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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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github-orgmode-tests
This is a test project where you can explore how github interprets Org-mode files
i strongly agree with what you are saying about Jupyter, however i strongly disagree about using netobooks in general
one of the key things that a good notebook system must allow you to do is to mix something like markup format + LaTeX + source code. writing math-heavy documentation and explanations is simply impractical and limited (readability suffers) if done in comments. jupyter however is severely limited as it is unreadable in its raw format and therefore does not play well with a version control system such as git
instead there is a solution that allows one to do everything jupyter does good with the additional benefit that it plays with version control really well - ie org-mode [1]. the only difference is that instead of using a browser to interact with it, you use emacs. the added benefit to this is that you can also use full-featured key bindings (emacs / vim) and even integrate a language server for auto-completion [2]
[1] https://orgmode.org/
[2] https://emacs-lsp.github.io/lsp-mode/manual-language-docs/ls...
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I use this plugin for my jupyter notebook git integration. It has a git diff option that's useful but gets very slow for complex documents. Perhaps under the hood it's using one of the other tools mentioned in the postscript.
https://github.com/jupyterlab/jupyterlab-git
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If there a good place to see Jupyter note books solving a real problem?
Idk, like importing some data and doing some analysis / forecasting?
Most notebooks appear really bad quality. Worse internally.
Better off looking at some excel https://github.com/martinshkreli/models
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Others have mentioned the usefulness of literate programming so I won't reiterate that.
Partially the lack of discipline comes from the implicit data dependancies between cells. Variables are all globally scoped and unless you ensure the notebook can be ran top to bottom its easy to introduce subtle bugs. I believe Julia's https://github.com/fonsp/Pluto.jl solves this issue quite well.
Another part comes from cells that should really be functions. In my opinion this is because functions are 2nd class citizens compared to cells, and could be improved with UI (function cells? node based programming?).
Programming is more than just manipulating text, so why shouldn't tools move in a direction of just being fancy text editors?
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nb-clean
Clean Jupyter notebooks for version control. Remove metadata, outputs, and execution counts with Git and pre-commit support.
https://github.com/srstevenson/nb-clean ?
Has been my go to for this. It seems like nbdev2 is fastais own cooked solution with a bunch of other tools.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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> It would be nice if there were something that would make out-of-order problems light up, the way that code editors can highlight errors while you're editing.
Check out https://github.com/nbsafety-project/nbsafety
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