Python json dumps integer value

I use the below python code to manipulate a set of JSON files in a specified folder. I extract nt from the data and I want to create new key value pair. If I were to print nt on my screen I get values as shown below.

nt 223 
nt 286 
nt 315 

These looks like integers to me. However If I use Kibana visualization tool to process it says this (i.e NXT is an analysed string fields). I want these values to be recognized as integers? Does this have something to do with the way I am encoding my json file (ensure_ascii=True) or is JSON value always a string?

#Process 'new' events to extract more info from 'Messages'
rootDir = '/home/s_parts'
for dirName, subdirList, fileList in os.walk(rootDir):
     for fname in fileList:
        fname='s_parts/'+fname
        with open(fname, 'r+') as f:
            json_data = json.load(f)
            m = json_data['Msg']
            nt = int(re.findall(r"NXT:\s*([^,m)]*)",m)[0])
            json_data["NXT"] = nt
            f.seek(0)
            json.dump(json_data,f,ensure_ascii=True)

asked Apr 7, 2015 at 2:02

liv2hakliv2hak

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1

It appears json.dump alone is most likely treating everything as strings. Using json.loads after it should convert it into a list or dict allowing you to use the json values as integers.

Example:

x = json.dumps({'1': 2, '3': 4}, ensure_ascii=True, sort_keys=True)
y = json.loads(x)
print(y)
print(y['3']+1)

Output:

{u'1': 2, u'3': 4}
5

You could convert the string value to int without using json.loads, however, converting it to a list or dict with json.loads is far easier to manage and retrieve values. If you are curious about the type your json.dump result is try doing:

x = json.dump(json_data,f,ensure_ascii=True)
print(type(x))

https://docs.python.org/3.3/library/json.html

answered Apr 7, 2015 at 2:49

l'L'll'L'l

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6

The full-form of JSON is JavaScript Object Notation. It means that a script (executable) file which is made of text in a programming language, is used to store and transfer the data. Python supports JSON through a built-in package called json. To use this feature, we import the json package in Python script. The text in JSON is done through quoted-string which contains the value in key-value mapping within { }. It is similar to the dictionary in Python.

Note: For more information, refer to Read, Write and Parse JSON using Python
 

Json.dumps()

json.dumps() function converts a Python object into a json string.
 

Syntax: 
json.dumps(obj, *, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)
Parameters: 
obj: Serialize obj as a JSON formatted stream 
skipkeys: If skipkeys is True (default: False), then dict keys that are not of a basic type (str, int, float, bool, None) will be skipped instead of raising a TypeError. 
ensure_ascii: If ensure_ascii is True (the default), the output is guaranteed to have all incoming non-ASCII characters escaped. If ensure_ascii is False, these characters will be output as-is. 
check_circular: If check_circular is False (default: True), then the circular reference check for container types will be skipped and a circular reference will result in an OverflowError (or worse). 
allow_nan: If allow_nan is False (default: True), then it will be a ValueError to serialize out of range float values (nan, inf, -inf) in strict compliance of the JSON specification. If allow_nan is True, their JavaScript equivalents (NaN, Infinity, -Infinity) will be used. 
indent: If indent is a non-negative integer or string, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0, negative, or “” will only insert newlines. None (the default) selects the most compact representation. Using a positive integer indent indents that many spaces per level. If indent is a string (such as “\t”), that string is used to indent each level. 
separators: If specified, separators should be an (item_separator, key_separator) tuple. The default is (‘, ‘, ‘: ‘) if indent is None and (‘, ‘, ‘: ‘) otherwise. To get the most compact JSON representation, you should specify (‘, ‘, ‘:’) to eliminate whitespace. 
default: If specified, default should be a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a TypeError. If not specified, TypeError is raised. 
sort_keys: If sort_keys is True (default: False), then the output of dictionaries will be sorted by key. 
 

Example #1: Passing the Python dictionary to json.dumps() function will return a string. 
 

Python3

import json

Dictionary ={1:'Welcome', 2:'to',

            3:'Geeks', 4:'for',

            5:'Geeks'}

json_string = json.dumps(Dictionary)

print('Equivalent json string of input dictionary:',

      json_string)

print("        ")

print(type(json_string))

Output
 

Equivalent json string of dictionary: {“1”: “Welcome”, “2”: “to”, “3”: “Geeks”, “4”: “for”, “5”: “Geeks”} 
<class ‘str’>

Example #2: By setting the skipkeys to True(default: False) we automatically skip the keys that are not of basic type.
 

Python3

import json

Dictionary ={(1, 2, 3):'Welcome', 2:'to',

            3:'Geeks', 4:'for',

            5:'Geeks'}

json_string = json.dumps(Dictionary,

                         skipkeys = True)

print('Equivalent json string of dictionary:',

      json_string)

Output 
 

Equivalent json string of dictionary: {“2”: “to”, “3”: “Geeks”, “4”: “for”, “5”: “Geeks”} 
 

Example #3: 
 

Python3

import json

Dictionary ={(1, 2, 3):'Welcome', 2:'to',

            3:'Geeks', 4:'for',

            5:'Geeks', 6:float('nan')}

json_string = json.dumps(Dictionary,

                         skipkeys = True,

                         allow_nan = True)

print('Equivalent json string of dictionary:',

      json_string)

Output : 
 

Equivalent json string of dictionary: {“2”: “to”, “3”: “Geeks”, “4”: “for”, “5”: “Geeks”, “6”: NaN} 

Example #4: 
 

Python3

import json

Dictionary ={(1, 2, 3):'Welcome', 2:'to',

            3:'Geeks', 4:'for',

            5:'Geeks', 6:float('nan')}

json_string = json.dumps(Dictionary,

                         skipkeys = True,

                         allow_nan = True,

                         indent = 6)

print('Equivalent json string of dictionary:',

      json_string)

Output: 
 

Equivalent json string of dictionary: {
      "2": "to",
      "3": "Geeks",
      "4": "for",
      "5": "Geeks",
      "6": NaN
}

Example #5: 
 

Python3

import json

Dictionary ={(1, 2, 3):'Welcome', 2:'to',

            3:'Geeks', 4:'for',

            5:'Geeks', 6:float('nan')}

json_string = json.dumps(Dictionary,

                         skipkeys = True,

                         allow_nan = True,

                         indent = 6,

                         separators =(". ", " = "))

print('Equivalent json string of dictionary:',

      json_string)

Output: 
 

Equivalent json string of dictionary: {
      "2" = "to". 
      "3" = "Geeks". 
      "4" = "for". 
      "5" = "Geeks". 
      "6" = NaN
}

Example #6: 
 

Python3

import json

Dictionary ={'c':'Welcome', 'b':'to',

            'a':'Geeks'}

json_string = json.dumps(Dictionary,

                         indent = 6,

                         separators =(". ", " = "),

                         sort_keys = True)

print('Equivalent json string of dictionary:',

      json_string)

Output: 
 

Equivalent json string of dictionary: {
      "a" = "Geeks". 
      "b" = "to". 
      "c" = "Welcome"
}

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