Working With Python JSON Objects

If you are coming up to read this article, perhaps you have come up with a situation where you need to store your data into a structured format which could easily be transported between web apps and servers.

 

JSON stands for Java Script Object Notation which as said above is a data format that is really very light weight and is pretty similar with Python Dictionary objects. They are really very useful since the web apps and APIs could easily parse through them and quickly transport the data between apps and services. In this article we will use the python “json” package to convert a python object into a JSON object. 

 

Before diving deep into the blog, clear the basics of python; First Step Towards Python.

 

Syntax of JSON Objects

 

JSON objects are often stored with keys and values format which is similar to the dictionary. 



{

 "key1" : "value1",

 "key2" : "value2",

 .

 .

 .

 }

 

Installing Package

 

The first thing we need to do is install the “json” package in python. The “json” package allows us to convert python objects into JSON objects. Following is the syntax to install the “json” package in the python environment.

 

#Importing JSON Package in Python

import json

 

Please note that the method of converting python objects into JSON is called serialization. It is because when we convert a python object into a JSON (and vice versa), it is a process of storing the data into a series of bytes.

 

There are four different methods in the python json module to work with python objects and JSON altogether. Those four are mentioned as below:

 

1. json.dumps() - This method allows you to convert a python object into a serialized JSON object.
2. json.dump() - This method allows you to convert a python object into JSON and additionally allows you to store the information into a file (text file)
3. json.loads() - Deserializes a JSON object to a standard python object.
4. json.load() - Deserializes a JSON file object into a standard python object.

 

When your computer is processing lots of information of various data types, it needs a data dump to process that information. Therefore, we have dumps() and dump() methods under python. 

 

(Also read: Data Types in Python)

 

Following is the table of conversion for python objects into equivalent JSON objects. It's pretty much straight forward, but needed to be shown.

 

Python Object	Equivalent JSON Object
String (str)	string
Integer (int)	Number - int
Floating point number (float)	Number - real
Boolean True (True)	true
Boolean False (False)	false
list	array
tuple	array
dictionary	object
None	Null

 

Now, we will move towards some examples where we use the methods mentioned above to convert a python object into an equivalent JSON object and vise-versa.

 

(Must catch: Python to Represent Output)

 

Example 1 : JSON.dumps()

 

The json.dumps() method allows us to convert a python object into an equivalent JSON string object. This is really useful while feeding information to the APIs which needs to be parsed or printed. See an example below:

 

#Importing JSON Package in Python

import json

#creatig a dictionary which can be converted into JSON string

my_details = {

    "Name" : "Lalit Salunkhe",

    "Age" : 28,

    "Job" : True,

    "Married" : False,

    "Bikes" : [

        {"Model1": "Jupiter 120", "price": 62000},

        {"Model2": "Yamaha YZF-R15", "price": 150000}

        ]

    }

print(json.dumps(my_details))

 

Here, we have created a python dictionary and used json.dumps() method to convert it into a JSON string object.

 

See the output as shown below:

---

Output of python to JSON conversion

---

We can use other functions too, in order to amend the code such that it can be sorted ascendingly and indented.

#Sorting the results into ascending order and indenting

print(json.dumps(my_details, indent = 3, sort_keys= True))

 See now the updated output as shown below:

---

Python object to JSON ordered and with indentations

---

Here, you could see how the output is sorted in ascending order where the key “Age” and equivalent value appears first rather than the key “Name” and value associated with it. This is because we used the sort_keys = True argument which allows us to sort the result in ascending order. Besides, you could also see how the output is now indented with each line as we have used the indent = 3 argument within the code.

 

Also, apart from all this, how could we make sure that the conversion (python object to JSON string) has actually happened? Well, we can always use the type() function to know the class of the object. See the code below for a better realization.

 

#checking class of the object

print(type(json.dumps(my_details, indent = 3, sort_keys= True)))

 

Now, if you see the output, it should look something as shown below:

---

Checking class of the JSON object

---

You can easily see that the entire object my_details, which was a python dictionary before, is now converted into a JSON object with class type string. 

