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from datetime import timedelta
from itertools import product as iter_product
import dask.dataframe as dd
import pandas as pd
import pytest
from test_utils.incite.collections.conftest import (
wall_collection,
task_adj_collection,
session_collection,
)
from test_utils.incite.mergers.conftest import enriched_wall_merge
@pytest.mark.parametrize(
argnames="offset, duration,",
argvalues=list(
iter_product(
["12h", "3D"],
[timedelta(days=5)],
)
),
)
class TestEnrichedTaskAdjust:
@pytest.mark.skip
def test_base(
self,
client_no_amm,
user_factory,
product,
task_adj_collection,
wall_collection,
session_collection,
enriched_wall_merge,
enriched_task_adjust_merge,
incite_item_factory,
delete_df_collection,
thl_web_rr,
):
from generalresearch.models.thl.user import User
# -- Build & Setup
delete_df_collection(coll=session_collection)
u1: User = user_factory(product=product)
for item in session_collection.items:
incite_item_factory(user=u1, item=item)
item.initial_load()
for item in wall_collection.items:
item.initial_load()
enriched_wall_merge.build(
client=client_no_amm,
session_coll=session_collection,
wall_coll=wall_collection,
pg_config=thl_web_rr,
)
enriched_task_adjust_merge.build(
client=client_no_amm,
task_adjust_coll=task_adj_collection,
enriched_wall=enriched_wall_merge,
pg_config=thl_web_rr,
)
# --
ddf = enriched_task_adjust_merge.ddf()
assert isinstance(ddf, dd.DataFrame)
df = client_no_amm.compute(collections=ddf, sync=True)
assert isinstance(df, pd.DataFrame)
assert not df.empty
|
