Reputation: 2781
I'm trying to create an endpoint for loading an excel file into server and importing the data in it. To do it I'm using django-import-export package. This is the view code:
def create(self, request, *args, **kwargs):
file_serializer = self.get_serializer(data=request.data)
file_serializer.is_valid(raise_exception=True)
if file_serializer.is_valid():
from tablib import Dataset
from workflows.submittals.admin import ItemImportResource
item_model_resource = ItemImportResource()
file_serializer.save()
dataset = Dataset()
file_obj = request.FILES['file']
imported_data = Dataset().load(open(file_obj).read())
result = item_model_resource.import_data(dataset, dry_run=True)
if not result.has_errors():
item_model_resource.import_data(dataset, dry_run=False)
return Response(file_serializer.data, status=status.HTTP_201_CREATED)
else:
return Response(file_serializer.errors, status=status.HTTP_400_BAD_REQUEST)
When loading the file into the (tablib) Dataset, I'm getting this error:
'invalid file: <InMemoryUploadedFile: Import_Sample_test1.xls (application/vnd.ms-excel)>'
I tried reffering the name of the file, so replaced
imported_data = Dataset().load(open(file_obj).read())
with
imported_data = Dataset().load(open(file_obj.name).read())
Then it seems like the Dataset does loads the file, because in the response I see some byte representation of the file, but I also get this error message:
'ascii' codec can't decode byte 0xd0 in position 0: ordinal not in range(128)
Any idea?
UPDATE: my ItemImportModel model:
class ItemImportModel(models.Model):
spec_section_identifier = models.CharField('Spec Section #', max_length=15)
spec_section_name = models.CharField('Spec Section Name',max_length=200)
sub_spec_section = models.CharField('Sub Spec Section', max_length=200, null=True, blank=True)
title = models.CharField(max_length=200)
description = models.TextField(null=True, blank=True, default="")
type = models.CharField(max_length=50, choices=Item.ITEM__TYPES)
Upvotes: 1
Views: 623
Reputation: 2781
The main issue was the dataset.load part.
Apparently there should be different handling for different types of file.
This what finally worked for me
for csv-
imported_data = dataset.load(open(file_obj.name).read())
for xls-
imported_data = dataset.load(open(file_obj.name, 'rb').read(), 'xls')
for xlsx -
imported_data = dataset.load(open(file_obj.name, 'rb').read(), 'xlsx')
Upvotes: 2