foundry
Ship full-stack agentic systems the way they're meant to be built - production-ready, secure by default, with the developer experience modern Python deserves.
https://github.com/promptise-com/foundry
Ship full-stack agentic systems the way they're meant to be built - production-ready, secure by default, with the developer experience modern Python deserves.
https://github.com/promptise-com/foundry
GitHub
GitHub - promptise-com/Foundry: The foundation layer for agentic intelligence.
The foundation layer for agentic intelligence. Contribute to promptise-com/Foundry development by creating an account on GitHub.
Using Bag-of-Words With PyCharm
Let's unpack how the bag-of-words model works, explore the techniques it uses to convert text into numerical representations, and look at where it fits relative to more modern NLP approaches.
https://blog.jetbrains.com/pycharm/2026/04/using-bag-of-words-with-pycharm/
Let's unpack how the bag-of-words model works, explore the techniques it uses to convert text into numerical representations, and look at where it fits relative to more modern NLP approaches.
https://blog.jetbrains.com/pycharm/2026/04/using-bag-of-words-with-pycharm/
The JetBrains Blog
Using Bag-of-Words With PyCharm | The PyCharm Blog
Let's unpack how the bag-of-words model works, explore the techniques it uses to convert text into numerical representations, and look at where it fits relative to more modern NLP approaches.
bluerock
Runtime visibility for Python MCP servers. Captures tool calls, session lifecycle, module imports (SHA-256), and subprocess execution as structured NDJSON. No code changes. Apache 2.0
https://github.com/bluerock-io/bluerock
Runtime visibility for Python MCP servers. Captures tool calls, session lifecycle, module imports (SHA-256), and subprocess execution as structured NDJSON. No code changes. Apache 2.0
https://github.com/bluerock-io/bluerock
GitHub
GitHub - bluerock-io/bluerock: Runtime visibility for Python MCP servers. Captures tool calls, session lifecycle, module imports…
Runtime visibility for Python MCP servers. Captures tool calls, session lifecycle, module imports (SHA-256), and subprocess execution as structured NDJSON. No code changes. Apache 2.0 - bluerock-io...
Fast Mesh Booleans in Python
Learn how to perform fast mesh boolean operations in Python. Union, intersection, and difference at interactive speed on million-polygon meshes. One pip install, NumPy arrays in and out.
https://polydera.com/tutorials/fast-mesh-booleans-in-python
Learn how to perform fast mesh boolean operations in Python. Union, intersection, and difference at interactive speed on million-polygon meshes. One pip install, NumPy arrays in and out.
https://polydera.com/tutorials/fast-mesh-booleans-in-python
Polydera
Fast Mesh Booleans in Python · Polydera
Learn how to perform fast mesh boolean operations in Python. Union, intersection, and difference at interactive speed on million-polygon meshes. One pip install, NumPy arrays in and out.
Boosting multimodal inference performance by >10% with a single Python dictionary
Multimodal models are promising, but inference engines haven't been optimized for them yet. We profiled SGLang’s scheduler on a multimodal workload and identified an opportunity to replace expensive book-keeping around shared GPU memory with a simple cache lookup. Throughput and latency both improved over 10% on our target workload.
https://modal.com/blog/boosting-multimodal-inference-performance-by-greater-than-10-with-a-single-python-dictionary
Multimodal models are promising, but inference engines haven't been optimized for them yet. We profiled SGLang’s scheduler on a multimodal workload and identified an opportunity to replace expensive book-keeping around shared GPU memory with a simple cache lookup. Throughput and latency both improved over 10% on our target workload.
https://modal.com/blog/boosting-multimodal-inference-performance-by-greater-than-10-with-a-single-python-dictionary
Modal
Boosting multimodal inference performance by >10% with a single Python dictionary | Modal Blog
If we've said it once, we've said it once per millisecond: never block the GPU.
auto-round
A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA, with multi-datatype support and full compatibility with vLLM, SGLang, and Transformers.
https://github.com/intel/auto-round
A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA, with multi-datatype support and full compatibility with vLLM, SGLang, and Transformers.
https://github.com/intel/auto-round
GitHub
GitHub - intel/auto-round: A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA…
A SOTA quantization algorithm for high-accuracy low-bit LLM inference, seamlessly optimized for CPU/XPU/CUDA, with multi-datatype support and full compatibility with vLLM, SGLang, and Transformers....
Pymetrica, a codebase analysis tool
Pymetrica is a static analysis tool that parses Python source code using the AST and evaluates metrics used to assess complexity, maintainability, and architectural stability.
https://github.com/JuanJFarina/pymetrica
Pymetrica is a static analysis tool that parses Python source code using the AST and evaluates metrics used to assess complexity, maintainability, and architectural stability.
https://github.com/JuanJFarina/pymetrica
GitHub
GitHub - JuanJFarina/pymetrica: Pymetrica is a Python static analysis tool that computes software engineering metrics such as Cyclomatic…
Pymetrica is a Python static analysis tool that computes software engineering metrics such as Cyclomatic Complexity, Halstead Volume, and Maintainability Cost. It analyzes code using the Python AST...
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/
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.…