds a rational view on GIL removal, believing that big-company demands are making Python more complex; recommends type hints only for code over 10,000 lines, keeping Python beginner-friendly.

2、The no-GIL future of Python web services

Benchmarks FastAPI and Flask on the Python 3.14 no-GIL build. The author finds the no-GIL version's performance loss dropped from 35% to 5-10%, with significantly reduced memory usage. In I/O-bound scenarios the no-GIL build slightly outperforms the standard build, bringing true multithreaded concurrency to Python web services and potentially reducing reliance on multiprocess architectures.

3、Goodbye GIL: exploring Python 3.14's no-GIL mode

A deep benchmark report shared by the author at PyCon JP 2025. Comparing the Python 3.14 standard build with the no-GIL build, it finds about 15% performance loss for single-threaded code, but significant gains for multithreaded CPU-bound tasks. It also covers how to set up no-GIL mode, performance behavior, and practical use cases.

4、Lazy imports: making Python start up 3x faster

For the explicit lazy import feature proposed in PEP 810, the author tested the pypistats CLI tool and found that lazy imports cut startup time from 104ms to 36ms, nearly a 3x speedup. This is especially beneficial for command-line tools, test suites, and applications with large dependency graphs, significantly reducing startup time and memory usage.

5、Python lazy import techniques you can use today

Introduces practical techniques for implementing lazy imports in existing Python versions by moving import statements inside functions to defer module loading. The article demonstrates several approaches, including using importlib.import_module() and diagnosing slow imports with python -X importtime.

6、Diskcache: more than just a cache

An in-depth look at diskcache, a SQLite-based local caching library for Python. It offers microsecond-level key-value storage plus advanced features like transactions, tags, locking, and queues. A sharding mechanism enables multiprocess concurrent writes, and it includes built-in thundering-herd protection and function decorators, making it a near drop-in replacement for lightweight Redis use cases.

7、Lessons from using Postgres as a task queue

The author shares practical experience using PostgreSQL as a task queue, achieving atomic locking via FOR UPDATE SKIP LOCKED and avoiding extra infrastructure setup and complex retry mechanisms. Compared with traditional message queues, this approach reduces system complexity, offers better observability, and makes it easy to add retries, delayed execution, and more.

8、Why performance matters in Python development

Starting from Python interpreter characteristics and GIL limitations, the article analyzes common performance pitfalls in detail, including unnecessary loops, string concatenation, and misuse of data structures. It emphasizes that performance optimization affects not only user experience and cloud costs but also directly impacts system scalability and developer efficiency.

9、Async Django: a solution in search of a problem?

The author questions the practical value of Django's async features. Although the Django team spent six years developing async support, a 2024 survey shows only 14% of developers use async views. The article notes that async Django adds framework complexity and creates a dual API, while traditional background task solutions (such as Celery) remain the best choice for resolving performance bottlenecks.

10、The Django bulk_update memory problem

While updating hundreds of thousands of database records, the author discovered a memory trap in Django bulk_update: despite setting the batch_size parameter, Django still prepares all batches of UPDATE statements in advance, causing memory to balloon to 4.8GB and trigger SIGTERM. The solution is to manually implement a batching loop, reducing memory usage to just 62MB.

11、An empirical evaluation of property-based testing in Python

An OOPSLA 2025 paper provides the first systematic evaluation of property-based testing in Python. The study finds that property-based testing excels at finding bugs, especially for boundary conditions and exceptional inputs. Compared with traditional unit tests, property-based testing automatically generates large numbers of test cases, significantly improving code coverage and bug detection.

12、From Python to Kotlin: a migration worth trying

The article analyzes the advantages of migrating from Python to Kotlin. Although the two languages have similar syntax, Kotlin offers static typing, immutability, and a stronger concurrency model. Benchmarks show Python is 10-100x slower than Java, while Kotlin inherits the JVM's high performance; its type safety and modern language features can significantly boost developer efficiency.

🐿️Projects & Resources

1、deepwiki-open: AI-driven codebase documentation generator

Automatically generates beautiful interactive documentation for GitHub, GitLab, or BitBucket code repositories, using AI to analyze code structure and produce comprehensive docs and visual diagrams. Supports private repositories, Mermaid diagram generation, and RAG-based AI Q&A. (11.5K stars)

2、tidal-dl-ng: multithreaded TIDAL music downloader

A powerful TIDAL music downloader supporting multithreaded and chunked downloads, capable of downloading music and videos up to HiRes Lossless / TIDAL MAX 24-bit 192 kHz quality, with Dolby Atmos support and both CLI and GUI. (1.4K stars)

3、hexstrike-ai: AI-driven cybersecurity automation platform

An advanced MCP server that lets AI agents autonomously run 150+ cybersecurity tools for penetration testing, vulnerability discovery, and security research. Uses a multi-agent architecture with an intelligent decision engine, real-time visualization interface, and vulnerability intelligence analysis. (4K stars)

4、maltrail: malicious traffic detection system

Identifies malicious network activity using public blacklists and threat intelligence. Supports detecting threat indicators such as domains, URLs, and IP addresses, integrates dozens of threat intelligence sources, and uses heuristics to discover unknown threats, with real-time monitoring and detailed reporting. (7.6K stars)

5、hyperflask: full-stack web development framework

A full-stack development framework built on Flask that pre-selects the entire tech stack and integrates file-based routing, SQL ORM, deep htmx integration, and more. Supports mixing multiple frontend technologies, enabling indie developers and small teams to quickly build and deploy web apps.

