Show_variables option can be turned on to show the relevant variable. Level option is used for selecting how deep you would like to look into. It will list the ' path' of different/mismatched ones from target to the reference. (Note that the algorithm can further be improved by removing the items found in object2, so that the next item of object1 would not compare itself with the items already found in the object2)įor others who'd like to debug the two JSON objects (usually, there is a reference and a target), here is a solution you may use. It by default works fine for the object of strings and numbers and for those eq() is defined appropriately. (Recursive comparison is performed)Įlse simply call obj1 = obj2. 'found' value is returnedĮlse if the objects to be compared are of type 'dict' then compare the values present for all the respective keys in both the objects. If the objects are of type 'list' then compare each item of the first list with the items of the second list until found, and if the item is not found after going through the second list, then 'found' would be = false. Which gave me the correct expected output! Ycm = YouchamaJsonDiffer(a, b, ignore_order_func=make_ignore_order_func([Īssert ycm.to_dict(no_pairs=True) = Yes! You can use jycm from jycm.helper import make_ignore_order_func If we apply this function to a and b, the results compare equal: > ordered(a) = ordered(b) Return sorted((k, ordered(v)) for k, v in obj.items()) To fix that, we can define an ordered function which will recursively sort any lists it finds (and convert dictionaries to lists of (key, value) pairs so that they're orderable): def ordered(obj): but that doesn't work, because in each case, the 'errors' item of the top-level dict is a list with the same elements in a different order, and sorted() doesn't try to sort anything except the 'top' level of an iterable. If you’re parsing JSON files on a regular basis, and you’re hitting performance or memory issues, or you just want built-in schemas, consider giving it a try.If you want two objects with the same elements but in a different order to compare equal, then the obvious thing to do is compare sorted copies of them - for instance, for the dictionaries represented by your JSON strings a and b: import json Msgspec has additional features, like encoding, MessagePack support (a faster alternative format to JSON), and more.

Specifying the schema involves more coding, and less flexibility to deal with imperfect data.

Streaming JSON parsers like ijson still offer the benefit of fixed memory usage during parsing, no matter how large the input file.

Memory usage when decoding still scales with the input file.

With standard JSON libraries, schema validation has to happen separately. If one of the records somehow was missing a field, or if the value was the wrong type, like an integer instead of a string, the parser would have complained. That meant lower RAM usage and faster decoding no need to waste time or memory creating thousands of Python objects we were never going to look at. The pros and cons of schema-based parsingīecause msgspec allows you to specify the schema, we were able to create Python objects for only those fields that we actually cared about.

The streaming solution only ever uses a fixed amount of memory for the parsing all the other solutions have memory usage that scales with the size of the input.īut of those three, msgspec has significantly lower memory usage, and it is by far the fastest solution. To summarize the three options we’ve seen, as well as a streaming ijson-based solution: Package $ /usr/bin/time -f 'RAM: %M KB, Elapsed: %E' python with_msgspec.py

Json compare in python