gotenberg
Pandas
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gotenberg | Pandas | |
---|---|---|
53 | 393 | |
6,693 | 41,923 | |
4.9% | 1.4% | |
8.9 | 10.0 | |
7 days ago | 3 days ago | |
Go | Python | |
MIT License | 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.
gotenberg
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Create PDFs with Tailwind
Use a server-side headless browser such as puppeteer to convert the HTML to PDF. This is the most reliable free option, but requires a server. If you need to use it in production, we recommend you use Gotenberg.
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Launch HN: Onedoc (YC W24) – A better way to create PDFs
We're using Gotenberg[1] to convert a rendered web page (with Elixir/Phoenix, in our case) to PDF. Works like a charm and we can use our existing frontend code/styling (including SVG graph generators) which is a huge bonus.
1: https://gotenberg.dev/
- Htmldocs: Typeset and Generate PDFs with HTML/CSS
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How to Simply Generate a PDF From HTML in Symfony With WeasyPrint
If you also want to convert Markdown or LibreOffice formats, the self-hosted API Gotenberg is worth checking out
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PDF rendering server-side using HTML 5 + CSS 3
I found a project that does exactly that (https://github.com/gotenberg/gotenberg). It’s my best bet for now, but I still need to test GraalVM integration with JS runtimes (and test JS libraries) and the Kotlin compiler targeting Node.
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PDF generation with Gotenberg
Gotenberg is a Docker-based stateless API for PDF generation from HTML and Markdown files.
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(Free) Open-source PDF Generation/Export
Think you mean https://gotenberg.dev ?
- Software welche PDF durchsuchbar macht?
- How to create a PDF?
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Best solution for generating pdf documents from templates
We use https://gotenberg.dev/ with handlebars templates.
Pandas
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Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
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What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
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How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
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10 Github repositories to achieve Python mastery
Explore here.
What are some alternatives?
DinkToPdf - C# .NET Core wrapper for wkhtmltopdf library that uses Webkit engine to convert HTML pages to PDF.
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
koodo-reader - A modern ebook manager and reader with sync and backup capacities for Windows, macOS, Linux and Web
tensorflow - An Open Source Machine Learning Framework for Everyone
PDFKit - A JavaScript PDF generation library for Node and the browser
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
go-wkhtmltopdf - Go bindings for wkhtmltopdf and high-level HTML to PDF conversion interface
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
docxtemplater - Generate docx, pptx, and xlsx from templates (Word, Powerpoint and Excel documents), from Node.js or the browser. Demo: https://www.docxtemplater.com/demo. #docx #office #generator #templating #report #json #generate #generation #template #create #pptx #docx #xlsx #react #vuejs #angularjs #browser #typescript #image #html #table #chart
Keras - Deep Learning for humans
PuppeteerSharp - Headless Chrome .NET API
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration