Poetry
cinder
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Poetry | cinder | |
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377 | 43 | |
29,397 | 3,371 | |
2.3% | 0.7% | |
9.6 | 9.4 | |
2 days ago | 2 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Poetry
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Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
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Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
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From Kotlin Scripting to Python
Poetry
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How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
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Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
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Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
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Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
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Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
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Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
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How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
cinder
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Meta Used Monolithic Architecture to Ship Threads in Only Five Months
Meta is actually contributing directly to upstream cpython. If you really wanted to, the internal fork is also open source: https://github.com/facebookincubator/cinder
- Meta pledges Three-Year sponsorship for Python if GIL removal is accepted
- Back end of Meta Threads is built with Python 3.10 with some interesting tweaks
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Lessons from Mojo for PHP 10+ ?
Just one example: last year Meta open-sourced Cinder, which powers Instagram and provides sizeable speedups compared to CPython.
- Python true static typing
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Best book on writing an optimizing compiler (inlining, types, abstract interpretation)?
I used to work on the Cinder JIT and can help document any passes you find interesting or confusing.
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Python-based compiler achieves orders-of-magnitude speedups
You might enjoy Cinder then. It's based on CPython so it is nearly 100% compatible.
https://github.com/facebookincubator/cinder/
Disclaimer: I used to work on it.
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beartype: It has documentation now. It only took two years, my last hair follicle, precious sanity points (SPs), and working with Sphinx. Don't be like @leycec. Go hard on documentation early.
I think Cinder's Static Python, which also performs runtime type checking, is more ambitious. Though it's not production ready yet.
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If there’s gonna be a Python 4.0 one day, what’s a breaking change you’d like to see? Let’s explore the ideas you have that can make Python even better!
Here's a fork that implements that https://github.com/facebookincubator/cinder - it might be nice to one day get that up streamed but obviously it'll be controversial and it certainly needs more time to bake. Hopefully at some point we can make it a pip installable extension though.
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Is it time for Python to have a statically-typed, compiled, fast superset?
The other thing that was interesting to me, was the potential of type annotations to help make for a faster, safer experience on the compiler end of things. One example is seen in Meta’s Cinder project, on the docs it explains how typing can be used to reduce the number of steps for the compiler ([cinder/static_python.rst at cinder/3.8 · facebookincubator/cinder · GitHub](https://github.com/facebookincubator/cinder/blob/cinder/3.8/CinderDoc/static_python.rst)), making it more effective.
What are some alternatives?
Pipenv - Python Development Workflow for Humans.
faster-cpython - How to make CPython faster.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
hatch - Modern, extensible Python project management
Pyjion
pyenv - Simple Python version management
graalpython - A Python 3 implementation built on GraalVM
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
MonkeyType - A Python library that generates static type annotations by collecting runtime types
virtualenv - Virtual Python Environment builder
hpy - HPy: a better API for Python