Python JSON pprint Data pretty printer in Python














































Python JSON pprint Data pretty printer in Python



pprint : Data pretty printer in Python


This article is about a pretty useful built-in module in Python, pprint.

The pprint module provides a capability to %u201Cpretty-print%u201D arbitrary Python data structures in a well-formatted and more readable way!

Let us consider an example:

# A python code without pprint 
import requests

def geocode(address):
url = "https://maps.googleapis.com/maps/api/geocode/json"
resp = requests.get(url, params = {'address': address})
return resp.json()

# calling geocode function
data = geocode('India gate')

# printing json response
print(data)


The above code is for getting the geocode information of a place using Google Maps API in JSON format.

The output of above program looks like this:

{'status': 'OK', 'results': [{'address_components': [{'long_name': 'Rajpath', 'types': ['route'], 
'short_name': 'Rajpath'}, {'long_name': 'India Gate', 'types': ['political', 'sublocality',
'sublocality_level_1'], 'short_name': 'India Gate'}, {'long_name': 'New Delhi', 'types':
['locality', 'political'], 'short_name': 'New Delhi'}, {'long_name': 'New Delhi',
'types': ['administrative_area_level_2', 'political'], 'short_name': 'New Delhi'}, {'long_name':
'Delhi', 'types': ['administrative_area_level_1', 'political'], 'short_name': 'DL'}, {'long_name':
'India', 'types': ['country', 'political'], 'short_name': 'IN'}, {'long_name': '110001', 'types':
['postal_code'], 'short_name': '110001'}], 'geometry': {'location': {'lng': 77.2295097, 'lat': 28.612912},
'viewport': {'northeast': {'lng': 77.2308586802915, 'lat': 28.6142609802915}, 'southwest': {'lng':
77.22816071970848, 'lat': 28.6115630197085}}, 'location_type': 'APPROXIMATE'}, 'types':
['establishment', 'point_of_interest'], 'formatted_address': 'Rajpath, India Gate, New Delhi, Delhi 110001,
India', 'place_id': 'ChIJC03rqdriDDkRXT6SJRGXFwc'}]}

As you can see, this output is not properly indented which affects readablity for nested data structures.

Now, consider the code below:

# A python code with pprint 
import requests
from pprint import pprint

def geocode(address):
url = "https://maps.googleapis.com/maps/api/geocode/json"
resp = requests.get(url, params = {'address': address})
return resp.json()

# calling geocode function
data = geocode('India gate')

# pretty-printing json response
pprint(data)


The output of above code looks like this:

{'results': [{'address_components': [{'long_name': 'Rajpath',
'short_name': 'Rajpath',
'types': ['route']},
{'long_name': 'India Gate',
'short_name': 'India Gate',
'types': ['political',
'sublocality',
'sublocality_level_1']},
{'long_name': 'New Delhi',
'short_name': 'New Delhi',
'types': ['locality', 'political']},
{'long_name': 'New Delhi',
'short_name': 'New Delhi',
'types': ['administrative_area_level_2',
'political']},
{'long_name': 'Delhi',
'short_name': 'DL',
'types': ['administrative_area_level_1',
'political']},
{'long_name': 'India',
'short_name': 'IN',
'types': ['country', 'political']},
{'long_name': '110001',
'short_name': '110001',
'types': ['postal_code']}],
'formatted_address': 'Rajpath, India Gate, New Delhi, Delhi '
'110001, India',
'geometry': {'location': {'lat': 28.612912, 'lng': 77.2295097},
'location_type': 'APPROXIMATE',
'viewport': {'northeast': {'lat': 28.6142609802915,
'lng': 77.2308586802915},
'southwest': {'lat': 28.6115630197085,
'lng': 77.22816071970848}}},
'place_id': 'ChIJC03rqdriDDkRXT6SJRGXFwc',
'types': ['establishment', 'point_of_interest']}],
'status': 'OK'}


As you can see, the output is now well formatted and much more readable.

All we did was to import the pprint function of pprint module. And use pprint() function rather than the print function!



Comments