integrating documentation of command line functionality into docs
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- Dominant language
- Jupyter Notebook
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- 5
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Description
The previous version of the introduction notebook started with describing the command line functionality. An issue with this notebook for documenting the command line is that it doesn't include the descriptions that can be found by using the -h flag. We could run each function with both the -h flag and then the example. Note that this programs have functional equivalents now that we could decide largely supersede the command line programs at some point.
This text:
PmagPy is a software package for analyzing paleomagnetic and rock magnetic data using Python. These notebooks demonstrate how to use PmagPy in a Jupyter notebook or Python script. For examples of how to use PmagPy scripts on the command line, see the static version of PmagPy_cli. If you are running this notebook locally, you can click the following link to launch PmagPy-cli.ipynb
has been simplified to:
PmagPy is a software package for analyzing paleomagnetic and rock magnetic data using Python. These notebooks demonstrate how to use PmagPy in a Jupyter notebook. These examples can be adapted into Python scripts.
to try and keep things more straight forward for a new user.
The text
For examples of how to use PmagPy scripts on the command line, see the static version of PmagPy_cli.
could be added later.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the previous introduction notebook and PmagPy-cli.ipynb, then compare the command-line examples with each function's -h output. Run each function with both -h and its example, and update the documentation so the command-line functionality and its relationship to the notebook examples are clear.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- cli, documentation
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100