def post(self, request, *args, **kwargs):
data_header = self.get_lang()
files = self.request.FILES.get('file')
if files:
excel_type = files.name.split('.')[1]
if excel_type in ['xlsx', 'xls', 'csv']:
self.get_queryset().delete()
df = pd.read_excel(files)
df.drop_duplicates(keep='first', inplace=True)
data_list = df.drop_duplicates(subset=[
data_header.get('customer_name')
],
keep='first').values
for d in range(len(data_list)):
data_validate(str(data_list[d]))
for i in range(len(data_list)):
if str(data_list[i][0]) == 'nan':
continue
else:
if str(data_list[i][1]) == 'nan':
data_list[i][1] = 'N/A'
if str(data_list[i][2]) == 'nan':
data_list[i][2] = 'N/A'
if is_number(str(data_list[i][3])):
if str(data_list[i][3]) == 'nan':
data_list[i][3] = 0
else:
data_list[i][3] = 0
if str(data_list[i][4]) == 'nan':
data_list[i][4] = 'N/A'
if is_number(str(data_list[i][5])):
if str(data_list[i][5]) == 'nan':
data_list[i][5] = 0
else:
data_list[i][5] = 0
customer.objects.create(
openid=self.request.auth.openid,
customer_name=str(data_list[i][0]).strip(),
customer_city=str(data_list[i][1]).strip(),
customer_address=str(data_list[i][2]).strip(),
customer_contact=data_list[i][3],
customer_manager=str(data_list[i][4]).strip(),
customer_level=data_list[i][5],
creater=self.request.auth.name)
else:
raise APIException(
{"detail": "Can Not Support This File Type"})
else:
raise APIException({"detail": "Please Select One File"})
return Response({"detail": "success"})
def post(self, request, *args, **kwargs):
files = self.request.FILES.get('file')
if files:
excel_type = files.name.split('.')[1]
if excel_type in ['xlsx', 'xls', 'csv']:
self.get_queryset().delete()
df = pd.read_excel(files)
data_list = df.drop_duplicates(keep='first',
inplace=True).values
for d in range(len(data_list)):
data_validate(str(data_list[d]))
for i in range(len(data_list)):
if str(data_list[i][0]) == 'nan':
data_list[i][0] = 'N/A'
if str(data_list[i][1]) == 'nan':
data_list[i][1] = 'N/A'
if is_number(str(data_list[i][2])):
if str(data_list[i][2]) == 'nan':
data_list[i][2] = 0
else:
data_list[i][2] = 0
if is_number(str(data_list[i][3])):
if str(data_list[i][3]) == 'nan':
data_list[i][3] = 0
else:
data_list[i][3] = 0
if is_number(str(data_list[i][4])):
if str(data_list[i][4]) == 'nan':
data_list[i][4] = 0
else:
data_list[i][4] = 0
if str(data_list[i][5]) == 'nan':
data_list[i][5] = 'N/A'
freight.objects.create(
openid=self.request.auth.openid,
send_city=str(data_list[i][0]).strip(),
receiver_city=str(data_list[i][1]).strip(),
weight_fee=data_list[i][2],
volume_fee=data_list[i][3],
min_payment=data_list[i][4],
transportation_supplier=str(data_list[i][5]).strip(),
creater=self.request.auth.name)
else:
raise APIException(
{"detail": "Can Not Support This File Type"})
else:
raise APIException({"detail": "Please Select One File"})
return Response({"detail": "success"})
def post(self, request, *args, **kwargs):
files = self.request.FILES.get('file')
if files:
excel_type = files.name.split('.')[1]
if excel_type in ['xlsx', 'xls', 'csv']:
self.get_queryset().delete()
df = pd.read_excel(files)
data_list = df.drop_duplicates(keep='first', inplace=True)
for d in range(len(data_list)):
data_validate(str(data_list[d]))
for i in range(len(data_list)):
if str(data_list[i][0]) == 'nan':
continue
else:
if is_number(str(data_list[i][1])):
if str(data_list[i][1]) == 'nan':
data_list[i][1] = 0
else:
data_list[i][1] = 0
if is_number(str(data_list[i][2])):
if str(data_list[i][2]) == 'nan':
data_list[i][2] = 0
else:
data_list[i][2] = 0
capital.objects.create(openid=self.request.auth.openid,
capital_name=str(
data_list[i][0]).strip(),
capital_qty=data_list[i][1],
capital_cost=data_list[i][2],
creater=self.request.auth.name)
else:
raise APIException(
{"detail": "Can Not Support This File Type"})
else:
raise APIException({"detail": "Please Select One File"})
return Response({"detail": "success"})
def create(self, request, *args, **kwargs):
data_header = self.get_lang()
files = self.request.FILES.get('file')
if files:
excel_type = files.name.split('.')[1]
if excel_type in ['xlsx', 'xls', 'csv']:
self.get_queryset().delete()
goodsunit.objects.all().delete()
goodsclass.objects.all().delete()
goodsbrand.objects.all().delete()
goodscolor.objects.all().delete()
goodsshape.objects.all().delete()
goodsspecs.objects.all().delete()
goodsorigin.objects.all().delete()
df = pd.read_excel(files)
df.drop_duplicates(keep='first', inplace=True)
data_list = df.drop_duplicates(subset=[data_header.get('goods_code')], keep='first').values
for d in range(len(data_list)):
