encoding and decoding binary data for inclusion into json with python 3

My seemingly working (confirmed by comparing MD5-sum of sent and received data) solution is doing the following:

def json_serialiser(byte_obj):
   if isinstance(byte_obj, (bytes, bytearray)):
   # File Bytes to Base64 Bytes then to String
return base64.b64encode(byte_obj).decode('utf-8')
raise ValueError('No encoding handler for data type ' + type(byte_obj))

def make_msg(filename, filedata):
   d = {
      "filename": filename,
      "datalen": len(filedata),
      "data": filedata
   }
return json.dumps(d,
   default = json_serialiser)

On the receiving end I simply do:

def parse_json(msg):
   d = json.loads(msg)
data = d.pop('data')
return base64.b64decode(data), d

def file_callback(ch, method, properties, body):
   filedata, fileinfo = parse_json(body)
print('File Name:', fileinfo.get("filename"))
print('Received File Size', len(filedata))

Suggestion : 2

My seemingly working (confirmed by comparing anycodings_python MD5-sum of sent and received data) solution anycodings_python is doing the following:,Mostly I'm surprised at not being able to anycodings_python find any examples online of doing this. anycodings_python Perhaps my google patience are still on anycodings_python holiday!,I need to decide on a schema for including anycodings_python binary elements into a message object so anycodings_python that it can be decoded again on the anycodings_python receiving end (In my situation a consumer on anycodings_python an Rabbit MQ / AMQP queue).,I decided against multipart MIME encoding anycodings_python over JSON mostly because it seems like using anycodings_python Thor's hammer to push in a thumb tack. I anycodings_python decided against manually joining parts anycodings_python (binary and JSON concatenated together) anycodings_python mostly because every time a new requirement anycodings_python arises it is a whole re-design. JSON with anycodings_python the binary encoded in one of the fields anycodings_python seems like an elegant solution.

My seemingly working (confirmed by comparing anycodings_python MD5-sum of sent and received data) solution anycodings_python is doing the following:

def json_serialiser(byte_obj):
   if isinstance(byte_obj, (bytes, bytearray)):
   # File Bytes to Base64 Bytes then to String
return base64.b64encode(byte_obj).decode('utf-8')
raise ValueError('No encoding handler for data type ' + type(byte_obj))

def make_msg(filename, filedata):
   d = {
      "filename": filename,
      "datalen": len(filedata),
      "data": filedata
   }
return json.dumps(d,
   default = json_serialiser)

On the receiving end I simply do:

def parse_json(msg):
   d = json.loads(msg)
data = d.pop('data')
return base64.b64decode(data), d

def file_callback(ch, method, properties, body):
   filedata, fileinfo = parse_json(body)
print('File Name:', fileinfo.get("filename"))
print('Received File Size', len(filedata))

Suggestion : 3

json exposes an API familiar to users of the standard library marshal and pickle modules.,The JSON format is specified by RFC 7159 and by ECMA-404. This section details this module’s level of compliance with the RFC. For simplicity, JSONEncoder and JSONDecoder subclasses, and parameters other than those explicitly mentioned, are not considered.,Extensible JSON encoder for Python data structures.,Deserialize s (a str, bytes or bytearray instance containing a JSON document) to a Python object using this conversion table.

>>>
import json
   >>>
   json.dumps(['foo', {
      'bar': ('baz', None, 1.0, 2)
   }])
'["foo", {"bar": ["baz", null, 1.0, 2]}]' >>>
print(json.dumps("\"foo\bar"))
"\"foo\bar" >>>
print(json.dumps('\u1234'))
"\u1234" >>>
print(json.dumps('\\'))
"\\" >>>
print(json.dumps({
      "c": 0,
      "b": 0,
      "a": 0
   }, sort_keys = True)) {
      "a": 0,
      "b": 0,
      "c": 0
   } >>>
   from io
import StringIO
   >>>
   io = StringIO() >>>
   json.dump(['streaming API'], io) >>>
   io.getvalue()
'["streaming API"]'

>>>
import json
   >>>
   json.dumps([1, 2, 3, {
      '4': 5,
      '6': 7
   }], separators = (',', ':'))
'[1,2,3,{"4":5,"6":7}]'

>>>
import json
   >>>
   print(json.dumps({
      '4': 5,
      '6': 7
   }, sort_keys = True, indent = 4)) {
      "4": 5,
      "6": 7
   }

>>>
import json
   >>>
   json.loads('["foo", {"bar":["baz", null, 1.0, 2]}]')['foo', {
      'bar': ['baz', None, 1.0, 2]
   }] >>>
   json.loads('"\\"foo\\bar"')
'"foo\x08ar' >>>
from io
import StringIO
   >>>
   io = StringIO('["streaming API"]') >>>
   json.load(io)['streaming API']

