In today’s fast-paced digital world, data is at the heart of decision making, and JSON has become a universal standard for data interchange. But what if you could make your JSON data more accessible, searchable, and transformable? This is where fastgron comes into play. Today, we delve into the realm of this high-performance JSON to GRON converter, developed using cutting-edge C++20, and utilizing the simdjson library.

JSON and GRON – A Match Made in Data Heaven

JSON’s human-readable format, simplicity, and ubiquity have made it a preferred choice for APIs and config files. However, its complex and nested structure can become a hurdle when we need to grep through vast amounts of JSON data. This is where GRON steps in. GRON transforms JSON into a flattened, greppable, and line-oriented format. Unfortunately, its performance on large files could be better. Enter fastgron, a tool that’s up to 50x faster than GRON on big files, making vast JSON files efficiently greppable.

Harness the Power of fastgron

fastgron is a powerhouse when it comes to manipulating large JSON files. Not only can it convert JSON to GRON and vice versa swiftly, but it also allows for easy filtering and conversion of data, even enabling you to turn your filtered data back into JSON. The magic doesn’t stop there. You can also use fastgron in stream mode with JSON lines, perfect for when data is streaming in from different sources.

Getting Started with fastgron

Installing fastgron is a straightforward process. If you’re on MacOS or Linux, you can install fastgron via brew. Windows users can download it from the release libcurl support, although HTTP / HTTPS URLs can’t yet be read directly on Windows.

Hands-on with fastgron

fastgron provides a comprehensive range of options, from basic usage to filtering and conversion of data using various flags such as -h, –help, -V, –version, -s, –stream, and more. What’s great is the ability to use “-” or leave the file name empty to read data from stdin. This flexibility makes fastgron a highly adaptable tool, regardless of your workflow.

Let’s suppose we have a JSON file (data.json) containing information about different users:

[
    {
        "name": "Alice",
        "age": 25,
        "city": "San Francisco"
    },
    {
        "name": "Bob",
        "age": 30,
        "city": "New York"
    }
]

If we want to convert this JSON file to GRON format, we can do it using fastgron:

$ fastgron data.json

This command would output:

json = [];
json[0] = {};
json[0].name = "Alice";
json[0].age = 25;
json[0].city = "San Francisco";
json[1] = {};
json[1].name = "Bob";
json[1].age = 30;
json[1].city = "New York";

Then, if you want to filter this output to get only users from San Francisco, you can use grep:

$ fastgron data.json | grep 'San Francisco'

This command would output:

json[0].city = "San Francisco";

In case you want to convert this filtered GRON data back to JSON, you can do so with the --ungron option:

$ fastgron data.json | grep 'San Francisco' | fastgron --ungron

This command would output:

{
"city": "San Francisco"
}

This is a very basic example, but fastgron can handle much larger and more complex JSON files with ease, thanks to its performance optimizations. The power and flexibility it provides make it an excellent tool for processing and manipulating JSON data.

Unleashing the Speed of fastgron

Perhaps the most exciting feature of fastgron is its performance. Our tests have shown that fastgron can convert a large JSON file back to JSON 50 times faster than gron. This speed difference can have a significant impact, especially when dealing with large files or streaming data.

The Fastgron Revolution

The fastgron project is revolutionizing how we manipulate JSON data. Its superior speed, combined with its versatile conversion capabilities, make it an essential tool for anyone dealing with JSON data. Whether you’re dealing with large files or APIs with poor documentation, fastgron is a game-changer.