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fix: replace arrow2 with arrow backend for connectorx (#2933)

Browse Source 
* replace arrow2 with arrow backend for connectorx

* updated docs/

* updated minimal deps

* update docs and pyproject.toml deps

* updated minimal deps to support 3.9

* converts +00:00 to UTC right after handover from connectorx

* fixes examples connectorx lint

---------

Co-authored-by: Marcin Rudolf <rudolfix@rudolfix.org>
This commit is contained in:
Thierry Jean
2025-08-04 11:01:34 -04:00
committed by GitHub
parent edad825a59
commit eb95c36f3c
8 changed files with 290 additions and 243 deletions
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25
dlt/common/libs/pyarrow.py
View File

@@ -1099,3 +1099,28 @@ def add_arrow_metadata(
return pyarrow.Table.from_arrays(item.columns, schema=new_schema)
else: # RecordBatch
return pyarrow.RecordBatch.from_arrays(item.columns, schema=new_schema)
def set_plus0000_timezone_to_utc(tbl: pyarrow.Table) -> pyarrow.Table:
"""
Convert any +00:00 timestamp columns to UTC.
Returns the original table object if nothing needed fixing.
"""
arrays, fields = [], []
changed = False
for col, fld in zip(tbl.columns, tbl.schema):
if pyarrow.types.is_timestamp(fld.type) and fld.type.tz == "+00:00":
changed = True
new_type = pyarrow.timestamp(fld.type.unit, "UTC")
arrays.append(pyarrow.compute.cast(col, new_type))
fields.append(pyarrow.field(fld.name, new_type, fld.nullable, fld.metadata))
else:
arrays.append(col)
fields.append(fld)
if not changed:
return tbl # perfect no-op
new_schema = pyarrow.schema(fields, metadata=tbl.schema.metadata)
return pyarrow.Table.from_arrays(arrays, schema=new_schema)

18
dlt/sources/sql_database/helpers.py
View File

@@ -214,7 +214,7 @@ class TableLoader:
# default settings
backend_kwargs = {
"return_type": "arrow2",
"return_type": "arrow",
"protocol": "binary",
**backend_kwargs,
}
@@ -233,7 +233,19 @@ class TableLoader:
f" literals that cannot be rendered, upgrade to 2.x: `{str(ex)}`"
) from ex
df = cx.read_sql(conn, query_str, **backend_kwargs)
yield df
yield self._maybe_fix_0000_timezone(df)
def _maybe_fix_0000_timezone(self, df: Any) -> Any:
"""Optionally convert +00:00 timezone to UTC"""
try:
from dlt.common.libs.pyarrow import set_plus0000_timezone_to_utc, pyarrow
# TODO: skip when Arrow releases timezone fix
if isinstance(df, pyarrow.Table):
return set_plus0000_timezone_to_utc(df)
except MissingDependencyException:
pass
return df
def table_rows(
@@ -338,7 +350,7 @@ def unwrap_json_connector_x(field: str) -> TDataItem:
column = pc.replace_with_mask(
column,
pc.equal(column, "null").combine_chunks(),
pa.scalar(None, pa.large_string()),
pa.scalar(None, pa.string()),
)
return table.set_column(col_index, table.schema.field(col_index), column)

2
docs/examples/connector_x_arrow/connector_x_arrow.py
View File

@@ -34,7 +34,7 @@ def read_sql_x(
yield cx.read_sql(
conn_str.to_native_representation(),
query,
return_type="arrow2",
return_type="arrow",
protocol="binary",
)

2
docs/examples/postgres_to_postgres/postgres_to_postgres.py
View File

@@ -74,7 +74,7 @@ def read_sql_x_chunked(conn_str: str, query: str, chunk_size: int = CHUNKSIZE):
data_chunk = cx.read_sql(
conn_str,
chunk_query,
return_type="arrow2",
return_type="arrow",
protocol="binary",
)
yield data_chunk

3
docs/website/docs/dlt-ecosystem/verified-sources/sql_database/configuration.md
View File

@@ -441,7 +441,8 @@ The [`ConnectorX`](https://sfu-db.github.io/connector-x/intro.html) backend comp
There are certain limitations when using this backend:
* It will ignore `chunk_size`. `ConnectorX` cannot yield data in batches.
* In many cases, it requires a connection string that differs from the `SQLAlchemy` connection string. Use the `conn` argument in `backend_kwargs` to set this.
* It will convert **decimals** to **doubles**, so you will lose precision.
* For `connectorx>=0.4.2`, on `reflection_level="minimal"`, `connectorx` can return decimal values. On higher `reflection_level`, dlt will coerce the data type (e.g., modify the decimal `precision` and `scale`, convert to `float`).
* For `connectorx<0.4.2`, dlt will convert decimals to doubles, thus losing numerical precision.
* Nullability of the columns is ignored (always true).
* It uses different mappings for each data type. (Check [here](https://sfu-db.github.io/connector-x/databases.html) for more details.)
* JSON fields (at least those coming from PostgreSQL) are double-wrapped in strings. To unwrap this, you can pass the in-built transformation function `unwrap_json_connector_x` (for example, with `add_map`):

