Django 6.0 Is Here! CSP Nonces, Background Tasks, Partials & More
The video tutorial covers the new features introduced in Django 6.0 alpha, including built-in Content Security Policy (CSP) nonce support, simpler background task management, and reusable template partials for cleaner code. It provides practical examples and explanations for implementing these features, highlighting improvements in security, asynchronous task handling, and template desig...
https://www.youtube.com/watch?v=doAMlgrTGbE
The video tutorial covers the new features introduced in Django 6.0 alpha, including built-in Content Security Policy (CSP) nonce support, simpler background task management, and reusable template partials for cleaner code. It provides practical examples and explanations for implementing these features, highlighting improvements in security, asynchronous task handling, and template desig...
https://www.youtube.com/watch?v=doAMlgrTGbE
YouTube
Django 6.0 Is Here! CSP Nonces, Background Tasks, Partials & More
The Django 6.0 Alpha release is here, and it brings some big improvements! In this tutorial, I’ll walk you through the key new features step by step, including:
🔹 Content Security Policy (CSP) Nonce Support
- Why inline scripts are dangerous
- How nonces…
🔹 Content Security Policy (CSP) Nonce Support
- Why inline scripts are dangerous
- How nonces…
drf-auth-kit
Modern Django REST Framework authentication toolkit with JWT cookies, social login, and 2FA support.
https://github.com/forthecraft/drf-auth-kit
Modern Django REST Framework authentication toolkit with JWT cookies, social login, and 2FA support.
https://github.com/forthecraft/drf-auth-kit
GitHub
GitHub - forthecraft/drf-auth-kit: Modern Django REST Framework authentication toolkit with JWT cookies, social login, and 2FA…
Modern Django REST Framework authentication toolkit with JWT cookies, social login, and 2FA support - forthecraft/drf-auth-kit
Klavis
MCP integration layers that let AI agents use thousands of tools reliably.
https://github.com/Klavis-AI/klavis
MCP integration layers that let AI agents use thousands of tools reliably.
https://github.com/Klavis-AI/klavis
GitHub
GitHub - Klavis-AI/klavis: Klavis AI (YC X25): MCP integration layers that let AI agents use thousands of tools reliably.
Klavis AI (YC X25): MCP integration layers that let AI agents use thousands of tools reliably. - Klavis-AI/klavis
How I used Cursor AI to migrate a Bash test suite to Python
The migration of a large Bash container test suite to Python using the Cursor AI code editor saved about 1.5 months of development time, with Cursor handling script conversion, function replacement, and automated PyTest suite generation. Although the migration was not entirely smooth and required some manual fixes, the resulting Python test suite passed tests successfully, demonstrating ...
https://developers.redhat.com/articles/2025/09/23/how-i-used-cursor-ai-migrate-bash-test-suite-python#our_real_world_results
The migration of a large Bash container test suite to Python using the Cursor AI code editor saved about 1.5 months of development time, with Cursor handling script conversion, function replacement, and automated PyTest suite generation. Although the migration was not entirely smooth and required some manual fixes, the resulting Python test suite passed tests successfully, demonstrating ...
https://developers.redhat.com/articles/2025/09/23/how-i-used-cursor-ai-migrate-bash-test-suite-python#our_real_world_results
Red Hat Developer
How I used Cursor AI to migrate a Bash test suite to Python | Red Hat Developer
Migrating a large codebase from one language to another can be time-consuming. What if an AI tool could do the heavy lifting for you? Our team recently needed to migrate our Bash container test suite
VectorLiteDB
The SQLite for vector embeddings — A simple, embedded vector database that stores everything in a single file.
https://github.com/vectorlitedb/vectorlitedb
The SQLite for vector embeddings — A simple, embedded vector database that stores everything in a single file.
https://github.com/vectorlitedb/vectorlitedb
GitHub
GitHub - vectorlitedb/vectorlitedb: The SQLite for vector embeddings — A simple, embedded vector database that stores everything…
The SQLite for vector embeddings — A simple, embedded vector database that stores everything in a single file. - vectorlitedb/vectorlitedb
fastapi-radar
A powerful debugging dashboard for FastAPI applications. Monitor HTTP requests, SQL queries, and exceptions in real-time with a beautiful React UI. One-line integration, zero configuration needed.
https://github.com/doganarif/fastapi-radar
A powerful debugging dashboard for FastAPI applications. Monitor HTTP requests, SQL queries, and exceptions in real-time with a beautiful React UI. One-line integration, zero configuration needed.
https://github.com/doganarif/fastapi-radar
GitHub
GitHub - doganarif/fastapi-radar: A powerful debugging dashboard for FastAPI applications. Monitor HTTP requests, SQL queries,…
A powerful debugging dashboard for FastAPI applications. Monitor HTTP requests, SQL queries, and exceptions in real-time with a beautiful React UI. One-line integration, zero configuration needed. ...
