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extract(): keep all-NULL rows unlinked even with a pre-existing NULL lookup row

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Follow-up to the #186 fix: skipping the all-NULL combination in the lookup
INSERT is not enough on its own. When extract() reuses a lookup table that
already contains an all-NULL row (e.g. one written by an older sqlite-utils
version or created manually), the IS-based foreign-key UPDATE would still
match that row and link all-NULL source rows to it.

The UPDATE now carries a trailing `WHERE NOT (<col> IS NULL AND ...)` so
all-NULL source rows are never assigned a foreign key and keep the NULL that
the freshly-added column starts with, regardless of the lookup table's
existing contents.

Adds test_extract_all_null_stays_null_with_preexisting_null_lookup_row.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Johnson K C 2026-06-08 14:59:25 -04:00
commit 3ab8406b1d
2 changed files with 35 additions and 7 deletions
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23
tests/test_extract.py
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@ -236,6 +236,25 @@ def test_extract_multi_column_keeps_partial_null_but_not_all_null(fresh_db):
assert rows[0]["ab_id"] == rows[1]["ab_id"] is not None # partial NULL shared
assert rows[3]["ab_id"] not in (None, rows[0]["ab_id"])
# The lookup table must not contain an all-NULL row.
assert not any(
row["a"] is None and row["b"] is None for row in fresh_db["ab"].rows
assert not any(row["a"] is None and row["b"] is None for row in fresh_db["ab"].rows)
def test_extract_all_null_stays_null_with_preexisting_null_lookup_row(fresh_db):
# Reusing a lookup table that already contains an all-NULL row (e.g. created
# by an older sqlite-utils version) must still leave all-NULL source rows with
# a NULL foreign key — the IS-based join must not link them to that row (#186).
fresh_db["type"].insert_all(
[{"id": 1, "type": None}, {"id": 2, "type": "dog"}], pk="id"
)
fresh_db["creatures"].insert_all(
[
{"id": 1, "name": "Simon", "type": None},
{"id": 2, "name": "Cleo", "type": "dog"},
],
pk="id",
)
fresh_db["creatures"].extract("type")
assert list(fresh_db["creatures"].rows) == [
{"id": 1, "name": "Simon", "type_id": None},
{"id": 2, "name": "Cleo", "type_id": 2},
]