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Getting started — django-import-export 4.3.10.dev1 documentation

This section describes how to get started with import-export. We’ll use the example application as a guide.

import-export can be used programmatically as described here, or it can be integrated with the Django Admin interface.

There are sample files which can be used to test importing data in the tests/core/exports directory.

For example purposes, we’ll use a simplified book app. Here is our models.py:

# app/models.py

class Author(models.Model):
    name = models.CharField(max_length=100)

    def __str__(self):
        return self.name


class Category(models.Model):
    name = models.CharField(max_length=100)

    def __str__(self):
        return self.name


class Book(models.Model):
    name = models.CharField('Book name', max_length=100)
    author = models.ForeignKey(Author, blank=True, null=True)
    author_email = models.EmailField('Author email', max_length=75, blank=True)
    imported = models.BooleanField(default=False)
    published = models.DateField('Published', blank=True, null=True)
    price = models.DecimalField(max_digits=10, decimal_places=2, null=True, blank=True)
    categories = models.ManyToManyField(Category, blank=True)

    def __str__(self):
        return self.name

To integrate import-export with our Book model, we will create a ModelResource class in admin.py that will describe how this resource can be imported or exported:

# app/admin.py

from import_export import resources
from core.models import Book

class BookResource(resources.ModelResource):

    class Meta:
        model = Book  # or 'core.Book'

Let’s import some data!

1>>> import tablib
2>>> from import_export import resources
3>>> from core.models import Book
4>>> book_resource = resources.modelresource_factory(model=Book)()
5>>> dataset = tablib.Dataset(['', 'New book'], headers=['id', 'name'])
6>>> result = book_resource.import_data(dataset, dry_run=True)
7>>> print(result.has_errors())
8False
9>>> result = book_resource.import_data(dataset, dry_run=False)

In the fourth line we use modelresource_factory() to create a default ModelResource. The ModelResource class created this way is equal to the one shown in the example in section Creating a resource. For more advanced usage of this function, see Using modelresource_factory.

In fifth line a Dataset with columns id and name, and one book entry, are created. A field (or combination of fields) which uniquely identifies an instance always needs to be present. This is so that the import process can manage creates / updates. In this case, we use id. For more information, see Create or update model instances.

In the rest of the code we first pretend to import data using import_data() and dry_run set, then check for any errors and actually import data this time.

See also

Import workflow

for a detailed description of the import workflow and its customization options.

To delete objects during import, implement the for_delete() method on your Resource class. You should add custom logic which will signify which rows are to be deleted.

For example, suppose you would like to have a field in the import dataset to indicate which rows should be deleted. You could include a field called delete which has either a 1 or 0 value.

In this case, declare the resource as follows:

class BookResource(resources.ModelResource):

    def for_delete(self, row, instance):
        return row["delete"] == "1"

    class Meta:
        model = Book

If the delete flag is set on a ‘new’ instance (i.e. the row does not already exist in the db) then the row will be skipped.

Now that we have defined a ModelResource class, we can export books:

>>> from core.admin import BookResource
>>> dataset = BookResource().export()
>>> print(dataset.csv)
id,name,author,author_email,imported,published,price,categories
2,Some book,1,,0,2012-12-05,8.85,1

Warning

Data exported programmatically is not sanitized for malicious content. You will need to understand the implications of this and handle accordingly. See Security.

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