feat: flexible null handling and insert subschemas in Python (#1827)

* Test that we can insert subschemas (omit nullable columns) in Python.
* More work is needed to support this in Node. See:
https://github.com/lancedb/lancedb/issues/1832
* Test that we can insert data with nullable schema but no nulls in
non-nullable schema.
* Add `"null"` option for `on_bad_vectors` where we fill with null if
the vector is bad.
* Make null values not considered bad if the field itself is nullable.
This commit is contained in:
Will Jones
2024-11-15 11:33:00 -08:00
committed by GitHub
parent b38a4269d0
commit 587c0824af
7 changed files with 288 additions and 27 deletions

View File

@@ -240,6 +240,121 @@ def test_add(db):
_add(table, schema)
def test_add_subschema(tmp_path):
db = lancedb.connect(tmp_path)
schema = pa.schema(
[
pa.field("vector", pa.list_(pa.float32(), 2), nullable=True),
pa.field("item", pa.string(), nullable=True),
pa.field("price", pa.float64(), nullable=False),
]
)
table = db.create_table("test", schema=schema)
data = {"price": 10.0, "item": "foo"}
table.add([data])
data = {"price": 2.0, "vector": [3.1, 4.1]}
table.add([data])
data = {"price": 3.0, "vector": [5.9, 26.5], "item": "bar"}
table.add([data])
expected = pa.table(
{
"vector": [None, [3.1, 4.1], [5.9, 26.5]],
"item": ["foo", None, "bar"],
"price": [10.0, 2.0, 3.0],
},
schema=schema,
)
assert table.to_arrow() == expected
data = {"item": "foo"}
# We can't omit a column if it's not nullable
with pytest.raises(OSError, match="Invalid user input"):
table.add([data])
# We can add it if we make the column nullable
table.alter_columns(dict(path="price", nullable=True))
table.add([data])
expected_schema = pa.schema(
[
pa.field("vector", pa.list_(pa.float32(), 2), nullable=True),
pa.field("item", pa.string(), nullable=True),
pa.field("price", pa.float64(), nullable=True),
]
)
expected = pa.table(
{
"vector": [None, [3.1, 4.1], [5.9, 26.5], None],
"item": ["foo", None, "bar", "foo"],
"price": [10.0, 2.0, 3.0, None],
},
schema=expected_schema,
)
assert table.to_arrow() == expected
def test_add_nullability(tmp_path):
db = lancedb.connect(tmp_path)
schema = pa.schema(
[
pa.field("vector", pa.list_(pa.float32(), 2), nullable=False),
pa.field("id", pa.string(), nullable=False),
]
)
table = db.create_table("test", schema=schema)
nullable_schema = pa.schema(
[
pa.field("vector", pa.list_(pa.float32(), 2), nullable=True),
pa.field("id", pa.string(), nullable=True),
]
)
data = pa.table(
{
"vector": [[3.1, 4.1], [5.9, 26.5]],
"id": ["foo", "bar"],
},
schema=nullable_schema,
)
# We can add nullable schema if it doesn't actually contain nulls
table.add(data)
expected = data.cast(schema)
assert table.to_arrow() == expected
data = pa.table(
{
"vector": [None],
"id": ["baz"],
},
schema=nullable_schema,
)
# We can't add nullable schema if it contains nulls
with pytest.raises(Exception, match="Vector column vector has NaNs"):
table.add(data)
# But we can make it nullable
table.alter_columns(dict(path="vector", nullable=True))
table.add(data)
expected_schema = pa.schema(
[
pa.field("vector", pa.list_(pa.float32(), 2), nullable=True),
pa.field("id", pa.string(), nullable=False),
]
)
expected = pa.table(
{
"vector": [[3.1, 4.1], [5.9, 26.5], None],
"id": ["foo", "bar", "baz"],
},
schema=expected_schema,
)
assert table.to_arrow() == expected
def test_add_pydantic_model(db):
# https://github.com/lancedb/lancedb/issues/562