将txt文件转换为python中的JSON

Question

I have a txt file which have the format shown below and the Key strings are not in quotes. How can I convert into a JSON using python?

name {
  first_name: "random"
}
addresses {
  location {
    locality: "India"
    street_address: "xyz"
    postal_code: "300092"
    full_address: "street 1 , abc,India"
  }
}
projects {
  url: "www.githib.com"
}

Answer 1

Assuming your data as,

{
    'addresses': {
        'location': {
            'full_address': 'street 1 , abc,India',
            'locality': 'India',
            'postal_code': '300092',
            'street_address': 'xyz'
        }
    },
    'name': {
        'first_name': 'random'
    },
    'projects': {
        'url': 'www.githib.com'
    }
}

Use json.dumps to convert dict to json

In [16]: import json

In [17]: data
Out[17]:
{'addresses': {'location': {'full_address': 'street 1 , abc,India',
   'locality': 'India',
   'postal_code': '300092',
   'street_address': 'xyz'}},
 'name': {'first_name': 'random'},
 'projects': {'url': 'www.githib.com'}}

In [18]: json.dumps(data)
Out[18]: '{"name": {"first_name": "random"}, "projects": {"url": "www.githib.com"}, "addresses": {"location": {"postal_code": "300092", "full_address": "street 1 , abc,India", "street_address": "xyz", "locality": "India"}}}'

In [19]:

Answer 2

There's no simple way in the standard library to convert that data format to JSON, so we need to write a parser. However, since the data format is fairly simple that's not hard to do. We can use the standard csv module to read the data. The csv.reader will handle the details of parsing spaces and quoted strings correctly. A quoted string will be treated as a single token, tokens consisting of a single word may be quoted but they don't need to be.

The csv.reader normally gets its data from an open file, but it's quite versatile, and will also read its data from a list of strings. This is convenient while testing since we can embed our input data into the script.

We parse the data into a nested dictionary. A simple way to keep track of the nesting is to use a stack, and we can use a plain list as our stack.

The code below assumes that input lines can be one of three forms:

1. Plain data. The line consists of a key - value pair, separated by at least one space.
2. A new subobject. The line starts with a key and ends in an open brace { .
3. The end of the current subobject. The line contains a single close brace }

import csv
import json

raw = '''\
name {
  first_name: "random"
}
addresses {
  location {
    locality: "India"
    street_address: "xyz"
    postal_code: "300092"
    full_address: "street 1 , abc,India"
  }
}
projects {
  url: "www.githib.com"
}
'''.splitlines()

# A stack to hold the parsed objects
stack = [{}]

reader = csv.reader(raw, delimiter=' ', skipinitialspace=True)
for row in reader:
    #print(row)
    key = row[0]
    if key == '}':
        # The end of the current object
        stack.pop()
        continue
    val = row[-1]
    if val == '{':
        # A new subobject
        stack[-1][key] = d = {}
        stack.append(d)
    else:
        # A line of plain data
        stack[-1][key] = val

# Convert to JSON
out = json.dumps(stack[0], indent=4)
print(out)

output

{
    "name": {
        "first_name:": "random"
    },
    "addresses": {
        "location": {
            "locality:": "India",
            "street_address:": "xyz",
            "postal_code:": "300092",
            "full_address:": "street 1 , abc,India"
        }
    },
    "projects": {
        "url:": "www.githib.com"
    }
}