since-cutoff: which APIs of your pinned Python dependencies changed after your coding model's training cutoff
Diffs each pinned dependency's API against the release current at the model's cutoff and writes AGENTS.md notes. No model calls.
https://github.com/MohammadHijjawi97/since-cutoff
Diffs each pinned dependency's API against the release current at the model's cutoff and writes AGENTS.md notes. No model calls.
https://github.com/MohammadHijjawi97/since-cutoff
GitHub
GitHub - MohammadHijjawi97/since-cutoff: Find which APIs of your pinned Python dependencies changed after your coding model's training…
Find which APIs of your pinned Python dependencies changed after your coding model's training cutoff, and give the agent short AGENTS.md / CLAUDE.md notes from a static API diff. No model c...
👀2
Python 3.15 Is About to Change Python
Python 3.15 is almost here! This video breaks down 10 of the most interesting new features and changes coming to Python 3.15, using real Python code and visual explanations.
https://www.youtube.com/watch?v=rxaDxyPUoSY
Python 3.15 is almost here! This video breaks down 10 of the most interesting new features and changes coming to Python 3.15, using real Python code and visual explanations.
https://www.youtube.com/watch?v=rxaDxyPUoSY
YouTube
Python 3.15 Is About to Change Python 🤯
Python 3.15 is almost here! 🐍🚀 In this video, we break down 10 of the most interesting new features and changes coming to Python 3.15, using real Python code and visual explanations.
Python 3.15.0rc2 was released on September 1, 2026, and the final Python…
Python 3.15.0rc2 was released on September 1, 2026, and the final Python…
🤔2
How to Build AI Agents in Python - 3 Ways
This video compares three Python frameworks for building more capable AI agents that can navigate codebases, edit files, and run commands: CrewAI, the OpenAI Agents SDK, and LangGraph. It walks through building an agent with each framework and compares their approaches to orchestration, tools, workflows, and choosing the right framework for a project.
https://www.youtube.com/watch?v=-RTgK6qX6A8
This video compares three Python frameworks for building more capable AI agents that can navigate codebases, edit files, and run commands: CrewAI, the OpenAI Agents SDK, and LangGraph. It walks through building an agent with each framework and compares their approaches to orchestration, tools, workflows, and choosing the right framework for a project.
https://www.youtube.com/watch?v=-RTgK6qX6A8
YouTube
How to Build AI Agents in Python - 3 Ways
Click this link https://boot.dev/?promo=TECHWITHTIM and use my code TECHWITHTIM to get 25% off your first payment for boot.dev.
Download the code from this video here: https://www.aiagentbuilders.co/yt-resources/three-ways-agents
Everyone talks about "AI…
Download the code from this video here: https://www.aiagentbuilders.co/yt-resources/three-ways-agents
Everyone talks about "AI…
💯3
django-upgrade-report
Which of your dependencies block a Django upgrade, and in which order to upgrade them.
https://github.com/derblub/django-upgrade-report
Which of your dependencies block a Django upgrade, and in which order to upgrade them.
https://github.com/derblub/django-upgrade-report
GitHub
GitHub - derblub/django-upgrade-report: Which of your dependencies block a Django upgrade, and in which order to upgrade them.
Which of your dependencies block a Django upgrade, and in which order to upgrade them. - derblub/django-upgrade-report
LangSmith Crash Course: LLMOps in Python
This video serves as a comprehensive crash course on LangSmith, the LangChain ecosystem platform used for tracing, debugging, evaluating, and monitoring AI agents. It covers essential LLMOps workflows including tracing agent runs, performing evaluations with custom datasets, creating alerts, and managing prompts.
https://www.youtube.com/watch?v=P3kmo04DiEw
This video serves as a comprehensive crash course on LangSmith, the LangChain ecosystem platform used for tracing, debugging, evaluating, and monitoring AI agents. It covers essential LLMOps workflows including tracing agent runs, performing evaluations with custom datasets, creating alerts, and managing prompts.
