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JSON Module

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Types

Defaults

the json module will handle encoding and decoding of the below types by default:

De-serialisation types:

JSON Python
object dict  
array list  
string str  
number (int) int  
number (real) float  
true, false True, False  
null None  

The json module also understands NaN, Infinity, and -Infinity as their corresponding float values, which is outside the JSON spec.

Serialisation types:

Python JSON
dict object
list, tuple array
str string
int, float number (int)
True, False true, false
None null

To disallow encoding of NaN, Infinity, and -Infinity you must encode with allow_nan=False. This will then raise a ValueError if you attempt to encode these values.

Custom (de-)serialisation

There are various hooks which allow you to handle data that needs to be represented differently. Use of functools.partial allows you to partially apply the relevant parameters to these functions for convenience.

Serialisation:

You can provide a function that operates on objects before they are serialised like so: 

# my_json module

import json
from functools import partial

def serialise_object(obj):
    # Do something to produce json-serialisable data
    return dict_obj

dump = partial(json.dump, default=serialise_object)
dumps = partial(json.dumps, default=serialise_object)

De-serialisation:

There are various hooks that are handled by the json functions, such as object_hook and parse_float. For an exhaustive list for your version of python, see here. 

# my_json module

import json
from functools import partial

def deserialise_object(dict_obj):
    # Do something custom
    return obj

def deserialise_float(str_obj):
    # Do something custom
    return obj

load = partial(json.load, object_hook=deserialise_object, parse_float=deserialise_float)
loads = partial(json.loads, object_hook=deserialise_object, parse_float=deserialise_float)

Further custom (de-)serialisation:

The json module also allows for extension/substitution of the json.JSONEncoder and json.JSONDecoder to handle miscellaneous types. The hooks documented above can be added as defaults by creating an equivalently named method. To use these simply pass the class as the cls parameter to the relevant function. Use of functools.partial allows you to partially apply the cls parameter to these functions for convenience, e.g. 

# my_json module

import json
from functools import partial

class MyEncoder(json.JSONEncoder):
    # Do something custom

class MyDecoder(json.JSONDecoder):
    # Do something custom

dump = partial(json.dump, cls=MyEncoder)
dumps = partial(json.dumps, cls=MyEncoder)
load = partial(json.load, cls=MyDecoder)
loads = partial(json.loads, cls=MyDecoder)
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JSON Module:
* JSON Module
* Storing data in a file
* Retrieving data from a file
* Formatting JSON output
* Creating Python dict from JSON
* load vs loads dump vs dumps
* Calling json.tool from the command line to pretty-print JSON output
* Creating JSON from Python dict
* JSON encoding custom objects
Table Of Contents
0 Getting Started
1 List comprehension
2 Filter
3 List
4 Functions
5 Decorators
6 Math module
7 Loops
8 Random module
9 Comparisons
10 Importing modules
11 Sorting Minimum and Maximium
12 Operator module
13 Variable Scope and Binding
14 Basic Input and Output
15 Files, Folders, I/O
16 JSON Module
17 String Methods
18 Metaclasses
19 Indexing and Slicing
20 Generators
21 Simple Mathematical Operators
22 Reduce
23 Map Function
24 Exponentation
25 Searching
26 Dictionary
27 Classes
28 Counting
29 Manipulating XML
30 Date and Time
31 Set
32 Collections module
33 Parallel computation
34 Multithreading
35 Writing C extensions
36 Unit Testing
37 Regular Expressions
38 Bitwise Operators
39 Incompatibilities moving from Python 2 to Python 3
40 Virtual environments
41 Copying data
42 Tuple
43 Context Managers with Statement
44 Hidden Features
45 Enum
46 String Formatting
47 Conditionals
48 Complex math
49 Unicode and bytes
50 The __name__ special variable
51 Check if path exists
52 Networking
53 Asyncio Module
54 Print Function
55 os.path module
56 Creating Python packages
57 Parsing Command Line Arguments
58 HTML Parsing
59 Subprocess Library
60 setup.py
61 List slicing
62 Sockets
63 Itertools Module
64 Recursion
65 Boolean Operators
66 dis module
67 Type Hints
68 pip PyPI Package Manager
69 locale module
70 Exceptions
71 Web scraping
72 deque module
73 Distributing self-contained applications
74 Property Objects
75 Overloading
76 Debugging
77 Reading and Writing CSV
78 Dynamic code execution with exec and eval
79 PyInstaller - Distributing Python Code
80 Iterables and Iterators
81 Data Visualization
82 The interpreter command line console
83 args and kwargs
84 functools module
85 Garbage Collection
86 Indentation
87 Security and Cryptograhy
88 Pickle data serialization
89 urllib
90 Binary Data
91 Python and Excel
92 Idioms
93 Method Overriding
94 Difference between a module and a package
95 Data Serialization
96 Python Concurrency
97 RabbitMQ using AMQPStorm
98 PostgreSQL
99 Descriptor
100 Common Pitfalls
101 Multiprocessing
102 Creating temporary files with tempfile
103 Working with ZIP files
104 Stack
105 Profiling
106 User-Defined Methods
107 Working around Global Interpreter Lock
108 Deployment using conda
109 Logging
110 Processes and Threads
111 os module
112 Comments and documentation
113 Database Access
114 Python HTTP Server
115 Alternatives to switch statement from other languages
116 List destructuring
117 Accessing Python source code and bytecode
118 Mixins
119 Attribute Access
120 ArcPy
121 Python Anti-Patterns
122 Plugin and Extension Classes
123 Websockets
124 Immutable data types
125 String representations of class
126 Arrays
127 Operator Precedence
128 Polymorphism
129 Alternative Python implementations
130 List Comprehensions
131 Web Server Gateway Intrerface WSGI
132 2to3 tool
133 Abstract Syntax Tree
134 Abstract Base Classes
135 Unicode
136 ssh in Python
137 Serial Communication with pyserial
138 Neo4j
139 Performance optimization
140 Curses
141 Templates
142 pass statement
143 Testing with py.test
144 Date Formatting
145 heapq
146 tkinter
147 CLI subcommands
148 Defining functions with list arguments
149 SQLite3 module
150 Persistence with pickle
151 Connecting to SQL Server
152 Design Patterns
153 Multidimensional arrays
154 Audio
155 pyglet
156 queue module
157 ijson
158 webbrowser module
159 base64 module
160 Flask
161 Groupby
162 Sockets and Message Encryption / Decryption
163 pygame
164 Input Subset and Output External Data Files using Pandas
165 hashlib
166 Gzip
167 ctypes
168 Creating a Windows Service
169 Mutable vs. Immutable
170 configparser
171 Common Exceptions
172 Optical Character Recognition OCR
173 Python Data Types
174 Partial functions
175 Generating graphs
176 Unzipping Files
177 Functional Programming
178 Python Virtual Environment - virtualenv
179 sys module
180 virtual environment with virtualenvwrapper
181 virtualenvwrapper on Windows
182 Python Requests Post
183 Plotting with Matplotlib
184 Python Lex-Yacc
185 pyaudio
186 shelve
187 pip and PyPI Package Manager
188 Writing to CSV from String or List
189 Raise Custom Errors Exceptions
190 Using loops within functions
191 Contributors