Mastering Python Logging Format: A Complete Guide for Developers
Set up Python logging format strings, custom formatters, and structured JSON output with copy-paste code examples for every major use case.
https://middleware.io/blog/python-logging-format/
Set up Python logging format strings, custom formatters, and structured JSON output with copy-paste code examples for every major use case.
https://middleware.io/blog/python-logging-format/
Middleware
Python Logging Format: Complete Guide to Formatters, Handlers & Structured Logs
Set up Python logging format strings, custom formatters, and structured JSON output with copy-paste code examples for every major use case.
I've been teaching intro Python for 3 years i notice the same weaknesses in almost every student. Am i missing something in how I'm explaining it?
https://www.reddit.com/r/learnpython/comments/1tbtrtv/ive_been_teaching_intro_python_for_3_years_i/
https://www.reddit.com/r/learnpython/comments/1tbtrtv/ive_been_teaching_intro_python_for_3_years_i/
Reddit
From the learnpython community on Reddit
Explore this post and more from the learnpython community
How we accelerated transpilation by compiling SQLGlot with mypyc
Fivetran accelerated SQLGlot, a pure Python SQL parser/transpiler, by 5x through compiling 100+ modules into C extensions with mypyc, without rewriting it in Rust. Key optimizations included sentinel tokens, native i64 integers, dispatch tables, and upstream mypyc primitives for string operations, resulting in 3.9 to 5x speedups across the tokenizer, parser, and generator.
https://www.fivetran.com/blog/how-we-accelerated-transpilation-by-compiling-sqlglot-with-mypyc
Fivetran accelerated SQLGlot, a pure Python SQL parser/transpiler, by 5x through compiling 100+ modules into C extensions with mypyc, without rewriting it in Rust. Key optimizations included sentinel tokens, native i64 integers, dispatch tables, and upstream mypyc primitives for string operations, resulting in 3.9 to 5x speedups across the tokenizer, parser, and generator.
https://www.fivetran.com/blog/how-we-accelerated-transpilation-by-compiling-sqlglot-with-mypyc
Fivetran
How we accelerated transpilation by compiling SQLGlot with mypyc | Blog | Fivetran
It has never been faster or easier to translate between different SQL dialects so that you can use different query engines.
ShadowBroker
Shadowbroker is a decentralized OSINT platform aggregating real-time data from 60+ feeds like private jets, spy satellites, and seismic events into a unified dashboard.
https://github.com/BigBodyCobain/Shadowbroker
Shadowbroker is a decentralized OSINT platform aggregating real-time data from 60+ feeds like private jets, spy satellites, and seismic events into a unified dashboard.
https://github.com/BigBodyCobain/Shadowbroker
GitHub
GitHub - BigBodyCobain/Shadowbroker: Open-source intelligence for the global theater. Track everything from the corporate/private…
Open-source intelligence for the global theater. Track everything from the corporate/private jets of the wealthy, and spy satellites, to seismic events in one unified interface. Hook an AI agent up...
ProgramBench
Can Language Models Rebuild Programs From Scratch? Given only a compiled binary and its documentation, AI agents must architect and implement a complete codebase that reproduces the original program's behavior.
https://programbench.com/
Can Language Models Rebuild Programs From Scratch? Given only a compiled binary and its documentation, AI agents must architect and implement a complete codebase that reproduces the original program's behavior.
https://programbench.com/
ProgramBench
ProgramBench evaluates whether language models can rebuild programs from scratch.
Create a 90s GeoCities style website in seconds (Python)
https://pypi.org/project/create-geocities-app/
https://pypi.org/project/create-geocities-app/
PyPI
create-geocities-app
Scaffold a 1990s Geocities-themed static website in seconds
Family Orienting Python Frozenset Dependent Type Theory
The post models dependent type theory in plain Python by treating types as finite “families,” or dictionaries from contexts to sets, rather than as standalone bare values. The key idea is that full judgments like Γ |- A should be interpreted as mappings, which makes contexts, weakening, terms, Sigma/Pi types, and identity types easier to represent uniformly.
https://www.philipzucker.com/dtt_python_family/
The post models dependent type theory in plain Python by treating types as finite “families,” or dictionaries from contexts to sets, rather than as standalone bare values. The key idea is that full judgments like Γ |- A should be interpreted as mappings, which makes contexts, weakening, terms, Sigma/Pi types, and identity types easier to represent uniformly.
https://www.philipzucker.com/dtt_python_family/
Hey There Buddo!
Family Orienting Python Frozenset Dependent Type Theory
I like trying to finitize things and put them in mundane trappings.
Reverting the incremental GC in Python 3.14 and 3.15
https://discuss.python.org/t/reverting-the-incremental-gc-in-python-3-14-and-3-15/107014
https://discuss.python.org/t/reverting-the-incremental-gc-in-python-3-14-and-3-15/107014
Discussions on Python.org
Reverting the incremental GC in Python 3.14 and 3.15
Python 3.14 shipped with a new incremental garbage collector. However, we’ve had a number of reports of significant memory pressure in production environments. We’ve decided to revert it in both 3.14 and 3.15, and go back to the generational GC from 3.13.…
Introducing Retrace: Record Production Python. Debug It Backwards.
