typst
orange
typst | orange | |
---|---|---|
110 | 27 | |
28,505 | 4,619 | |
4.3% | 1.0% | |
9.8 | 9.6 | |
3 days ago | 8 days ago | |
Rust | Python | |
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.
typst
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German state ditches Microsoft for Linux and LibreOffice
https://github.com/typst/typst looks promising, both the language and the tooling. I wonder where it will find its place in a world that is dominated by either Word or LaTex.
- Ask HN: What Underrated Open Source Project Deserves More Recognition?
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LaTeX and Neovim for technical note-taking
I hope in a couple of years we start seeing posts like these with Typst instead of LaTeX. It seems like setting this up would be a bit easier since Typst is much more concise than LaTeX.
[0] https://github.com/typst/typst
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I'm able to take notes in mathematics lectures using LaTeX and Vim (2019)
For writing math notes (especially in vim), I switch to using Typst (https://typst.app).
Here's a few points:
- The syntax is a lot lighter and easier to type fast. I was up and running in half hour after starting to use it. Once in a while I can look up some symbol name in the docs but that's about it.
- Empty document is a valid document. No preambles, no includes etc, it's all optional and the defaults are sensible. Just start typing.
- It's incremental. Live preview from neovim is in the browser and it's lightning fast, pretty much immediate. No pdf sync pain. No build files, makefiles and all that. Just start typing.
While it's not going to beat latex in terms of serious academic use, for personal use and notes it's close to perfect.
(And of course it's written in Rust...)
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I don't always use LaTeX, but when I do, I compile to HTML (2013)
Except the main theme, which was HTML export? https://github.com/typst/typst/issues/721
Though it's in the roadmap!
- Htmldocs: Typeset and Generate PDFs with HTML/CSS
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"LibreOffice is better at reading old Word files than Word"
I don't use LaTeX for anything these days but Typst popped up recently and seems like a decent alternative: https://github.com/typst/typst
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Which software do you use to create presentations using Vim that is superior to existing ones?
I am surprised that no one mentions the typst. It is super smooth with typst-preview.
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Bibliography CSL
I suggest you ask in the discord channel: https://discord.gg/2uDybryKPe. Or open an issue or question on GitHub: https://github.com/typst/typst
- Besseres Schreibprogramm als Word?
orange
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Hierarchical Clustering
I know I've tooted its horn before, but Orange3 is a pretty neat Python-based GUI platform that makes this and a metric buttload of other statistical/ML techniques available to non-programmer types.
Just watch out for null character `x00` in the corpus. That always seems to kill it stone dead.
https://orangedatamining.com/
https://orange3.readthedocs.io/projects/orange-visual-progra...
- Orange Data Mining
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The Graph of Wikipedia [video]
For all you folks who aren't ace programmer types, the Orange3[1] platform gives you a very miniaturized[2] ability to turn out these sorts of visualizations very rapidly. It's not the most stable thing in the world, but the node-based ML workflow designer is worth the price of admission all by itself.
[1] https://orangedatamining.com/
[2] The Wikipedia extension in Text limits each search result to 25 articles, so sucking all of Wikipedia is . . well, Orange text analytics crashes when I look at it sideways with a null character, so let's not think about what would happen.
- Ask HN: What Underrated Open Source Project Deserves More Recognition?
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Taxonomy Management?
First is identifying the "similar" things in a corpus. Best way I know to do that, for non-programmer audiences, is the Orange Data Mining tool, which gives you a node-based text mining interface to perform statistical analysis on text. Hierarchical Clustering shows - very rapidly - how similar your "modules" are, which ones are most similar. There's many other techniques (semantic viewer, similarity hash, etc) as well - the right one will depend on how your content is laying about.
- Orange: Open-source machine learning and data visualization
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What exactly is AutoGPT?
Both tools are ripoffs of a data mining framework named Orange 3
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Why don't more people use Altair for python Visualizations instead of Plotly?
You should also check out Orange Data Mining, it allows to create a lot of charts, filter data from a chart to another, build ML models, predictions and a lot more. And you can do it with zero code.
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Advice on Transitioning to Data Science/ML/AI without Coding Experience
You can start with a free GUI based tool Orange. It is a component based data science workflow tool, which you can use to handle 60-75% of the traditional data science tasks from classification, regression, to basic neural networks.
- Has anybody used Orange?
What are some alternatives?
asciidoctor-latex - :triangular_ruler: Add LaTeX features to AsciiDoc & convert AsciiDoc to LaTeX
glue - Linked Data Visualizations Across Multiple Files
typst.nvim - WIP. Goals: Treesitter highlighting, snippets, and a smooth intergration with neovim.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
KeenWrite - Free, open-source, cross-platform desktop Markdown text editor with live preview, string interpolation, and math.
RDKit - The official sources for the RDKit library
typst-lsp - A brand-new language server for Typst, plus a VS Code extension
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
json-resume-template - JSON-based standard for resume
Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python
tree-sitter-typst - A TreeSitter parser for the Typst File Format
NumPy - The fundamental package for scientific computing with Python.