Python requests format json

Python Post JSON using requests library

In this article, I will let you know how to post a JSON from a client to a server using a requests library. Also, if you are facing a “400 bad request error” while posting JSON to the server, this article will try to solve that.

Further Reading:

Steps to Build a JSON POST request

Create a URL object: Let’s create a URL object. We need a target URI string that accepts the JSON data via HTTP POST method. In this example, I am using httpbin.org service to Post JSON data. httpbin.org is a web service that allows us to test the HTTP request. You can use it to test and inspect your POST request. httpbin.org responds with data about your request.

So my URL is: “https://httpbin.org/post“

Set the Request Method: As the name suggests, we need to use a post method of a request module.

requests.post('https://httpbin.org/post')

Specify the POST data: As per the HTTP specification for a POST request, we pass data through the message body. Using requests, you’ll pass the payload to the corresponding function’s data parameter. Data can be anything including JSON, dictionary, a list of tuples, bytes, or a file-like object. In this example, I am sending the following JSON data.

If you have data in the form of a dictionary or any Python object, you can convert it into JSON like this.

import json sampleDict = < "id": 1, "name":"Jessa" >jsonData = json.dumps(sampleDict)

Use The json parameter: The requests module provides a json parameter that we can use to specify JSON data in the POST method. i.e., To send JSON data, we can also use the json parameter of the requests.post() method.

requests.post('https://httpbin.org/post', json=)

Why set it to json? Because it will help the request module to serialize your data into the JSON format. Now, Let’s see the example.

Approach 1: Using json parameter

import requests response = requests.post('https://httpbin.org/post', json=) print("Status code: ", response.status_code) print("Printing Entire Post Request") print(response.json())

Status code: 200 Printing Entire Post Request , 'data': '', 'files': <>, 'form': <>, 'headers': , ' json': , 'origin': 'xxx.xx.xx.xx, xxx.xx.xx.xx', 'url': 'https://httpbin.org/post'>

Note: This service returns your entire request as a response so it will help you to know details about your request.

Approach 2: By setting header information

Alternatively, we can set the request’s content-type. In this example, we are passing JSON, so the request’s content type is application/json .

By specifying correct request headers so that the requests module can serialize your data into the correct Content-Type header format. In this can we don’t need to use the json parameter. This is useful for an older version. Let’s see the example now.

import requests newHeaders = response = requests.post('https://httpbin.org/post', data=, headers=newHeaders) print("Status code: ", response.status_code) response_Json = response.json() print("Printing Post JSON data") print(response_Json['data']) print("Content-Type is ", response_Json['headers']['Content-Type'])

Status code: 200 Printing Post JSON data id=1&name=Jessa application/json

Test Your JSON POST request using postman before executing

It is always a best practice to test your request along with its message body using postman to verify JSON data, and a request is in the required format. Let’s see how to test POST request using postman.

Add Postman extension or install a native postman app. Let’s see the steps now.

• Select POST request and enter your service POST operation URL.
• Click on Headers. In the key column enter Content-Type and in the Value column enter application/json .
• Click on the body section and click the raw radio button. enter your JSON data. Click the Send button.

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About Vishal

I’m Vishal Hule, Founder of PYnative.com. I am a Python developer, and I love to write articles to help students, developers, and learners. Follow me on Twitter

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response.json() – Working with JSON in Python requests

In this tutorial, you’ll learn how to parse a Python requests response as JSON and convert it to a Python dictionary. Whenever the requests library is used to make a request, a Response object is returned. The Python requests library provides a helpful method, json(), to convert a Response object to a Python dictionary.

By the end of this tutorial, you’ll have learned:

• How to parse a requests.Response to a Python dictionary using the Response.json() method
• How to convert a Python requests JSON response to a dictionary
• How to handle errors when parsing a Python requests JSON response
• How to convert a Python requests JSON object to a Pandas DataFrame

Parsing Python requests Response JSON Content

Every request that is made using the Python requests library returns a Response object. This is true for any type of request made, including GET , POST , and PUT requests. The requests library offers a number of different ways to access the content of a response object:

• .content returns the actual content in bytes
• .text returns the content converted to a string, using a character encoding such as UTF-8

Since you’re reading an article about how to parse the JSON from a response into a Python dictionary, the two options above may not be ideal. While you could use the json library to serialize the response, this adds an additional step and complexity to your code.

The requests library comes with a helpful method, .json() , that helps serialize the response of the request. In order to look at an example, let’s the public endpoints provided by the website reqres.in . These endpoints work without signing up, so following along with the tutorial is easy.

