lineapy
codon
| lineapy | codon | |
|---|---|---|
| 7 | 34 | |
| 656 | 13,851 | |
| 0.5% | 0.6% | |
| 2.0 | 7.9 | |
| 9 months ago | 9 days ago | |
| Jupyter Notebook | C++ | |
| Apache License 2.0 | 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.
lineapy
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Rant: Jupyter notebooks are trash.
There are a few projects that can help close this gap between notebook prototype -> production. One of them is ipyflow (https://github.com/ipyflow/ipyflow), another is lineapy (https://github.com/linealabs/lineapy).
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The hand-picked selection of the best Python libraries and tools of 2022
LineaPy — notebooks in production
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Model artifacts mess and how to deal with it?
If you are mainly using python, there is a library called lineapy that is pretty much trying to solve all the challenges you just listed.
- lineapy: Data engineering, simplified. LineaPy creates a frictionless path for taking your data science artifact from development to production.
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Overwhelmed about consolidating code
Hi, I'm a contributor of LineaPy. We're building a tool that solves this problem. Our goal is to reduce the friction between developing Jupyter notebooks(or python scripts) and production codes.
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When to use Jupyter Notebooks vs. “Organized” Python Code?
I think you might want to give LineaPy a try! It is a tool trying to bridge the gap between Jupyter notebooks and production pipelines. One of the feature it provides is extracting codes only related to objects(you've selected) from your notebook into a python script and I think it is helpful for anyone who is using both Jupyter notebooks and python scripts.
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Introducing LineaPy!
GitHub
codon
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Should I Open Source my Company?
https://github.com/exaloop/codon/blob/develop/LICENSE
Here are some others: https://github.com/search?q=%22Business+Source+License%22+%2...
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Python running on the Dart VM?
I found at least one project that managed to compile python AOT to LLVM https://github.com/exaloop/codon. Even if LLVM is more expressive than Dart Kernel, that should at least be some evidence that this might not be too impractical.
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Codon: Python Compiler
Their fannkuch benchmark seems to be a bit dishonest. They claim an enormous perf delta on https://exaloop.io/benchmarks.html but fannkuch uses factorial a lot and they define factorial with a very small (n=20) table: https://github.com/exaloop/codon/blob/fb461371613049539654c1...
Disclaimer: I've worked on several Python runtimes and compilers, but I'm not by any means out to get Codon. Just happened across this by accident while looking at their inline LLVM, which is neat.
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The father of Swift made another baby: Mojo: looks to be based on Python using MLIR
If you literally want Python, but compiled ... Look at Codon: https://github.com/exaloop/codon
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Mojo – a new programming language for all AI developers
Another "Python with high-performance compiled builds" would be https://github.com/exaloop/codon.
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MIT Turbocharges Python’s Notoriously Slow Compiler
This is the project being discussed: https://github.com/exaloop/codon
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Is there a way to use turn a project into a single executable file that doesn't require anyone to do anything like install Python before using it?
Try Codon? https://github.com/exaloop/codon
- Since when did Python haters spread out everywhere? Maybe DNF5 would be faster because of ditched it, maybe.
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Budget HomeLab converted to endless money-pit
https://github.com/exaloop/codon might save you from the rewrite.
- What are your thoughts on Codon compiler having a paid licence?
What are some alternatives?
ruff - An extremely fast Python linter and code formatter, written in Rust.
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
lingua-py - The most accurate natural language detection library for Python, suitable for short text and mixed-language text
Numba - NumPy aware dynamic Python compiler using LLVM
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Cython - The most widely used Python to C compiler
python-benedict - :blue_book: dict subclass with keylist/keypath support, built-in I/O operations (base64, csv, html, ini, json, pickle, plist, query-string, toml, xls, xml, yaml), s3 support and many utilities.
taichi - Productive, portable, and performant GPU programming in Python.
ipyflow - A reactive Python kernel for Jupyter notebooks.
julia - The Julia Programming Language
whylogs - An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).