GraphQL is an efficient query language for APIs. If you are looking for an alternative query language to Oracle PL/SQL or Apollo, GraphQL might be an ideal option for you. As with every developer tool, there are pros and cons to using GraphQL.
Follow this complete guide of the top 10 GraphQL best practices to make it easier for you to work with the tool. First, you will learn details about how GraphQL works, common concepts you will come across as you use GraphQL, and challenges you may face if you ignore these guidelines. Finally, you will find a list of the best coding bootcamps and online courses to learn GraphQL best practices.
What Is GraphQL?
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GraphQL is a programming interface for web technologies that are traditionally deployed in integrated development environments. Apart from Facebook, companies like Shopify, PayPal, and Netflix are among the most popular organizations that use GraphQL as their primary query language.
5 Concepts You Need to Understand for GraphQL Best Practices
To master GraphQL best practices, there are some terms, concepts, and frameworks you need to understand. These are some of the most popular concepts you will come across as a GraphQL developer so it is better to learn what they mean first before learning the best practices.
- API. API is an acronym for Application Programming Interface (API). It is the connection between software or computers that simplifies the programming process.
- Schema. A schema in GraphQL is a collection of data in a blueprint format. It reflects how the data is constructed into categories for analysis by a database management system.
- Pagination. Pagination in GraphQL is the process of separating your data schema into different pages digitally. Pagination ensures that each part of the dataset is divided and identified by attributes. It makes it easier for you to show the relationship between different datasets in one schema or program.
- Breaking changes. In GraphQL and other aspects of development, breaking changes occur when a seemingly small upgrade to one part of the system causes the entire program to fail. It is an avoidable problem that can only be solved by remapping the initial implementation.
- Unions and interfaces. These are abstract GraphQL types. They enable a schema field to return one of multiple object types.
5 Common Challenges That GraphQL Guidelines Can Address
Pay attention to the following best practices listed below to avoid some common pitfalls of using GraphQL. These five common challenges can be solved with proper preparation.
Breaking changes occur when a small change or upgrade to a system causes a catastrophic failure. It happens most commonly when developers do not leave room for possible future changes to the software.
Writing queries with GraphQL can be tricky. You may wind up with many illogical fragments that make your schema less readable. Ensure that when you write a GraphQL query, you are diligent in making it clean and readable.
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Slow Update Speed
When the initial schema is not properly configured, it invites a host of problems when you eventually need to expand or increase scalability. For this reason, updates will take longer than necessary.
Resource Exhaustion Attacks
A resource exhaustion attack is a security bridge that can disrupt an API interface or crash it. This common problem happens when you do not use pagination in your schema.
When you embed data into the source code of your software, it is called hardcoding. This practice reduces code readability, information privacy, makes caching more difficult, giving you limited control and little flexibility. Seasoned professionals do not rely on hardcoded arguments when they use a GraphQL server.
Top 10 GraphQL Best Practices and Guidelines
In the software development industry, best practices refer to procedures and guidelines that are widely accepted as the most effective ways to get the job done. Below is a list of some of the most popular GraphQL best practices you need to learn.
Use Consistent Naming in Your Schema
Providing consistent naming within your schema allows you to identify data easily and efficiently. When you do not set and follow a single standard for schema naming, you might find different attributes or names in the same schema referring to the same set of data. This can lead to a host of complications not just for you but for the program.
Make sure that all naming conventions like fields, data type, and pages are efficiently done and the same standard is maintained throughout. Some great naming conventions you can use for your GraphQL are camelCase and pascalCase for the fields and types respectively.
Stick to Paginate Lists
Just like paginated lists make written documents more structured and defined, they also play a role when it comes to your GraphQL schema design. Client-side pagination does more than add structure to the dataset, it also helps to link different parts of a dataset to each other. Most importantly, it is a security feature that protects your program from resource exhaustion attacks.
One of the best forms of pagination for GraphQL is cursor-based pagination. It is currently one of the most scalable options for pagination lists so you can make future changes in your schema with ease.
Make Room for Future Schema Modifications
The only constant thing when it comes to GraphQL schemas is that there will always be a need for modifications in the future. So, when you implement your schema, you need to take this into account. What happens when your web app is expanding and you need to add more fields or data to your schema? Do you have to break the original schema or did you already make room for possible modifications or expansions? Making this additional consideration will help you in the long run.
Without room for upgrades and modification during initial implementation, you will be faced with breaking changes. In this case, to solve this issue, you would have to remap the entire schema, wasting time and resources that could be better used elsewhere.
Rely on Unions and Interfaces
In the world of GraphQL, you can use interfaces and unions to simplify schemas by significantly reducing the complexity of the dataset. At the time of writing, one of the best interfaces used in GraphQL is Node Interface. Learning how to use and implement Node Interface in your schema is a good way to keep things simple.
Get Rid of Excess Illogical Fragments
In GraphQL, a fragment is a piece of logic that you can share between mutations and queries at the same time. Fragments ensure that all your queries are short, readable, and consistent. Unfortunately, these fragments can become illogical and excessive when they are not used properly.
