pants
Nuitka
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pants | Nuitka | |
---|---|---|
35 | 93 | |
3,094 | 10,744 | |
2.4% | 2.1% | |
9.8 | 10.0 | |
7 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
pants
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The xz attack shell script
> C/C++'s header system with conditional inclusion
Wouldn't it be more accurate to say something like "older build systems"? I don't think any of the things you listed are "modern". Which isn't a criticism of their legacy! They have been very useful for a long time, and that's to be applauded. But they have huge problems, which is a big part of why newer systems have been created.
FWIW, I have been using pants[0] (v2) for a little under a year. We chose it after also evaluating it and bazel (but not nix, for better or worse). I think it's really really great! Also painful in some ways (as is inevitably the case with any software). And of course it's nearly impossible to entirely stomp out "genrules" use cases. But it's much easier to get much closer to true hermeticity, and I'm a big fan of that.
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Monorepo + Microservices + Dependency Managment + Build system HELL
Does pants/bazel can help me?
- Pants 2: The ergonomic build system
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Go Dependency management in large company projects - How do you do it?
Hyper-large tech companies managing hyper-large monorepos using Bazel (google), buck (Facebook), please (thought machine), pants (Twitter, Foursquare & Square) enjoy them but also have a lot of resources devoted to running and maintaining it.
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Reason to use other Build Tool than Make?
Yeah there's definitely some alternatives out there. Pants is another one that has a lot of traction.
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Is it possible pickle a function with its dependencies?
You should look into pex, or it’s parent build system pants. A PEX (Python EXecutable) file can package up all your code including dependencies and run on another machine of similar OS with just an available compatible interpreter.
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Sanity check of my decision for "Iterative AI" (DVC, MLEM, CML) pipeline over Azure ML
We don't have the CD yet, but I think what I put in place counts as simple CI (even if incomplete)? Every push & PR trigger an azure pipeline, which runs pants. This install the dependencies from the lockfile, run some linters, uses DVC to pull the data necessary for tests, and run unit tests (mypy check is deactivated until I solve a weird error). Basically the same script runs on laptops cross-platform (one of us uses Max, one Ubuntu with GPU, one Ubuntu with CPU, the scripts runs on every platform). The only difference with CI is the installation of Pants and the gestion of Cache (needs to be downloaded in CI so it takes ~3min in CI versus 20 seconds on my laptop).
- Pants 2: fast, scalable, user-friendly build system for codebases of all sizes
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Maintain a Clean Architecture in Python with Dependency Rules
This has also been recently integrated in pants.
- Blazing fast CI with MicroVMs
Nuitka
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Python Is Portable
This is a good place to mention https://nuitka.net/ which aims to compile python programs into standalone binaries.
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We are under DDoS attack and we do nothing
For Python, you could make a proper deployment binary using Nuitka (in standalone mode – avoid onefile mode for this). I'm not pretending it's as easy as building a Go executable: you may have to do some manual hacking for more unusual unusual packages, and I don't think you can cross compile. I think a key element you're getting at is that Go executables have very few dependencies on OS packages, but with Python (once you've sorted the actual Python dependencies) you only need the packages used for manylinux [2], which is not too onerous.
[2] https://peps.python.org/pep-0599/#the-manylinux2014-policy
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Faster Blogging: A Developer's Dream Setup
glee is rich in blogging features but has some drawbacks. One of the main drawbacks is its compatibility with multiple operating systems and system architectures. We lost one potential customer due to glee incompatibility in macOS. Another major issue is the deployment time. We built the first version of glee entirely in Python and used nuitka, nuitka compiles Python programs into a single executable binary file. We need to create three separate stages for creating executable binaries for Windows, Mac, and Linux in deployment, and it takes around 20 minutes to complete.
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Python 3.13 Gets a JIT
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.
And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.
And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.
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Briefcase: Convert a Python project into a standalone native application
Nuitka deals pretty well with those in general: https://nuitka.net/
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Ask HN: How does Nuitka (Python compiler) work?
Hi HN,
Has anyone explored Nuitka [1] and developed understanding from a blank slate?
Is there any toy version of this, so that one can start playing with the language translation concepts?
Is there any underlying theory/inspiration upon which this project is built?
Are there any similar projects, in say other languages?
[1] https://github.com/Nuitka/Nuitka
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Why not tell people to “simply” use pyenv, poetry or anaconda
That's more of cultural problem in the Python community.
If I provide an end user software to my client written an Python (so not a backend, not a lib...), I will compile it with nuitka (https://github.com/Nuitka/Nuitka) and hide the stack trace (https://www.bitecode.dev/p/why-and-how-to-hide-the-python-st...) to provide a stand alone executable.
This means the users don't have to know it's made with Python or install anything, and it just works.
However, Python is not like Go or Rust, and providing such an installer requires more than work, so a huge part of the user base (which have a lot of non professional coders) don't have the skill, time or resources to do it.
And few people make the promotion of it.
I should write an article on that because really, nobody wants to setup python just to use a tool.
- Python cruising on back of c++
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Is cython a safe option for obfuscate a python project?
As for a simpler option, you could use a "compiler": https://github.com/Nuitka/Nuitka
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Extending web applications with WebAssembly and Python
> Your comment would make sense if Python code could be compiled into x86 or ARM assembly in the first place.
It can actually be compiled (or transpiled) into C code [1] with few limitations, so I can't see why not.
What are some alternatives?
Bazel - a fast, scalable, multi-language and extensible build system
PyInstaller - Freeze (package) Python programs into stand-alone executables
megalinter - 🦙 MegaLinter analyzes 50 languages, 22 formats, 21 tooling formats, excessive copy-pastes, spelling mistakes and security issues in your repository sources with a GitHub Action, other CI tools or locally.
pyarmor - A tool used to obfuscate python scripts, bind obfuscated scripts to fixed machine or expire obfuscated scripts.
please - High-performance extensible build system for reproducible multi-language builds.
PyOxidizer - A modern Python application packaging and distribution tool
pyflow - An installation and dependency system for Python
py2exe - modified py2exe to support unicode paths
pyupgrade - A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.
false-positive-malware-reporting - Trying to release your software sucks, mostly because of antivirus false positives. I don't have an answer, but I do have a list of links to help get your code whitelisted.
Buck - A fast build system that encourages the creation of small, reusable modules over a variety of platforms and languages.
py2app