6、modshim: Python package enhancement tool

Override and customize Python module functionality without modifying source code. By creating "shim" modules that combine original code with enhancements, it uses AST rewriting to ensure consistency and avoid the global pollution issues of monkey-patching.

7、django-keel: versatile Django project template

A production-ready Django project template designed around 12-Factor App principles, supporting Django 5.2 and Python 3.12+. Offers optional features like REST Framework, GraphQL, HTMX+Tailwind, and Celery, and generates customized projects through interactive configuration.

8、buttonpad: cross-platform button grid GUI toolkit

A cross-platform Python GUI toolkit designed for button interfaces, built on Tkinter. It uses CSV-style layout strings to quickly create grid interfaces, supports callbacks, tooltips, and hotkey mapping, and includes built-in demos like a calculator and a 2048 game.

9、django-bolt: high-performance Django API framework

A high-performance Rust-based Django API framework achieving 60k+ RPS throughput. It uses Actix Web to handle HTTP requests and bridges Python and Rust via PyO3. Fully compatible with the Django ORM and existing packages, and deployable directly without gunicorn.

10、burla: large-scale Python distributed computing platform

An open-source Python distributed computing platform that scales code to 10,000 CPUs or GPUs with a single function. It supports a local development experience, automatically syncs local packages to the cluster, and includes a built-in web platform for monitoring long-running tasks.

11、klavis: AI agent tool integration platform

An MCP integration platform that lets AI agents reliably use a wide range of tools at scale. It offers 100+ prebuilt integrations and OAuth authentication, uses progressive discovery to avoid tool overload, and supports cloud hosting and self-deployment. (5.3K stars)

12、computer_use_ootb: out-of-the-box desktop GUI agent solution

An out-of-the-box desktop GUI agent solution supporting an API mode (Claude 3.5 Computer Use) and a local mode (ShowUI, UI-TARS). No Docker required; supports both Windows and macOS, with a friendly Gradio-based interface and support for multiple monitors, any resolution, and remote control. Local mode costs 30-200x less than Claude Computer Use, and the computer can be controlled remotely via a mobile browser. (1.8K stars)

🐢Podcasts & Videos

1、Armin Ronacher interview: Python, Go, Rust, TypeScript, and AI

An interview with Flask creator Armin Ronacher on The Pragmatic Engineer Podcast, sharing insights on programming language choice, the impact of AI tools, and error handling. He believes Rust, while excellent, isn't suited to early-stage startups, that the Python 2 to 3 migration was more challenging than expected, and that AI tools are changing the need for a unified codebase. He also discusses why different programming languages still matter and the downsides of agentic programming.

2、EuroPython 2025 video collection (44 videos)

Python Trending Weekly #112: Welcoming the New Generation of AI-Era Programmers

Python Trending Weekly — Sat, 26 Jul 2025 13:38:08 +0000

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full issue：https://www.patreon.com/posts/python-trending-135001605

Here are the title summaries for this issue:

🦄Articles & Tutorials

① Unpacking in Comprehensions

② Using reduce() for Multithreaded Aggregation

③ PEP 799 – A dedicated profilers package for organizing Python profiling tools

④ metap: A Meta-Programming Layer for Python

⑤ Checking Out CPython 3.14's remote debugging protocol

⑥ How to Avoid N+1 Queries in Django Python

⑦ Announcing Toad - a universal UI for agentic coding in the terminal

⑧ The Step-by-Step Guide to Python Packaging Tools 2025

⑨ Welcoming The Next Generation of Programmers

⑩ What "Parse, don't validate" means in Python?

⑪ Python: fix BrokenPipeError when piping output to other commands

⑫ My favorite use-case for AI is writing logs

⑬ How to Think About Time in Programming

🐿️Projects & Resources

① Qwen3-Coder: Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team, Alibaba Cloud.

② awesome-claude-code: A curated list of awesome commands, files, and workflows for Claude Code

③ open_deep_research: Open Deep Research

④ PhotoshopAPI: A modern and performant C++20 read/write parser of Photoshop Files

⑤ LanceDB: Developer-friendly, embedded retrieval engine for multimodal AI

⑥ MediaManager: A modern selfhosted media management system for your media library

⑦ fstrings.wtf: Python F-String Quiz

⑧ complexipy: An extremely fast Python library to calculate the cognitive complexity of Python files, written in Rust.