>>>
import json
   >>>
   def as_complex(dct):
   ...
   if '__complex__' in dct:
   ...
   return complex(dct['real'], dct['imag'])
      ...
      return dct
         ...
         >>>
         json.loads('{"__complex__": true, "real": 1, "imag": 2}',
            ...object_hook = as_complex)
         (1 + 2 j) >>>
         import decimal >>>
         json.loads('1.1', parse_float = decimal.Decimal)
Decimal('1.1')

>>>
import json
   >>>
   class ComplexEncoder(json.JSONEncoder):
   ...def
default (self, obj):
...
if isinstance(obj, complex):
   ...
   return [obj.real, obj.imag]
      ...# Let the base class
default method raise the TypeError
   ...
   return json.JSONEncoder.default(self, obj)
      ...
      >>>
      json.dumps(2 + 1 j, cls = ComplexEncoder)
'[2.0, 1.0]' >>>
ComplexEncoder().encode(2 + 1 j)
'[2.0, 1.0]' >>>
list(ComplexEncoder().iterencode(2 + 1 j))['[2.0', ', 1.0', ']']

Suggestion : 4

I need to decide on a schema for including binary elements into a message object so that it can be decoded again on the receiving end (In my situation a consumer on an Rabbit MQ / AMQP queue).,My google-fu left me unable to confirm whether what I am doing is in fact valid. In particular I am concerned whether the line that produces the string from the binary data for inclusion into JSON is correct, eg the line return base64.b64encode(byte_obj).decode('utf-8'),I decided against multipart MIME encoding over JSON mostly because it seems like using Thor's hammer to push in a thumb tack. I decided against manually joining parts (binary and JSON concatenated together) mostly because every time a new requirement arises it is a whole re-design. JSON with the binary encoded in one of the fields seems like an elegant solution.,And it seems that I am able to take a shortcut with the decoding back to binary data as the base64.b64decode() method handles the UTF-8 data as if it is ASCII - As one would expect it to be coming from the output of base64.b64encode() ... But is this a valid assumption in all cases?

My seemingly working (confirmed by comparing MD5-sum of sent and received data) solution is doing the following:

def json_serialiser(byte_obj):
   if isinstance(byte_obj, (bytes, bytearray)):
   # File Bytes to Base64 Bytes then to String
return base64.b64encode(byte_obj).decode('utf-8')
raise ValueError('No encoding handler for data type ' + type(byte_obj))

def make_msg(filename, filedata):
   d = {
      "filename": filename,
      "datalen": len(filedata),
      "data": filedata
   }
return json.dumps(d,
   default = json_serialiser)

On the receiving end I simply do:

def parse_json(msg):
   d = json.loads(msg)
data = d.pop('data')
return base64.b64decode(data), d

def file_callback(ch, method, properties, body):
   filedata, fileinfo = parse_json(body)
print('File Name:', fileinfo.get("filename"))
print('Received File Size', len(filedata))

Suggestion : 5

Last Updated : 03 Jun, 2022

Output:

{
   "age": 31,
   "Salary": 25000,
   "name": "John"
}

Output:

["Welcome", "to", "GeeksforGeeks"]
["Welcome", "to", "GeeksforGeeks"]
"Hi"
123
23.572
true
false
null

For Windows:

pip install demjson

Syntax:

demjson.encode(self, obj, nest_level = 0)

Syntax:

demjson.decode(self, obj)

Suggestion : 6

Class Starts on 27th August,2022

Example:

 import json

Example:

import json
people_string = ''
' {
   "people": [{
         "emp_name": "John smith",
         "emp_no.": "924367-567-23",
         "emp_email": ["johnsmith@dummyemail.com"],
         "has_license": "false"
      },
      {
         "emp_name": "harshit kant",
         "emp_number": "560-555-5153",
         "emp_email": "null",
         "has_license": "true"
      }
   ]
}
''
'
data = json.loads(people_string)
print(data)

The following generic structure can be used to load the JSON string into the DataFrame.

import pandas as pd

pd.read_json(r 'Path where you saved the JSON fileFile Name.json')

Example (Serialization of JSON dataset):

import json

with open('nobel_prize.json.html') as f:
   data = json.load(f)

with open('new_nobel_prize.json.html') as f:
   json.dump(data, f, indent = 2)

Example(Deserialization of JSON dataset):

import json

with open('nobel_prize.json.html') as f:
   data = json.load(f)

for nobel_prize in data['prizes']:
   print(nobel_prize['year'], nobel_prize['category'])