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Kanal postlari
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
| 2 | 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/ | 31 |
| 3 | 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 | 40 |
| 4 | 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 | 51 |
| 5 | Python Hub Weekly Digest for 2026-10-04
https://pythonhub.dev/digest/2026-10-04/ | 90 |
| 6 | 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 | 103 |
| 7 | 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 | 109 |
| 8 | 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 | 94 |
| 9 | Speeding Up a Python Service with CinderX: JIT and Static Typing
Timofei Ivankov explores how CinderX’s JIT compiler and Static Python can accelerate real-world Python services, comparing their internals and performance with CPython 3.14’s experimental JIT. Benchmarks show that combining Static Python with JIT compilation increased a CPU-bound endpoint’s throughput from 140 to 250 requests per second, while NumPy-heavy workloads saw no benefit and gar...
https://dev.to/deadlovelll/speeding-up-a-python-service-with-cinderx-jit-and-static-typing-53bh | 91 |
| 10 | apowerb
The open-source agentic framework to build, orchestrate, and operate production AI agents.
https://github.com/apowerb/apowerb | 86 |
| 11 | ouroboros
Ouroboros is an open-source AI coding framework that turns vague ideas into verified code through structured interviews, specification-driven execution, automated evaluations, and iterative improvement across multiple coding agents
https://github.com/Q00/ouroboros | 91 |
| 12 | TATS
TATS is an open-source Python tool for analyzing OAuth 2.0, OpenID Connect, and Microsoft Entra ID tokens, helping security researchers trace authentication flows, identify risky permissions, and visualize token lifecycles.
https://github.com/IceMoonHSV/TATS | 94 |
| 13 | jev-ultrafast
A browser agent with a dynamic, indexed action space.
https://github.com/browser-use/jev-ultrafast | 98 |
| 14 | Share how you use Django with Django Probe
The post introduces Django Probe, a tool that scans Django projects and anonymously aggregates how framework APIs and patterns are actually used. The goal is to give Django maintainers better data for decisions around deprecations, new features, documentation, and community priorities.
https://www.better-simple.com/django/2026/09/17/share-how-you-use-django-with-django-probe/ | 100 |
| 15 | superdesigndev / treg
OpenRouter for agent tools. Join community here: https://discord.gg/6mQYYfFMAn
https://github.com/superdesigndev/treg | 102 |
| 16 | Put the Arithmetic in the Tool: an MCP Server for an AWS Waste Scanner
The article shows how to add an MCP server to a Python-based AWS cost scanner so AI agents can query computed totals, breakdowns, filters, and cleanup plans without doing arithmetic themselves. It also covers JSON-RPC over stdio, read-only tool design, end-to-end testing, rounding consistency, and integration with Claude Code.
https://dev.to/aws-builders/put-the-arithmetic-in-the-tool-an-mcp-server-for-an-aws-waste-scanner-3n79 | 120 |
| 17 | This Design Pattern Replaces an Entire Class Hierarchy
This video compares three ways to model type-based variation in Python: subclasses, storing a type value such as an enum, and representing each variation as an object. Using a subscription system, it introduces the Type Object pattern and explains when each approach is the better fit.
https://www.youtube.com/watch?v=IdwdqdywNOM | 101 |
| 18 | DeepTeam
DeepTeam is a framework to red team LLMs and AI agents.
https://github.com/confident-ai/deepteam | 96 |
| 19 | Yoo... https://subprocess.run actually redirects to the Python docs for subprocess.run()
https://www.reddit.com/r/Python/comments/1wp8325/yoo_httpssubprocessrun_actually_redirects_to_the/ | 102 |
| 20 | nonetrace: tells you where a None came from when Python crashes on it
When Python crashes on None, it points at the wrong line. nonetrace shows which call returned the None, why, and the fix.
https://pypi.org/project/nonetrace/ | 214 |