⑨ ART: Agent Reinforcement Trainer

⑩ NeuralAgent: The AI Agent That Lives On Your Desktop And Uses It Like You Do!

⑪ SkyReels-V2: Infinite-length Film Generative model

⑫ gitingest: Turn any Git repository into a prompt-friendly text ingest for LLMs

After subscribing, you can view the full text of Issue 112 for free: https://www.patreon.com/posts/python-trending-135001605

Python Trending Weekly #110: JIT Compiler Two-Year Retrospective, AI Agent Tools Explosion

Python Trending Weekly — Sat, 12 Jul 2025 09:55:53 +0000

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Full article https://www.patreon.com/posts/python-trending-133956776

Here are the title summaries for this issue:

🦄Articles & Tutorials

① Reflections on 2 years of CPython's JIT Compiler: The good, the bad, the ugly

② Types are Transforming Python

③ Solving Wordle with uv's dependency resolver

④ Developing a Real-time Dashboard with FastAPI, MongoDB, and WebSockets

⑤ Escaping Contravariance Hell

⑥ LangFlow Tutorial: Building Production-Ready AI Applications With Visual Workflows

⑦ Scaling recommendations service at OLX

⑧ Getting extensions to work with free-threaded Python

⑨ Augmented Coding: Beyond the Vibes

⑩ Context Engineering for Agents

⑪ PyTorch is dead. Long live JAX.

⑫ operators, not users and programmers

🐿️Projects & Resources

① trae-agent: LLM-based agent for general purpose software engineering tasks

② xai-sdk-python: The official Python SDK for the xAI API

③ desto: web-interface and cli to manage python and shell scripts in tmux sessions

④ devin.cursorrules: Magic to turn Cursor/Windsurf as 90% of Devin

⑤ LingChat: GPT chat with emotional expressions

⑥ rowboat: AI-powered multi-agent builder

⑦ agent-factory: A tool for generating Python code for agentic workflows

⑧ throttled-py: High-performance Python rate limiting library

⑨ tubearchivist: Your self hosted YouTube media server

⑩ mlx-audio: A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework

⑪ sloppy-xml-py: A Python library to parse malformed XML

⑫ Python-Scripts: A curated list of python scripts for automating your tasks

After subscribing, you can view the full text of Issue 110 for free: https://www.patreon.com/posts/python-trending-133956776

Python Trending Weekly #108：Will AI Replace Junior Developers?

Python Trending Weekly — Sat, 28 Jun 2025 13:46:35 +0000

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This week we're sharing 12 articles, 12 open source projects, 2 podcasts & videos

Here are the title summaries for this issue:

🦄Articles & Tutorials

① My First Open Source AI Generated Library

② Fun with uv and PEP 723

③ Will AI Replace Junior Developers? I Asked Experts at Pycon US

④ Fixing Python Properties

⑤ Python can run Mojo now

⑥ Django: Introducing inline-snapshot-django

⑦ Cut Django Database Latency by 50-70ms With Native Connection Pooling

⑧ The Waiting Time Paradox, or, Why Is My Bus Always Late?

⑨ Kalman and Bayesian Filters in Python

⑩ Switching from virtualenvwrapper to direnv, Starship, and uv

⑪ How to think about agent frameworks

⑫ Lessons From 9 More Years of Tricky Bugs

🐿️Projects & Resources

① gemini-cli: An open-source AI agent that brings the power of Gemini directly into your terminal

② nxtscape: Nxtscape is an open-source agentic browser

③ augmentoolkit: Create Custom LLMs

④ BitNet: Official inference framework for 1-bit LLMs

⑤ local-deep-research: AI-powered assistant for deep, iterative research

⑥ pyfuze: Package Python projects into executables

⑦ nbdev: Create delightful software with Jupyter Notebooks

⑧ fastapi_mcp: Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!

⑨ Awesome-ML-SYS-Tutorial: My learning notes/codes for ML SYS

⑩ machine-learning-visualized: ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy

⑪ code-graph-rag: Search Monorepos and get relevant answers

⑫ FeedMe: AI-powered RSS reader, deployable to GitHub Pages or with Docker

🐢Podcasts & Videos

① Watch the DjangoCon Europe 2025 talks

② Add Features Without Touching Source Code!

After subscribing, you can view the full text of Issue 108 for free: https://www.patreon.com/posts/python-trending-132603667

Python Trending Weekly #107: GIL-Free Python Gets Official Approval

Python Trending Weekly — Sat, 21 Jun 2025 09:46:12 +0000

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This week we're sharing 12 articles, 12 open source projects, 2 podcasts & videos, and 2 hot topics.

Here are the title summaries for this issue:

🦄Articles & Tutorials

① Design Patterns You Should Unlearn in Python-Part1

② The Python Language Summit 2025

③ State of Free-Threaded Python

④ An introduction to Python for R users

⑤ How global variables work in Python bytecode

⑥ Are Python Dictionaries Ordered Data Structures?

