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mavysavydavmavysavydav
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Removed s comments by using conftest file
Signed-off-by: David Y Liu <davidyliuliu@gmail.com>
1 parent 25dae14 commit 9e99e90

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Lines changed: 47 additions & 53 deletions

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‎sdk/python/tests/conftest.py‎

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@@ -12,8 +12,10 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import multiprocessing
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from datetime import datetime, timedelta
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from sys import platform
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import pandas as pd
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import pytest
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@@ -45,3 +47,43 @@ def pytest_collection_modifyitems(config, items):
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for item in items:
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if "integration" in item.keywords:
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item.add_marker(skip_integration)
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@pytest.fixture
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def simple_dataset_1() -> pd.DataFrame:
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now = datetime.utcnow()
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ts = pd.Timestamp(now).round("ms")
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data = {
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"id": [1, 2, 1, 3, 3],
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"float_col": [0.1, 0.2, 0.3, 4, 5],
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"int64_col": [1, 2, 3, 4, 5],
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"string_col": ["a", "b", "c", "d", "e"],
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"ts_1": [
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ts,
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ts - timedelta(hours=4),
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ts - timedelta(hours=3),
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ts - timedelta(hours=2),
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ts - timedelta(hours=1),
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],
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}
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return pd.DataFrame.from_dict(data)
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@pytest.fixture
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def simple_dataset_2() -> pd.DataFrame:
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now = datetime.utcnow()
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ts = pd.Timestamp(now).round("ms")
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data = {
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"id": ["a", "b", "c", "d", "e"],
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"float_col": [0.1, 0.2, 0.3, 4, 5],
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"int64_col": [1, 2, 3, 4, 5],
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"string_col": ["a", "b", "c", "d", "e"],
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"ts_1": [
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ts,
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ts - timedelta(hours=4),
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ts - timedelta(hours=3),
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ts - timedelta(hours=2),
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ts - timedelta(hours=1),
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],
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}
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return pd.DataFrame.from_dict(data)

‎sdk/python/tests/test_feature_store.py‎

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@@ -16,13 +16,12 @@
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from tempfile import mkstemp
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import pytest
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from fixtures.data_source_fixtures import simple_dataset_1 # noqa: F401
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from fixtures.data_source_fixtures import (
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from pytest_lazyfixture import lazy_fixture
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from utils.data_source_utils import (
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prep_file_source,
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simple_bq_source_using_query_arg,
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simple_bq_source_using_table_ref_arg,
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)
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from pytest_lazyfixture import lazy_fixture
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from feast.data_format import ParquetFormat
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from feast.data_source import FileSource

‎sdk/python/tests/test_inference.py‎

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@@ -1,7 +1,5 @@
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import pytest
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from fixtures.data_source_fixtures import simple_dataset_1 # noqa: F401
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from fixtures.data_source_fixtures import simple_dataset_2 # noqa: F401
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from fixtures.data_source_fixtures import (
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from utils.data_source_utils import (
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prep_file_source,
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simple_bq_source_using_query_arg,
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simple_bq_source_using_table_ref_arg,
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@pytest.mark.integration
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def test_data_source_ts_col_inference_success(simple_dataset_1): # noqa: F811
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def test_data_source_ts_col_inference_success(simple_dataset_1):
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with prep_file_source(df=simple_dataset_1) as file_source:
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actual_file_source = file_source.event_timestamp_column
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actual_bq_1 = simple_bq_source_using_table_ref_arg(
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assert expected == actual_file_source == actual_bq_1 == actual_bq_2
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def test_infer_entity_value_type_from_feature_views(
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simple_dataset_1, simple_dataset_2 # noqa: F811
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):
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def test_infer_entity_value_type_from_feature_views(simple_dataset_1, simple_dataset_2):
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with prep_file_source(
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df=simple_dataset_1, event_timestamp_column="ts_1"
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) as file_source, prep_file_source(

sdk/python/tests/fixtures/data_source_fixtures.py renamed to sdk/python/tests/utils/data_source_utils.py

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@@ -1,55 +1,12 @@
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import contextlib
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import tempfile
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from datetime import datetime, timedelta
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import pandas as pd
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import pytest
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from google.cloud import bigquery
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from feast.data_format import ParquetFormat
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from feast.data_source import BigQuerySource, FileSource
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@pytest.fixture
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def simple_dataset_1() -> pd.DataFrame:
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now = datetime.utcnow()
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ts = pd.Timestamp(now).round("ms")
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data = {
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"id": [1, 2, 1, 3, 3],
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"float_col": [0.1, 0.2, 0.3, 4, 5],
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"int64_col": [1, 2, 3, 4, 5],
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"string_col": ["a", "b", "c", "d", "e"],
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"ts_1": [
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ts,
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ts - timedelta(hours=4),
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ts - timedelta(hours=3),
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ts - timedelta(hours=2),
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ts - timedelta(hours=1),
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],
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}
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return pd.DataFrame.from_dict(data)
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@pytest.fixture
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def simple_dataset_2() -> pd.DataFrame:
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now = datetime.utcnow()
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ts = pd.Timestamp(now).round("ms")
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data = {
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"id": ["a", "b", "c", "d", "e"],
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"float_col": [0.1, 0.2, 0.3, 4, 5],
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"int64_col": [1, 2, 3, 4, 5],
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"string_col": ["a", "b", "c", "d", "e"],
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"ts_1": [
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ts,
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ts - timedelta(hours=4),
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ts - timedelta(hours=3),
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ts - timedelta(hours=2),
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ts - timedelta(hours=1),
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],
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}
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return pd.DataFrame.from_dict(data)
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@contextlib.contextmanager
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def prep_file_source(df, event_timestamp_column="") -> FileSource:
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with tempfile.NamedTemporaryFile(suffix=".parquet") as f:

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