-
Notifications
You must be signed in to change notification settings - Fork 302
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge branch 'main' into feature/default_rounding_mode
- Loading branch information
Showing
13 changed files
with
379 additions
and
307 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,123 @@ | ||
| # Copyright 2023 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| """Shared helper functions for connecting BigQuery and pyarrow.""" | ||
|
|
||
| from typing import Any | ||
|
|
||
| from packaging import version | ||
|
|
||
| try: | ||
| import pyarrow # type: ignore | ||
| except ImportError: # pragma: NO COVER | ||
| pyarrow = None | ||
|
|
||
|
|
||
| def pyarrow_datetime(): | ||
| return pyarrow.timestamp("us", tz=None) | ||
|
|
||
|
|
||
| def pyarrow_numeric(): | ||
| return pyarrow.decimal128(38, 9) | ||
|
|
||
|
|
||
| def pyarrow_bignumeric(): | ||
| # 77th digit is partial. | ||
| # https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#decimal_types | ||
| return pyarrow.decimal256(76, 38) | ||
|
|
||
|
|
||
| def pyarrow_time(): | ||
| return pyarrow.time64("us") | ||
|
|
||
|
|
||
| def pyarrow_timestamp(): | ||
| return pyarrow.timestamp("us", tz="UTC") | ||
|
|
||
|
|
||
| _BQ_TO_ARROW_SCALARS = {} | ||
| _ARROW_SCALAR_IDS_TO_BQ = {} | ||
|
|
||
| if pyarrow: | ||
| # This dictionary is duplicated in bigquery_storage/test/unite/test_reader.py | ||
| # When modifying it be sure to update it there as well. | ||
| # Note(todo!!): type "BIGNUMERIC"'s matching pyarrow type is added in _pandas_helpers.py | ||
| _BQ_TO_ARROW_SCALARS = { | ||
| "BOOL": pyarrow.bool_, | ||
| "BOOLEAN": pyarrow.bool_, | ||
| "BYTES": pyarrow.binary, | ||
| "DATE": pyarrow.date32, | ||
| "DATETIME": pyarrow_datetime, | ||
| "FLOAT": pyarrow.float64, | ||
| "FLOAT64": pyarrow.float64, | ||
| "GEOGRAPHY": pyarrow.string, | ||
| "INT64": pyarrow.int64, | ||
| "INTEGER": pyarrow.int64, | ||
| "NUMERIC": pyarrow_numeric, | ||
| "STRING": pyarrow.string, | ||
| "TIME": pyarrow_time, | ||
| "TIMESTAMP": pyarrow_timestamp, | ||
| } | ||
|
|
||
| _ARROW_SCALAR_IDS_TO_BQ = { | ||
| # https://arrow.apache.org/docs/python/api/datatypes.html#type-classes | ||
| pyarrow.bool_().id: "BOOL", | ||
| pyarrow.int8().id: "INT64", | ||
| pyarrow.int16().id: "INT64", | ||
| pyarrow.int32().id: "INT64", | ||
| pyarrow.int64().id: "INT64", | ||
| pyarrow.uint8().id: "INT64", | ||
| pyarrow.uint16().id: "INT64", | ||
| pyarrow.uint32().id: "INT64", | ||
| pyarrow.uint64().id: "INT64", | ||
| pyarrow.float16().id: "FLOAT64", | ||
| pyarrow.float32().id: "FLOAT64", | ||
| pyarrow.float64().id: "FLOAT64", | ||
| pyarrow.time32("ms").id: "TIME", | ||
| pyarrow.time64("ns").id: "TIME", | ||
| pyarrow.timestamp("ns").id: "TIMESTAMP", | ||
| pyarrow.date32().id: "DATE", | ||
| pyarrow.date64().id: "DATETIME", # because millisecond resolution | ||
| pyarrow.binary().id: "BYTES", | ||
| pyarrow.string().id: "STRING", # also alias for pyarrow.utf8() | ||
| # The exact scale and precision don't matter, see below. | ||
| pyarrow.decimal128(38, scale=9).id: "NUMERIC", | ||
| } | ||
|
|
||
| # Adds bignumeric support only if pyarrow version >= 3.0.0 | ||
| # Decimal256 support was added to arrow 3.0.0 | ||
| # https://arrow.apache.org/blog/2021/01/25/3.0.0-release/ | ||
| if version.parse(pyarrow.__version__) >= version.parse("3.0.0"): | ||
| _BQ_TO_ARROW_SCALARS["BIGNUMERIC"] = pyarrow_bignumeric | ||
| # The exact decimal's scale and precision are not important, as only | ||
| # the type ID matters, and it's the same for all decimal256 instances. | ||
| _ARROW_SCALAR_IDS_TO_BQ[pyarrow.decimal256(76, scale=38).id] = "BIGNUMERIC" | ||
|
|
||
|
|
||
| def bq_to_arrow_scalars(bq_scalar: str): | ||
| """ | ||
| Returns: | ||
| The Arrow scalar type that the input BigQuery scalar type maps to. | ||
| If it cannot find the BigQuery scalar, return None. | ||
| """ | ||
| return _BQ_TO_ARROW_SCALARS.get(bq_scalar) | ||
|
|
||
|
|
||
| def arrow_scalar_ids_to_bq(arrow_scalar: Any): | ||
| """ | ||
| Returns: | ||
| The BigQuery scalar type that the input arrow scalar type maps to. | ||
| If it cannot find the arrow scalar, return None. | ||
| """ | ||
| return _ARROW_SCALAR_IDS_TO_BQ.get(arrow_scalar) |
Oops, something went wrong.