A complete library to create dynamic model instances for testing purposes.
- Motivation
- Basic Example of Usage
- Installation
- Documentation
- Django Dynamic Fixture
- Data generation options
- Other configurations
- Debugging
- Other goodies
- Other Links
- It is a TERRIBLE practice to use STATIC data in tests.
- Create dynamic fixture for each model is boring and it produces a lot of replicated code.
- It is a bad idea to use uncontrolled data in tests, like bizarre random data.
from django.db import models
class Author(models.Model):
name = models.CharField(max_length=255)
class Book(models.Model):
name = models.CharField(max_length=255)
authors = models.ManyToManyField(Author)from django.test import TestCase
from django_dynamic_fixture import G
class SearchingBooks(TestCase):
def test_search_book_by_author(self):
author1 = G(Author)
author2 = G(Author)
book1 = G(Book, authors=[author1])
book2 = G(Book, authors=[author2])
books = Book.objects.search_by_author(author1.name)
self.assertTrue(book1 in books)
self.assertTrue(book2 not in books)pip install django-dynamic-fixture
1. Download zip file
2. Extract it
3. Execute in the extracted directory: python setup.py install
pip install -e git+git@github.com:paulocheque/django-dynamic-fixture.git#egg=django-dynamic-fixture
django-dynamic-fixture==1.6.5
# or use the development version
git+git://github.com/paulocheque/django-dynamic-fixture.git#egg=django-dynamic-fixture
pip install django-dynamic-fixture --upgrade --no-deps
- Python 2.6 or 2.7
- Django 1.2, 1.3 or 1.4
- We tried to use another fixture tools in a big Django project but the experience was not satisfactory.
- Either they are incomplete, or bugged or it produces erratic tests, because they use random and uncontrolled data.
- Also, the syntax of others tools is too verbose, which polutes the tests.
- Complete, lean and practice documentation.
- It is hard to debug tests with another tools.
- List of other tools: http://djangopackages.com/grids/g/fixtures
- The core of the tool is the algorithm, it is not the data generation as all other tools. That mean you can change the data generation logic as you want.
- Highly customizable: you can customize fields recursively
- Deal with unique=True
- Deal with cyclic dependencies (including self references)
- Deal with many to many relationship (common M2M or M2M with additional data, i.e. through='table')
- Deal with custom fields (specially if the custom field inherit of a django field)
- It is supported for parallel tests
- Deal with auto calculated attributes
- It is easy to debug errors
- Nose plugin that enable a setup for the entire suite (unittest2 includes only setups for class and module)
- Nose plugin to count how many queries are executed by test
- Command to count how many queries are executed to save any kind of model instance
- FileSystemDjangoTestCase that facilitate to create tests for features that use filesystem.
- Simple documentation: https://github.com/paulocheque/django-dynamic-fixture/wiki/Simple-Documentation
- Full documentation: https://github.com/paulocheque/django-dynamic-fixture/wiki/Documentation
- Examples of Usage: https://github.com/paulocheque/django-dynamic-fixture/wiki/Example-of-usage
- Patterns and Anti-patterns: https://github.com/paulocheque/django-dynamic-fixture/wiki/Patterns-and-Anti-Patterns
- Wiki: https://github.com/paulocheque/django-dynamic-fixture/wiki