modin
pandoc
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modin | pandoc | |
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11 | 420 | |
9,476 | 32,396 | |
1.3% | - | |
9.6 | 9.8 | |
4 days ago | 6 days ago | |
Python | Haskell | |
Apache License 2.0 | GNU General Public License v2.0 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.
modin
- The Distributed Tensor Algebra Compiler (2022)
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A Polars exploration into Kedro
The interesting thing about Polars is that it does not try to be a drop-in replacement to pandas, like Dask, cuDF, or Modin, and instead has its own expressive API. Despite being a young project, it quickly got popular thanks to its easy installation process and its “lightning fast” performance.
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Modern Polars: an extensive side-by-side comparison of Polars and Pandas
Yeah, tried Polars a couple of times: the API seems worse than Pandas to me too. eg the decision only to support autoincrementing integer indexes seems like it would make debugging "hmmm, that answer is wrong, what exactly did I select?" bugs much more annoying. Polars docs write "blazingly fast" all over them but I doubt that is a compelling point for people using single-node dataframe libraries. It isn't for me.
Modin (https://github.com/modin-project/modin) seems more promising at this point, particularly since a migration path for standing Pandas code is highly desirable.
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Polars: The Next Big Python Data Science Library... written in RUST?
If anyone wants a faster version of pandas it’s not hard to find, modin for example uses multiple cores to speed it up, so if you have 4 cores it’s about 4 times faster than pandas, and has the same API as pandas.
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Working with more than 10gb csv
Modin should fit. It implements Pandas APIs with e.g. Ray as backend. https://github.com/modin-project/modin
- Modern Python Performance Considerations
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I made a video about efficient memory use in pandas dataframes!
If you really want speed you should try modin.pandas which makes pandas multi-threaded.
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Almost no one knows how easily you can optimize your AI models
I am guessing XGB is fairly optimised as it is. If you would want to use the sklearn libraries with pandas, look into Modin
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TIL about modin.pandas which significantly speeds up pandas if you import modin.pandas instead of pandas.
Source
- How to Speed Up Pandas with 1 Line of Code
pandoc
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Beautifying Org Mode in Emacs (2018)
My main authoring tool is then Emacs Markdown Mode (https://jblevins.org/projects/markdown-mode/). For data entry, it comes with some bells and whistles similar to org-mode, like C-c C-l for inserting links etc.
I seldom export my notes for external usage, but if it is the case, I use lowdown (https://kristaps.bsd.lv/lowdown/) which also comes with some nice output targets (among the more unusual are Groff and Terminal). Of cource pandoc (https://pandoc.org/) does a very good job here, too.
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Show HN: I made a tool to clean and convert any webpage to Markdown
This is one of those things that the ever-amazing pandoc (https://pandoc.org/) does very well, on top of supporting virtually every other document format.
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LaTeX makes me so angry at word
Folks feel the same way about Markdown versus LaTeX: why use something significantly more complicated where a looser, human-readable grammar works better?
For any other situations, I use https://pandoc.org/, or, generate a Word doc scriptomatically.
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📓 Versionner et builder l'eBook de son Entretien Annuel d'Evaluation sur Git(Hub)
pandoc toolchain pour builder une version confortable/imprimable en phase de travail (ePub, pdf, docx, html)
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Launch HN: Onedoc (YC W24) – A better way to create PDFs
Congrats on the launch, I guess, but there are so many free options that I can't think of a situation where paying $0.25 per document would be justified...? Just to name a few:
Back in the days, I used to use XSL-FO [0] and it was okay. It was not very precise but it rarely if ever broke, and was perfectly integrated with an XML/XSLT solution. Yeah, this was a long time ago.
Last month I used html-to-pdfmake [1] and it's also not very precise and more fragile, but very efficient and fast.
Yet another approach would be to pro grammatically generate .rtf files (for example) and use Pandoc [2] to produce PDFs (I have not tried this in production but don't see why it wouldn't work).
[0] https://en.wikipedia.org/wiki/XSL_Formatting_Objects
[1] https://www.npmjs.com/package/html-to-pdfmake
[2] https://pandoc.org/
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Ask HN: Looking for lightweight personal blogging platform
Others have mentioned static site generators. I like Hakyll [1] because it can tightly integrate with Pandoc [2] and allows you to develop custom solutions if your needs ever grow.
[1]: https://jaspervdj.be/hakyll/
[2]: https://pandoc.org/
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Show HN: CLI for generating beautiful PDF for offline reading
Have you compared it with a conversion by pandoc (https://pandoc.org/)?
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Pandoc
I have used it to kickstart a blogging project that I wish to come back to soon. The Lua inter-op for custom readers, writers and filters is great but I wish there was more editor integration and even perhaps an official IDE/editor with built-in debugging features (probably something already do-able with Emacs but I haven't checked). The only blocker for my project is no support for "ChunkedDoc" for Lua filters [1] which forces me to write more code and a complicated Makefile.
[1]: https://github.com/jgm/pandoc/issues/9061
- I don't always use LaTeX, but when I do, I compile to HTML (2013)
- What Happened to Pandoc-Discuss?
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
pandoc-highlighting-extensions - Extensions to Pandoc syntax highlighting
swifter - A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
obsidian-html - :file_cabinet: A simple tool to convert an Obsidian vault into a static directory of HTML files.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
obsidian-export - Rust library and CLI to export an Obsidian vault to regular Markdown
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Obsidian-MD-To-PDF - A command line python script to convert Obsidian md files to a pdf
PandasGUI - A GUI for Pandas DataFrames
kramdown - kramdown is a fast, pure Ruby Markdown superset converter, using a strict syntax definition and supporting several common extensions.
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
wavedrom - :ocean: Digital timing diagram rendering engine