6
pyproject.toml
View File

@@ -238,8 +238,8 @@ dev = [
# NOTE: those dependencies are used to test built in sources
sources = [
"connectorx>=0.3.3 ; python_version >= '3.9'",
"connectorx>=0.4.0,<0.4.2 ; python_version >= '3.10'",
"connectorx>=0.4.2 ; python_version >= '3.10'",
"connectorx<0.4.2 ; python_version < '3.10'",
"pymysql>=1.1.0,<2",
"openpyxl>=3,<4",
"mimesis>=7.0.0,<8",
@@ -304,7 +304,7 @@ docs = [
"psycopg2-binary>=2.9",
"lancedb>=0.8.2 ; python_version < '3.13'",
"openai>=1.45",
"connectorx>=0.3.2,<0.4.2",
"connectorx>=0.4.2 ; python_version >= '3.10'",
"modal>=0.64.170",
# google secrets provider
"google-api-python-client>=1.7.11",

14
tests/load/sources/sql_database/test_sql_database_source.py
View File

@@ -648,7 +648,9 @@ def test_reflection_levels(
assert col_names == expected_col_names
# Pk col is always reflected
# TODO move to separate test
# in `sql_source_db`, column `id` from table `app_user` is a primary key
# primary key hint should always be reflected
pk_col = schema.tables["app_user"]["columns"]["id"]
assert pk_col["primary_key"] is True
@@ -1417,6 +1419,7 @@ def assert_row_counts(
), f"Table {table} counts do not match with the source"
# TODO tests shouldn't modify the return values of the tested functions
def assert_precision_columns(
columns: TTableSchemaColumns, backend: TableBackend, nullable: bool
) -> None:
@@ -1427,16 +1430,17 @@ def assert_precision_columns(
if backend == "sqlalchemy":
expected = remove_timestamp_precision(expected)
actual = remove_dlt_columns(actual)
if backend == "pyarrow":
elif backend == "pyarrow":
expected = add_default_decimal_precision(expected)
if backend == "pandas":
elif backend == "pandas":
expected = remove_timestamp_precision(expected, with_timestamps=False)
if backend == "connectorx":
elif backend == "connectorx":
# connector x emits 32 precision which gets merged with sql alchemy schema
del columns["int_col"]["precision"]
assert actual == expected
# TODO tests shouldn't modify the return values of the tested functions
def assert_no_precision_columns(
columns: TTableSchemaColumns, backend: TableBackend, nullable: bool
) -> None:
@@ -1525,6 +1529,8 @@ def convert_connectorx_types(columns: List[TColumnSchema]) -> List[TColumnSchema
if column["data_type"] == "bigint":
if column["name"] == "int_col":
column["precision"] = 32 # only int and bigint in connectorx
elif column["name"] == "smallint_col":
column["precision"] = 16 # only int and bigint in connectorx
if column["data_type"] == "text" and column.get("precision"):
del column["precision"]
return columns

463
uv.lock generated
View File

@@ -354,75 +354,75 @@ name = "apache-airflow"
version = "2.11.0"
source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/0b/e6/fe73a65cff795e93fd82256a10c7e19010f09bc30445afdd288acce41862/apache_airflow-2.11.0.tar.gz", hash = "sha256:252ae1a2f3d75547bb35907ac6abe6a105d02eaab265434ca587b5757940ce08", size = 12502139 }
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@@ -434,7 +434,7 @@ name = "apache-airflow-providers-common-compat"
version = "1.7.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "apache-airflow", marker = "python_full_version < '3.13'" },
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@@ -446,7 +446,7 @@ name = "apache-airflow-providers-common-io"
version = "1.6.0"
source = { registry = "https://pypi.org/simple" }
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@@ -458,10 +458,10 @@ name = "apache-airflow-providers-common-sql"
version = "1.27.1"
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@@ -473,13 +473,13 @@ name = "apache-airflow-providers-fab"
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@@ -491,7 +491,7 @@ name = "apache-airflow-providers-ftp"
version = "3.13.0"
source = { registry = "https://pypi.org/simple" }
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