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Fix: reverse month, xlsx format

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dx-tan 2024-02-06 15:59:27 +07:00
parent 0bed104cac
commit e6302c8f3b
3 changed files with 26 additions and 11 deletions
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3
cope2n-api/fwd_api/celery_worker/internal_task.py
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@ -132,9 +132,12 @@ def process_csv_feedback(csv_file_path, feedback_id):
else: else:
None None
else: else:
try:
_predict_result = {"retailername": None, "sold_to_party": None, "purchase_date": [], "imei_number": [_predict_result["imei_number"][image.index_in_request]]} _predict_result = {"retailername": None, "sold_to_party": None, "purchase_date": [], "imei_number": [_predict_result["imei_number"][image.index_in_request]]}
_feedback_result = {"retailername": None, "sold_to_party": None, "purchase_date": None, "imei_number": [_feedback_result["imei_number"][image.index_in_request]]} if _feedback_result else None _feedback_result = {"retailername": None, "sold_to_party": None, "purchase_date": None, "imei_number": [_feedback_result["imei_number"][image.index_in_request]]} if _feedback_result else None
_reviewed_result = {"retailername": None, "sold_to_party": None, "purchase_date": None, "imei_number": [_reviewed_result["imei_number"][image.index_in_request]]} if _reviewed_result else None _reviewed_result = {"retailername": None, "sold_to_party": None, "purchase_date": None, "imei_number": [_reviewed_result["imei_number"][image.index_in_request]]} if _reviewed_result else None
except Exception as e:
print (f"[ERROR]: {request_id} - {e}")
image.predict_result = _predict_result image.predict_result = _predict_result
image.feedback_result = _feedback_result image.feedback_result = _feedback_result
image.reviewed_result = _reviewed_result image.reviewed_result = _reviewed_result

4
cope2n-api/fwd_api/utils/accuracy.py
View File

@ -206,7 +206,9 @@ class ReportAccumulateByRequest:
save_data = {"file": {"overview": f"{root_report_id}/{root_report_id}.xlsx"}, save_data = {"file": {"overview": f"{root_report_id}/{root_report_id}.xlsx"},
"data": fine_data} # {"sub_report_id": "S3 location", "data": fine_data} "data": fine_data} # {"sub_report_id": "S3 location", "data": fine_data}
# extract data # extract data
for month in report_data.keys(): month_keys = list(report_data.keys())
month_keys.sort(reverse=True)
for month in month_keys:
fine_data.append(report_data[month][0]) fine_data.append(report_data[month][0])
day_keys = list(report_data[month][1].keys()) day_keys = list(report_data[month][1].keys())
day_keys.sort(reverse = True) day_keys.sort(reverse = True)

18
cope2n-api/fwd_api/utils/file.py
View File

@ -22,7 +22,7 @@ from ..celery_worker.client_connector import c_connector
import imagesize import imagesize
import csv import csv
from openpyxl import load_workbook from openpyxl import load_workbook
from openpyxl.styles import Font, Border, Side, PatternFill, NamedStyle from openpyxl.styles import Font, Border, Side, PatternFill, NamedStyle, numbers
s3_client = S3Util.MinioS3Client( s3_client = S3Util.MinioS3Client(
endpoint=settings.S3_ENDPOINT, endpoint=settings.S3_ENDPOINT,
@ -496,6 +496,8 @@ def dict2xlsx(input: json, _type='report'):
if _type == 'report': if _type == 'report':
if subtotal['subs'] == '+': if subtotal['subs'] == '+':
ws[key + str(start_index)].font = font_black_bold ws[key + str(start_index)].font = font_black_bold
if key_index in [6, 8, 9, 10, 11, 12, 13]:
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
if key_index == 0 or (key_index >= 9 and key_index <= 15): if key_index == 0 or (key_index >= 9 and key_index <= 15):
ws[key + str(start_index)].fill = fill_gray ws[key + str(start_index)].fill = fill_gray
elif key_index == 1: elif key_index == 1:
@ -503,12 +505,20 @@ def dict2xlsx(input: json, _type='report'):
elif key_index >= 4 and key_index <= 8: elif key_index >= 4 and key_index <= 8:
ws[key + str(start_index)].fill = fill_yellow ws[key + str(start_index)].fill = fill_yellow
else: else:
if 'average_accuracy_rate' in mapping[key] and type(value) in [int, float] and value < 95: if 'average_accuracy_rate' in mapping[key] and type(value) in [int, float]:
if value < 95:
ws[key + str(start_index)].style = normal_cell_red ws[key + str(start_index)].style = normal_cell_red
elif 'average_processing_time' in mapping[key] and type(value) in [int, float] and value > 2.0: ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
elif 'average_processing_time' in mapping[key] and type(value) in [int, float]:
if value > 2.0:
ws[key + str(start_index)].style = normal_cell_red ws[key + str(start_index)].style = normal_cell_red
elif 'bad_percent' in mapping[key] and type(value) in [int, float] and value > 10: ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
elif 'bad_percent' in mapping[key] and type(value) in [int, float]:
if value > 10:
ws[key + str(start_index)].style = normal_cell_red ws[key + str(start_index)].style = normal_cell_red
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
elif 'percent' in mapping[key] and type(value) in [int, float]:
ws[key + str(start_index)].number_format = numbers.FORMAT_NUMBER_00
else : else :
ws[key + str(start_index)].style = normal_cell ws[key + str(start_index)].style = normal_cell
elif _type == 'report_detail': elif _type == 'report_detail':