Try to Google this kind of stuff first. :)

import json

array = [1, 2, 3]
jsonArray = json.dumps(array)

By the way, the result you asked for can not be achieved with the list you provided.

You need to use python dictionaries to get json objects. The conversion is like below

Python -> JSON
list -> array
dictionary -> object

And here is the link to the docs https://docs.python.org/3/library/json.html

import json
row = [1L,[0.1,0.2],[[1234L,1],[134L,2]]]
row_json = json.dumps(row)

Tested on Ideone.

import json
array = '{"fruits": ["apple", "banana", "orange"]}'
data  = json.loads(array)
fruits_list = data['fruits']
print fruits_list

To solve this, you need to split the input list into chunks, by 7 in your case. For this, let's use this approach. Then, use a list comprehension producing a list of dictionaries:

>>> from pprint import pprint
>>> l = [['String 1'],['String 2'],['String 3'],['String 4'],['String 5'],
... ['String 6'],['String 7'],['String 8'],['String 9'],['String 10'],
... ['String 11']]
>>> def chunks(l, n):
...     """Yield successive n-sized chunks from l."""
...     for i in range(0, len(l), n):
...         yield l[i:i+n]
... 
>>>
>>> result = [{"title%d" % (i+1): chunk[i][0] for i in range(len(chunk))} 
              for chunk in chunks(l, 7)]
>>> pprint(result)
[{'title1': 'String 1',
  'title2': 'String 2',
  'title3': 'String 3',
  'title4': 'String 4',
  'title5': 'String 5',
  'title6': 'String 6',
  'title7': 'String 7'},
 {'title1': 'String 8',
  'title2': 'String 9',
  'title3': 'String 10',
  'title4': 'String 11'}]

Use json.dumps before json.loads to convert your data to dictionary object This also helps prevent valueError: Expecting property name enclosed in double quotes.

Ex:

import json
myJSONStringList = ['{"user": "testuser", "data": {"version": 1, "timestamp": "2018-04-03T09:23:43.388Z"}, "group": "33"}',
'{"user": "otheruser", "data": {"version": 2, "timestamp": "2018-04-03T09:23:43.360Z", }, "group": "44"}']

print([json.loads(json.dumps(i)) for i in myJSONStringList])

Output:

[u'{"user": "testuser", "data": {"version": 1, "timestamp": "2018-04-03T09:23:43.388Z"}, "group": "33"}', u'{"user": "otheruser", "data": {"version": 2, "timestamp": "2018-04-03T09:23:43.360Z", }, "group": "44"}']

It's not 100% clear what you have or what you want, but with a few assumptions (input is list of dict, desired output is list of dict):

json_obj = [
    {
        "document": {
            "id": "1",
            "image": "https://xxx.xxx.png",
            "name": "xxx",
        },
    },
    {
        "document": {
            "id": "2",
            "image": "https://xx2.xxx.png",
            "name": "xx2",
        },
    },
]

desired_output = [x["document"] for x in json_obj]
print(desired_output)

This returns an array of JSON objects based off of Chandella07's answer.

from bs4 import BeautifulSoup
import pandas as pd
import requests
import json

r = requests.get("https://www.emojimeanings.net/list-smileys-people-whatsapp")

soup = BeautifulSoup(r.text, "lxml")

emojiLinkList = []
emojiTitleList = []
emojiDescriptionList = []
jsonData = []

for tableRow in soup.find_all("tr", attrs={"class": "ugc_emoji_tr"}):
    for img in tableRow.findChildren("img"):
        emojiLinkList.append(img['src'])

for tableData in soup.find_all("td"):
    for boldTag in tableData.findChildren("b"):
        emojiTitleList.append(boldTag.text)

for tableRow in soup.find_all("tr", attrs={"class": "ugc_emoji_tr"}):
    for tabledata in tableRow.findChildren("td"):
        if tabledata.has_attr("id"):
            k = tabledata.text.strip().split('\n')[-1]
            l = k.lstrip()
            emojiDescriptionList.append(l)

for link, title, desc in zip(emojiLinkList, emojiTitleList, emojiDescriptionList):
    dict = {"link": link, "title": title, "desc": desc}
    jsonData.append(dict)

print(json.dumps(jsonData, indent=2))

Data Example:

{
    "link": "https://www.emojimeanings.net/img/emojis/purse_1f45b.png",
    "title": "Wallet",
    "desc": "After the shopping trip, the money has run out or the wallet was forgotten at home. The accessory keeps loose money but also credit cards or make-up. Can refer to shopping or money and stand for femininity and everything girlish."
  },