https://www.youtube.com/watch?v=P3kmo04DiEw
YouTube
LangSmith Crash Course: LLMOps in Python
Check out Arcade: https://arcade.dev.plug.dev/fU177V4
💻️ Need some help with a project or some consulting? Contact me here: https://www.neuralnine.com/services
🐍 The Python Bible Book: https://www.neuralnine.com/books/
💻 The Algorithm Bible Book: https…
💻️ Need some help with a project or some consulting? Contact me here: https://www.neuralnine.com/services
🐍 The Python Bible Book: https://www.neuralnine.com/books/
💻 The Algorithm Bible Book: https…
SQLite in Production: Why WAL Mode, busy_timeout, and 1-Writer Pools
https://www.reddit.com/r/Python/comments/1wowf4q/sqlite_in_production_why_wal_mode_busy_timeout/
https://www.reddit.com/r/Python/comments/1wowf4q/sqlite_in_production_why_wal_mode_busy_timeout/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
🤯2
asgeirtj / system_prompts_leaks
Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity. xAI - Grok, Grok Bot, Cursor, Kimi and more! Updated regularly.
https://github.com/asgeirtj/system_prompts_leaks
Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity. xAI - Grok, Grok Bot, Cursor, Kimi and more! Updated regularly.
https://github.com/asgeirtj/system_prompts_leaks
GitHub
GitHub - asgeirtj/system_prompts_leaks: Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude…
Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity. xAI - Grok, ...
💯1
Ciaren: open-source visual ETL exporting pandas and Polars code (alpha)
Build data pipelines visually, run locally, preview intermediate data, and export standalone Python scripts. Open-source alpha, AGPL-3.0.
https://ciaren.com/
Build data pipelines visually, run locally, preview intermediate data, and export standalone Python scripts. Open-source alpha, AGPL-3.0.
https://ciaren.com/
Ciaren
Ciaren: open-source visual ETL for pandas and Polars
Ciaren is an open source visual ETL tool. Build data flows on a local canvas, preview each step, and export readable pandas or Polars code.
❤1
livenerf
A long-running, deterministic-as-possible benchmark for detecting whether a frontier model gets quietly worse after launch.
https://github.com/ninjahawk/livenerf
A long-running, deterministic-as-possible benchmark for detecting whether a frontier model gets quietly worse after launch.
https://github.com/ninjahawk/livenerf
GitHub
GitHub - ninjahawk/livenerf: Benchmark for tracking model capability after release.
Benchmark for tracking model capability after release. - ninjahawk/livenerf
🙏1
Python Algorithmic Trading Course – Massive, SnapTrade & Alpaca Integrations
This course demonstrates how to build an algorithmic paper trading system using Python and Django to calculate momentum scores and execute trades. The project integrates Massive for market data, SnapTrade for portfolio management, and Alpaca for risk-free brokerage simulation
https://www.youtube.com/watch?v=zH2Mg782XhA
This course demonstrates how to build an algorithmic paper trading system using Python and Django to calculate momentum scores and execute trades. The project integrates Massive for market data, SnapTrade for portfolio management, and Alpaca for risk-free brokerage simulation
https://www.youtube.com/watch?v=zH2Mg782XhA
YouTube
Python Algorithmic Trading Course – Massive, SnapTrade & Alpaca Integrations
Learn how to build a complete algorithmic paper trading system from the ground up using Python and Django. This hands-on course guides you through configuring a pipeline that connects market data from Massive, manages portfolios securely via SnapTrade, and…
👀1
A Lean Proof Printing Python Union Find
Philip Zucker shows how a Python union-find data structure can generate Lean proof certificates, turning union and path-compression operations into machine-checkable equality proofs. He uses the experiment to explore the broader idea of treating proofs as traces of search, with applications to e-graphs and theorem-proving systems.
https://www.philipzucker.com/proof_uf/
Philip Zucker shows how a Python union-find data structure can generate Lean proof certificates, turning union and path-compression operations into machine-checkable equality proofs. He uses the experiment to explore the broader idea of treating proofs as traces of search, with applications to e-graphs and theorem-proving systems.
https://www.philipzucker.com/proof_uf/
Hey There Buddo!
A Lean Proof Printing Python Union Find
It is somewhat strange, but I haven’t really spent much time working on proof production or recording out of egraphs.
