Introducing fastpages, An easy to use blogging platform with extra features for Jupyter Notebooks.
Summary
fastpages is a newly released, free, ad-free blogging platform that leverages GitHub Pages and GitHub Actions to automate blog creation. It supports generating posts directly from Jupyter Notebooks, Microsoft Word documents, and Markdown files. Key features for Jupyter Notebooks include interactive Altair visualizations, collapsible code cells, and options to hide cell input/output. Users can define post metadata like title, summary, author, categories, and enable features such as a table of contents, Google Colab/GitHub links, and comments via front matter. The platform also supports embedding GitHub Flavored Emojis, images with captions, Twitter cards, YouTube videos, and various callout boxes. Setup is automated and requires no technical expertise, taking approximately three minutes.
Key takeaway
For data scientists or researchers looking to publish technical content, fastpages simplifies sharing interactive Jupyter Notebooks and code. You can quickly set up a free blog, automate post generation from your existing notebooks or Word documents, and enhance readability with features like collapsible code and interactive charts. This reduces friction in disseminating your work, allowing you to focus on content creation rather than blog infrastructure.
Key insights
fastpages offers automated, feature-rich blogging from Jupyter Notebooks, Word, or Markdown via GitHub Pages and Actions.
Principles
- Automate content conversion.
- Support multiple input formats.
- Integrate interactive elements.
Method
Save Jupyter notebooks, Word documents, or Markdown files into specified directories; GitHub Actions, powered by nbdev, automatically convert them into blog posts.
In practice
- Use front matter to control post features.
- Embed Altair charts for interactive data.
- Utilize `#collapse-hide` for cleaner code views.
Topics
- Automated Blogging
- Jupyter Notebooks
- GitHub Actions
- nbdev
- Interactive Data Visualization
Code references
Best for: Software Engineer, Data Scientist, Research Scientist
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Editorial summary, takeaway, and curation by AIssential. Original article published by Hamel Husain's Blog.