⑦ Understanding and Coding the KV Cache in LLMs from Scratch

⑧ 从 browser-use 出发，品 Agent 实现

⑨ PEP 795 – Deep Immutability in Python

⑩ The Missing Manual for Signals: State Management for Python Developers

⑪ Create your customized running plan: A step-by-step guide using Python, Elasticsearch, and Agno

⑫ The fastest way to detect a vowel in a string

🐿️Projects & Resources

① MiniMax-M1: the world's first open-weight, large-scale hybrid-attention reasoning model

② A functional standard library for Python

③ TurboDRF: The dead simple Django REST Framework API generator with role-based permissions

④ WinUp: A ridiculously Pythonic and powerful framework for building beautiful desktop applications

⑤ Framefox: Python web framework that makes development enjoyable

⑥ miniDiffusion: A reimplementation of Stable Diffusion 3.5 in pure PyTorch

⑦ pyleak: Detect leaked asyncio tasks, threads, and event loop blocking with stack trace in Python

⑧ Shiny for Python

⑨ AI design agent, local alternative for Lovart

⑩ FlareSolverr: Proxy server to bypass Cloudflare protection

⑪ ii-agent: a new open-source framework to build and deploy intelligent agents

⑫ ChinaTextbook: Complete Collection of Chinese K-12 and University PDF Textbooks

🐢Podcasts & Videos

① My PyCon Talk This Year: Discussing My First Completed PEP

② Program Your Own Computer in Python

🥂Discussions & Questions

① PEP 779: Criteria for supported status for free-threaded Python

② Any convenient and user-friendly Python GUI frameworks?

After subscribing, you can view the full text of Issue 107 for free: https://www.patreon.com/posts/python-weekly-131958235

Python Trending Weekly #106: PEP 734 officially accepted, the era of multiple interpreters is coming

Python Trending Weekly — Sat, 14 Jun 2025 07:27:15 +0000

Stay ahead of the curve: Subscribe now for weekly insights that keep you at the forefront of Python innovation!

This week we're featuring 12 articles and 15 open source projects.

Here are the title summaries for this issue:

🦄Articles & Tutorials

① PEP 734: Multiple Interpreters in the Stdlib

② Why pandas feels clunky when coming from R

③ Faster Python: Concurrency in async/await and threading

④ A Deep Dive into CrewAI and Agentic Design

⑤ MonsterUI: Bringing Beautiful UI to FastHTML

⑥ Dewu's Community Data Generation Service Integrates with MCP

⑦ Data Validation Libraries for Polars (2025 Edition)

⑧ Exploring AI Integration with Adobe Photoshop, InDesign and Premiere Pro

⑨ Beyond htmx: building modern Django apps with Alpine AJAX

⑩ How I'm using Django, JavaScript modules and importmaps together

⑪ Field Notes From Shipping Real Code With Claude

⑫ Fixing FastAPI Throughput Without Going Fully Async

🐿️Projects & Resources

① Archon: AI Agent Builder

② excel-mcp-server: A Model Context Protocol server for Excel file manipulation

③ crudadmin: Modern admin interface for FastAPI with built-in authentication, event tracking, and security features

④ py-pglite: PGlite wrapper in Python for testing

⑤ openai-agents-python: A lightweight, powerful framework for multi-agent workflows

⑥ ai-manus: AI Manus is a general-purpose AI Agent system

⑦ WebAgent: WebWalker [ACL2025] & WebDancer [Preprint]

⑧ poethepoet: A task runner that works well with poetry or uv

⑨ ragbits: Building blocks for rapid development of GenAI applications

⑩ WorldGen: Generate Any 3D Scene in Seconds

⑪ docext: An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit

⑫ Orpheus-TTS: Towards Human-Sounding Speech

⑬ VACE: All-in-One Video Creation and Editing

⑭ langmem: LangMem helps agents learn and adapt from their interactions over time

⑮ terminator: Automate desktop apps like a browser

After subscribing, you can view the full text of Issue 106 for free: https://www.patreon.com/posts/python-trending-131437980

⚡ Supercharge Your Python Learning with These 9 Weekly Newsletters

Python Trending Weekly — Sun, 08 Jun 2025 05:22:12 +0000

Hey Python enthusiasts! 🐍 Ready to discover some game-changing resources that'll supercharge your development journey?

I've been reading Python newsletters for years, and I wanted to share the ones that have actually been worth my time. After testing 9 different newsletters, I've got some thoughts on which ones deliver real value and which ones... well, let's just say your inbox deserves better.

Here's my honest take on each one, ranked from the newsletters I actually look forward to reading down to the ones I'd probably unsubscribe from. If you're tired of sifting through mediocre content, this might help you find something worthwhile.

