Usually the json will be a string and you will try and deserialise it into a object graph (which in python are typically are made up of maps and arrays).

so assuming your response is actually a string (eg that was retrieved from a HTTP request/endpoint) then you deserialise it with json.loads (the function is basically load from string), then you've got a map with a 'password' key, that is an array, so grab the first element from it.

import json

resp = '{ "password": [ "Ensure that this field has atleast 5 and atmost 50 characters" ] }'
print json.loads(resp)['password'][0]

Here's an alternative solution using requests:

import requests
wjdata = requests.get('url').json()
print wjdata['data']['current_condition'][0]['temp_C']

If you arrived at this question simply looking for a way to read a json file into memory, then use the built-in json module.

with open(file_path, 'r') as f:
    data = json.load(f)

If you have a json string in memory that needs to be parsed, use json.loads() instead:

data = json.loads(my_json_string)

Either way, now data is converted into a Python data structure (list/dictionary) that may be (deeply) nested and you'll need Python methods to manipulate it.

If you arrived here looking for ways to get values under several keys as in the OP, then the question is about looping over a Python data structure. For a not-so-deeply-nested data structure, the most readable (and possibly the fastest) way is a list / dict comprehension. For example, for the requirement in the OP, a list comprehension does the job.

store_list = [{'name': item['name'], 'city': item['city']} for item in json_array]
# [{'name': 'Mall of America', 'city': 'Bloomington'}, {'name': 'Tempe Marketplace', 'city': 'Tempe'}]

Other types of common data manipulation:

1. For a nested list where each sub-list is a list of items in the json_array.

   store_list = [[item['name'], item['city']] for item in json_array]
   # [['Mall of America', 'Bloomington'], ['Tempe Marketplace', 'Tempe']]
   

2. For a dictionary of lists where each key-value pair is a category-values in the json_array.

   store_data = {'name': [], 'city': []}
   for item in json_array:
       store_data['name'].append(item['name'])
       store_data['city'].append(item['city'])
   # {'name': ['Mall of America', 'Tempe Marketplace'], 'city': ['Bloomington', 'Tempe']}
   

3. For a "transposed" nested list where each sub-list is a "category" in json_array.

   store_list = list(store_data.values())
   # [['Mall of America', 'Tempe Marketplace'], ['Bloomington', 'Tempe']]
   

Use json loads to parse a json string and json dumps for stringifying the json to a json string

Here in your case you will need json loads

input = {
    "Data": {
        "Name": "myname",
        "AccountName": "test",
        "classic": [
          {
            "cName": "mycname",
            "tags": ["tag1", "tag2"],
            "Version": "1.14.10",
            "app": "myapp"
        }
        ]
    }
}

parsed_input = json.loads(input)
output  = parsed_input["Data"]["classic"][0]["app"]
print(output)

1) Accessing a json array obtained as a response for a GET request.

[{"symbol":"EURUSD","bid":1.13859,"ask":1.13911,"price":1.13885,"timestamp":1541215930}]

    json_data = json.loads(response.text)
    bid = json_data[0]['bid']
    ask = json_data[0]['ask']
    price = json_data[0]['price']
    timestamp = json_data[0]['timestamp']

2) Accessing a simple json without having an array as follows.

{"rates":{"EURUSD":{"rate":1.138789,"timestamp":1541224588014}},"code":200}

json_data = json.loads(response.text)
result = json_data['rates']['EURUSD']
rate = json_data['rates']['EURUSD']['rate']
timestamp = json_data['rates']['EURUSD']['timestamp']
code = json_data['code']

You can try like below to get the values from json response:

import json

content=[{
    "username": "admin",
    "first_name": "",
    "last_name": "",
    "roles": "system_admin system_user",
    "locale": "en",
    "delete_at": 0,
    "update_at": 1511335509393,
    "create_at": 1511335500662,
    "auth_service": "",
    "email": "adminuser@cognizant.com",
    "auth_data": "",
    "position": "",
    "nickname": "",
    "id": "pbjds5wmsp8cxr993nmc6ozodh"
}, {
    "username": "chatops",
    "first_name": "",
    "last_name": "",
    "roles": "system_user",
    "locale": "en",
    "delete_at": 0,
    "update_at": 1511335743479,
    "create_at": 1511335743393,
    "auth_service": "",
    "email": "chatops@cognizant.com",
    "auth_data": "",
    "position": "",
    "nickname": "",
    "id": "akxdddp5p7fjirxq7whhntq1nr"
}]

for item in content:
    print("Name: {}\nEmail: {}\nID: {}\n".format(item['username'],item['email'],item['id']))

Output:

Name: admin
Email: adminuser@cognizant.com
ID: pbjds5wmsp8cxr993nmc6ozodh

Name: chatops
Email: chatops@cognizant.com
ID: akxdddp5p7fjirxq7whhntq1nr