Meta loves Python
Meta engineers discuss their contributions to Python 3.12, including new features such as custom JIT hooks, Immortal Objects, type system improvements, and faster comprehensions, highlighting their collaboration with the Python community and the company's support for open source
https://engineering.fb.com/2024/02/12/developer-tools/meta-loves-python/
Meta engineers discuss their contributions to Python 3.12, including new features such as custom JIT hooks, Immortal Objects, type system improvements, and faster comprehensions, highlighting their collaboration with the Python community and the company's support for open source
https://engineering.fb.com/2024/02/12/developer-tools/meta-loves-python/
Engineering at Meta
Meta loves Python
By now you’re already aware that Python 3.12 has been released. But did you know that several of its new features were developed by Meta? Meta engineer Pascal Hartig (@passy) is joined on the Meta …
How to avoid a count query in Django if you can
https://www.peterbe.com/plog/how-to-avoid-a-count-query-in-django-if-you-can
https://www.peterbe.com/plog/how-to-avoid-a-count-query-in-django-if-you-can
Peterbe
How to avoid a count query in Django if you can - Peterbe.com
ml-mgie
Apple's new open-source AI model that can edit images based on natural language instructions.
https://github.com/apple/ml-mgie
Apple's new open-source AI model that can edit images based on natural language instructions.
https://github.com/apple/ml-mgie
GitHub
GitHub - apple/ml-mgie
Contribute to apple/ml-mgie development by creating an account on GitHub.
modguard
A Python tool to enforce a modular, decoupled package architecture.
https://github.com/Never-Over/modguard
A Python tool to enforce a modular, decoupled package architecture.
https://github.com/Never-Over/modguard
GitHub
GitHub - gauge-sh/tach: A Python tool to visualize + enforce dependencies, using modular architecture 🌎 Open source 🐍 Installable…
A Python tool to visualize + enforce dependencies, using modular architecture 🌎 Open source 🐍 Installable via pip 🔧 Able to be adopted incrementally - ⚡ Implemented with no runtime impact ♾️ Intero...
Counting CPU Instructions in Python
Did you know it takes about 17,000 CPU instructions to print("Hello") in Python? And that it takes ~2 billion of them to import seaborn?
https://blog.mattstuchlik.com/2024/02/08/counting-cpu-instructions-in-python.html
Did you know it takes about 17,000 CPU instructions to print("Hello") in Python? And that it takes ~2 billion of them to import seaborn?
https://blog.mattstuchlik.com/2024/02/08/counting-cpu-instructions-in-python.html
Matt Stuchlik
Counting CPU Instructions in Python
Did you know it takes about 17,000 CPU instructions1 to print("Hello") in Python? And that it takes ~2 billion of them to import seaborn? Since writting this I have upgraded Cirron to substract its own overhead; it now measures print at ~9,000 instructions. ↩
Toolong
A terminal application to view, tail, merge, and search log files (plus JSONL).
https://github.com/textualize/toolong
A terminal application to view, tail, merge, and search log files (plus JSONL).
https://github.com/textualize/toolong
GitHub
GitHub - Textualize/toolong: A terminal application to view, tail, merge, and search log files (plus JSONL).
A terminal application to view, tail, merge, and search log files (plus JSONL). - Textualize/toolong
Why AI has a Python Problem
Artificial Intelligence (AI) has propelled Python to unprecedented popularity, making it the go-to language for developers and researchers worldwide. Yet, beneath the surface, a significant challenge looms. Let's get into the specific difficulties Python poses for AI's evolution, backed by real-world examples and technical insights.
https://www.youtube.com/watch?v=cGgTvMmtzNU
Artificial Intelligence (AI) has propelled Python to unprecedented popularity, making it the go-to language for developers and researchers worldwide. Yet, beneath the surface, a significant challenge looms. Let's get into the specific difficulties Python poses for AI's evolution, backed by real-world examples and technical insights.
https://www.youtube.com/watch?v=cGgTvMmtzNU
YouTube
Why AI has a Python Problem
Artificial Intelligence (AI) has propelled Python to unprecedented popularity, making it the go-to language for developers and researchers worldwide. Yet, beneath the surface, a significant challenge looms. Let's get into the specific difficulties Python…
HypoFuzz
Open source smart fuzzing for Python's best testing workflow.
https://github.com/Zac-HD/hypofuzz
Open source smart fuzzing for Python's best testing workflow.
https://github.com/Zac-HD/hypofuzz
GitHub
GitHub - Zac-HD/hypofuzz: Adaptive fuzzing of Hypothesis tests
Adaptive fuzzing of Hypothesis tests. Contribute to Zac-HD/hypofuzz development by creating an account on GitHub.
The Many Ways to Deploy a Model
There are many ways to deploy models and perform inference. Here, we share our decision rubric for model deployments using LLM inference as an example.
https://outerbounds.com/blog/the-many-ways-to-deploy-a-model
There are many ways to deploy models and perform inference. Here, we share our decision rubric for model deployments using LLM inference as an example.
https://outerbounds.com/blog/the-many-ways-to-deploy-a-model
Outerbounds
The Many Ways to Deploy a Model | Outerbounds
There are many ways to deploy models and perform inference. Here, we share our decision rubric for model deployments using LLM inference as an example.
Lag-Llama
Towards Foundation Models for Probabilistic Time Series Forecasting.
https://github.com/time-series-foundation-models/lag-llama
Towards Foundation Models for Probabilistic Time Series Forecasting.
https://github.com/time-series-foundation-models/lag-llama
GitHub
GitHub - time-series-foundation-models/lag-llama: Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting - time-series-foundation-models/lag-llama
Visualizing Neural Network Internals
Visualizing some of the internals of a neural network during training and inference.
https://www.youtube.com/watch?v=ChfEO8l-fas
Visualizing some of the internals of a neural network during training and inference.
https://www.youtube.com/watch?v=ChfEO8l-fas
YouTube
Visualizing Neural Network Internals
Visualizing some of the internals of a neural network during training and inference.
Starting and full code: https://github.com/Sentdex/neural-net-internals-visualized
Neural Networks from Scratch book: https://nnfs.io
Channel membership: https://www.y…
Starting and full code: https://github.com/Sentdex/neural-net-internals-visualized
Neural Networks from Scratch book: https://nnfs.io
Channel membership: https://www.y…
Summary of Major Changes Between Python Versions
This post is designed to be a quick reference for the major changes introduced with each new version of Python. This can help with taking advantages of using new features as you upgrade your code base, or ensuring that you have the correct guards for compatibility with older versions.
https://www.nicholashairs.com/posts/major-changes-between-python-versions/
This post is designed to be a quick reference for the major changes introduced with each new version of Python. This can help with taking advantages of using new features as you upgrade your code base, or ensuring that you have the correct guards for compatibility with older versions.
https://www.nicholashairs.com/posts/major-changes-between-python-versions/
NicholasHairs.com
Summary of Major Changes Between Python Versions
A quick reference for the major changes introduced with each new version of Python.
netease-youdao / QAnything
Question and Answer based on Anything.
https://github.com/netease-youdao/QAnything
Question and Answer based on Anything.
https://github.com/netease-youdao/QAnything
GitHub
GitHub - netease-youdao/QAnything: Question and Answer based on Anything.
Question and Answer based on Anything. Contribute to netease-youdao/QAnything development by creating an account on GitHub.