Convert JSON data Into a Custom Python Object

Let us see how to convert JSON data into a custom object in Python. Converting JSON data into a custom python object is also known as decoding or deserializing JSON data. To decode JSON data we can make use of the json.loads(), json.load() method and the object_hook parameter. The object_hook parameter is used so that, when we execute json.loads(), the return value of object_hook will be used instead of the default dict value.We can also implement custom decoders using this.
Example 1 : 

• Python3

# importing the moduleimportjsonfromcollections importnamedtuple# creating the datadata ='{"name" : "Geek", "id" : 1, "location" : "Mumbai"}'# making the objectx =json.loads(data, object_hook =               lambdad : namedtuple('X', d.keys())               (*d.values()))# accessing the JSON data as an objectprint(x.name, x.id, x.location)

Output : 

As we can see in the above example, the namedtuple is a class, under the collections module. It contains keys that are mapped to some values. In this case, we can access the elements using keys and indexes. We can also create a custom decoder function, in which we can convert dict into a custom Python type and pass the value to the object_hook parameter which is illustrated in the next example.
Example 2 :  

• Python3

# importing the moduleimportjsonfromcollections importnamedtuple# customDecoder functiondefcustomDecoder(geekDict):    returnnamedtuple('X', geekDict.keys())(*geekDict.values())# creating the datageekJsonData ='{"name" : "GeekCustomDecoder", "id" : 2, "location" : "Pune"}'# creating the objectx =json.loads(geekJsonData, object_hook =customDecoder)# accessing the JSON data as an objectprint(x.name, x.id, x.location)

Output : 

We can also use SimpleNamespace class from the types module as the container for JSON objects. Advantages of a SimpleNamespace solution over a namedtuple solution: –

1. It is faster because it does not create a class for each object.
2. It is shorter and simpler.

Example 3 : 

• Python3

# importing the moduleimportjsontry:    fromtypes importSimpleNamespace as NamespaceexceptImportError:    fromargparse importNamespace# creating the datadata ='{"name" : "GeekNamespace", "id" : 3, "location" : "Bangalore"}'# creating the objectx =json.loads(data, object_hook =lambdad : Namespace(**d))# accessing the JSON data as an objectprint(x.name, x.id, x.location)