Compiling Python to Run Anywhere
The article discusses an innovative approach to compiling Python code into cross-platform, ahead-of-time optimized machine code executables without modifying the original Python source. It details building a custom symbolic tracer, propagating types for lowering to C++, leveraging AI to generate C++ operators, and empirically optimizing performance across multiple hardware targets to ena...
https://blog.codingconfessions.com/p/compiling-python-to-run-anywhere
The article discusses an innovative approach to compiling Python code into cross-platform, ahead-of-time optimized machine code executables without modifying the original Python source. It details building a custom symbolic tracer, propagating types for lowering to C++, leveraging AI to generate C++ operators, and empirically optimizing performance across multiple hardware targets to ena...
https://blog.codingconfessions.com/p/compiling-python-to-run-anywhere
Codingconfessions
Compiling Python to Run Anywhere
A guest post on building a Python compiler that generates optimized kernels while preserving the language’s simplicity.
MapAnything
Universal Feed-Forward Metric 3D Reconstruction
https://github.com/facebookresearch/map-anything
Universal Feed-Forward Metric 3D Reconstruction
https://github.com/facebookresearch/map-anything
GitHub
GitHub - facebookresearch/map-anything: MapAnything: Universal Feed-Forward Metric 3D Reconstruction
MapAnything: Universal Feed-Forward Metric 3D Reconstruction - facebookresearch/map-anything
How Well Do New Python Type Checkers Conform? A Deep Dive into Ty, Pyrefly, and Zuban
The Python type checking landscape in 2025 includes three new Rust-based tools: Astral's ty, Meta's pyrefly, and Zuban. Ty emphasizes gradual adoption with fewer false positives, pyrefly focuses on aggressive inference to catch more issues early, and Zuban aims for seamless mypy compatibility; while conformance tests reveal differences, all show promise for real-world Python development.
https://sinon.github.io/future-python-type-checkers/
The Python type checking landscape in 2025 includes three new Rust-based tools: Astral's ty, Meta's pyrefly, and Zuban. Ty emphasizes gradual adoption with fewer false positives, pyrefly focuses on aggressive inference to catch more issues early, and Zuban aims for seamless mypy compatibility; while conformance tests reveal differences, all show promise for real-world Python development.
https://sinon.github.io/future-python-type-checkers/
Rob's Blog | Python • Rust • Ramblings?
How Well Do New Python Type Checkers Conform? A Deep Dive into Ty, Pyrefly, and Zuban — Rob's Blog | Python • Rust • Ramblings?
A comparison of three new Rust-based Python type checkers through the lens of typing spec conformance: Astral's ty, Meta's pyrefly, and David Halter's zuban
Cloud-Native Pipelines for Scientific Data Processing with Prefect and Dask
This article explains how to build scalable, cloud-native scientific data processing pipelines using Prefect for workflow orchestration and Dask for parallel computation. It covers cloud-optimized formats (like Zarr), integration with tools like xarray and echopype, and demonstrates end-to-end ETL pipelines that load, process, and store multidimensional data directly in the cloud.
https://oceanstream.io/cloud-native-data-processing-pipelines-with-prefect-and-dask/
This article explains how to build scalable, cloud-native scientific data processing pipelines using Prefect for workflow orchestration and Dask for parallel computation. It covers cloud-optimized formats (like Zarr), integration with tools like xarray and echopype, and demonstrates end-to-end ETL pipelines that load, process, and store multidimensional data directly in the cloud.
https://oceanstream.io/cloud-native-data-processing-pipelines-with-prefect-and-dask/
OceanStream
Cloud‑Native Pipelines for Scientific Data Processing with Prefect and Dask
An extended tutorial on the open-source libraries that we use to build the OceanStream cloud‑native data processing stack used to ingest data from sonar instruments and other marine sensors.
LLM-Deflate: Extracting LLMs Into Datasets
LLM-Deflate is a technique for systematically extracting structured datasets from trained large language models by probing their internal knowledge with hierarchical topic exploration and prompt engineering. This reverse-compression process enables model analysis, knowledge transfer, training data augmentation, and debugging, potentially making knowledge extraction a standard tool as inf...
https://www.scalarlm.com/blog/llm-deflate-extracting-llms-into-datasets
LLM-Deflate is a technique for systematically extracting structured datasets from trained large language models by probing their internal knowledge with hierarchical topic exploration and prompt engineering. This reverse-compression process enables model analysis, knowledge transfer, training data augmentation, and debugging, potentially making knowledge extraction a standard tool as inf...
https://www.scalarlm.com/blog/llm-deflate-extracting-llms-into-datasets
ScalarLM
LLM-Deflate: Extracting LLMs Into Datasets
Large Language Models compress massive amounts of training data into their parameters. This compression is lossy but highly effective—billions of parameters can encode the essential patterns from terabytes of text. However, what’s less obvious is that this…