jSON with python code example

Example 1: print json python

import json

uglyjson = '{"firstnam":"James","surname":"Bond","mobile":["007-700-007","001-007-007-0007"]}'

#json.load method converts JSON string to Python Object
parsed = json.loads(uglyjson)

print(json.dumps(parsed, indent=2, sort_keys=True))

Example 2: load json

import json

with open('data.txt') as json_file:
    data = json.load(json_file)

Example 3: json python

import json

# some JSON:
x = '{ "name":"John", "age":30, "city":"New York"}'

# parse x:
y = json.loads(x)

# the result is a Python dictionary:
print(y["age"])

Example 4: Json in python

import json

json_file = json.load(open("your file.json", "r", encoding="utf-8"))

# For see if you don't have error:
print(json_file)

Example 5: python to json

# a Python object (dict):
x = {
  "name": "John",
  "age": 30,
  "city": "New York"
}

# convert into JSON:
y = json.dumps(x)

Example 6: python import json data

# Basic syntax:
import ast
# Create function to import JSON-formatted data:
def import_json(filename):
  for line in open(filename):
    yield ast.literal_eval(line)
# Where ast.literal_eval allows you to safely evaluate the json data.
# 	See the following link for more on this:
# 	https://stackoverflow.com/questions/15197673/using-pythons-eval-vs-ast-literal-eval
        
# Import json data
data = list(import_json("/path/to/filename.json"))

# (Optional) convert json data to pandas dataframe:
dataframe = pd.DataFrame.from_dict(data)
# Where keys become column names