datasci/ds-voidlinux-popcorn
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Validate CSV output schemas

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Also moved code dir to src.
There are reasons to do standard things in standard ways. While it is
possible to get the `code/` directory to work, and recognize it as a
package path, this requires wrangling the pyproject.toml file.
Additionally, any import from the `code.something` path automatically
shadows the python stdlib `code` module. While it may not be necessary,
it still is good to not shadow standard library modules.
This commit is contained in:
Marty Oehme 2025-09-30 22:14:30 +02:00
parent de96b67fac
commit 2faeda87c3
Signed by: Marty
GPG key ID: 4E535BC19C61886E
14 changed files with 111 additions and 7 deletions
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code/README.md
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# Popcorn dataset code
Each script can be run stand-alone like `python code/files.py <input-dir> <output-dir>`,
exchanging the script file for the one intended.
It is suggested, however, to run the scripts using the `just` command runner from the
dataset root, such as `just files` for the same effect as above.
This will automatically populate the correct input and output directories.
To create new `datalad` versioned output data, run `just versioned` or `just` without any arguments.
A new commit containing the updated data will be created,
and an automatic entry in the CHANGELOG made.