Converting such an array into an object may therefore be a sensible pre-comparison step in order to get only ‘real’ changes identified. When JSON is generated, arrays are often used where the data could be represented as objects. So it is arrays that cause most problems in comparing JSON data. Ī more intelligent ordered comparison might just say that 2 has been inserted. In this case, comparing with by position would give three differences: 2 != 4, 4 != 5 and 5 is a deleted item. It compares each element according to their position in the. So comparing by position or as unordered items are alternative approaches to be applied depending on the interpretation of the array data.įurthermore, comparing by position is not always what is needed when we use an array as a list, where the item order is significant. JSON diff tool makes a semantic comparison, it compares every attributevalue pairs of objects. However, if the array is being used as an unordered set of numbers, then the arrays should be considered equal. For example, if an array is used to represent an x,y coordinate, then the expectation is that is not the same as . This is because arrays are used for different purposes. See the example below.Īrrays present more of a problem for comparison. The Overflow Blog Satellite internet: More useful than sending a car into space (Ep. JSON AĪny object that has a unique key member should ideally be represented as an object where the key is pulled out as the member string – this leads to unambiguous comparison. Browse other questions tagged json groovy or ask your own question. Therefore corresponding members can be identified without ambiguity even if the order of the members is different. Objects also compare well in that each member property is identified by a string which should be unique within the object (it does not have to be unique but behaviour is unpredictable if they are not unique!). Strings may also need some normalisation to handle special character encodings so that for example. Similarly 100 and 1e2 would also be deemed to be equal. The three literal names, true, falseand nullare not a problem, though note they must be lower case.īefore comparing two numbers, they should be normalised so that 1 and 1.0 would not show a change. What makes it powerful is that, during the comparison, deepdiff does not consider the order in which the elements inside the dictionaries are present.Comparing two JSON files is fairly straightforward, though there are a few areas where it is not quite as simple as it seems. Deepdiff is a powerful python library to compare 2 dictionaries. #2 JSON COMPARE CODE#But, we don’t really have to worry of writing code and all, This is where deepdiff comes in handy. Programmatically, one can write a small piece of code which would iterate every keys of json and pick the differences, but this work will become very difficult if we don’t know how nested the json is. Difference in Jsons:įinding exact difference in two json sounds difficult task, it may become even more difficult, if we try to find differences in nested jsons. Now let’s image we have the following dicts to compare :ĭict 1 : ' > a, b = json.loads(a), json.loads(b) > a.sort() > b.sort() > a = b TrueĪbove example will work for the JSON in the question. Edge case of comparing Json object using “=”:Ĭomparing two dictionaries has been solved in the first part of this articles. Note: ‘=’ and ‘is’ operator are not same, ‘=’ operator is use to check equality of values, whereas ‘is’ operator is used to check reference equality, hence one should use ‘=’ operator, ‘is’ operator will not give expected result.
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