AsyncIO - Complete Guide to Asynchronous Programming with Animations
The video teaches how to write asynchronous code in Python using AsyncIO with async/await syntax. It covers core concepts like coroutines, tasks, and the event loop, shows how to convert synchronous code to async, and demonstrates performance benefits using real-world examples and animations.
https://www.youtube.com/watch?v=oAkLSJNr5zY
The video teaches how to write asynchronous code in Python using AsyncIO with async/await syntax. It covers core concepts like coroutines, tasks, and the event loop, shows how to convert synchronous code to async, and demonstrates performance benefits using real-world examples and animations.
https://www.youtube.com/watch?v=oAkLSJNr5zY
YouTube
Python Tutorial: AsyncIO - Complete Guide to Asynchronous Programming with Animations
In this video, we'll be learning all about AsyncIO in Python and how to write asynchronous code using the async/await syntax. We'll explore how AsyncIO works under the hood with visual animations, understand key concepts like coroutines, tasks, and the event…
monkeSearch
Fully local, temporally aware natural language file search on your pc! even without a GPU. find relevant files using natural language in less than 1 second.
https://github.com/monkesearch/monkeSearch
Fully local, temporally aware natural language file search on your pc! even without a GPU. find relevant files using natural language in less than 1 second.
https://github.com/monkesearch/monkeSearch
GitHub
GitHub - monkesearch/monkeSearch: fully local, temporally aware natural language file search on your pc! even without a GPU. find…
fully local, temporally aware natural language file search on your pc! even without a GPU. find relevant files using natural language in less than 1 second. - monkesearch/monkeSearch
We Needed Better Cloud Storage for Python so We Built Obstore
Obstore is a fast, lightweight Python library for working with object storage—backed by Rust and built for clarity, speed, and interoperability. It’s already being used across cloud-native geospatial tools and supports common workflows out of the box.
https://developmentseed.org/blog/2025-08-01-obstore/
Obstore is a fast, lightweight Python library for working with object storage—backed by Rust and built for clarity, speed, and interoperability. It’s already being used across cloud-native geospatial tools and supports common workflows out of the box.
https://developmentseed.org/blog/2025-08-01-obstore/
developmentseed.org
We Needed Better Cloud Storage for Python so We Built Obstore — Development Seed
Obstore solves the friction we kept hitting in cloud-native workflows.
👍1
Preventing Domain Resurrection Attacks
PyPI has implemented new security measures to prevent domain resurrection attacks, where expired domains are re-registered by attackers to hijack accounts via password resets. Since June 2025, PyPI has unverified over 1,800 email addresses tied to expiring domains, blocking these addresses from being used for account recovery and enhancing account security.
https://blog.pypi.org/posts/2025-08-18-preventing-domain-resurrections/
PyPI has implemented new security measures to prevent domain resurrection attacks, where expired domains are re-registered by attackers to hijack accounts via password resets. Since June 2025, PyPI has unverified over 1,800 email addresses tied to expiring domains, blocking these addresses from being used for account recovery and enhancing account security.
https://blog.pypi.org/posts/2025-08-18-preventing-domain-resurrections/
blog.pypi.org
Preventing Domain Resurrection Attacks - The Python Package Index Blog
PyPI now checks for expired domains to prevent domain resurrection attacks, a type of supply-chain attack where someone buys an expired domain and uses it to take over PyPI accounts through password resets.
MCPMark
MCP Servers are shaping the future of software. MCPMark is a comprehensive, stress-testing benchmark and a collection of diverse, verifiable tasks designed to evaluate model capabilities in real-world MCP use.
https://github.com/eval-sys/mcpmark
MCP Servers are shaping the future of software. MCPMark is a comprehensive, stress-testing benchmark and a collection of diverse, verifiable tasks designed to evaluate model capabilities in real-world MCP use.
https://github.com/eval-sys/mcpmark
GitHub
GitHub - eval-sys/mcpmark: MCP Servers are shaping the future of software. MCPMark is a comprehensive, stress-testing benchmark…
MCP Servers are shaping the future of software. MCPMark is a comprehensive, stress-testing benchmark and a collection of diverse, verifiable tasks designed to evaluate model capabilities in real-wo...
Pro-Tip – Sometimes LFU > LRU
This article discusses how AI/web crawlers create excessive sessions that push legitimate user sessions out of cache, degrading user experience on sites like e-commerce platforms. It suggests configuring Redis with an LFU (Least Frequently Used) eviction policy, rather than the common LRU (Least Recently Used), to preferentially keep frequently used sessions (like those of real users) wh...
https://www.revsys.com/tidbits/sometimes-lfu-lru/
This article discusses how AI/web crawlers create excessive sessions that push legitimate user sessions out of cache, degrading user experience on sites like e-commerce platforms. It suggests configuring Redis with an LFU (Least Frequently Used) eviction policy, rather than the common LRU (Least Recently Used), to preferentially keep frequently used sessions (like those of real users) wh...
https://www.revsys.com/tidbits/sometimes-lfu-lru/
REVSYS
Sometimes LFU > LRU
Stop letting bot traffic evict your customers' sessions. A simple Redis configuration switch from LRU to LFU solved our crawler problem, with a Django configuration example.
