Sometimes, you may want to generate the same fake data output every time your code is run. Try running the script a couple times more to see what happens. Here is what happens when we run the above example: Once your provider is ready, add it to your Faker instance like we have done here: Our TravelProvider example only has one method but more can be added. That class can then define as many methods as you want. To define a provider, you need to create a class that inherits from the BaseProvider. # Add the TravelProvider to our faker object # We select a random destination from the list and return it # Our custom provider inherits from the BaseProviderĭestinations = Let’s create our own provider to test this out. You can see the default included providers here. In the localization example above, the name method we called on the myGenerator object is defined in a provider somewhere. Providers are just classes which define the methods we call on Faker objects to generate fake data.
In this case, running this code gives us the following output: Let’s change our locale to to Russia so that we can generate Russian names: Some built-in location providers include English (United States), Japanese, Italian, and Russian to name a few. Localizationįaker comes with a way of returning localized fake data using some built-in providers. You can run the example test case with this command:Īt the moment, we have two test cases, one testing that the user object created is actually an instance of the User class and one testing that the user object’s username was constructed properly. We can then go ahead and make assertions on our User object, without worrying about the data generated at all. We do not need to worry about coming up with data to create user objects. The user object is populated with values directly generated by Faker. Python calls the setUp function before each test case is run so we can be sure that our user is available in each test case. You can see that we are creating a new User object in the setUp function. Self.assertEqual(expected_username, _name)
In our test cases, we can easily use Faker to generate all the required data when creating test user objects.Įxpected_username = _name + " " + _name It also defines class properties user_name, user_job and user_address which we can use to get a particular user object’s properties. This code defines a User class which has a constructor which sets attributes first_name, last_name, job and address upon object creation. Return er_name + " lives at " + self.address Return er_name + " is a " + user_address(self): Return self.first_name + ' ' + user_job(self): Our code will live in the example file and our tests in the test file.ĭef _init_(self, first_name, last_name, job, address): Now, create two files, example.py and test.py, in a folder of your choice. Do not exit the virtualenv instance we created and installed Faker to it in the previous section since we will be using it going forward. If you are still in the Python REPL, exit by hitting CTRL+D. Let’s now use what we have learnt in an actual test. Integrating Faker with an Actual Unit Test You can also find more things to play with in the official docs. If you would like to try out some more methods, you can see a list of the methods you can call on your myFactory object using dir.
You should keep in mind that the output generated on your end will probably be different from what you see in our example - random output. Once you have created a factory object, it is very easy to call the provider methods defined on it. You can see how simple the Faker library is to use. 'Iure expedita eaque at odit soluta repudiandae nam.' Porro veritatis numquam nisi corrupti.'Īs you can see some random text was generated. Then, we are going to use the Faker class to create a myFactory object whose methods we will use to generate whatever fake data we need. Type "help", "copyright", "credits" or "license" for more information. Once in the Python REPL, start by importing Faker from faker: $ python3 -m venv faker $ source faker/bin/activateĪfter that, enter the Python REPL by typing the command python in your terminal. Let’s see how this works first by trying out a few things in the shell.īefore we start, go ahead and create a virtual environment and run it: Prerequisitesįor this tutorial, it is expected that you have Python 3.6 and Faker 0.7.11 installed.
#Generate fake data python how to
This tutorial will help you learn how to do so in your unit tests. However, you could also use a package like faker to generate fake data for you very easily when you need to. If you already have some data somewhere in a database, one solution you could employ is to generate a dump of that data and use that in your tests (i.e. When writing unit tests, you might come across a situation where you need to generate test data or use some dummy data in your tests.
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