We’re exited to introduce ProtoPI, a VS Code extension designed to enhance collaboration between frontend and backend developers. Envision frontend developers building interfaces without waiting on backend APIs and backend developers crafting systems fully aligned with frontend requirements - right from the start. ProtoPI bridges this gap, empowering both sides to work independently while staying fully synchronized.
In the upcoming release of ProtoPI, we're excited to unveil a new and improved data structure specifically designed to optimize the management of hierarchical data like YAML files. This feature is currently under iteration and promises to transform how complex nested data is handled in our application. Below is a detailed glimpse into how the revised coreTreeData structure and its derivatives will streamline data operations and enhance user interaction.
In complex software projects like ProtoPI, efficient management of hierarchical data is essential, especially when dealing with nested structures typical of XML or YAML files. General trees are versatile for representing such data but can hinder access speeds due to the need to traverse numerous nodes. To mitigate these performance bottlenecks, ProtoPI employs index maps, enhanced by unique identifiers in the form of UUIDs, within a TypeScript-based framework to improve data retrieval capabilities. This article discusses the integration of UUIDs and TypeScript to implement index maps in general trees, ensuring O(1) access times and robust data management.
When it comes to representing hierarchical data such as YAML files in a data structure, the choice of structure can significantly impact the efficiency and complexity of the operations performed on the data. While binary trees and their self-balancing variant, AVL trees, offer certain advantages, the decision to use a general tree often aligns more closely with the requirements and characteristics of YAML data. This article explores why a general tree was chosen for representing YAML files in environments like ProtoPI.
While exploring the provided YAML files—OpenAPI-Collection.yaml, OpenAPI-MultiServer.yaml, and OpenAPI-StarWars.yaml—it's important to note that some of these files may not be fully compatible with the Prism mock server. Here’s a brief overview:
OpenAPI-Collection.yaml [DOWNLOAD] [VIEW]: This file, with its complex hierarchical structures, is excellent for parsing and understanding how to extract collections from YAML files.
OpenAPI-MultiServer.yaml [DOWNLOAD] [VIEW]: A reasonable example of multiple base URLs.
OpenAPI-StarWars.yaml [DOWNLOAD] [VIEW]: A straightforward and simple specification launchable by the PRISM mock server.
Despite these potential issues, these YAML files serve as valuable resources for understanding API specifications and can provide a solid foundation for parsing and studying YAML structures. They offer a practical approach to learning about various API configurations, even if they require some adaptations or additional tools to simulate entirely in a mock environment.
As we advance in managing YAML files within development projects, the choice of data storage and management solution plays a critical role in impacting both performance and efficiency.
Have you ever been building out a UI for your app, and you needed to test your links, but the backend team hadn't finished putting together the API, and you had to wait around? Wouldn't it be great if you didn't have to?
Now, you don't. Introducing ProtoPI (that's proto•pee•eye)
With the ProtoPI VS Code extension, you can quickly generate an OpenAPI specification YAML file with all your desired endpoints, run a mock server based on the file, and test 'til your heart's content.