def validate_assignments_file(input_directory: str,
sections: pd.DataFrame) -> List[str]:
"""
Validates that the latest assignments file has the expected
columns and all columns whose names end with `Date` or `DateTime` have the
proper format.
Parameters
----------
input_directory: str
Base / parent directory containing files created by an LMS extractor.
sections: pd.DataFrame
DataFrame containing section information read from a Sections file.
Returns
-------
List[str]
List containing detailed error messages, if any.
"""
df = fread.get_all_assignments(input_directory, sections, nrows=2)
if df.empty:
return _file_is_empty("Assignments")
expected = set([
"SourceSystemIdentifier",
"SourceSystem",
"Title",
"AssignmentCategory",
"AssignmentDescription",
"StartDateTime",
"EndDateTime",
"DueDateTime",
"SubmissionType",
"MaxPoints",
"LMSSectionSourceSystemIdentifier",
"CreateDate",
"LastModifiedDate",
"SourceCreateDate",
"SourceLastModifiedDate",
])
return _validate_columns(expected, df,
"Assignments") + _validate_date_formats(
df, "Assignments")
def it_should_return_an_empty_DataFrame(mocker, fixture) -> None:
df = get_all_assignments(BASE_DIRECTORY, INPUT_DF)
assert df.empty
def it_should_return_empty_data_frame(mocker, fixture) -> None:
df = get_all_assignments(BASE_DIRECTORY, pd.DataFrame())
assert df.empty
def it_should_read_file_into_DataFrame(mocker, fixture) -> None:
df = get_all_assignments(BASE_DIRECTORY, INPUT_DF)
assert df.iloc[0][ASSIGNMENTS] == 1
def _get_assignments_df(csv_path: str) -> DataFrame:
sections_df: DataFrame = _get_sections_df(csv_path)
if sections_df.empty:
return DataFrame()
return file_reader.get_all_assignments(csv_path, sections_df)