data_validate(str(data_list[d]))
for i in range(len(data_list)):
if str(data_list[i][0]) == 'nan':
continue
else:
if str(data_list[i][1]) == 'nan':
data_list[i][1] = 'None'
if str(data_list[i][2]) == 'nan':
data_list[i][2] = 'None'
if is_number(str(data_list[i][3])):
if str(data_list[i][3]) == 'nan':
data_list[i][3] = 0
else:
data_list[i][3] = 0
if is_number(str(data_list[i][4])):
if str(data_list[i][4]) == 'nan':
data_list[i][4] = 0
else:
data_list[i][4] = 0
if is_number(str(data_list[i][5])):
if str(data_list[i][5]) == 'nan':
data_list[i][5] = 0
else:
data_list[i][5] = 0
if is_number(str(data_list[i][6])):
if str(data_list[i][6]) == 'nan':
data_list[i][6] = 0
else:
data_list[i][6] = 0
if is_number(str(data_list[i][7])):
if str(data_list[i][7]) == 'nan':
data_list[i][7] = 0
else:
data_list[i][7] = 0
if str(data_list[i][8]) == 'nan':
data_list[i][8] = 'None'
if str(data_list[i][9]) == 'nan':
data_list[i][9] = 'None'
if str(data_list[i][10]) == 'nan':
data_list[i][10] = 'None'
if str(data_list[i][11]) == 'nan':
data_list[i][11] = 'None'
if str(data_list[i][12]) == 'nan':
data_list[i][12] = 'None'
if str(data_list[i][13]) == 'nan':
data_list[i][13] = 'None'
if str(data_list[i][14]) == 'nan':
data_list[i][14] = 'None'
if is_number(str(data_list[i][15])):
if str(data_list[i][15]) == 'nan':
data_list[i][15] = 0
else:
data_list[i][15] = 0
if is_number(str(data_list[i][16])):
if str(data_list[i][16]) == 'nan':
data_list[i][16] = 0
else:
data_list[i][16] = 0
goodslist.objects.create(openid=self.request.auth.openid,
goods_code=str(data_list[i][0]).strip(),
goods_desc=str(data_list[i][1]).strip(),
goods_supplier=str(data_list[i][2]).strip(),
goods_weight=data_list[i][3],
goods_w=data_list[i][4],
goods_d=data_list[i][5],
goods_h=data_list[i][6],
unit_volume=data_list[i][7],
goods_unit=str(data_list[i][8]).strip(),
goods_class=str(data_list[i][9]).strip(),
goods_brand=str(data_list[i][10]).strip(),
goods_color=str(data_list[i][11]).strip(),
goods_shape=str(data_list[i][12]).strip(),
goods_specs=str(data_list[i][13]).strip(),
goods_origin=str(data_list[i][14]).strip(),
goods_cost=data_list[i][15],
goods_price=data_list[i][16],
creater=self.request.auth.name
)
goods_unit_list = df.drop_duplicates(subset=[data_header.get('goods_unit')], keep='first').loc[:,
data_header.get('goods_unit')].values
for i in goods_unit_list:
if str(i) == 'nan':
i = 'None'
goodsunit.objects.create(openid=self.request.auth.openid,
goods_unit=str(i).strip(),
creater=self.request.auth.name
)
goods_class_list = df.drop_duplicates(subset=[data_header.get('goods_class')], keep='first').loc[:,
data_header.get('goods_class')].values
for i in goods_class_list:
if str(i) == 'nan':
i = 'None'
goodsclass.objects.create(openid=self.request.auth.openid,
goods_class=str(i).strip(),
creater=self.request.auth.name
)
goods_brand_list = df.drop_duplicates(subset=[data_header.get('goods_brand')], keep='first').loc[:,
data_header.get('goods_brand')].values
for i in goods_brand_list:
if str(i) == 'nan':
i = 'None'
goodsbrand.objects.create(openid=self.request.auth.openid,
goods_brand=str(i).strip(),
creater=self.request.auth.name
)
goods_color_list = df.drop_duplicates(subset=[data_header.get('goods_color')], keep='first').loc[:,
data_header.get('goods_color')].values
for i in goods_color_list:
if str(i) == 'nan':
i = 'None'
goodscolor.objects.create(openid=self.request.auth.openid,
goods_color=str(i).strip(),
creater=self.request.auth.name
)
goods_shape_list = df.drop_duplicates(subset=[data_header.get('goods_shape')], keep='first').loc[:,
data_header.get('goods_shape')].values
for i in goods_shape_list:
if str(i) == 'nan':
i = 'None'
goodsshape.objects.create(openid=self.request.auth.openid,
goods_shape=str(i).strip(),
creater=self.request.auth.name
)
goods_specs_list = df.drop_duplicates(subset=[data_header.get('goods_specs')], keep='first').loc[:,
data_header.get('goods_specs')].values
for i in goods_specs_list:
if str(i) == 'nan':
i = 'None'
goodsspecs.objects.create(openid=self.request.auth.openid,
goods_specs=str(i).strip(),
creater=self.request.auth.name
)
goods_origin_list = df.drop_duplicates(subset=[data_header.get('goods_origin')], keep='first').loc[:,
data_header.get('goods_origin')].values
for i in goods_origin_list:
if str(i) == 'nan':
i = 'None'
goodsorigin.objects.create(openid=self.request.auth.openid,
goods_origin=str(i).strip(),
creater=self.request.auth.name
)
else:
raise APIException({"detail": "Can Not Support This File Type"})
else:
raise APIException({"detail": "Please Select One File"})
return Response({"detail": "Success"})