 

(Read also: Word embedding in NLP using Python)

 

Example 2 : JSON.dump()

 

In addition to json.dumps(), json.dump() method allows us to convert the given python object into an equivalent JSON object and then stores the result in a text file. We are going to use the same Example as above for this one

import json

my_details = {

    "Name" : "Lalit Salunkhe",

    "Age" : 28,

    "Job" : True,

    "Married" : False,

    "Bikes" : [

        {"Model1": "Jupiter 120", "price": 62000},

        {"Model2": "Yamaha YZF-R15", "price": 150000}

        ]

    }

#Using file I/O operation to create a new json file into working directory

with open("Data_File.json", "w") as file: 

#Using json.dump() to write the data into a JSON file.    

    json.dump(my_details, file)

Here, we have used the file input output operation to create a new JSON file with the name “Data_File.json”. This file will be used to store a python dictionary named my_details as a JSON string, when we hit the json.dump() method. 

 

Also, there is nothing we could show you as an output in the python console. However, on the working directory of your python, you could see a json file with name Data_File. See the screenshot below:

---

Data_File is created on working python directory

---

If you open the JSON file into any text editor, you will see a JSON string with the data equivalent to my_details under it as shown below.

---

Output of the Data_File looks like this

---

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Decoding of JSON data into Python Object

 

In order to convert (decode) JSON strings into equivalent python objects, we have json.loads() and jso.load() methods, which we have described earlier at the start of this article itself. Decoding look as below:
 

JSON Object	Equivalent Python Object
Null	None
Object	Dictionary
array	list
Boolean false (False)	False
Boolean true (True)	True
Number - int	int
Number - real	Float
string	String (str)

 

We are now going towards the examples which will help us to decode the JSON data into equivalent python objects.

 

Example 3 : JSON.loads()

 

The json.loads() method allows you to convert a JSON string into an equivalent python object (Specifically a python dictionary). See the code below:

#Importing JSON Package in Python

import json



#JSON string my_details_json being printed

print(type(my_details_json))



#Decoding a JSON string into a python dictionary with json.loads() method

my_details_dict = json.loads(my_details_json)



print(type(my_details_dict))                 #To check if conversion worked

 

Here, we have a json object named my_details_json. We can have used the type() function to check whether it is actually a json string or not. After that, we have used the json.loads() method to decode the json object into an equivalent python dictionary and checked it’s type as well (it should be dict). See the output as shown below:

---

Conversion of JSON string into an equivalent Python Dictionary

---

Example 4 : JSON.load()

 

Now, we will see an example where we use the json.load() methods to convert/decode a JSON file into a python object (dictionary). Remember, in example 2, we have created a JSON file named Data_File.json. We will use the same file as a source into this example and apply the json.load() method to decode it into a python dictionary. See the example below:

 

#Importing JSON Package in Python

import json



#Using python I/O open function to read the json file named Data_File.

with open("C:/Users/lsalunkhe/.spyder-py3/Data_File.json") as file:

    

    #Using json.load() to deserialize a python object into python object

    Py_object = json.load(file)

    

    print(Py_object)

    print(type(Py_object))

 

Here, we are using the python built-in I/O open function to read the json file name Data_File and then using json.load() to convert the data from that file into a relevant python object (i.e. a dictionary). See the output below:

---

Converting a data from json file object into a python object using json.load() method

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Well, we will end this article here with following summary points

 

(Recommended blog: How Do We Implement Beautiful Soup For Web Scraping?)

 

 

Summary

 

• The json.dumps() method allows us to convert a python object into an equivalent JSON object. Or in other words to send the data from python to json.

• The json.dump() method allows us to convert a python object into an equivalent JSON object and store the result into a JSON file at the working directory.

 

(Must read: 20 Python interview questions)

 

• The json.loads() method allows us to convert a JSON string into an equivalent python object (dictionary). In other words, it helps us to receive the data from json to python.

• The json.load() method allows us to read a JSON data file and then convert the data into an equivalent python data object.