root
WeasyPrint
root | WeasyPrint | |
---|---|---|
31 | 43 | |
2,430 | 6,684 | |
1.5% | 2.0% | |
10.0 | 9.5 | |
3 days ago | 10 days ago | |
C++ | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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.
root
-
If you can't reproduce the model then it's not open-source
I think the process of data acquisition isn't so clear-cut. Take CERN as an example: they release loads of data from various experiments under the CC0 license [1]. This isn't just a few small datasets for classroom use; we're talking big-league data, like the entire first run data from LHCb [2].
On their portal, they don't just dump the data and leave you to it. They've got guides on analysis and the necessary tools (mostly open source stuff like ROOT [3] and even VMs). This means anyone can dive in. You could potentially discover something new or build on existing experiment analyses. This setup, with open data and tools, ticks the boxes for reproducibility. But does it mean people need to recreate the data themselves?
Ideally, yeah, but realistically, while you could theoretically rebuild the LHC (since most technical details are public), it would take an army of skilled people, billions of dollars, and years to do it.
This contrasts with open source models, where you can retrain models using data to get the weights. But getting hold of the data and the cost to reproduce the weights is usually prohibitive. I get that CERN's approach might seem to counter this, but remember, they're not releasing raw data (which is mostly noise), but a more refined version. Try downloading several petabytes of raw data if not; good luck with that. But for training something like a LLM, you might need the whole dataset, which in many cases have its own problems with copyrights…etc.
[1] https://opendata.cern.ch/docs/terms-of-use
[2] https://opendata.cern.ch/docs/lhcb-releases-entire-run1-data...
[3] https://root.cern/
- What software is used to generate plots/graphs like this seen in many particle physics papers?
-
Interactive GCC (igcc) is a read-eval-print loop (REPL) for C/C++
The odd part is that this is not just for fun. For many physicists when I was at CERN, a C++ REPL was a commonly used tool to interactively debug analyses to such a degree that many never compiled their code. Back then, I believe, it was some custom implementation included in ROOT (https://root.cern/). I even went out of my way to write C++ code compatible to it just so it could run with this implementation, otherwise some colleagues weren't interested in collaborating at all.
-
Stable Diffusion in pure C/C++
That Python ML code is calling C++ code running in the GPU, one more reason to use C++ across the whole stack.
CERN already used prototyping in C++, with ROOT and CINT, 20 years ago.
https://root.cern/
Nowadays it is even usable from Netbooks via Xeus.
It is more a matter of lack of exposure to C++ interpreters than anything else.
- Root: Analyzing Petabytes of Data, Scientifically
-
Aliens might be waiting for humans to solve a puzzle
Quantum computing is a pretty interesting science too. https://home.cern/news/press-release/knowledge-sharing/cern-quantum-technology-initiative-unveils-strategic-roadmap they have to deal with lots of data streaming too https://root.cern/
-
cppyy Generated Wrappers and Type Annotations
I'm a user of CERN's ROOT (https://root.cern/) and while I'd usually write in C++, I've been trying to write as much Python as I can recently to get a bit better in the language.
- Root: Analyzing Petabytes of Scientific Data
-
Span: how to cast pointer of pointer to other types?
I'm dealing with a C++ software called ROOT made by CERN, which is, if I'm not wrong, the only C++ API that we could use for data analysis such as plotting histograms, fitting multi-parameter functions and storing data in the size of TB to the disk and many more. That's the only reason why physicists still stick to this software. you can check here .
-
How exactly would you go about writing a program to simplify algebraic expressions?
Hey, I found something which could be useful: https://root.cern
WeasyPrint
-
Launch HN: Onedoc (YC W24) – A better way to create PDFs
Is there a reason you didn't consider something like Weasyprint?
https://weasyprint.org
I've gone through a number of systems to convert CV's, business cards, and other docs and it hasn't let me down yet.
-
CSS for Printing to Paper
You don't _have_ to use a browser. I had very good results with Weasyprint [0]. And there's also PrinceXML [1] if you're willing to pay.
[0]: https://weasyprint.org/
-
Show HN: A new open-source library to design PDF using React
Thanks for your answer! I imagined you would be using PrinceXML behind the scenes since that is probably the gold standard in HTML+CSS rendering.
The only open source alternative I know of is WeasyPrint at https://weasyprint.org/. I'm not sure how well it fares against PrinceXML, though.
And thanks for the pointer to Taffy - I didn't know it before!
- 1.5M PDFs in 25 Minutes
-
Htmldocs: Typeset and Generate PDFs with HTML/CSS
Flexbox support has been [included][1] since 2018, although my use case was the prototypical one - a single row w/ 3 columns - so YMMV with how it handles more complex layouts.
[1]: https://github.com/Kozea/WeasyPrint/pull/579
-
How to Simply Generate a PDF From HTML in Symfony With WeasyPrint
Performance is not the strength of WeasyPrint, meaning that heavy HTML files will increase generation time. You should always compress images before attaching them, as they are not compressed by default. Generating a 50-page-long PDF may take up to a minute in extreme cases, although multi-page documents generated on my project take fewer than 2 seconds to generate.
-
Show HN: Invoice Dragon – An Open Source App to Create PDF Invoices for Free
For Python there is Weasyprint: you prepare the invoice as an HTML document, and Weasyprint turns it into a PDF
https://weasyprint.org/
-
The Gemini protocol seen by this HTTP client person (curl dev)
Well yes, but you can implement HTML+CSS. WeasyPrint did from scratch, and independent implementations of HTML+CSS are considerably more numerous than HTML+CSS+JS.
-
Library to convert HTML to pdf in Golang
In a recent project I used https://github.com/Kozea/WeasyPrint/ it is written in python, so you will need to use it like so:
-
RE: If you had to pick a library from another language (Rust, JS, etc.) that isn’t currently available in Python and have it instantly converted into Python for you to use, what would it be?
You should maybe check out weasyprint. https://weasyprint.org/
What are some alternatives?
PyMesh - Geometry Processing Library for Python
ReportLab
xeus - Implementation of the Jupyter kernel protocol in C++
PyPDF2 - A pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files
tfgo - Tensorflow + Go, the gopher way
WKHTMLToPDF - Convert HTML to PDF using Webkit (QtWebKit)
windows-telemetry-blocklist - Blocks outgoing Windows telemetry, compatible with Pi-Hole.
QuestPDF - QuestPDF is a modern open-source .NET library for PDF document generation. Offering comprehensive layout engine powered by concise and discoverable C# Fluent API. Easily generate PDF reports, invoices, exports, etc.
decimal - Arbitrary-precision fixed-point decimal numbers in Go
PDFMiner - Python PDF Parser (Not actively maintained). Check out pdfminer.six.
apd - Arbitrary-precision decimals for Go
MathJax - Beautiful and accessible math in all browsers