1. Python Trending Weekly

This newsletter started in May 2023 and combines AI filtering with human curation. Each issue includes 12 articles/tutorials and 12 projects, sourced from 400+ Python-related sites. They also cover podcasts, videos, and community discussions.

What I like: Instead of just dropping links, they actually write descriptions and include screenshots. They highlight projects with 1000+ stars, which saves time when you're looking for mature tools.

The standout feature? Every 30 issues gets compiled into comprehensive e-book collections with seasonal reviews and curated compilations. These aren't just archives - they're well-organized reference materials that you can actually use for learning and project discovery.

It's a paid newsletter, but the current pricing seems reasonable for what you get.

Recommendation: ⭐⭐⭐⭐⭐

Subscribe: https://patreon.com/PythonCat666

Website：https://weekly.pythoncat.top

2. Python Weekly

The OG Python newsletter with 700+ issues since 2012. Each week brings 11-15 articles/tutorials/talks and 9-12 projects, plus Python event listings.

The quality is inconsistent - some article descriptions are thoughtful, others are just copy-pasted excerpts. Project descriptions usually come straight from GitHub repos without much editorial input. But honestly? The consistency over 12+ years is impressive.

Respect to the creator for building something sustainable. They also run newsletters for other programming topics and entrepreneurship.

Recommendation: ⭐⭐⭐⭐⭐

Subscribe: https://www.pythonweekly.com

3. Pycoder's Weekly

Running since 2012 with 680+ issues, 171K subscribers, and 122K Twitter followers. Each issue has about 15 articles and 6 projects, plus Python events. There are usually 2-3 ads, but they're not too intrusive.

What I appreciate: They actually put effort into descriptions, include source credits, and mention where content comes from. They also feature reader submissions that you won't see elsewhere.

The Real Python connection means you'll sometimes get exclusive content from their educational platform.

Recommendation: ⭐⭐⭐⭐

Subscribe: https://pycoders.com

4. Python Hub Weekly Digest

Been around since 2012, created by a developer from Ukraine. Each issue has about 11 articles and 8 projects.

I like their curation approach - they mix recent popular content with older stuff that other newsletters missed. Most articles get descriptions (usually excerpts), though they don't separate videos from articles, which can be confusing.

The design is clean and ad-free, which is refreshing. They've built a solid following with 145K Twitter followers.

Recommendation: ⭐⭐⭐⭐

Subscribe: https://pythonhub.dev/digest

5. Django News

Started in December 2019, focusing exclusively on Django: news, articles, projects, events, and jobs. With 4.2K subscribers, it's smaller than the general Python newsletters, but that's the point.

Interesting business model - they're transparent about ad pricing ($250 per spot, two spots per issue) and let you book online. Smart way to monetize a niche audience.

Recommendation: ⭐⭐⭐

Subscribe: https://django-news.com

6. Python on Microcontrollers Newsletter

For Python + hardware folks, though the dark theme layout with lots of images can feel visually cluttered.

Despite the name, it's mostly about single-board computers like Raspberry Pi rather than actual microcontrollers. If you're into IoT or hardware projects, this covers a growing niche that most Python newsletters ignore.

Recommendation: ⭐⭐⭐

Subscribe: https://www.adafruitdaily.com

7. This Week in Python

Started in March 2022 with a simple format: exactly 5 articles and 5 projects per issue. Used to have descriptions, now it's just titles and links. Content is decent but overlaps with other newsletters. No ads.

The creator seems genuinely enthusiastic and sometimes writes original content. Shows that you don't need fancy formatting to run a newsletter - just share what you're reading.

Recommendation: ⭐⭐

Subscribe: https://bas.codes

8. Python weekly newsletter

Quantity over quality here - just titles and links with comment counts, no descriptions. Warning: they sometimes include actual snake articles mixed with Python programming content. The author runs about 20 tech newsletters with automated aggregation.

Content comes from scraping Hacker News, Reddit, Twitter, and Mastodon based on engagement metrics. Quality varies wildly.

Upside: lots of content (25-30 items) with minimal ads.

Recommendation: ⭐⭐

Subscribe: https://discu.eu/weekly/python

9. Awesome Python Weekly

Running since 2016 with 10 articles and 5 projects per issue, reaching 19K subscribers. Just titles and links, no descriptions.

Why I'd skip it: They mix actual snake articles with Python programming content, which is confusing. Project links redirect through their site before going to GitHub, which is annoying. Plus, 3 ads per issue makes it the most ad-heavy newsletter here.

Credit where it's due - running 20 newsletters is quite the operation, even if the quality suffers.

Recommendation: ⭐

Subscribe: https://python.libhunt.com/newsletter

That's my take on 9 Python newsletters, from excellent to questionable. 📊

Newsletters can be a good way to stay updated without spending hours browsing. The variety of approaches is interesting - some focus on automation and volume, others prioritize quality and stay ad-free, and a few are experimenting with paid models.

