jsonq | simple json field access for golang | JSON Processing library

The typical approach to working with JSON in Python is to load the JSON object as a Python dict:

Flask-Cache uses the RedisCache backend provided by Werkzeug, which serializes values using pickle.dumps. It also prepends a ! for help when deserializing. You should typically not mess with these values directly, and let Flask-Caching handle it.

You can use pickletools.dis to safely examine the representation, then pickle.loads to deserialize it. Security note: pickle.loads can execute arbitrary code, so make sure you understand untrusted data first using pickletools.dis.

Unfortunately, this data is poorly structured for easy unmarshaling via the golang JSON infrastructure.

The general approach for unmarshaling data such as this example is to define a type (or set of types) which contain the structure you desire and implement the json.Unmarshaler interface with logic to inspect the incoming structure and populate the desired structs manually.

For example:

I don't think you need an external library to validate any complex JSON responses in Karate framework. Karate's built-in capability is really strong enough to do any JSON validations. I used to work on projects which will give complex JSON responses which can be very easily validated using Karate. Using Karate you can validate

• Any key & values
• JSON Objects, JSON arrays
• Subsets of JSON's from a response
• You can iterate and check values
• Headers
• Status
• Fuzzy Matching (Check null, boolean, string, etc)
• Use regular expressions for validations
• JSON schema validations etc

I would suggest going through the documentation and webinars of Karate to understand the details of validation capabilities.

• https://github.com/intuit/karate
• https://www.techgig.com/webinar/Karate-DSL-for-writing-web-service-API-acceptance-tests-BDD-1042
• https://www.youtube.com/watch?time_continue=2092&v=YWK4J3lhFw4

a json string can always be unmarshalled to map[string]interface{}. That is what you need to work with then.

Easy to do. Simply convert.

Well, you can implement your own sorting criterion, and pass it to Array.sort().

This criterion takes the form of a function(a, b) that returns a number:

• Negative if a should go before b in the sorted list
• Zero if a and b are essentially equal
• Postive if a should go after b

This may look pretty arbitrary, but think about it this way: in the simple case of sorting numbers from lesser to greater, the function returns a - b. So, f(a, b) is a - b, and a - b < 0 means a < b.

Back to your case. Let's implement a criterion function that sorts the years from lesser to greater, putting Pre 1950 at the top: