Use raw SQLite executemany for bulk database writes#268
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Replace Peewee ORM insert_many() calls in _efficient_write_many_data with raw cursor.executemany(), bypassing per-row ORM overhead. The old approach batched in groups of 125 to stay under SQLite's 999-variable limit; executemany uses a single prepared statement executed repeatedly, so no such limit applies and the full dataset can be flushed in one call. New functions insert_many_activities() and insert_many_exchanges() in schema.py handle the raw insertion. _efficient_write_dataset() no longer returns lists or flushes mid-loop; _efficient_write_many_data() calls the new functions once after iterating all datasets. Co-authored-by: Raphael Jolivet <contact@raphael-jolivet.name>
SQLite's raw executemany cannot bind Python tuples to TEXT columns,
but locations like ("foo", "bar") are valid in brightway. Coerce
location to str() before binding, matching Peewee's TextField behavior.
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Summary
Extracted from #255 by Raphael Jolivet — isolating just the
executemanybulk-insert optimization without the schema normalization, pickle→JSON, ordrop_metadatachanges from that PR.insert_many_activities()andinsert_many_exchanges()toschema.py, each usingcursor.executemany()on the raw SQLite connection to bypass Peewee ORM overhead per row_efficient_write_dataset()no longer flushes batches of 125 mid-loop (that limit existed because Peewee'sinsert_manybuilds one largeINSERT ... VALUES (?, ?...), (?, ?...)statement that hits SQLite's 999-variable limit;executemanyuses a single prepared statement executed repeatedly, so no such limit applies)_efficient_write_many_data()collects all datasets in one pass, then calls the two new functions onceCo-authored-by: Raphael Jolivet contact@raphael-jolivet.name
Test plan