If you're looking to subscribe, I'd suggest picking 2-3 that match how you like to consume content. No need to overwhelm your inbox.

I'll probably write about more Python resources in the future. If this was useful, feel free to share it with other developers who might be interested.

Python Trending Weekly #105: Dify Breaks 100K Stars, Full-Stack Development Best Practices for 2025

Python Trending Weekly — Sat, 07 Jun 2025 14:56:18 +0000

Stay ahead of the curve: Subscribe now for weekly insights that keep you at the forefront of Python innovation!

This week we're featuring 12 articles and 12 open source projects.

Here are the title summaries for this issue:

🦄Articles & Tutorials

① Create a React + Flask Project in 2025

② How I'm bundling frontend assets using Django and rspack these days

③ Python: sharing common tests in unittest

④ Local Speed, Smooth Deploys: Heroku Adds Support for uv

⑤ Ways to Optimize Your Code in Python

⑥ Import Name Metadata

⑦ How to split up a Django monolith without using microservices

⑧ How local variables work in Python bytecode

⑨ Globally Disabling Foreign Keys in Django

⑩ I made a worse search engine than Elasticsearch

⑪ Developing a PDF Chat App with Pinata, OpenAI and Streamlit

⑫ A dinosaur learns poetry

🐿️Projects & Resources

① dify: Dify is an open-source LLM app development platform

② sequor: Sequor is a SQL-centric platform for building API integrations

③ bilive: Extremely fast live recording, automatic slicing, rendering, uploading and Integrating MLLMs

④ local-ai-packaged: Run all your local AI together in one package - Ollama, Supabase, n8n, Open WebUI, and more!

⑤ NLWeb: Natural Language Web

⑥ OpenThinkIMG: OpenThinkIMG is an end-to-end open-source framework that empowers LVLMs to think with images

⑦ pageql: Embed SQL directly into HTML

⑧ AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework

⑨ LMCache: Redis for LLMs

⑩ davia: The easiest way to build apps from your Python code

⑪ ovld: Advanced multiple dispatch for Python functions

⑫ arc-export: Export pinned Arc Browser tabs for importing bookmarks into other browsers

After subscribing, you can view the full text of Issue 105 for free: https://www.patreon.com/posts/python-trending-130927753

Python 潮流周刊#85：让 AI 帮你写出更好的代码

Python Trending Weekly — Sat, 11 Jan 2025 02:53:19 +0000

本周刊由 Python猫出品，精心筛选国内外的 250+ 信息源，为你挑选最值得分享的文章、教程、开源项目、软件工具、播客和视频、热门话题等内容。愿景：帮助所有读者精进 Python 技术，并增长职业和副业的收入。

分享了 12 篇文章，12 个开源项目，1 则音视频，全文 2300 字。

以下是本期摘要：

🦄文章&教程

① 如果一直要求 LLM “写出更好的代码”，它们能写出更好的代码吗？

② Python 并发：线程、进程与 asyncio 详解

③ 为什么在 Python 中 hash(-1) == hash(-2)？

④ 在浏览器中轻松运行 Python

⑤ PEP-769：给 'attrgetter' 和 'itemgetter' 添加 'default' 关键字参数

⑥ Pipx 的三个使用技巧

⑦ Django vs. FastAPI，真诚的比较

⑧ Python 弱引用与垃圾回收器

⑨ AI-text-to-video-model-from-scratch：从零开发一个微型的文本到视频模型

⑩ Python 在 DevOps 领域的应用

⑪ 用机器学习开发一个贫血检测系统

⑫ Google 发布 AI Agent（智能体）技术白皮书

🐿️项目&资源

① AI-reads-books-page-by-page: AI 逐页从 PDF 提取知识与生成摘要

② ai-book-writer: 用 AI 代理编写整本书

③ web-ui：在浏览器中运行 AI 代理

④ F5-TTS：通过流匹配伪造流畅且忠实语音的童话讲述者

⑤ AutoMouser：基于鼠标运动来生成浏览器自动化代码

⑥ paper_to_podcast：将论文转化为三人对谈的播客

⑦ xhs_ai_publisher：小红书 AI 运营助手（内容生成和自动发布）

⑧ ipychat：IPython 的 AI 扩展，使其像 Cursor 一样

⑨ magnetron：从零开始开发的 PyTorch

⑩ dendrite-python-sdk：用于开发网络 AI 代理的工具

⑪ 热门 Django 项目的导航网站

⑫ zh-style-guide：中文技术文档的写作风格指南

🐢播客&视频

① AI 制作的英文播客：Python潮流周刊第一季精选合集

周刊实行付费订阅制，年费 128 元，平均每天不到 4 毛钱，但绝对是一笔有眼光的投资。花钱学习知识，花钱提升自己，欢迎订阅这个你绝对不会后悔的专栏：https://xiaobot.net/p/python_weekly

订阅后，可免费查看第 85 期周刊的全文：https://www.xiaobot.net/post/900bb219-7e37-47c6-b795-ef7061d18a51

