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Fix Python SDK ingestion for featureset name that exist in multiple projects #868

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Merged
woop merged 5 commits into from
Jul 26, 2020
Merged

Fix Python SDK ingestion for featureset name that exist in multiple projects #868

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df0ff4d
Fix ingestion with same featureset name
Jul 9, 2020
e0f1cb9
Address PR comments
Jul 14, 2020
73bedaf
Merge branch 'master' into bugfix/py-sdk-ingest
Jul 14, 2020
791e8bd
Remove unrelated test
Jul 14, 2020
1be168d
Remove unnecessary line
woop Jul 26, 2020
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26 changes: 25 additions & 1 deletion sdk/python/feast/client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -836,11 +836,33 @@ def ingest(
Returns:
str:
ingestion id for this dataset

Examples:
>>> from feast import Client
>>>
>>> client = Client(core_url="localhost:6565")
>>> fs_df = pd.DataFrame(
>>> {
>>> "datetime": [pd.datetime.now()],
>>> "driver": [1001],
>>> "rating": [4.3],
>>> }
>>> )
>>> client.set_project("project1")
>>> client.ingest("driver", fs_df)
>>>
>>> driver_fs = client.get_feature_set(name="driver", project="project1")
>>> client.ingest(driver_fs, fs_df)
"""

if isinstance(feature_set, FeatureSet):
name = feature_set.name
project = feature_set.project
elif isinstance(feature_set, str):
if self.project is not None:
project = self.project
else:
project = "default"
name = feature_set
else:
raise Exception("Feature set name must be provided")
Expand All @@ -858,7 +880,9 @@ def ingest(
while True:
if timeout is not None and time.time() - current_time >= timeout:
raise TimeoutError("Timed out waiting for feature set to be ready")
fetched_feature_set: Optional[FeatureSet] = self.get_feature_set(name)
fetched_feature_set: Optional[FeatureSet] = self.get_feature_set(
name, project
)
if (
fetched_feature_set is not None
and fetched_feature_set.status == FeatureSetStatus.STATUS_READY
Expand Down
106 changes: 106 additions & 0 deletions tests/e2e/redis/basic-ingest-redis-serving.py
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Original file line number Diff line number Diff line change
Expand Up @@ -558,6 +558,112 @@ def try_get_features2():
)


@pytest.mark.timeout(600)
@pytest.mark.run(order=16)
def test_basic_ingest_retrieval_fs(client):
# Set to another project to test ingestion based on current project context
client.set_project(PROJECT_NAME + "_NS1")
driver_fs = FeatureSet(
name="driver_fs",
features=[
Feature(name="driver_fs_rating", dtype=ValueType.FLOAT),
Feature(name="driver_fs_cost", dtype=ValueType.FLOAT),
],
entities=[Entity("driver_fs_id", ValueType.INT64)],
max_age=Duration(seconds=3600),
)
client.apply(driver_fs)

N_ROWS = 2
time_offset = datetime.utcnow().replace(tzinfo=pytz.utc)
driver_df = pd.DataFrame(
{
"datetime": [time_offset] * N_ROWS,
"driver_fs_id": [i for i in range(N_ROWS)],
"driver_fs_rating": [float(i) for i in range(N_ROWS)],
"driver_fs_cost": [float(i) + 0.5 for i in range(N_ROWS)],
}
)
client.ingest(driver_fs, driver_df, timeout=600)
time.sleep(15)

online_request_entity = [{"driver_fs_id": 0}, {"driver_fs_id": 1}]
online_request_features = ["driver_fs_rating", "driver_fs_cost"]

def try_get_features():
response = client.get_online_features(
entity_rows=online_request_entity, feature_refs=online_request_features
)
return response, True

online_features_actual = wait_retry_backoff(
retry_fn=try_get_features,
timeout_secs=90,
timeout_msg="Timed out trying to get online feature values",
)

online_features_expected = {
"driver_fs_id": [0, 1],
"driver_fs_rating": [0.0, 1.0],
"driver_fs_cost": [0.5, 1.5],
}

assert online_features_actual.to_dict() == online_features_expected


@pytest.mark.timeout(600)
@pytest.mark.run(order=17)
def test_basic_ingest_retrieval_str(client):
# Set to another project to test ingestion based on current project context
client.set_project(PROJECT_NAME + "_NS1")
customer_fs = FeatureSet(
name="cust_fs",
features=[
Feature(name="cust_rating", dtype=ValueType.INT64),
Feature(name="cust_cost", dtype=ValueType.FLOAT),
],
entities=[Entity("cust_id", ValueType.INT64)],
max_age=Duration(seconds=3600),
)
client.apply(customer_fs)

N_ROWS = 2
time_offset = datetime.utcnow().replace(tzinfo=pytz.utc)
cust_df = pd.DataFrame(
{
"datetime": [time_offset] * N_ROWS,
"cust_id": [i for i in range(N_ROWS)],
"cust_rating": [i for i in range(N_ROWS)],
"cust_cost": [float(i) + 0.5 for i in range(N_ROWS)],
}
)
client.ingest("cust_fs", cust_df, timeout=600)
time.sleep(15)

online_request_entity = [{"cust_id": 0}, {"cust_id": 1}]
online_request_features = ["cust_rating", "cust_cost"]

def try_get_features():
response = client.get_online_features(
entity_rows=online_request_entity, feature_refs=online_request_features
)
return response, True

online_features_actual = wait_retry_backoff(
retry_fn=try_get_features,
timeout_secs=90,
timeout_msg="Timed out trying to get online feature values",
)

online_features_expected = {
"cust_id": [0, 1],
"cust_rating": [0, 1],
"cust_cost": [0.5, 1.5],
}

assert online_features_actual.to_dict() == online_features_expected


@pytest.fixture(scope="module")
def all_types_dataframe():
return pd.DataFrame(
Expand Down