Files
wehub-resource-sync ee3943b5b1
CI / test (deps-minimum, windows-latest, unit) (push) Blocked by required conditions
CI / test_py314 (deps-latest, ubuntu-latest, unit) (push) Blocked by required conditions
CI / test_py314 (deps-latest, windows-latest, unit) (push) Blocked by required conditions
CI / test_py314_future (deps-latest, ubuntu-latest, unit) (push) Blocked by required conditions
CI / test_py314_future (deps-latest, windows-latest, unit) (push) Blocked by required conditions
Secret Leaks / trufflehog (push) Waiting to run
CI / check_code_quality (push) Waiting to run
CI / test (deps-latest, ubuntu-latest, integration) (push) Blocked by required conditions
CI / test (deps-latest, ubuntu-latest, unit) (push) Blocked by required conditions
CI / test (deps-latest, windows-latest, integration) (push) Blocked by required conditions
CI / test (deps-latest, windows-latest, unit) (push) Blocked by required conditions
CI / test (deps-minimum, ubuntu-latest, integration) (push) Blocked by required conditions
CI / test (deps-minimum, ubuntu-latest, unit) (push) Blocked by required conditions
CI / test (deps-minimum, windows-latest, integration) (push) Blocked by required conditions
Build documentation / build (push) Failing after 0s
chore: import upstream snapshot with attribution
2026-07-13 13:24:32 +08:00

103 lines
4.1 KiB
Python

import contextlib
import os
import sqlite3
import pytest
import datasets.config
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
STRING_FROM_PANDAS = "large_string" if datasets.config.PANDAS_VERSION.major >= 3 else "string"
def _check_sql_dataset(dataset, expected_features):
assert isinstance(dataset, Dataset)
assert dataset.num_rows == 4
assert dataset.num_columns == 3
assert dataset.column_names == ["col_1", "col_2", "col_3"]
for feature, expected_dtype in expected_features.items():
assert dataset.features[feature].dtype == expected_dtype
@require_sqlalchemy
@pytest.mark.parametrize("keep_in_memory", [False, True])
def test_dataset_from_sql_keep_in_memory(keep_in_memory, sqlite_path, tmp_path, set_sqlalchemy_silence_uber_warning):
cache_dir = tmp_path / "cache"
expected_features = {"col_1": STRING_FROM_PANDAS, "col_2": "int64", "col_3": "float64"}
with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
dataset = SqlDatasetReader(
"dataset", "sqlite:///" + sqlite_path, cache_dir=cache_dir, keep_in_memory=keep_in_memory
).read()
_check_sql_dataset(dataset, expected_features)
@require_sqlalchemy
@pytest.mark.parametrize(
"features",
[
None,
{"col_1": "string", "col_2": "int64", "col_3": "float64"},
{"col_1": "string", "col_2": "string", "col_3": "string"},
{"col_1": "int32", "col_2": "int32", "col_3": "int32"},
{"col_1": "float32", "col_2": "float32", "col_3": "float32"},
],
)
def test_dataset_from_sql_features(features, sqlite_path, tmp_path, set_sqlalchemy_silence_uber_warning):
cache_dir = tmp_path / "cache"
default_expected_features = {"col_1": STRING_FROM_PANDAS, "col_2": "int64", "col_3": "float64"}
expected_features = features.copy() if features else default_expected_features
features = (
Features({feature: Value(dtype) for feature, dtype in features.items()}) if features is not None else None
)
dataset = SqlDatasetReader("dataset", "sqlite:///" + sqlite_path, features=features, cache_dir=cache_dir).read()
_check_sql_dataset(dataset, expected_features)
def iter_sql_file(sqlite_path):
with contextlib.closing(sqlite3.connect(sqlite_path)) as con:
cur = con.cursor()
cur.execute("SELECT * FROM dataset")
for row in cur:
yield row
@require_sqlalchemy
def test_dataset_to_sql(sqlite_path, tmp_path, set_sqlalchemy_silence_uber_warning):
cache_dir = tmp_path / "cache"
output_sqlite_path = os.path.join(cache_dir, "tmp.sql")
dataset = SqlDatasetReader("dataset", "sqlite:///" + sqlite_path, cache_dir=cache_dir).read()
SqlDatasetWriter(dataset, "dataset", "sqlite:///" + output_sqlite_path, num_proc=1).write()
original_sql = iter_sql_file(sqlite_path)
expected_sql = iter_sql_file(output_sqlite_path)
for row1, row2 in zip(original_sql, expected_sql):
assert row1 == row2
@require_sqlalchemy
def test_dataset_to_sql_multiproc(sqlite_path, tmp_path, set_sqlalchemy_silence_uber_warning):
cache_dir = tmp_path / "cache"
output_sqlite_path = os.path.join(cache_dir, "tmp.sql")
dataset = SqlDatasetReader("dataset", "sqlite:///" + sqlite_path, cache_dir=cache_dir).read()
SqlDatasetWriter(dataset, "dataset", "sqlite:///" + output_sqlite_path, num_proc=2).write()
original_sql = iter_sql_file(sqlite_path)
expected_sql = iter_sql_file(output_sqlite_path)
for row1, row2 in zip(original_sql, expected_sql):
assert row1 == row2
@require_sqlalchemy
def test_dataset_to_sql_invalidproc(sqlite_path, tmp_path, set_sqlalchemy_silence_uber_warning):
cache_dir = tmp_path / "cache"
output_sqlite_path = os.path.join(cache_dir, "tmp.sql")
dataset = SqlDatasetReader("dataset", "sqlite:///" + sqlite_path, cache_dir=cache_dir).read()
with pytest.raises(ValueError):
SqlDatasetWriter(dataset, "dataset", "sqlite:///" + output_sqlite_path, num_proc=0).write()