Let’s see how we can access the /users endpoint and serialize the response into a Python dictionary using the .json() method:

# Serializing a GET Request with .json() import requests resp = requests.get('https://reqres.in/api/users') resp_dict = resp.json() print(type(resp_dict)) # Returns:

From the code above, we can see that applying the .json() method to our response created a Python dictionary. In the following section, you’ll learn how to work with the resulting dictionary to access some content.

How to Access Python requests Response Content as a Dictionary

After applying the .json() method to a response created by the requests library, we created a dictionary. This means that we can access the data in the dictionary using common dictionary methods, such as square-bracket indexing or the .get() method.

Let’s see how we can access the ‘page’ key in the data:

# Accessing Data in a Python Request Response import requests resp = requests.get('https://reqres.in/api/users') resp_dict = resp.json() print(resp_dict.get('page')) # Returns: 1

In the code above, we applied the .get() method to access the value corresponding with the key ‘page’ . Using the .get() method is a safer way of handling this operation. This is because the method will simply return None , if a key doesn’t exist.

How to Handle Errors When Parsing a JSON Response from Python requests

In some cases, the data that’s returned from a Response object can’t be serialized. In these cases, you’ll encounter a JSONDecodeError . You can safely handle these errors by wrapping your request in a try-except block.

Let’s see how we can safely handle a JSONDecodeError using the requests library:

# Handling a JSONDecodeError in Python from json import JSONDecodeError import requests resp = requests.get('https://reqres.in/api/users/page4') try: resp_dict = resp.json() except JSONDecodeError: print('Response could not be serialized')

How to Pretty Print a JSON Object From Python requests

In this section, we’ll take a look at how to pretty print a JSON object that is returned from using the Python requests library. Pretty printing a JSON file is made easy using the json.dumps() function.

Let’s see how we can pretty print a JSON object from the Python requests library:

import json import requests resp = requests.get('https://reqres.in/api/users') resp_dict = resp.json() pretty = json.dumps(resp_dict, indent=4) print(pretty) # Returns: # < # "page": 1, # "per_page": 6, # "total": 12, # "total_pages": 2, # "data": [ # < # "id": 1, # "email": "[email protected]", # "first_name": "George", # "last_name": "Bluth", # "avatar": "https://reqres.in/img/faces/1-image.jpg" # >, # . # < # "id": 6, # "email": "[email protected]", # "first_name": "Tracey", # "last_name": "Ramos", # "avatar": "https://reqres.in/img/faces/6-image.jpg" # > # ], # "support": < # "url": "https://reqres.in/#support-heading", # "text": "To keep ReqRes free, contributions towards server costs are appreciated!" # ># >

Let’s break down what we did in the code above:

1. We loaded the response the GET request
2. We serialized the response using the .json() method
3. We then used the dumps() function with an indent of 4 to pretty print the response

How to Convert a Python requests JSON Object to a Pandas DataFrame

In this final section, we’ll take a look at how to convert a requests.Reponse object into a Pandas DataFrame. Because Pandas allows you to easily create DataFrames from a list of dictionaries, we can simply pass in part of our serialized response.

From the code above, we know that the data are stored in a key named ‘data’ as a list of dictionaries. We can easily pass this dictionary into a Pandas DataFrame constructor and convert it to a DataFrame:

# Converting JSON Data to a Pandas DataFrame import requests import pandas as pd resp = requests.get('https://reqres.in/api/users') resp_dict = resp.json() df = pd.DataFrame(resp_dict.get('data')) print(df) # Returns: # id email first_name last_name avatar # 0 1 [email protected] George Bluth https://reqres.in/img/faces/1-image.jpg # 1 2 [email protected] Janet Weaver https://reqres.in/img/faces/2-image.jpg # 2 3 [email protected] Emma Wong https://reqres.in/img/faces/3-image.jpg # 3 4 [email protected] Eve Holt https://reqres.in/img/faces/4-image.jpg # 4 5 [email protected] Charles Morris https://reqres.in/img/faces/5-image.jpg # 5 6 [email protected] Tracey Ramos https://reqres.in/img/faces/6-image.jpg

In the code above, we serialized our response to a dictionary. From there, we passed the values of the ‘data’ key into the pd.DataFrame constructor, which accepts a list of dictionaries.

Conclusion

In this tutorial, you learned how to use the Python requests library’s Response object and serialize the JSON data using the .json() method. You first learned how to use the .json() method. Then, you learned how to access data from the resulting dictionary. You also learned how to handle errors caused by this method, how to pretty print the resulting data, and how to load it into a Pandas DataFrame.

Additional Resources

To learn more about related topics, check out the tutorials below:

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