FakeIt Series 4 of 5: Working with Existing Data

Aaron Benton is an experienced architect who specializes in creative solutions to develop innovative mobile applications. He has over 10 years experience in full stack development, including ColdFusion, SQL, NoSQL, JavaScript, HTML, and CSS. Aaron is currently an Applications Architect for Shop.com in Greensboro, North Carolina and is a Couchbase Community Champion.

FakeIt Series 4 of 5: Working with Existing Data

So far in our FakeIt series we’ve seen how we can Generate Fake Data, Share Data and Dependencies, and use Definitions for smaller models. Today we are going to look at the last major feature of FakeIt, which is working with existing data through inputs.

Rarely as developers do we get the advantage of working on greenfield applications, our domains are more often than not a comprised of different legacy databases and applications. As we are modeling and building new applications, we need to reference and use this existing data.  FakeIt allows you to provide existing data to your models through JSON, CSV or CSON files. This data is exposed as an inputs variable in each of a models *run and *build functions.

Users Model

We will start with our users.yaml model that we updated to in our most recent post to use Address y Phone definitions.

 

Currently, our Address definition is generating a random country. What if our ecommerce site only supports a small subset of the 195 countries? Let’s say we support six countries to start with: US, CA, MX, UK, ES, DE. We could update the definitions country property to grab a random array element:

(For brevity the other properties have been left off of the model definition)

While this would work, what if we have other models that rely on this same country info, we would have to duplicate this logic. We can achieve this same thing by creating a countries.json file, and adding an inputs property to the data property that can be an absolute or relative path to our input. When are model is generated, our countries.json file will be exposed to each of the models build functions via the inputs argument as inputs.countries

(For brevity the other properties have been left off of the model definition)

By changing one existing line and adding another line in model we have provided existing data to our Users model. We can still generate a random country, based on the countries our application supports. Lets test our changes by using the following command:

Products Model

Our ecommerce application is using a separate system for categorization, we need to expose that data to our randomly generated products so that we are using valid category information. We will start with the products.yaml that we defined in the FakeIt Series 2 of 5: Shared Data and Dependencies post.

Our existing categories data has been provided in CSV format.

Now we need to update our products.yaml model to use this existing data.

(For brevity the other properties have been left off of the model definition)

There are a few things to notice about how we’ve updated our products.yaml model.

• inputs: is defined as an array not a string. While we are only using a single input, you can provide as many input files to your model as necessary.
• A pre_build function is defined at the root of the model. This is because we cannot grab a random array element for each of our three category properties as the values would not match. Each time an individual document is generated for our model, this pre_build function will run first.
• Each of our category properties build functions reference the global variable set by the pre_build function on our model.

We can test our changes by using the following command:

Conclusión

Being able to work with existing data is an extremely powerful feature of FakeIt. It can be used to maintain the integrity of randomly generated documents to work with existing system, and can even be used to transform existing data and import it into Couchbase Server.

Up Next

• FakeIt Series 5 of 5: Rapid Mobile Development w/ Sync-Gateway

Previous

• FakeIt Series 1 of 5: Generating Fake Data
• FakeIt Series 2 of 5: Shared Data and Dependencies
• FakeIt Series 3 of 5: Lean Models through Definitions

This post is part of the Couchbase Community Writing Program