def test_make_prereq_blob_competency():
df = pd.DataFrame({"HS diploma required?": ["No"], "Eligible groups": ["Veteran"]})
transformer = PathwaysTransformer(dataframe=df)
row = df.iloc[0]
results = transformer._make_prereq_blob(row)
assert (
results["competency_required"]
== "Must belong to one or more of the following group(s): Veteran"
)
assert "credential_category" not in results
def test_filter_non_pathways_programs():
df = pd.DataFrame(
{
"Program Name": ["Technical Academy Program", "Sales Leadership"],
"Should this program be available in Google Pathways?": ["Yes", "No"],
}
)
transformer = PathwaysTransformer(dataframe=df)
filtered_df = transformer._filter_non_pathways_programs()
assert len(transformer.dataframe) == 2
assert len(filtered_df) == 1
def test_make_address_blob_for_multiple_addresses_with_pipe():
df = pd.DataFrame(
{
"Organization Address": ["234 Mulberry Street, Chicago IL 74444"],
"Program Address (if different from organization address)": [
"111 Grickle Grass Lane, Springfield MA 88884 | 3344 Lifted Lorax Street, Chicago IL 88884"
],
}
)
transformer = PathwaysTransformer(dataframe=df)
row = df.iloc[0]
results = transformer._make_address_blob(row)
expected_results = [
{
"street_address": "234 Mulberry Street",
"address_locality": "Chicago",
"address_region": "IL",
"address_country": "US",
"postal_code": "74444",
},
{
"street_address": "111 Grickle Grass Lane",
"address_locality": "Springfield",
"address_region": "MA",
"address_country": "US",
"postal_code": "88884",
},
{
"street_address": "3344 Lifted Lorax Street",
"address_locality": "Chicago",
"address_region": "IL",
"address_country": "US",
"postal_code": "88884",
},
]
assert len(results) == 3
assert expected_results == results
def test_make_address_blob_for_provider():
df = pd.DataFrame(
{
"Organization Address": ["111 Grickle Grass Lane, Springfield MA 88884"],
"Program Address (if different from organization address)": [""],
}
)
transformer = PathwaysTransformer(dataframe=df)
row = df.iloc[0]
results = transformer._make_address_blob(row)
expected_results = [
{
"street_address": "111 Grickle Grass Lane",
"address_locality": "Springfield",
"address_region": "MA",
"address_country": "US",
"postal_code": "88884",
}
]
assert len(results) == 1
assert expected_results == results
def test_convert_duration_to_isoformat(input, expected_output):
transformer = PathwaysTransformer(dataframe=pd.DataFrame({}))
output = transformer._convert_duration_to_isoformat(input)
assert output == expected_output
opt_out = OptOut(google_sheet_as_list=sheet_as_list,
programs_table=programs_table,
engine=engine)
deleted_records = opt_out.remove_deleted_programs()
logger.info(
f"----Deleted {len(deleted_records)} records from the Pathways database. {' '.join(deleted_records)}"
)
opt_out_records = opt_out.remove_programs_not_marked_for_pathways()
logger.info(
f"----Found {len(opt_out_records)} records that 'opt-out' of Pathways. {' '.join(opt_out_records)}"
)
dataframe = DataframeTransformer(sheet=sheet_as_list,
engine=engine).transform()
logger.info(
f"----Initial transformation complete: {len(dataframe)} records prepped for PathwaysTransformer."
)
pathways_dataframe = PathwaysTransformer(
dataframe=dataframe).pathways_transform()
logger.info(
f"----Pathways transformation complete: {len(pathways_dataframe)} records prepped for loading."
)
loader = Loader(engine=engine)
loader.load_data(dataframe=pathways_dataframe,
metadata_table=programs_table,
primary_key="id")
logger.info("----Data loaded into Google Pathways API")