You may find a short and cogent primer on JSON here. Next, you will learn progressively more complex ways of connecting these operators together.īy the end of the lesson, you will understand how to combine basic operators to create queries that can reshape many types of JSON data. This lesson will begin with an overview of the basic operators of the jq query syntax. Working with data from an art museum API and from the Twitter API, this lesson teaches how to use the command-line utility jq to filter and parse complex JSON files into flat CSV files. CSV), and because JSON is such a flexible data format, often with many nested levels of data, there is no one-size-fits-all graphical user interface for transforming JSON into other formats. However, many tools for data analysis and visualization require input in flat tables (i.e. (On accessing APIs, see downloading structured data with wget and the series of lessons on working with APIs.) Many libraries, archives, museums, and social media sites expose their data through JSON-based APIs. JSON (JavaScript Object Notation) is a common data sharing format that can describe complex relationships. One-to-many relationships: Tweet hashtags.The DSL for filtering, querying, and creating JSON goes much deeper than what I’ve covered here, so see for the full documentation. Jq is awesome and makes working with JSON in bash easy. We have a huge front-end monolith with a single package.json that has 250 dependencies ?, so some automated assistance was necessary. I used something similar to this recently at work to prune unused dependencies. There’s more that could be done to the grep-ing in that script to make it more robust, but that’s the basic gist. We tell it to start a bash subshell where our grep_dep function is called with it’s args P 4 defines the concurrency, so 4 concurrent greps Let’s say we have JSON that looks like this: defines the replacement string where the dependency string will get placed Luckily, it’s really intuitive (unlike awk ?). Also like sed or awk, it basically has it’s own domain specific language (DSL) for querying JSON. Jq works similarly to sed or awk - like a filter that you pipe to and extract values from. See jq’s install help page for how to install on other environments. Jq isn’t a built-in command in any environment, so you have to install it. To me, bash is more expressive and succinct for certain tasks than node is. For most automation tasks, I like to use bash whenever possible because it’s faster and even more portable (I can share a bash script with team members that don’t have node.js installed). Why not just use node.js when you need to deal with JSON? By making JSON easy to work with in bash, jq opens up a lot of automation possibilities that otherwise required me to write something in node.js (which isn’t bad, it just takes longer generally). Jq can simplify the above bash to this: curl -s "" | jq '.value.joke' Luckily there’s a better way using a tool called jq. You have to pipe to 4 different utilities just to get to a property in the JSON response body! Bash doesn’t understand JSON out of the box, and using the typical text manipulation tools like grep, sed, or awk, gets difficult. That’s tough to read and even tougher to write. (Note: the above code was taken from, which is a great article). Perhaps you’ve seen or even written bash that looks like this: curl -s '' \
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