![]() ![]() ![]() To get the age and profession of a person using the flattened data, we have to get them separately one by one.Ī flattened JSON file is useful when we only have to get a single value, but we can use the original JSON file if we want to get all the information about an object or attribute. There is a difference in the original data and the flattened data we can get the age and profession of a person at the same time using the original data because age and profession have the same parent attribute, which is the name of the person, but we cannot do the same using the flattened data. ![]() The example JSON file does not contain any lists, but the above code will also work with JSON files containing lists. In the above output, we can see that the original data contains two dicts, but the flattened data contains only one dict. While reading the data, if a dict comes, the first loop will work if a list comes, the second loop will work. In the above code, we use the if-else conditional statement to check the input data type and the type() function, which returns the data type of objects. For example, an example JSON file is given below. #PYTHON JSON COMPARE DIFF PATCH#In addition to that, DeepDiff checks for type changes and attribute value changes that Json Patch does not cover since there are no such things in Json. For example, we can use a JSON file to store students’ data like their name, age, address, and class.Įach student’s data will be stored in an array containing attributes and values of different data types. Difference with Json Patch Unlike Json Patch which is designed only for Json objects, DeepDiff is designed specifically for almost all Python types. We see different attributes with values separated by arrays or lists in a JSON file. JSON stores and transmits data that a human can read and understand. JSON is a file format, and it stands for JavaScript Object Notation. This tutorial will discuss flattening JSON using conditional statements, loops, and the type() function in Python. ![]()
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