Retrace introduces deterministic record-replay debugging for Python, allowing production executions to be recorded with very low overhead and replayed locally in VS Code with reverse debugging support. Instead of relying on logs or reproducing failures, it records the boundary between application code and nondeterministic systems like APIs, databases, threads, and file I/O, enabling deve...
https://retracesoftware.com/blog/introducing-retrace/
Retrace introduces deterministic record-replay debugging for Python, allowing production executions to be recorded with very low overhead and replayed locally in VS Code with reverse debugging support. Instead of relying on logs or reproducing failures, it records the boundary between application code and nondeterministic systems like APIs, databases, threads, and file I/O, enabling deve...
https://retracesoftware.com/blog/introducing-retrace/
Retrace | Explore your production, distributed application in real-time
Retrace: Deterministic Record-Replay for Python
Record production crashes, replay them locally in VS Code. <1% overhead, open source.
The Simplest MCP Example Possible in Python
The post shows the simplest Python example of MCP (Model Context Protocol) for connecting a local LLM like Llama 3.2 to tools. It uses fastmcp and ollama packages with two scripts: mcpserver.py for time/date tools and ollamaclient.py to run the chat loop.
https://inventwithpython.com/blog/basic-mcp-python-example.html
The post shows the simplest Python example of MCP (Model Context Protocol) for connecting a local LLM like Llama 3.2 to tools. It uses fastmcp and ollama packages with two scripts: mcpserver.py for time/date tools and ollamaclient.py to run the chat loop.
https://inventwithpython.com/blog/basic-mcp-python-example.html
Inventwithpython
The Simplest MCP Example Possible in Python
Labb - UI components for Django
This video looks at labb - a UI component library for Django apps that builds on top of TailwindCSS, DaisyUI, django-cotton and Alpine.js. This library has over 70 components that can be dropped into Django projects, and makes it easy to add custom themes, for example using DaisyUI Theme Generator.
https://www.youtube.com/watch?v=ZZd7cvbJ-1w
This video looks at labb - a UI component library for Django apps that builds on top of TailwindCSS, DaisyUI, django-cotton and Alpine.js. This library has over 70 components that can be dropped into Django projects, and makes it easy to add custom themes, for example using DaisyUI Theme Generator.
https://www.youtube.com/watch?v=ZZd7cvbJ-1w
YouTube
Labb - UI components for Django (built on Tailwind, django-cotton, Alpine.js!)
▶ Django & HTMX FULL COURSE: https://www.udemy.com/course/django-htmx-hypermedia-web-apps/?couponCode=BUGBYTES-MAY
🙏 Join our channel to get access to perks:
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To support the…
🙏 Join our channel to get access to perks:
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☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲:
To support the…
DRY Often Makes Your Code Worse
A DRY refactor can make code worse when it removes duplication by hiding different behaviors behind flags and shared abstractions. Better refactoring focuses on separating responsibilities and making behavior clear, not just making the code look smaller.
https://www.youtube.com/watch?v=GmlZBdKhl9Y
A DRY refactor can make code worse when it removes duplication by hiding different behaviors behind flags and shared abstractions. Better refactoring focuses on separating responsibilities and making behavior clear, not just making the code look smaller.
https://www.youtube.com/watch?v=GmlZBdKhl9Y
YouTube
DRY Often Makes Your Code Worse
🧱 Build software that lasts. Join the Software Design Mastery waiting list → https://arjan.codes/mastery.
In this video, I show how a “clean” DRY refactor can actually make your code worse. Instead of improving the design, it introduces hidden complexity…
In this video, I show how a “clean” DRY refactor can actually make your code worse. Instead of improving the design, it introduces hidden complexity…
aidlc-workflows
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents.
https://github.com/awslabs/aidlc-workflows
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents.
https://github.com/awslabs/aidlc-workflows
GitHub
GitHub - awslabs/aidlc-workflows: AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents - awslabs/aidlc-workflows
❤1
In-Kernel Broadcast Optimization: Co-Designing Kernels for RecSys Inference
In-Kernel Broadcast Optimization (IKBO) eliminates redundant user-embedding replication by fusing broadcast logic directly into interaction kernels, significantly reducing memory bandwidth and compute waste. This co-design approach delivers up to a two-thirds reduction in latency across Meta's recommendation stack, optimized for high-performance hardware like NVIDIA H100 and Meta’s MTIA.
https://pytorch.org/blog/in-kernel-broadcast-optimization-co-designing-kernels-for-recsys-inference/
In-Kernel Broadcast Optimization (IKBO) eliminates redundant user-embedding replication by fusing broadcast logic directly into interaction kernels, significantly reducing memory bandwidth and compute waste. This co-design approach delivers up to a two-thirds reduction in latency across Meta's recommendation stack, optimized for high-performance hardware like NVIDIA H100 and Meta’s MTIA.
https://pytorch.org/blog/in-kernel-broadcast-optimization-co-designing-kernels-for-recsys-inference/