Python has had async for 10 years – why isn't it more popular?
https://tonybaloney.github.io/posts/why-isnt-python-async-more-popular.html
https://tonybaloney.github.io/posts/why-isnt-python-async-more-popular.html
tonybaloney.github.io
Python has had async for 10 years -- why isn't it more popular?
A deep-dive into the challenges and misconceptions surrounding async programming in Python
How to migrate from pip-tools to uv
A guide to migrating from pip-tools to uv in Python projects, focusing on preserving pinned versions.
https://www.caktusgroup.com/blog/2025/08/25/migrate-pip-tools-to-uv/
A guide to migrating from pip-tools to uv in Python projects, focusing on preserving pinned versions.
https://www.caktusgroup.com/blog/2025/08/25/migrate-pip-tools-to-uv/
Caktusgroup
How to migrate from pip-tools to uv | Caktus Group
A guide to migrating from pip-tools to uv in Python projects, focusing on preserving pinned versions.
Weaponizing image scaling against production AI systems
Attackers can hide malicious prompts in images that become visible only after being downscaled—tricking AI systems like Gemini CLI and Vertex AI Studio into executing hidden instructions. Trail of Bits demonstrates these “image scaling” exploits and introduces Anamorpher, an open-source tool to craft and test such attacks, while also proposing defenses.
https://blog.trailofbits.com/2025/08/21/weaponizing-image-scaling-against-production-ai-systems/
Attackers can hide malicious prompts in images that become visible only after being downscaled—tricking AI systems like Gemini CLI and Vertex AI Studio into executing hidden instructions. Trail of Bits demonstrates these “image scaling” exploits and introduces Anamorpher, an open-source tool to craft and test such attacks, while also proposing defenses.
https://blog.trailofbits.com/2025/08/21/weaponizing-image-scaling-against-production-ai-systems/
The Trail of Bits Blog
Weaponizing image scaling against production AI systems
In this blog post, we’ll detail how attackers can exploit image scaling on Gemini CLI, Vertex AI Studio, Gemini’s web and API interfaces, Google Assistant, Genspark, and other production AI systems. We’ll also explain how to mitigate and defend against these…
How to Build an Advanced AI Agent with Search (LangGraph, Python, Bright Data & More)
The video demonstrates building a multi-step, scalable AI research agent in Python using LangGraph. The agent can pull live search data from sources like Google, Bing, and Reddit, aggregate and analyze the information, and provide comprehensive answers, showcasing advanced Python coding, complex architecture, and effective use of APIs like Bright Data and OpenAI GPT. The tutorial covers ...
https://www.youtube.com/watch?v=cUC-hyjpNxk
The video demonstrates building a multi-step, scalable AI research agent in Python using LangGraph. The agent can pull live search data from sources like Google, Bing, and Reddit, aggregate and analyze the information, and provide comprehensive answers, showcasing advanced Python coding, complex architecture, and effective use of APIs like Bright Data and OpenAI GPT. The tutorial covers ...
https://www.youtube.com/watch?v=cUC-hyjpNxk
YouTube
How to Build an Advanced AI Agent with Search (LangGraph, Python, Bright Data & More)
Get started with BrightData and get $20 in credits for free: https://brdta.com/twt_websearch
Check out PyCharm, the Python IDE for data and web professionals: https://jb.gg/check-pycharm-now
In this video, we're building an advanced AI agent in Python…
Check out PyCharm, the Python IDE for data and web professionals: https://jb.gg/check-pycharm-now
In this video, we're building an advanced AI agent in Python…
lemonade
Lemonade helps users run local LLMs with the highest performance by configuring state-of-the-art inference engines for their NPUs and GPUs.
https://github.com/lemonade-sdk/lemonade
Lemonade helps users run local LLMs with the highest performance by configuring state-of-the-art inference engines for their NPUs and GPUs.
https://github.com/lemonade-sdk/lemonade
GitHub
GitHub - lemonade-sdk/lemonade: Lemonade helps users run local LLMs with the highest performance by configuring state-of-the-art…
Lemonade helps users run local LLMs with the highest performance by configuring state-of-the-art inference engines for their NPUs and GPUs. Join our discord: https://discord.gg/5xXzkMu8Zk - lemonad...
AI Agents for Beginners
11 Lessons to Get Started Building AI Agents.
https://github.com/microsoft/ai-agents-for-beginners
11 Lessons to Get Started Building AI Agents.
https://github.com/microsoft/ai-agents-for-beginners
GitHub
GitHub - microsoft/ai-agents-for-beginners: 12 Lessons to Get Started Building AI Agents
12 Lessons to Get Started Building AI Agents. Contribute to microsoft/ai-agents-for-beginners development by creating an account on GitHub.