🙏1
Anyone still using Flask, or has FastAPI completely taken over? 🤔
https://www.reddit.com/r/Python/comments/1wxkk8m/anyone_still_using_flask_or_has_fastapi/
https://www.reddit.com/r/Python/comments/1wxkk8m/anyone_still_using_flask_or_has_fastapi/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Why You NEED This New Python Tool
Pyrefly is Meta’s open-source static type checker for Python, designed to catch type-related bugs before code runs instead of waiting for runtime failures. The video explains why Python and type hints alone can miss these errors, and shows how Pyrefly detects them early in real-world codebases.
https://www.youtube.com/watch?v=lFA-zuZRG4Q
Pyrefly is Meta’s open-source static type checker for Python, designed to catch type-related bugs before code runs instead of waiting for runtime failures. The video explains why Python and type hints alone can miss these errors, and shows how Pyrefly detects them early in real-world codebases.
https://www.youtube.com/watch?v=lFA-zuZRG4Q
YouTube
Why You NEED This New Python Tool
Get started with Pyrefly: https://pyrefly.org/twt
This code looks completely fine — it even runs — right up until it crashes on a line that should never have shipped. Python won't warn you, because it doesn't check types until your code is actually running.…
This code looks completely fine — it even runs — right up until it crashes on a line that should never have shipped. Python won't warn you, because it doesn't check types until your code is actually running.…
laya
Laya is a fast multilingual decision engine that produces typed classifications, scores, and probabilities in a single forward pass.
https://github.com/NandhaKishorM/laya
Laya is a fast multilingual decision engine that produces typed classifications, scores, and probabilities in a single forward pass.
https://github.com/NandhaKishorM/laya
GitHub
GitHub - NandhaKishorM/laya: Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text…
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per re...
Django: serve a security.txt file
The post shows how to serve a standards-compliant security.txt file in Django so security researchers know how to report vulnerabilities. It also adds tests and a Django system check to validate the file and warn before its required Expires field becomes stale.
https://adamj.eu/tech/2026/10/01/django-security-txt/
The post shows how to serve a standards-compliant security.txt file in Django so security researchers know how to report vulnerabilities. It also adds tests and a Django system check to validate the file and warn before its required Expires field becomes stale.
https://adamj.eu/tech/2026/10/01/django-security-txt/
adamj.eu
Django: serve a security.txt file - Adam Johnson
When a security researcher finds a vulnerability in your site, they need a way to tell you about it. Without a clear contact, they may resort to guessing at addresses like security@<yourdomain>, messaging random folks on social media, or give up. And of course…
ollaya
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.
https://github.com/ollaya-dev/ollaya
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.
https://github.com/ollaya-dev/ollaya
GitHub
GitHub - ollaya-dev/ollaya: Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe…
Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models. - ollaya-dev/ollaya
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Language Models for Text Classification: From Bag-of-Words to Jev
A concise history of text classification, from bag-of-words and neural networks to transformers and modern LLM-based approaches. It also introduces Jev and examines where specialized classifiers can still outperform or complement general-purpose language models.
https://magazine.sebastianraschka.com/p/classifier-history-and-jev
A concise history of text classification, from bag-of-words and neural networks to transformers and modern LLM-based approaches. It also introduces Jev and examines where specialized classifiers can still outperform or complement general-purpose language models.
https://magazine.sebastianraschka.com/p/classifier-history-and-jev
Sebastian Raschka, PhD
Language Models for Text Classification: From Bag-of-Words to Jev
A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency
Building an Ultra-High Throughput AI-SQL Engine
Quail is an open-source AI-SQL engine that jointly optimizes query planning and LLM inference to reduce redundant model work and keep GPUs busy when running large numbers of AI-powered database operations. In benchmarks across 29 queries, it was 1.84x faster on average than tuned vLLM baselines and up to 14.04x faster on a workload with substantial KV-cache reuse.
https://fsdatalab.github.io/blog/introducing-quail/
Quail is an open-source AI-SQL engine that jointly optimizes query planning and LLM inference to reduce redundant model work and keep GPUs busy when running large numbers of AI-powered database operations. In benchmarks across 29 queries, it was 1.84x faster on average than tuned vLLM baselines and up to 14.04x faster on a workload with substantial KV-cache reuse.
https://fsdatalab.github.io/blog/introducing-quail/
Full Stack Data Lab
Building an Ultra-High Throughput AI-SQL Engine
Quail jointly plans AI-SQL queries and model inference. Across 29 QUAIL-B queries, it is 1.84x faster on average than well-tuned vLLM baselines.