Configure Mocks (Part 2)

Improve Your Tests With the Python Mock Object Library Lee Gaines 01:41

00:00 One more quick thing about configuring your mocks. Here’s another example. In our previous code, we had this mocked response from our get_holidays() API that had two holidays in it. In reality, your responses from an API may have thousands, tens of thousands, hundreds of thousands of key-value pairs in it.

00:20 When you configure your Mock object, obviously you don’t want to one-by-one type out every single key-value pair. Usually you’re going to have that stored somewhere in memory, in a variable like this.

00:32 So, holidays is the same exact dictionary as what we had typed in our mock response. So if you have access to a variable that contains the data that you want to mock, you can configure your mock to use that instead of hand typing it yourself.

00:50 So instead of creating a response_mock as just a generic Mock object and then defining its .json.return_value, what you could do is say response_mock is a Mock object, and then use this little syntax here—this double star (**)—to unpack a dictionary of 'json.return_value', and then this key will have the value of holidays.

01:20 So now we can say response_mock.json() and it returns that dictionary.

01:29 That’s just a really nice tool to have actual data inside your Mock object without having to copy and paste it or type it by hand.

gabrielyassunaga on Dec. 26, 2022

isn’t this the same as using this?

response_mock.json.return_value = holidays

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