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33 lines
1.3 KiB
Markdown
33 lines
1.3 KiB
Markdown
🌐 **English** · [Dansk](Description.da) · [Bahasa Melayu](Description.ms)
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# Description
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## What it does
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The program follows the steps of the lecture:
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1. `read_csv` reads the census file.
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2. `count_by_fur_color` counts the sightings of Gray, Cinnamon and Black.
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3. `build_summary` turns the counts into the rows of a summary.
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4. `write_csv` writes the summary to `squirrel_count.csv`.
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On the 2018 census file the result is Gray 2473, Cinnamon 392 and Black 103. Sightings without a fur colour are counted in none of them.
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## Why no Pandas
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The lecture uses Pandas. This project uses only the Python standard library (`csv` and `collections.Counter`) so that there is nothing to install to run it. The decision is recorded as ADR-0001 in the repository.
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## Layout
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| Path | Content |
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| --- | --- |
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| `src/squirrel/census.py` | The four steps above |
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| `src/squirrel/cli.py` | The command line, `python -m squirrel` |
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| `src/squirrel/constants.py` | Every literal, defined once |
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| `tests/` | The pytest tests |
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| `docs/` | Business case, plan, models, review records |
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## Quality
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Every document and every piece of code was reviewed against the checklists of the SQA and QC framework, in autonomous mode: the reviewer is an AI stand-in, so the reviews are not independent.
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