58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
import argparse
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from collections.abc import Iterator
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import datetime
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import urllib.parse
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from pathlib import Path
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from personal_data.util import load_csv_file
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from ..data import WorkSample
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def iterate_samples_from_dicts(rows: list[dict]) -> Iterator[WorkSample]:
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max_title_parts = 2
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for event_data in rows:
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# Select data
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possible_time_keys = [
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k for k, v in event_data.items() if isinstance(v, datetime.date)
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]
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possible_name_keys = [k for k, v in event_data.items() if isinstance(v, str)]
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possible_image_keys = [
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k for k, v in event_data.items() if isinstance(v, urllib.parse.ParseResult)
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]
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possible_misc_keys = list(event_data.keys())
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for k in possible_image_keys:
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if k in possible_misc_keys:
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possible_misc_keys.remove(k)
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del k
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for k in possible_time_keys :
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if k in possible_misc_keys:
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possible_misc_keys.remove(k)
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del k
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date = event_data[possible_time_keys[0]] if possible_time_keys else None
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image = event_data[possible_image_keys[0]] if possible_image_keys else None
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if date is None:
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continue
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title = ': '.join(event_data[k] for k in possible_name_keys[:max_title_parts])
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description = '\n\n'.join(event_data[k] for k in possible_name_keys[max_title_parts:])
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labels = [f'{k}:{event_data[k]}' for k in possible_misc_keys]
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# Create event
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yield WorkSample(
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labels=tuple(labels),
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start_at=None,
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end_at=date,
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)
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del event_data
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def iterate_samples_from_csv_file(file_path: Path) -> Iterator[WorkSample]:
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dicts = load_csv_file(file_path)
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yield from iterate_samples_from_dicts(dicts)
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