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import csv |
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import sys |
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from pathlib import Path |
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from datasets import load_dataset |
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from markdown_it import MarkdownIt |
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from mdit_plain.renderer import RendererPlain |
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from minicli import cli, run |
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from progressist import ProgressBar |
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csv.field_size_limit(sys.maxsize) |
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catalog = Path("datasets-filtered.csv") |
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@cli |
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def generate(): |
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""" |
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Loads catalog, parse markdown description, return concatenated title and description |
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""" |
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print("Loading corpus...") |
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corpus = [] |
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parser = MarkdownIt(renderer_cls=RendererPlain) |
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with catalog.open() as f: |
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reader = csv.DictReader(f) |
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lines = list(reader) |
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bar = ProgressBar(total=len(lines)) |
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for line in bar.iter(lines): |
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description = parser.render(line["description"]) |
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corpus.append({ |
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"id": line["id"], |
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"content": f'{line["title"]} {description}', |
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"tags": line["tags"], |
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}) |
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with open("data/datagouvfr-datasets.csv", "w") as f: |
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writer = csv.DictWriter(f, fieldnames=["id", "content", "tags"]) |
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writer.writeheader() |
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writer.writerows(corpus) |
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return corpus |
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@cli |
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def inspect(): |
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ds = load_dataset("abulte/datagouvfr-datasets", split="train") |
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print(list(zip(ds["id"][:10], ds["content"][:10], ds["tags"][:10]))) |
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if __name__ == "__main__": |
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run() |
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