# Awesome Tools / Guides

## Tools

- Note taking:
- Real-time collaborative markdown: https://hackmd.io
- Organising:
- https://www.when2meet.com/
- https://calendly.com/
- Diagrams:
- Web-based but with XML download, linking to Google Drive etc: https://diagrams.net (formerly draw.io)
- Generate from text, inject into markdown: https://mermaid.live
[](https://mermaid.live/edit#pako:eNo1jMEOgjAQRH9l3TP8QA8aQW960YMH62HTFtrQUlOWGAP8uzXonCaZ92ZCFbVBgY2PL2UpMZwusoec_XSzxOAGOJsUyOndAmW5nWvvVAds8-ACtWaGahWqex2j3zwACwyrko-n7yiRrQlGoshVU-okyn7J3PjUxOaoHceEoiE_mAJp5Hh99woFp9H8oYOjNlH4UcsHHdw-AA)
(Documentation: https://mermaid-js.github.io/mermaid/)
- (plantUML is similar but more powerful, but more complex to set up)
- https://www.hackerdraw.com is good for simple quick diagrams
- Code sharing
- Record terminal sessions: https://asciinema.org/

- JupyterLab real-time collaboration (upcoming)
- Software engineering tools/services
- GitHub Actions: https://docs.github.com/en/actions

- Things that might be worth suggesting
- Pair programming (VSCode, PyCharm extensions; Terminal ...) with video call (free: 4people, 45min): https://duckly.com/
- ploomber.io
- https://notebooks.academy/en/latest/lessons/02-clean-nbs.html

## Learning resources

- general:
- https://coderefinery.org/lessons/
- https://software-carpentry.org/
- https://the-turing-way.netlify.app/
- Python in geoscience
- https://projectpythia.org/
- git:
- (the above +)
- https://learngitbranching.js.org/
- http://ndpsoftware.com/git-cheatsheet.html
- https://missing.csail.mit.edu/2020/version-control/
- testing:
- https://www.software.ac.uk/tags/unit-testing-scale-and-profit
- packaging:
- https://py-pkgs.org/
- https://www.pyopensci.org/python-package-guide/package-structure-code/intro.html
- data science pipeline / notebook tips:
- https://ploomber.io/blog/checklist/
- https://ploomber.io/blog/nbs-myths/
- https://ploomber.io/blog/clean-nbs/

- Organisations:
- SSI: https://www.software.ac.uk/ (might be able to get code review from them)