#Local dynamodb flaky tests how to
#Local dynamodb flaky tests code

The code would handle a local endpoint resource passed into the test methods.

Earlier, I launched a docker instance of DynamoDB before running the tests.I made a basic comparison of how long it took to run before and after using mocking in Github Actions CI. Using a mock library has definitely made it easier and faster to run tests. HereвЂ™s the final test file that we have written. (env ) We can now confirm that our DynamoDB operations are written correctly.

Test_table_exists (_main_.TestDatabaseFunctions ). Test_put_movie (_main_.TestDatabaseFunctions ). Test_get_movie (_main_.TestDatabaseFunctions ). This ensures that any operation is run on the mock resource and not the local database instance.

Remember that part about dynamodb argument, this is where we use it to pass the mock database resource to the function. Self.table is the mock table that will be used by the rest of the test methods. Hence, the import within the test method ensures that mock is already established. To avoid this, we make sure all the mocks are established BEFORE the resources are setup. Well, in this case, if we do an import of a function that instantiates a boto3 resource, it might actually make calls to AWS. After all we want to make sure weвЂ™re using the table that is actually used in production and this helps us not rewrite a whole block of code to create a table.ДЄ question you might ask is why donвЂ™t we import all the functions at the top of the file? Most examples seems to use that. The line from MoviesCreateTable import create_movie_table is weвЂ™re going to use the create_movie_table function to create our mock table. We can rest assured that moto will take care of mocking the calls to create this resource. The self.dynamodb is the mock DynamoDB resource that will be used for the test. resource( 'dynamodb', region_name = 'us-east-1')ДЇrom MoviesCreateTable import create_movie_table

Import a few modules that we will be using in our tests.

Now, just keep that argument in mind going in to the next steps.

As the example shows, if no resource is provided, it attempts to make a dynamodb resource by connecting to the local address, hence the endpoint_url is set to Bascially, the function expects to have a local instance of DynamoDB running, if no resource is passed.

(where the default argument value is set to None if no database resource is provided.)

Note that this function takes an argument dynamodb.

This function creates the DynamoDB table вЂMoviesвЂ™ with the primary-key year (partition-key) and title (sort-key).

#Local dynamodb flaky tests how to

WeвЂ™ll use 3 of the DynamoDB functions shown in the example.Д«efore we start, we need to think of how to structure them. The Python and DynamoDB examples used in the AWS documentation is a good reference point, so we can start writing some tests for a few functions. The goal is to share a general idea of how to approach to writing unit tests for your app code and show how to use moto library. In this post, IвЂ™ll be explaining an example of using this library to test DynamoDB operations using Python unittest. It allows you to mock AWS services so that you can run unit tests locally, with expected responses from AWS, without actually calling any services/resources on AWS. Moto is a really cool Python library that helped me a lot recently.

Tests might run slow due to latency issues.

Tests might end up changing actual data or resources on a production environment.

When running tests for functions that use AWS services, we would be calling actual services/resources on AWS if we didnвЂ™t mock them.