CodeClimate VS json-api

Resource Link: CodeClimate

Want to know how to enforce allowing only high-quality software into production? Check out this post on how to use CodeClimate can help you do just that! #DevOps #SoftwareDeveloper #softwaredevelopment #SoftwareEngineering #webdevelopment #codequality

Ideally, software can quickly go from development to production. Continuous deployment and delivery are some processes that make this possible. Continuous deployment means establishing an automated pipeline from development to production while continuous delivery means maintaining the main branch in a deployable state so that a deployment can be requested at any time. Predecos uses these tools. When a commit goes into master, the code is pushed directly to the public environment. Deployment also occurs when a push is made to a development branch enabling local/e2e testing before push to master. In this manner the master branch can be kept clean and ready for deployment most of the time. Problems that surface resulting from changes are visible before reaching master. Additional automated tools are used. Docker images are built for each microservice on commit to a development or master branch, a static code analysis is performed by SonarCloud revealing quality and security problems, Snyk provides vulnerability analysis and CodeClimate provides feedback on code quality while Coveralls provides test coverage. Finally, a CircleCI build is done. Each of these components use badges which give a heads-up display of the health of the system being developed. Incorporating each of these tools into the development process will keep the code on a trajectory of stability. For example, eliminating code smells, security vulnerabilities, and broken tests before merging a pull-request (PR) into master. Using Husky on development machines to ensure that code is well linted and locally tested before it is allowed to be pushed to source-control management (SCM). Applying additional processes such as writing tests around bugs meaning reintroduction of a given bug would cause a test to fail. The automated tools would then require that test to be fixed before push to SCM meaning fewer bugs will be reintroduced. Proper development processes and automation have a strong synergy.

The new code should not drop existing code coverage I've found in practice mainly catches changes to existing code that lack proper updates to existing tests. Our company uses Code Climate for these checks, so we don't have to manage / write our own tooling for this purpose.

Code Climate

Some exciting NYC companies tech companies I like are alloy.co, hyperscience.com, vanta.com, and codeclimate.com.

Best code quality - Thanks to SaaS such as CodeClimate I can tell when my code quality is too low. I try to keep "code smells" absolute zero.

Maintainable with smaller methods, less complexity – To know more on this make a habit of using code analyzer like rubocop, Code Climate

In addition to saving you time on boilerplate, the API provided by Hatchify fully implements the JSON: API specification, which stipulates solid standards to define the peculiarities of CRUD REST APIs. Get back all the time spent bike-shedding how to implement standard API features like filtering, pagination, including related data, etc. JSON: API offers consistent practices for frontend and backend developers to agree on how resources are fetched and returned. Since Hatchify provides the core of your API for you, you can count on it’s standardized functionality to give your API a consistent start.

-JSON:API format responses (https://jsonapi.org) for better standardization.

Built using Ruby on Rails, Sunnybox is designed to offer a powerful yet easy-to-use solution for developers managing email systems.

I'd really appreciate your feedback on:

- The API's user-friendliness and efficiency.

https://github.com/json-api/json-api/issues/795

There is an atomic operations extension:

JSON:API to format each message

As we’re building a RESTful API that’s formatted by the JSON:API specification and store our data in a MySQL8 relational database, a few things were pretty straightforward – we need a new model and we’ll name it Custom Field (naming wasn’t an issue here 🥲).

I found json api spec[1] recently. This kind of is better standard for REST APIs. It is bit rough to handle client side but once you get the hang of it, it is breeze to use

[1] https://jsonapi.org/

That's it! Now we have a complete set of RESTful CRUD APIs at "/api/zen" that conforms to the JSON:API specification, and the access policies fully protect the APIs. The API provides rich filtering and relation-fetching capabilities. The following are some examples; you can find more details here.

Does this have any relation to https://jsonapi.org/ ?

Basic REST and JSON RPC are very simple to start with, but have common problems when application gets bigger. How do you represent relations, pagination, filtering etc? My go-to specification for structuring JSON documents is https://jsonapi.org/ It covers most basic needs of a standard API.