Python 潮流周刊第 2 季完结了，分享几项总结：https://pythoncat.top/posts/2024-07-14-iweekly

周刊前30期的免费合集，含精美电子书（EPUB/PDF）：https://pythoncat.top/posts/2023-12-11-weekly

万字浓缩版，Python 潮流周刊第 1 季的 800 个链接！：https://xiaobot.net/post/78c3d645-86fa-4bd8-8eac-46fb192a339e

微信关注 Python猫：https://img.pythoncat.top/python_cat.jpg

Python 潮流周刊#58：最快运行原型的语言（摘要）

Python Trending Weekly — Sat, 29 Jun 2024 14:30:26 +0000

本期周刊分享了 12 篇文章，12 个开源项目，赠书 5 本，全文 2100 字。

以下是本期摘要：

🦄文章&教程

① 最快运行原型的语言

② PEP-2026 提议 Python 采用日历版本号

③ 优化 Python 的路由和调度：一个新的开源求解器 Timefold

④ 深入了解 Python 的集合数据结构

⑤ 使用 weakref 介绍 Python 的弱引用

⑥ 这就是软件开发现在的样子

⑦ 在命令行终端使用大语言模型

⑧ 如何将 Python 包发布到 PyPI？

⑨ 基本 Python 项目设置

⑩ 用 Make 提升 Python 开发者体验

⑪ Notebooks 是代码中的麦当劳

⑫ 花了 6 个月时间开发 LiveAPI 代理，我得到的 10 个经验教训

🐿️项目&资源

① Your-Journey-To-Fluent-Python：你的流畅的 Python 之旅

② llm：从命令行访问大语言模型

③ lmdocs：使用 LLM 生成 Python 项目的帮助文档

④ make-python-devex：使用 Make、Homebrew、pyenv、poetry 等工具的示例

⑤ vulture：查找无效的 Python 代码

⑥ CleanMyWechat: 自动删除 PC 端微信缓存数据

⑦ wxauto：Windows 版微信自动化，可发送/接收消息，简单微信机器人

⑧ youdaonote-pull：一键导出/备份有道云笔记的所有笔记

⑨ reladiff：跨数据库对大型数据集作高性能比对

⑩ hrms：开源人力资源和薪资管理软件

⑪ burr：构建能够做出决策的应用（聊天机器人、代理、仿真等）

⑫ thread：AI 驱动的 Jupyter Notebook

目前周刊实行付费订阅制，年费 128 元，平均每天不到 4 毛钱，但绝对是一笔有眼光的投资。花钱学习知识，花钱提升自己，欢迎订阅这个：你绝对不会后悔的专栏

订阅后，可免费查看第 58 期周刊的全文

PS.本周刊前30期的合集永久免费，另外，付费期数将在其 50 期后免费开放，例如第 58 期将在第 108 期时免费，敬请留意。

Python Trending Weekly #42 (2024-03-16)

Python Trending Weekly — Sat, 16 Mar 2024 08:31:21 +0000

Welcome to the Python Trending Weekly, a weekly newsletter about Python, AI and general programming techniques, with the majority links in English and a small portion in Chinese.

The original version of the weekly was written in Chinese. What you are reading here is mostly translated by LLMs.

Substack Channel : Click to subscribe

🦄Articles & Tutorials

Why Our Company Still Uses Python for Project Development?

This article gave me a sense of "industry secrets you don't know." Small companies are still sticking with Python 2.7 + Django 1.8, and they are supporting hundreds of millions of dollars in transactions each year. The author also shared several projects, and my feeling is: Maybe you don't need to consider "which language is better" too much. Just choose the one you are familiar with and focus on business implementation.

Should Python Strings Use Single or Double Quotes?

Python strings allow both single and double quotes, and even triple quotes. This flexibility is great, but it's also a source of conflict for standards pedants. This article shares an interesting story about it, recommended reading!

Understanding Context Manager and Its Syntactic Sugar

Why do we need context managers? What problems do they solve? The article also introduces the context manager protocol, the with syntax sugar, implementing context managers with contextlib, and four practical use cases.

Python deque tutorial

A deque is a double-ended queue data structure in the collections module, similar to a list but optimized for fast addition and removal from either end. This tutorial covers its basic usage and some advanced use cases.

Python Generic function and class types

Python performs type checking at runtime and emphasizes the behavior of objects rather than their types, so it doesn't put much emphasis on "generics" that focus on type safety. However, Python does support generics, and this article introduces how to implement generic functions and generic classes using the typing module.

Gevent in practice: Common pitfalls to keep in mind

Gevent is a high-performance networking library built on top of greenlet, a lightweight coroutine implementation. This article introduces common pitfalls of Gevent and provides solutions.

Insecurity and Python pickles

pickle is Python's standard library for serialization, but it has a major security risk when deserializing! The article introduces how it works, the root of the security risk, and how the machine learning community collaborated to design a safer alternative format called safetensors.

