how to import csv data into django models

I have some CSV data and I want to import into django models using the example CSV data:

1;"02-01-101101";"Worm Gear HRF 50";"Ratio 1 : 10";"input shaft, output shaft, direction A, color dark green";
2;"02-01-101102";"Worm Gear HRF 50";"Ratio 1 : 20";"input shaft, output shaft, direction A, color dark green";
3;"02-01-101103";"Worm Gear HRF 50";"Ratio 1 : 30";"input shaft, output shaft, direction A, color dark green";
4;"02-01-101104";"Worm Gear HRF 50";"Ratio 1 : 40";"input shaft, output shaft, direction A, color dark green";
5;"02-01-101105";"Worm Gear HRF 50";"Ratio 1 : 50";"input shaft, output shaft, direction A, color dark green";

I have some django models named Product. In Product there are some fields like name, description and price. I want something like this:

product=Product()
product.name = "Worm Gear HRF 70(02-01-101116)"
product.description = "input shaft, output shaft, direction A, color dark green"
product.price = 100

You want to use the csv module that is part of the python language and you should use Django's get_or_create method

 with open(path) as f:
        reader = csv.reader(f)
        for row in reader:
            _, created = Teacher.objects.get_or_create(
                first_name=row[0],
                last_name=row[1],
                middle_name=row[2],
                )
            # creates a tuple of the new object or
            # current object and a boolean of if it was created

In my example the model teacher has three attributes first_name, last_name and middle_name.

Django documentation of get_or_create method

If you want to use a library, a quick google search for csv and django reveals two libraries - django-csvimport and django-adaptors. Let's read what they have to say about themselves...

django-adaptors:

Django adaptor is a tool which allow you to transform easily a CSV/XML file into a python object or a django model instance.

django-importcsv:

django-csvimport is a generic importer tool to allow the upload of CSV files for populating data.

The first requires you to write a model to match the csv file, while the second is more of a command-line importer, which is a huge difference in the way you work with them, and each is good for a different type of project.

So which one to use? That depends on which of those will be better suited for your project in the long run.

However, you can also avoid a library altogether, by writing your own django script to import your csv file, something along the lines of (warning, pseudo-code ahead):

# open file & create csvreader
import csv, yada yada yada

# import the relevant model
from myproject.models import Foo

#loop:
for line in csv file:
     line = parse line to a list
     # add some custom validation\parsing for some of the fields

     foo = Foo(fieldname1=line[1], fieldname2=line[2] ... etc. )
     try:
         foo.save()
     except:
         # if the're a problem anywhere, you wanna know about it
         print "there was a problem with line", i

It's super easy. Hell, you can do it interactively through the django shell if it's a one-time import. Just - figure out what you want to do with your project, how many files do you need to handle and then - if you decide to use a library, try figuring out which one better suits your needs.

You can also use, django-adaptors

>>> from adaptor.model import CsvModel
>>> class MyCSvModel(CsvModel):
...     name = CharField()
...     age = IntegerField()
...     length = FloatField()
...
...     class Meta:
...         delimiter = ";"

You declare a MyCsvModel which will match to a CSV file like this:

Anthony;27;1.75

To import the file or any iterable object, just do:

>>> my_csv_list = MyCsvModel.import_data(data = open("my_csv_file_name.csv"))
>>> first_line = my_csv_list[0]
>>> first_line.age
    27

Without an explicit declaration, data and columns are matched in the same order:

Anthony --> Column 0 --> Field 0 --> name
27      --> Column 1 --> Field 1 --> age
1.75    --> Column 2 --> Field 2 --> length

For django 1.8 that im using,

I made a command that you can create objects dynamically in the future, so you can just put the file path of the csv, the model name and the app name of the relevant django application, and it will populate the relevant model without specified the field names. so if we take for example the next csv:

field1,field2,field3
value1,value2,value3
value11,value22,value33

it will create the objects [{field1:value1,field2:value2,field3:value3}, {field1:value11,field2:value22,field3:value33}] for the model name you will enter to the command.

the command code:

from django.core.management.base import BaseCommand
from django.db.models.loading import get_model
import csv


class Command(BaseCommand):
    help = 'Creating model objects according the file path specified'

    def add_arguments(self, parser):
        parser.add_argument('--path', type=str, help="file path")
        parser.add_argument('--model_name', type=str, help="model name")
        parser.add_argument('--app_name', type=str, help="django app name that the model is connected to")

    def handle(self, *args, **options):
        file_path = options['path']
        _model = get_model(options['app_name'], options['model_name'])
        with open(file_path, 'rb') as csv_file:
            reader = csv.reader(csv_file, delimiter=',', quotechar='|')
            header = reader.next()
            for row in reader:
                _object_dict = {key: value for key, value in zip(header, row)}
                _model.objects.create(**_object_dict)

note that maybe in later versions

from django.db.models.loading import get_model

is deprecated and need to be change to

from django.apps.apps import get_model

how to import csv data into django models

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