def test_all_formats(mock_find_executable):
mock_find_executable.return_value = True
csvw = CSVW(csv_path="./tests/books.csv",
metadata_path="./tests/books.csv-metadata.json")
assert mock_find_executable.call_count == 0
# Create file like objects
input_val = []
for f in TEST_PARAMS:
input_val.append((tempfile.TemporaryFile(), f[0]))
csvw.to_rdf_files(input_val)
# Check each output
for fmt in zip(input_val, TEST_PARAMS):
file_obj = fmt[0][0]
validate_func = fmt[1][1]
rdflib_input = fmt[1][2]
# Rewind and read
file_obj.seek(0)
contents = file_obj.read().decode('utf-8')
# Validate
validate_func(contents)
verify_rdf_contents(contents, rdflib_input)
assert mock_find_executable.call_count == 1
def process_csv(csv_file, metadata_file, riotpath, g = None):
# Generate RDF from a CSV file and metadata file pair,
# csv_file is a path string
# metadata-file is a path string path optionally merging it into a Graph
if g is None:
g = Graph()
csvw = CSVW(csv_path = csv_file, metadata_path = metadata_file, riot_path = riotpath)
with NamedTemporaryFile() as f:
rdf_output = csvw.to_rdf_files([ (f,'turtle') ])
f.seek(0)
g.parse(f, format = 'ttl')
csvw.close()
return g