Building An Open Source Decentralized E-Book Search Engine

This tutorial uses JavaScript and Python to develop an e-book search engine that relies on Glitter (a decentralized database service built with Tendermint) and uses React to develop the page that displays the search results.

What's the Difference Between Python import and Java import?

Many programming languages have the import keyword, and their functions are similar, but what are the differences in their underlying mechanisms? This article analyzes the similarities and differences between import in Java and Python, which can deepen your understanding of this topic.

PDM's Internal Implementation (1)

pdm is an excellent dependency management tool in Python, created by the Chinese developer @frostming. The author plans to write a series of articles about its internal implementation. This is the first article, which introduces what Lockfile is and how Lockfile is generated.

Does Python have pointers?

Does Python have pointers? The answer depends on how you understand "pointers". The author gives a brief but insightful answer. Python does not have the classic pointer operations of the C language, but every variable in Python is a pointer, i.e., everything is an implicit pointer. (In addition: A project "brings the pointer hell to Python", which is as superfluous as the Python version with curly braces below.)

When Python can’t thread: a deep-dive into the GIL’s impact

The GIL-less feature was finally merged into Python's main branch this week! Here is a long article that provides an in-depth introduction to the GIL, helping to understand how the GIL works and predict where concurrency bottlenecks are located. The article uses many thread timing analysis graphs for easy understanding.

🎁 Python Trending Weekly 🎁 organizes its content into seasons, with every 30 issues forming a season. The highlights from the first season have been compiled for your convenience. You can access them online here (Chinese).

🐿️Projects & Resources

Flet enables developers to easily build realtime web, mobile and desktop apps in Python

No front-end experience required, quickly build cross-platform, multi-user, real-time single-page applications (SPAs); no SDK needed, development can be done with an IDE or text editor, front-end uses Flutter UI, back-end currently supports Python, with plans to support Go and C#. (8.7K stars) (Contributed by @bear)

ss-python: A Python project template covering the entire development lifecycle

A Python project template with various integrations, configurations, and modules, featuring: project setup and template updates with copier, dependency and virtual environment management with pdm, containerization with dev container, mypy, ruff, and other commonly used tech stacks. (Contributed by @huxuan_org)

dukpy: Simple JavaScript interpreter for Python

A JS interpreter built on the duktape engine, used to execute JS code in Python. It has no other external dependencies, and has built-in common transpilers (TypeScript, JSX, LESS, CoffeeScript). It also supports passing parameters, running multiple scripts, global interpreters, loading modules using require, and installing packages from npmjs.org.

>>> import dukpy
>>> dukpy.evaljs("var o = {'value': 5}; o['value'] += 3; o")
{'value': 8}

PyKidos: A Python Programming Practice Website

An online Python programming website that makes it easy to teach kids how to code through games.

hatchet: A distributed, fault-tolerant task queue

Replaces hard-to-manage traditional queues and pub/sub systems, supports fault recovery, and solves concurrency, fairness, and rate limiting issues. Features low latency and high throughput, supports strategies like FIFO, LIFO, round-robin, and priority queues, allows for customizable retry policies, and supports integrated error handling. (2.4K stars)

full-stack-fastapi-template: Full stack, modern web application template

Supports JWT authentication, email-based password recovery, and uses Traefik as a reverse proxy/load balancer, with FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS, etc. (17.5K stars)

bython: Python with braces

I think Python's use of whitespace for indentation is its most beautiful design feature! But some people prefer curly braces. This project adds curly braces to Python, with a basic example:

def print_message(num_of_times) {
    for i in range(num_of_times) {
        print("Bython is awesome!");
    }
}

if __name__ == "__main__" {
    print_message(10);
}

treq: Python requests-like API built on top of Twisted's HTTP client

A simple, requests-like HTTP client built on top of Twisted.

JavSP: Video Metadata Scraper Aggregating Data from Multiple Sites

Automatically fetches, aggregates, and categorizes video files based on specified rules, creating metadata files for use with software like Emby, Jellyfin, Kodi, etc. (1.6K stars)

botasaurus: The All in One Framework to build Awesome Scrapers

Access Cloudflare protected pages with simple HTTP requests, the only scraper framework with SSL support for authenticated proxies, integrate any Chrome extension with just one line of code, sitemap support, data cleaning support, caching support, provides Selenium shortcuts, and more.

pywebview: Build GUI for your Python program with JavaScript, HTML, and CSS

A lightweight cross-platform wrapper around the WebView component, displaying HTML content in a GUI window. Can be used with web frameworks or standalone to bridge Python with the DOM. The latest 5.0 release introduces Android support. (4.2K stars)

Paper-Piano: Piano like no other, Piano on Paper

Allows you to practice playing the piano directly on a sheet of paper! Currently supports up to two fingers, primarily intended for those who cannot afford a piano.

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