One way to make sure that every fragment is needed is by ensuring that you only use it on fields on the schemas that have a logical semantic relationship. When you add fragments inadequately or illogically, you may end up with the opposite effect. Your queries will become less readable.
Only Query What You Need
You should only query the data you need in a particular instance and for a specific purpose. You do not need to clutter your work or take up unnecessary space by querying an entire dataset when you only need a small piece or subset. The good news is that GraphQL has declarative data-fetching capabilities that allow you to query only the fields you want to render.
Instead of using a single query for large datasets, make smaller queries for specific pieces of data. This prevents delayed responses and makes it difficult for the same type of query to be reused on the server-side.
Avoid Hardcoded Arguments
As a beginner, it is better for you to avoid hardcoded arguments that require embedding data directly into your source code. Instead, use variables for all your GraphQL arguments. Hardcoded arguments add everything, including sensitive information, to the query string. This leaves sensitive information exposed and easily accessible to bad actors.
Apart from the obvious privacy risk attached to hardcoded arguments, there is also a caching problem. For example, when you try to cache, hardcoded arguments take up unnecessary space and reduce overall caching performance.
Invest in Metrics Reporting
After your app has been developed, you should invest in premium metrics reporting tools for real-time analysis of how your product is fairing. Add your app name and version to the tool Apollo Studio and configure metrics reporting immediately. This way, you can make the necessary changes when you discover a problem or an opportunity for an upgrade.
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Apollo Studio is a cloud-based platform for building, validating, and securing an organization’s group. It is not the only option for GraphQL in the industry. Some other great alternatives to the Apollo client are Helios, Red Hat OpenShift, and Heroku.
Have a Plan for Error Handling
It is not uncommon for errors to occur at intervals regardless of how advanced the application you’re dealing with is. Error handling is the fallback plan you put in place to respond to errors as they occur and offer recovery solutions.
Enable error handling from the beginning so that your app will always have an ideal payload response even when it starts to expand and scale. When you have a good system in place, you’ll be able to tell exactly why something went wrong and be able to fix the problem.
Take Advantage of Nested Object Queries
Nesting queries is a good way to save space and improve caching among other benefits. It helps to give the server more specific instructions when a request is made. Nesting is also efficient for GraphQL if you want your app server to be capable of processing multiple fetches at the same time.
How to Learn GraphQL Best Practices
There are several resources available online to help you learn GraphQL best practices and most of them come with learning the query language itself. The most popular options to learn GraphQL are bootcamps and online courses on platforms like Udemy, Coursera, and Udacity.
Can a Bootcamp Help You Learn GraphQL Best Practices?
Yes, a bootcamp that offers GraphQL courses can help you learn GraphQL best practices and guidelines. These bootcamps have gained a lot of popularity in the tech industry over the last two decades. This is because they provide accelerated training at more affordable rates than colleges.
If you choose to learn GraphQL in a bootcamp, you will have two options. Option one is enrolling in bootcamps that offer standalone programs for GraphQL. Option two is enrolling in bootcamps that offer GraphQL as a part of a larger program. Some bootcamps you should consider are React GraphQL Academy, Code Chrysalis, and Rocket Academy.
Best Courses and Training Programs to Learn GraphQL Best Practices
|edX||Exploring GraphQL: A Query Language for APIs||$149|
|LinkedIn Learning||GraphQL Essential Training||$34.99|
|Udemy||GraphQL with React: The Complete Developers Guide||$13.99|
|Udemy||The Modern GraphQL Bootcamp with Node.js and Apollo||$13.99|
|Udemy||GraphQL by Example||$13.99|
Should You Learn GraphQL Best Practices?
Yes, you should learn GraphQL best practices if your goal is to become a professional GraphQL developer. GraphQL developers are among the highest-earning experts in the tech industry with average salaries reaching $114,997 according to ZipRecruiter. So, if you want to thrive in this field, you will benefit significantly from learning these best practices.
GraphQL Best Practices and Guidelines FAQ
Actions and mutations are the two most common actions in GraphQL on the Hasura GraphQL engine. Actions allow you to fetch data from any data source you want without making structural changes. Mutations allow you to modify your state object.
GraphQL has a bad rap when it comes to caching, which is considered one of its biggest pitfalls. It has limited capabilities when it is time for you to send complex data back and forth. The only time GraphQL does this efficiently is when it comes to caching plain text. This is why REST and Falcor are considered more efficient than GraphQL APIs.
When it comes to GraphQL vs REST, GraphQL is a query language while REST is an API architecture for web-based software. While GraphQL is primarily used to optimize the performance of existing APIs, REST API can be used to create new APIs. Both have their strengths and weaknesses depending on what you are working on.
GraphQL is traditionally used to improve the function of APIs making them faster, more reliable, and more efficient for developers. Using GraphiQL, the integrated environment for GraphQL, developers can use a single source APIs version to fetch data from different sources at the same time with a common pattern.
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