Typst
Quarto
Obsidian.md
Astro Build
Nue
Reveal.js
Docusaurus
DuckDuckGo
Jupyter
Looker
Databricks
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
JupyterBased on our record, Jupyter seems to be a lot more popular than Typst. While we know about 205 links to Jupyter, we've tracked only 18 mentions of Typst. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I have been using Typst[1] for taking notes on machine learning. It's fast (updates are instantaneous). The syntax is almost like Markdown. I tried to learn LaTeX but Typst seems to have an easier learning curve. [1]: https://typst.app/. - Source: Hacker News / 3 months ago
I'd personally consider using Typst (https://typst.app) instead of LaTeX. It has a much more readable syntax and you don't need as much snippets to write it. You can use in on their website or run the compiler locally just like LaTeX. - Source: Hacker News / 3 months ago
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... - Source: Hacker News / 3 months ago
Have you seen typst? I have moved over from LaTex to Typst and most if not all your use cases are covered. https://typst.app/. - Source: Hacker News / 4 months ago
How does this compare to Typst?[1] What I like about Typst is that I can use it completely offline and with my editor of choice. Is this planned for htmldocs too? [1] https://typst.app/. - Source: Hacker News / 4 months ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 21 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / about 1 month ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 27 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
Quarto - Open-source scientific and technical publishing system built on Pandoc.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Obsidian.md - A second brain, for you, forever. Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Astro Build - Astro is the web framework that you'll love to use.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.