def get_items(
source: Union[str, pd.DataFrame, RawItems],
start: int,
count: Optional[int],
filters: Optional[api.Filters],
expand: bool,
) -> Union[JobItems, CollectionItems]:
if isinstance(source, pd.DataFrame):
return Items.from_df(source, expand=expand)
elif isinstance(source, Iterable) and not isinstance(source, str):
return Items.from_array(source, expand=expand)
elif helpers.is_job_key(source):
return JobItems(key=source,
start=start,
count=count,
filters=filters,
expand=expand)
elif helpers.is_collection_key(source):
if start:
raise ValueError(
"Collections API does not support 'start' parameter")
return CollectionItems(key=source,
count=count,
filters=filters,
expand=expand)
else:
raise ValueError(
f"'{source}' is not a valid job or collection key")
def test_flat_df(data, expected_data, expected_map):
i = Items.from_array(data, expand=True)
pd.testing.assert_frame_equal(i.flat_df,
pd.DataFrame(expected_data),
check_like=False)
for new, old in expected_map.items():
assert i.origin_column_name(new) == old
def get_items(
source: Union[str, pd.DataFrame, RawItems],
count: Optional[int],
start: Optional[str],
filters: Optional[api.Filters],
) -> Items:
if isinstance(source, pd.DataFrame):
return Items.from_df(source)
elif isinstance(source, Iterable) and not isinstance(source, str):
return Items.from_array(cast(RawItems, source))
elif helpers.is_job_key(source):
return JobItems(source, count, int(start or 0), filters)
elif helpers.is_collection_key(source):
return CollectionItems(source, count, start, filters)
else:
raise ValueError(
f"'{source}' is not a valid job or collection key")
def test_items_from_array(raw):
items = Items.from_array(raw)
np.testing.assert_array_equal(items.raw, np.array(raw))
pd.testing.assert_frame_equal(items.df, pd.DataFrame(list(raw)))