Replace pandas-backed data_mod with a plain dict - #12
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bot.data_mod was a DataFrame used purely as a keyed collection (mask
by message_id, concat to append, iterrows to list) - no aggregation
or numeric computation anywhere, evidenced by mod_row["x"].values[0]
unwrapping scattered through moderacion.py. Replaced with a plain
dict[message_id, dict], loaded via a new utils.read_csv_dicts()
(csv.DictReader) instead of pd.read_csv.
- bot.py: builds bot.data_mod as {message_id: row} directly, filtering
out already-accepted/rejected ids via set operations instead of
DataFrame masking.
- moderacion.py: ValidatedPost.mod_row is now a plain dict (dropped
the now-unneeded condition: pd.Series field); lookups are
data_mod.get(post_id), removal is del data_mod[post_id],
get_mod_pending iterates data.values().
- pandas dropped from requirements.txt and every import.
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bot.data_mod was a DataFrame used purely as a keyed collection (mask by message_id, concat to append, iterrows to list) - no aggregation or numeric computation anywhere, evidenced by mod_row["x"].values[0] unwrapping scattered through moderacion.py. Replaced with a plain dict[message_id, dict], loaded via a new utils.read_csv_dicts() (csv.DictReader) instead of pd.read_csv.