def compress_into_one_file(self) -> pd.DataFrame:
path_to_files = search_import_file(
where=os.path.join(self.parent, self.master, self.download_folder),
extension=".xlsx",
)
consolidated = pd.DataFrame()
for path_to_file in path_to_files:
dummy = pd.read_excel(path_to_file, sheet_name="Data")
consolidated = pd.concat([consolidated, dummy], sort=False)
return consolidated
def run_delete_all_xlsx(self):
xlsx_dir = os.path.join(self.parent, self.master, self.download_folder)
if os.path.isdir(xlsx_dir):
xlsx = search_import_file(".xlsx", where=xlsx_dir)
list(map(lambda x: os.remove(x), xlsx))
if len(xlsx) == 0:
logging.getLogger(self.script_name).info(
"tried to delete the xlsx files but they could not be found")
else:
logging.getLogger(self.script_name).info(
f"{len(xlsx)} xlsx files were deleted")
def rename(self, filename: str) -> None:
"""
Visit the temp file, rename the file with the correct name and move it
to the self.download_folder
"""
path_where_file_to_rename = os.path.join(self.parent, self.master,
self.temp_folder)
found = search_import_file(where=path_where_file_to_rename,
extension="xls")
if len(found) > 1:
raise ValueError(
f"Too many temp files in the {self.temp_folder} folder")
try:
file_to_rename = found[0]
abs_path = os.path.join(self.parent, self.master,
self.download_folder, filename)
os.rename(file_to_rename, abs_path)
except IndexError:
time.sleep(10)
def process_files(self) -> list:
path_to_mapping = os.path.join(
self.parent, self.master, self.mapping_file_name)
files = search_import_file(
where=os.path.join(self.parent, self.master, self.download_folder),
extension=".xls",
)
keep_track_test_case_num = 1
data = dict()
self.init_progress_counter(path_to_mapping)
for file in files:
logging.getLogger(self.script_name).info(
f"Processing started for: {file}")
path_to_file = os.path.join(
self.parent, self.master, self.download_folder, file
)
if self.check_file_size(path_to_file):
process = pd.read_excel(
path_to_file,
encoding="iso-8859-1",
header=None
)
final_json = self.mash_data(process)
df = self.convert_to_df(final_json)
if (
self.ticket_does_not_exist(path_to_mapping, file)
and df.empty is False
):
df = self.complement_missing_data(df)
ordering = self.grab_first_item(df)
df = self.apply_ordering(df, ordering)
df = self.convert_to_xray_format(
df,
file,
keep_track_test_case_num,
path_to_mapping,
)
df = self.add_url(df, path_to_mapping, file)
payload = self.create_jira_ticket_payload(df, file)
if (
payload is not None
and "description" in payload.keys()
):
_id = payload["description"]
data[_id] = payload
payloads = self.save_json(data)
jira_key = self.create_jira_ticket(payload)
self.add_jira_key(jira_key, path_to_mapping, file)
if len(jira_key) > 0:
self.update_label_jira_ticket(df, jira_key)
self.generate_excel(df, file)
keep_track_test_case_num += 1
else:
logging.getLogger(self.script_name).info(
f"Webservice not called as there is nothing to create. The process on ARIS does not justify the test case creation"
)
else:
logging.getLogger(self.script_name).info(
f"{path_leaf(file)} is too small, skipping"
)
if self.total_tickets != 0:
progress = (keep_track_test_case_num-1)*100/self.total_tickets
self.update_progress_bar(progress, keep_track_test_case_num)
return payloads