We are creating Postman Collections for each of the APIs we are profiling for inclusion in the Streamdata.io API Gallery. To make sure we have a complete working profile of each API, we prefer firing them up using the Postman Client, and then exporting them as a Postman Collection. We intend to include each of these Postman Collections in the Streamdata.io API Gallery, allowing each API path to eventually be executable in one click from each of the gallery detail pages. Postman Collections are great for working with an API in Postman, but for further documenting, benchmarking, and indexing the APIs we include in the gallery, we also like having OpenAPI definitions present.
The two API definition formats overlap, but Postman tends to be better for more runtime needs, where OpenAPI tends to have some advantages for working with an API at other stops along the API lifecycle. OpenAPI has an advantage over Postman Collections mostly because of the tooling that has emerged to work with the specification. Postman does a great job serving a handful of stops, but OpenAPI has a wider availability when it comes to the tooling that has been developed.
To produce an OpenAPI, in parallel with the Postman Collections we have, we are using API Transformer to convert from Postman Collection to OpenAPI 2.0. Eventually we will upgrade to using OpenAPI 3.0, but for now we’ll stick with the latest version, as there are more tools available for 2.0, than there is for 3.0 currently. Using the API Transformer web interface, or their API, we can convert each Postman Collection into an OpenAPI, which we then use to generate each profile in the gallery. Making for a pretty essential tool for managing API definitions, and making sure APIs are usable in a variety of development environments, services, and tooling.
We wanted to share the story of how we are using Postman Collections, and OpenAPI definitions, so that you can be putting the APIs we are profiling to work in your own projects. We are in the business of helping you streamline your data operations, which includes profiling high value data, and working to make it as easy to use as we possibly can. Sure, we want you using Streamdata.io to be making data more real time, but we also want your API operations to be as functional, and integrated with as many valuable data sources as we possibly can. The more efficient you are at putting APIs to work, the more successful you will be in your business, and the greater the chances are you will need our streaming and event-driven architecture.