Apollo IOS Schema Customization Removing Unused Input Object Fields

Hey guys! Today, we're diving deep into a challenge faced when dealing with server-generated schemas in Apollo iOS, specifically the issue of bloated input objects. We'll explore a proposed solution to customize these schemas, making our generated code cleaner and more efficient. So, buckle up and let's get started!

Understanding the Problem: Bloated Input Objects

First off, a huge shoutout to the amazing folks maintaining and supporting this project! Seriously, you're the best! 🙏

The core problem we're tackling is the scenario where server-generated schemas contain input objects loaded with tons of optional parameters. Think of it like a Swiss Army knife with all the attachments, but you only need the knife blade. The application code often only requires a small subset of these parameters, leading to bloated generated input objects. These objects contain a lot of code that's simply not needed, making the codebase larger and potentially impacting performance. This bloat can come from various sources, including the evolution of APIs over time, where older fields are retained for compatibility but are no longer actively used by all clients. Additionally, the schema might be designed to cater to a wide range of use cases, with each client application only needing a specific subset of the available fields. Furthermore, the use of generic input objects to handle different scenarios can lead to an overabundance of optional parameters, many of which may not be relevant in a particular context. Dealing with this bloat requires a systematic approach to identify and eliminate unused fields, ensuring that the generated code is lean and efficient. By focusing on the specific needs of the application and trimming the schema accordingly, we can significantly reduce the complexity and size of the generated code, leading to improved performance and maintainability. Ultimately, the goal is to create a schema that accurately reflects the application's requirements, avoiding the overhead of unnecessary fields and types.

The trivial solution might be to rewrite the query or mutation, passing only the selected parameters into the input object. This does work, but it introduces a few disadvantages. One of the main issues with this approach is the loss of auto-generated code comments on the input variables. These comments are incredibly helpful for understanding the purpose and usage of each variable, and losing them can make the code harder to maintain and debug. Another significant drawback is that the variables become coupled with the operation. This means they can't be reused by other queries or mutations, even if the same input parameters are needed. This lack of reusability can lead to code duplication and make it more challenging to keep the codebase consistent. Moreover, the problem can extend to nested input object types, which may also contain redundant parameters. Customizing these nested types at the operation level isn't feasible, leaving a significant portion of the bloat unaddressed. Therefore, a more comprehensive solution is needed to tackle the problem of bloated input objects and ensure that only the necessary code is generated. This solution should ideally allow for customization at the schema level, enabling developers to specify the desired fields for selected input objects. Such customization would not only reduce the amount of generated code but also improve the overall clarity and maintainability of the codebase. By focusing on the specific needs of the application, we can create a more efficient and streamlined development process.

Disadvantages of the Trivial Approach

Let's break down why simply rewriting the query/mutation isn't the ideal solution:

1. No Auto-Generated Code Comments: We lose those helpful comments that explain what each input variable is for.
2. Coupled Variables: The variables become tied to the specific operation and can't be reused elsewhere. Imagine having to define the same input parameters multiple times – yikes!
3. Nested Input Objects: Redundant parameters in nested input object types can't be customized at the operation level. It's like trying to clean your room but only being able to tidy the surface – the mess is still lurking underneath.

So, the ask is to enhance the code generator configuration to allow specifying the desired fields of selected input objects. This customization can help reduce the amount of code generated where a specific application doesn't need it. Think of it as tailoring a suit – we want it to fit perfectly, not be a one-size-fits-all monstrosity.

The Proposed Solution: Schema Customization

The goal here is to enhance the code generator configuration, enabling us to specify the desired fields for selected input objects. This customization would significantly reduce the amount of code generated, focusing only on what the application truly needs. Think of it as decluttering – we're getting rid of the unnecessary baggage and keeping only the essentials. This approach not only streamlines the codebase but also enhances its clarity and maintainability. By tailoring the generated code to the specific requirements of the application, we can avoid the bloat and complexity that come with handling unused fields. Furthermore, this customization can lead to performance improvements, as the application doesn't have to process or manage irrelevant data. The key is to provide a flexible mechanism for developers to define which fields are necessary for their use case, allowing for a more efficient and targeted code generation process. By focusing on the specific needs of the application, we can create a codebase that is both lean and robust, making it easier to develop, maintain, and scale.

Looking at https://www.apollographql.com/docs/ios/code-generation/codegen-configuration#schema-customization, one solution could be updating the fields mapping to be [String: String?]. Fields with null values would then be removed from the generated code.

"MyInputObject" : {
        "inputObject" : {
          "fields" : {
            "myField" : "customField",
            "bloatedField": null
          },
          "name" : "CustomInputObject"
        }
      }

In this example, we're suggesting a modification to the schema customization configuration to allow for more granular control over the generated code. Specifically, the proposal involves updating the fields mapping to accept null values. This simple change would enable developers to explicitly remove fields from the generated code by setting their corresponding values to null in the configuration. For instance, in the provided JSON snippet, the bloatedField is set to null, indicating that it should be excluded from the generated code. This approach provides a clean and intuitive way to trim the schema, ensuring that only the necessary fields are included in the final output. By allowing developers to specify which fields are essential for their application, we can significantly reduce the size and complexity of the generated code. This not only improves the overall performance of the application but also makes it easier to maintain and debug. The key advantage of this solution is its simplicity and flexibility, allowing developers to tailor the generated code to their specific needs without having to resort to more complex workarounds. Ultimately, this enhancement to the schema customization configuration would empower developers to create more efficient and streamlined applications.

If we assume bloatedField is another object which is only used in this input object, then this small change could result in multiple types not needing to be generated. It's like a domino effect – remove one unnecessary field, and you might eliminate entire types that are no longer needed!

Similarly, we can specify any input object we need, even when it's nested deep in the schema. This gives us the flexibility to target specific areas of bloat, no matter how deeply buried they are.

Benefits of This Approach

• Reduced Code Size: Less generated code means smaller application size and faster compile times. 🚀
• Improved Performance: By removing unnecessary fields, we can optimize the application's performance. 💪
• Better Maintainability: A cleaner codebase is easier to understand, maintain, and debug. 🧹
• Increased Reusability: By having more focused input objects, we can promote code reuse across different parts of the application. ♻️

Conclusion

Schema customization to allow removing unused fields and types of input objects is a powerful way to optimize Apollo iOS applications. By tailoring the generated code to our specific needs, we can create leaner, faster, and more maintainable applications. This approach addresses the challenge of bloated input objects head-on, providing a flexible and intuitive solution for developers. The ability to remove unnecessary fields and types from the generated code not only reduces the size and complexity of the application but also improves its overall performance and maintainability. By focusing on the specific requirements of the application, we can ensure that only the essential code is included, leading to a more efficient and streamlined development process. Moreover, this customization can lead to increased reusability of input objects, as they become more focused and aligned with the specific use cases within the application. Ultimately, the proposed solution empowers developers to take control of their generated code, making it easier to build robust and scalable applications with Apollo iOS. By embracing schema customization, we can unlock the full potential of our applications and deliver a better experience for our users. So, let's champion this enhancement and pave the way for a cleaner, more efficient future for Apollo iOS development! 🌟

What do you guys think about this approach? Let's discuss in the comments below!