10-Apr-2020
Testing GraphQL To Leverage API
By Raghav Vashishth
10-Apr-2020
By Raghav Vashishth
GraphQL is a query language for APIs, which offers simplification of queries and responses for usage with mobile applications, and complex APIs. GraphQL was initially created to solve selected problems. In 2011 as people migrated from web to mobile, most of the users were interfacing with applications from their browsers. In the case of Facebook, particularly, it is required to call multiple APIs from various locations within the application. Counting on what the scenario was trying to realize, those APIs would either provide an excessive amount of or insufficient information. So, to unravel this challenge, Facebook sought to make how that might simplify the delivery of data and reduce the entire traffic that was required to achieve their scenarios. At that time, GraphQL was employed by the iOS team of Facebook and generated to the remaining mobile interfaces. Soon an overwhelming majority of cellular interactions were leveraging their GraphQL APIs. In 2015, Facebook announced the implementation, and the planet saw the benefits of using it, with rising adoption.
With increasing popularity, developers are looking out for GraphQL documentation generators. There are few best GraphQL documentation generators and tools, like Graphdoc, GraphQL Docs, DocQL (Beta), and Graphqldoc by Mvochoa, which will save a lot of your time in documenting your code.
GraphQL is an abstraction layer that lies between the backend APIs and the front-end systems. This abstraction layer grants you to construct queries that approach multiple resources at the backend and accumulate that data well-adjusted into an individual consequential reply. It is way to streamline the interactions with your backend info, by using a medium whose schemas express the system behaviour to get adequate data from your APIs. Functions make subsequent calls to the backend, consistent with your business logic, against your REST APIs, databases, and the other resources necessary to gather the info that was requested.
It is crucial to validate your GraphQL APIs, in order to ensure that your API consumers access their information efficiently. Automated testing of GraphQL plays a vital role here as the most functional GraphQL testing is designed in a way to ensure that the schema, queries, and mutations work on the front-end, according to the expectations. One can create complex tests against GraphQL APIs and data, and easily create assertions against data queried using GraphQL. It helps in reducing test creation time and improves overall coverage of the back-end.
Many GraphQL testing tools are available in the market to perform testing based on your language, platform, test infrastructure, and testing requirements. Let us have a look at some of them:
While using GraphQL for APIs, it is essential to test them, and automation is a bonus to it. Karate is an open-source tool for GraphQL API test automation with plenty of features to adapt to GraphQL testing quickly. Karate uses Gherkin, which is the same syntax as used for cucumber specification. Without going deep into many implementation details, it gives an extremely simplified way for test description.
It is one of the most popular functional GraphQL testing tools used by JavaScript developers. One can quickly test assertions to verify API responses by integrating with a library like Mocha, for test automation. Few tests like Query tests, Mutation tests, Load tests, and Security tests are beneficial for better performance.
Testing GraphQL queries and mutations is preferred using Ready API, and performance can be assessed with load testing, along with web services virtualization. Developers can create, manage, and execute all these test automation in a single centralized interface without writing a lot of code, and enhance the quality of API for Agile and DevOps teams.
With GraphQL, the user is in a position to form one call to fetch the specified information instead of constructing several REST requests. Below are some of the advantages of using GraphQL.
· Characterize a data type
As GraphQL queries mirror their reply, it is easy to anticipate the form of the information returned from a question. It helps in writing a query according to your app requirements.
· Hierarchical by nature
GraphQL instinctively follows an exchange between objects, where a RESTful service may require multiple round-trips or a posh join statement in SQL. This hierarchy pairs well with graph-structured info stores and conclusively with the hierarchical user interfaces.
· Firmly Typed
Every level of a GraphQL query corresponds to a specific type, which in turn describes a group of obtainable fields. Like SQL, this enables GraphQL to supply descriptive error messages before executing code.
· Thoughtful
A GraphQL server creates a secure platform for tools and client software, mainly for code generation in statically typed languages, Relay, or IDEs like GraphiQL. GraphiQL helps developers master and examine an API quickly without grepping the codebase.
· No Versions
The shape of the returned data is decided entirely by the client’s query, so servers become simple and straightforward to conclude. When you’re incorporating new product features, additional fields are mostly added to the server. When you’re sunsetting older features, the corresponding server fields are deprecated. This gradual, backward-compatible process removes the necessity for an incrementing version number.
To conclude, the GraphQL is one of the preferred query languages for APIs, mainly because of its strongly typed schema, which enables rapid product development with a fantastic community and open-source ecosystem. Extensive usage of GraphQL can attribute to lower traffic congestion and accurate and fast applications in the future.
Raghav Vashishth
Raghav is a QA enthusiast working as a Team Lead at BugRaptors. He has diverse exposure in various projects and application testing with a comprehensive understanding of all aspects of SDLC. He has 7 plus years of hands-on experience with blue-chip companies like Hitachi, Vmware, and Kloves. He is well versed in Load and Performance testing, API Testing, Manual testing, Mobile application testing, Web application testing and can create effective documentation related to testing such as Test Plan, Test Cases, Test Reports, etc.
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