Django: fixing a memory “leak” from Python 3.14’s incremental garbage collection
Adam Johnson explains how Python 3.14's new incremental garbage collection caused excessive memory growth during Django migrations, leading to out-of-memory errors on resource-constrained servers. He shares a practical workaround by explicitly triggering garbage collection after each migration step, and notes the issue helped support the planned revert to the prior GC behavior in Python ...
https://adamj.eu/tech/2026/04/20/django-python-3.14-incremental-gc/
Adam Johnson explains how Python 3.14's new incremental garbage collection caused excessive memory growth during Django migrations, leading to out-of-memory errors on resource-constrained servers. He shares a practical workaround by explicitly triggering garbage collection after each migration step, and notes the issue helped support the planned revert to the prior GC behavior in Python ...
https://adamj.eu/tech/2026/04/20/django-python-3.14-incremental-gc/
adamj.eu
Django: fixing a memory “leak” from Python 3.14’s incremental garbage collection - Adam Johnson
Back in February, I encountered an out-of-memory error while migrating a client project to Python 3.14. The issue occurred when running Django’s database migration command (migrate) on a limited-resource server, and seemed to be caused by the new incremental…
browser-harness
Self-healing browser harness that enables LLMs to complete any task.
https://github.com/browser-use/browser-harness
Self-healing browser harness that enables LLMs to complete any task.
https://github.com/browser-use/browser-harness
GitHub
GitHub - browser-use/browser-harness: Browser Harness | Self-healing harness that enables LLMs to complete any task.
Browser Harness | Self-healing harness that enables LLMs to complete any task. - browser-use/browser-harness
I built a dev blog! First deep dive: How Ruff and UV changed my mind about Python setups.
https://www.reddit.com/r/Python/comments/1s7lna7/i_built_a_dev_blog_first_deep_dive_how_ruff_and/
https://www.reddit.com/r/Python/comments/1s7lna7/i_built_a_dev_blog_first_deep_dive_how_ruff_and/
Reddit
From the Python community on Reddit: I built a dev blog! First deep dive: How Ruff and UV changed my mind about Python setups.
Explore this post and more from the Python community
lingbot-map
A feed-forward 3D foundation model for reconstructing scenes from streaming data.
https://github.com/Robbyant/lingbot-map
A feed-forward 3D foundation model for reconstructing scenes from streaming data.
https://github.com/Robbyant/lingbot-map
GitHub
GitHub - Robbyant/lingbot-map: A feed-forward 3D foundation model for reconstructing scenes from streaming data
A feed-forward 3D foundation model for reconstructing scenes from streaming data - Robbyant/lingbot-map
Best Python framework for industry-level desktop app? (PySide/PyQt/wxPython/Kivy/Web approacg)
https://www.reddit.com/r/Python/comments/1s9oh61/best_python_framework_for_industrylevel_desktop/
https://www.reddit.com/r/Python/comments/1s9oh61/best_python_framework_for_industrylevel_desktop/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Reimagine Python Notebooks in the AI Era
Traditional notebooks are evolving as AI shifts more value from writing syntax to guiding workflows, reviewing outputs, and iterating through natural-language prompts. The emerging model emphasizes reactive cells and integrated LLM tooling that can turn linear notebooks into more interactive, dynamic applications.
https://mljar.com/blog/reimagine-python-notebook-in-ai-era/
Traditional notebooks are evolving as AI shifts more value from writing syntax to guiding workflows, reviewing outputs, and iterating through natural-language prompts. The emerging model emphasizes reactive cells and integrated LLM tooling that can turn linear notebooks into more interactive, dynamic applications.
https://mljar.com/blog/reimagine-python-notebook-in-ai-era/
MLJAR
Reimagine Python Notebooks in the AI Era
We describe how conversational notebook works in MLJAR Studio. It is a virtual AI Data Analyst that can answer data analysis questions using Python behind scenes. It was created on top of Jupyter notebook but has user frinedly design and is AI powered.
What Most Python Developers Miss About Generators
Most Python developers view generators as a memory optimization, but their deeper value is controlling when computation happens and how data flows through a system. They enable lazy pipelines, backpressure handling, two-way communication, and patterns that extend naturally into async streaming architectures.
https://www.youtube.com/watch?v=5VN-3rIUPZ8
Most Python developers view generators as a memory optimization, but their deeper value is controlling when computation happens and how data flows through a system. They enable lazy pipelines, backpressure handling, two-way communication, and patterns that extend naturally into async streaming architectures.
https://www.youtube.com/watch?v=5VN-3rIUPZ8
YouTube
What Most Python Developers Miss About Generators
Talk to the internet when you need answers. Talk to Recall when you need your answers. 🔗 https://www.recall.it/?t=arjan Use code ARJAN25 for 25% off, valid until 1 June 2026.
