Python JSON Encoder & Decoder Overview

Python_Json_Overview.md

JSON Overview

Json is a lightweight data interchange format and its module always produces string objects, not bytes objects. That said, you can serialize or deserialize data. But.. What is data serialization?

Data serialization

Data serialization is the process of converting structure data to a format that allows sharing or storage of data in a way that it is possible to recover its original format.

Why serialize data?

It can be used to minimize the data's size which can reduces space or badwidth requirements.

How to serialize data?

You can use JSON Python builting library (json.dumps or json.dump).

Compact Enconding

json.dumps()

Description: Serialize object as a JSON format.

• json.dump(obj, fp, *, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, default=None, sort_keys=False, **kw)

• 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)

     skipkeys=True --> dict keys that are not of a basic type (string, integer, float, boolean, None) can be skipped instead of raising TypeError
     
     sort_keys=True --> the outupt of dicts will be sorted by key
  

Usage Example

import json


my_object = {
                 "market_id": "1",
                 "stock_code": "AZUL4",
                 "price": "52.25",
                 "quantity": 100,
                 "financial_volume": "522500",
                 "aggressor": "C",
                 "buying_broker": "3",
                 "is_after_market": "0",
                 "selling_broker": "238",
                 "time": "103244",
                 "date": "20190919",
                 "identifier": "009140",
                 "type": 0
             }

my_object_serialized = json.dumps(my_object)

print(my_object_serialized)

>>> '{"market_id": "1", "stock_code": "AZUL4", "price": "52.25", "quantity": 100, "financial_volume": "522500",
      "aggressor": "C", "buying_broker": "3", "is_after_market": "0", "selling_broker": "238", "time": "103244",
      "date":  "20190919", "identifier": "009140", "type": 0}'

Decoding JSON

json.loads()

Description: Deserialize a string, bytes, bytearray instance containing a JSON document to a Python Object.

• json.loads(s, *, encoding=None, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)

• json.load(fp, *, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw)

Usage Example

import json

my_object_serialized = '{"market_id": "1", "stock_code": "AZUL4", "price": "52.25", "quantity": 100,
                         "financial_volume": "522500", "aggressor": "C", "buying_broker": "3", 
                         "is_after_market": "0", "selling_broker": "238", "time": "103244",
                         "date":  "20190919", "identifier": "009140", "type": 0}'


my_object_deserialized = json.loads(my_object_serialized)

print(my_object_deserialized)

>>> {'market_id': '1',
     'stock_code': 'AZUL4',
     'price': '52.25',
     'quantity': 100,
     'financial_volume': '522500',
     'aggressor': 'C',
     'buying_broker': '3',
     'is_after_market': '0',
     'selling_broker': '238',
     'time': '103244',
     'date': '20190919',
     'identifier': '009140',
     'type': 0}

References:

https://docs.python.org/3/library/json.html#py-to-json-table

https://docs.python-guide.org/scenarios/serialization/