From GPT-2 to gpt-oss: Analyzing the Architectural Advances
The article analyzes the architectural advances from GPT-2 to OpenAI’s new open-weight gpt-oss models, highlighting innovations like Mixture-of-Experts, grouped query attention, and sliding-window layers for efficiency and scaling. He compares these changes with models like Qwen3 and notes how gpt-oss is optimized for reasoning, tool use, and agentic workflows, while remaining memory-eff...
https://magazine.sebastianraschka.com/p/from-gpt-2-to-gpt-oss-analyzing-the
The article analyzes the architectural advances from GPT-2 to OpenAI’s new open-weight gpt-oss models, highlighting innovations like Mixture-of-Experts, grouped query attention, and sliding-window layers for efficiency and scaling. He compares these changes with models like Qwen3 and notes how gpt-oss is optimized for reasoning, tool use, and agentic workflows, while remaining memory-eff...
https://magazine.sebastianraschka.com/p/from-gpt-2-to-gpt-oss-analyzing-the
Sebastianraschka
From GPT-2 to gpt-oss: Analyzing the Architectural Advances
And How They Stack Up Against Qwen3
How to Write Great Unit Tests in Python
The video teaches how to write effective and maintainable unit tests in Python, focusing on practical techniques such as mocking, monkey patching, fixtures, and parametrization with pytest. It uses a realistic WeatherService example to demonstrate these concepts, emphasizing best practices for robust testing and improving code quality in production systems.
https://www.youtube.com/watch?v=EIV_ixKGPmc
The video teaches how to write effective and maintainable unit tests in Python, focusing on practical techniques such as mocking, monkey patching, fixtures, and parametrization with pytest. It uses a realistic WeatherService example to demonstrate these concepts, emphasizing best practices for robust testing and improving code quality in production systems.
https://www.youtube.com/watch?v=EIV_ixKGPmc
YouTube
How to Write Great Unit Tests in Python
Check out https://www.squarespace.com/arjancodes to save 10% off your first purchase of a website or domain using code ARJANCODES.
Want to learn how to write professional, maintainable unit tests in Python? In this video, I’ll walk you through the entire…
Want to learn how to write professional, maintainable unit tests in Python? In this video, I’ll walk you through the entire…
DiffMem
Git Based Memory Storage for Conversational AI Agent.
https://github.com/Growth-Kinetics/DiffMem
Git Based Memory Storage for Conversational AI Agent.
https://github.com/Growth-Kinetics/DiffMem
GitHub
GitHub - Growth-Kinetics/DiffMem: Git Based Memory Storage for Conversational AI Agent
Git Based Memory Storage for Conversational AI Agent - Growth-Kinetics/DiffMem
LEANN
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
https://github.com/yichuan-w/LEANN
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
https://github.com/yichuan-w/LEANN
GitHub
GitHub - yichuan-w/LEANN: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private…
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device. - yichuan-w/LEANN
oLLM
oLLM is a lightweight Python library for large-context LLM inference, built on top of Huggingface Transformers and PyTorch. It enables running models like Llama-3.1-8B-Instruct on 100k context using ~$200 consumer GPU with 8GB VRAM. Example performance: ~20 min for the first token, ~17s per subsequent token.
https://github.com/Mega4alik/ollm
oLLM is a lightweight Python library for large-context LLM inference, built on top of Huggingface Transformers and PyTorch. It enables running models like Llama-3.1-8B-Instruct on 100k context using ~$200 consumer GPU with 8GB VRAM. Example performance: ~20 min for the first token, ~17s per subsequent token.
https://github.com/Mega4alik/ollm
GitHub
GitHub - Mega4alik/ollm
Contribute to Mega4alik/ollm development by creating an account on GitHub.
TIL: Using SQLModel Asynchronously with FastAPI (and Air) with PostgreSQL
This post explains how to leverage SQLModel with FastAPI and PostgreSQL to enable fully asynchronous database operations, improving scalability and efficiency for concurrent web applications. Key steps include setting up async database engines and sessions, using dependency injection in FastAPI, and aligning everything with non-blocking patterns.
https://daniel.feldroy.com/posts/til-2025-08-using-sqlmodel-asynchronously-with-fastapi-and-air-with-postgresql
This post explains how to leverage SQLModel with FastAPI and PostgreSQL to enable fully asynchronous database operations, improving scalability and efficiency for concurrent web applications. Key steps include setting up async database engines and sessions, using dependency injection in FastAPI, and aligning everything with non-blocking patterns.
https://daniel.feldroy.com/posts/til-2025-08-using-sqlmodel-asynchronously-with-fastapi-and-air-with-postgresql
https://daniel.feldroy.com
TIL: Using SQLModel Asynchronously with FastAPI (and Air) with PostgreSQL
SQLModel is a really useful library for working with SQL databases in Python, built on top of SQLAlchemy and Pydantic. However, AFAIK there's no documentation supporting asynchronous operations for PostgreSQL, which can be a limitation when building high…