Do the Ports & Adapters quiz here: https://app.getrecall.ai/challenge/e24770a5…
Do the Ports & Adapters quiz here: https://app.getrecall.ai/challenge/e24770a5…
Array API adoption: Performance wins across the ecosystem
Adopting the Array API standard lets major Python libraries run the same code across backends like NumPy, PyTorch, CuPy, and JAX, unlocking dramatic speedups with minimal user changes. The broader impact is a more interoperable scientific Python ecosystem where GPU acceleration and new hardware become accessible without rewriting entire libraries.
https://labs.quansight.org/blog/array-api-meta-blogpost
Adopting the Array API standard lets major Python libraries run the same code across backends like NumPy, PyTorch, CuPy, and JAX, unlocking dramatic speedups with minimal user changes. The broader impact is a more interoperable scientific Python ecosystem where GPU acceleration and new hardware become accessible without rewriting entire libraries.
https://labs.quansight.org/blog/array-api-meta-blogpost
Community consensus on when to use dataclasses vs non-OO types?
https://www.reddit.com/r/Python/comments/1s7v9ug/community_consensus_on_when_to_use_dataclasses_vs/
https://www.reddit.com/r/Python/comments/1s7v9ug/community_consensus_on_when_to_use_dataclasses_vs/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Implementing MikroTik's Binary API Protocol in Python from Scratch
A deep dive into implementing MikroTik's proprietary RouterOS binary API protocol in Python — variable-length encoding, sentence-based messaging, and programmatic network infrastructure control. Zero dependencies, 137 lines.
https://www.joekarlsson.com/blog/implementing-mikrotik-binary-api-protocol-in-python/
A deep dive into implementing MikroTik's proprietary RouterOS binary API protocol in Python — variable-length encoding, sentence-based messaging, and programmatic network infrastructure control. Zero dependencies, 137 lines.
https://www.joekarlsson.com/blog/implementing-mikrotik-binary-api-protocol-in-python/
Joe Karlsson
Implementing MikroTik's Binary API Protocol in Python from Scratch | Joe Karlsson
A deep dive into implementing MikroTik's proprietary RouterOS binary API protocol in Python — variable-length encoding, sentence-based messaging, and programmatic network infrastructure control. Zero dependencies, 137 lines.
Dinobase
Dinobase is an agent-first data platform that syncs 100+ sources like APIs, databases, files, and MCP servers into SQL-ready tables with automatic data annotation.
https://github.com/DinobaseHQ/dinobase
Dinobase is an agent-first data platform that syncs 100+ sources like APIs, databases, files, and MCP servers into SQL-ready tables with automatic data annotation.
https://github.com/DinobaseHQ/dinobase
GitHub
GitHub - DinobaseHQ/dinobase: The agent-first data platform
The agent-first data platform. Contribute to DinobaseHQ/dinobase development by creating an account on GitHub.
What’s a low memory way to run a Python http endpoint?
https://www.reddit.com/r/Python/comments/1slbp28/whats_a_low_memory_way_to_run_a_python_http/
https://www.reddit.com/r/Python/comments/1slbp28/whats_a_low_memory_way_to_run_a_python_http/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Alishahryar1 / free-claude-code
Use claude-code for free in the terminal, VSCode extension or via discord like openclaw
https://github.com/Alishahryar1/free-claude-code
Use claude-code for free in the terminal, VSCode extension or via discord like openclaw
https://github.com/Alishahryar1/free-claude-code
GitHub
GitHub - Alishahryar1/free-claude-code: Use claude-code for free in the terminal, VSCode extension or discord like OpenClaw (voice…
Use claude-code for free in the terminal, VSCode extension or discord like OpenClaw (voice supported) - Alishahryar1/free-claude-code
ai-engineering-from-scratch
From linear algebra to autonomous agent swarms. learn AI with AI, then ship the tools.
https://github.com/rohitg00/ai-engineering-from-scratch
From linear algebra to autonomous agent swarms. learn AI with AI, then ship the tools.
https://github.com/rohitg00/ai-engineering-from-scratch
GitHub
GitHub - rohitg00/ai-engineering-from-scratch: Learn it. Build it. Ship it for others.
Learn it. Build it. Ship it for others. Contribute to rohitg00/ai-engineering-from-scratch development by creating an account on GitHub.
Exploring Petabytes of the Night Sky — Jupyter Notebooks at NOIRLab’s Astro Data Lab Science Platform
The post shows how NOIRLab’s Astro Data Lab uses Jupyter notebooks to let astronomers explore and analyze petabytes of sky data directly in the browser, without local setup. It also highlights the value of notebooks for making large-scale astronomy workflows more interactive, reproducible, and accessible to researchers and students.
https://blog.jupyter.org/exploring-petabytes-of-the-night-sky-jupyter-notebooks-at-noirlabs-astro-data-lab-science-ae012dfd4723
The post shows how NOIRLab’s Astro Data Lab uses Jupyter notebooks to let astronomers explore and analyze petabytes of sky data directly in the browser, without local setup. It also highlights the value of notebooks for making large-scale astronomy workflows more interactive, reproducible, and accessible to researchers and students.
https://blog.jupyter.org/exploring-petabytes-of-the-night-sky-jupyter-notebooks-at-noirlabs-astro-data-lab-science-ae012dfd4723
Medium
Exploring Petabytes of the Night Sky — Jupyter Notebooks at NOIRLab’s Astro Data Lab Science Platform
By Robert Nikutta & Stéphanie Juneau (NSF NOIRLab)
Building a Python Library in 2026
So you want to build a Python library in 2026? Here's everything you need to know about the state of the art.
https://stephenlf.dev/blog/python-library-in-2026/
So you want to build a Python library in 2026? Here's everything you need to know about the state of the art.
https://stephenlf.dev/blog/python-library-in-2026/
stephenlf.dev
Building a Python Library in 2026
So you want to build a Python library in 2026? Here's everything you need to know about the state of the art.