api-key-nodejs VS libcurl

You can find the complete code on GitHub. To follow along with this article, you’ll need:

This Docker image is designed to support implementing Github Actions with Python. It starts with the official python docker image as the base, which is a Debian OS. It specifically uses python:3-slim to keep the image size down for faster loading of Github Actions that use pyaction. On top of the base, we've installed curl gpg, git, and the GitHub CLI. We added curl and gpg because they are needed to install the GitHub CLI, and they may come in handy anyway (especially curl) when implementing a GitHub Action.

The application calls several APIs to retrieve settings and their values from OpenAM. For simplicity, we'll use examples using the curl utility instead of programmatic API calls.

Today I had much more time to focus on the project and I did that. Yesterday, I had just got to know about the cURL library that is used to send the HTTP requests in C++. But today, I imported the library, went through the documentation and with the help of some chatbots, was able to build functions to download and extract packages from Pypi. Using the Thunder Client, I got to know that I am receiving JSON from Pypi. But I don't know how to parse JSON in C++, so using AI I found that I need to use nlohmann json.

I like curl it's available as a command line tool and is pretty ubiquitous across platforms.

Complex applications, with their interwoven layers of front-end, back-end, and database logic, often obscure bugs. Simplifying the problem by isolating components—such as a React component, a REST API endpoint, or a PostgreSQL query—helps developers focus on the failure point. Spencer Romenco, Chief Growth Strategist at Growth Spurt, shares a case study: “Simplifying and isolating the problem has always been the most reliable way to track down bugs.” When a content delivery dashboard failed to display uploaded videos, Romenco’s team isolated the front-end with mock data, ruling out UI issues, and tested the API with curl, uncovering a backend file path error. This divide-and-conquer approach, supported by tools like Postman for API testing, reduces complexity and accelerates resolution.

It's great of programmers to aim for portability, but frankly it's kind of a stretch that an arbitrary C compiler that is limited in standard support would the same time be sophisticated enough to process these tricks as intended.

In my fork of chibicc (a small C11 compiler) there are plenty of additional logic that were implemented solely to play nice with C tricks from real world projects that could have been easier if they target later standards. The most recent being how curl's build script determines the size of primitive types: they use (sizeof(T) == N) as a case index and expect the compiler to error on case-duplication[1], and I had to add a backtracking loop to check exactly that[2]. I'm not complaining as more error checks isn't a bad thing, however, I'll advise programmers willing to invest in obscure tricks to actually test them on obscure compilers (instead of just flipping -std).

[1]: https://github.com/curl/curl/blob/339464432555b9bd71a5e4a4c4...

HTTP client - Tools like Postman or cURL for testing API calls