What is json loads in python?

JSON is a syntax for storing and exchanging data.

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JSON in Python
Parse JSON - Convert from JSON to Python
Convert from Python to JSON
Format the Result
Order the Result
Basic Usage¶
Encoders and Decoders¶
Exceptions¶
Standard Compliance and Interoperability¶
Character Encodings¶
Infinite and NaN Number Values¶
Repeated Names Within an Object¶
Top-level Non-Object, Non-Array Values¶
Implementation Limitations¶
Command Line Interface¶
Command line options¶
What is JSON load and loads?
What is JSON dumps and JSON loads?
What is JSON in Python used for?
What is JSON dumps in Python?

JSON is text, written with JavaScript object notation.

JSON in Python

Python has a built-in package called json, which can be used to work with JSON data.

Example

Import the json module:

import json

Parse JSON - Convert from JSON to Python

If you have a JSON string, you can parse it by using the json.loads() method.

Example

Convert from JSON to Python:

import json

# some JSON:
x = '{ "name":"John", "age":30, "city":"New York"}'

# parse x:
y = json.loads(x)

# the result is a Python dictionary:
print(y["age"])

Try it Yourself »

Convert from Python to JSON

If you have a Python object, you can convert it into a JSON string by using the json.dumps() method.

Example

Convert from Python to JSON:

import json

# a Python object (dict):
x = {
"name": "John",
"age": 30,
"city": "New York"
}

# convert into JSON:
y = json.dumps(x)

# the result is a JSON string:
print(y)

Try it Yourself »

You can convert Python objects of the following types, into JSON strings:

dict
list
tuple
string
int
float
True
False
None

Example

Convert Python objects into JSON strings, and print the values:

import json

print(json.dumps({"name": "John", "age": 30}))
print(json.dumps(["apple", "bananas"]))
print(json.dumps(("apple", "bananas")))
print(json.dumps("hello"))
print(json.dumps(42))
print(json.dumps(31.76))
print(json.dumps(True))
print(json.dumps(False))
print(json.dumps(None))

Try it Yourself »

When you convert from Python to JSON, Python objects are converted into the JSON (JavaScript) equivalent:

Python	JSON
dict	Object
list	Array
tuple	Array
str	String
int	Number
float	Number
True	true
False	false
None	null

Example

Convert a Python object containing all the legal data types:

import json

x = {
"name": "John",
"age": 30,
"married": True,
"divorced": False,
"children": ("Ann","Billy"),
"pets": None,
"cars": [
{"model": "BMW 230", "mpg": 27.5},
{"model": "Ford Edge", "mpg": 24.1}
]
}

print(json.dumps(x))

Try it Yourself »

Format the Result

The example above prints a JSON string, but it is not very easy to read, with no indentations and line breaks.

The json.dumps() method has parameters to make it easier to read the result:

Example

Use the indent parameter to define the numbers of indents:

json.dumps(x, indent=4)

Try it Yourself »

You can also define the separators, default value is (", ", ": "), which means using a comma and a space to separate each object, and a colon and a space to separate keys from values:

Example

Use the separators parameter to change the default separator:

json.dumps(x, indent=4, separators=(". ", " = "))

Try it Yourself »

Order the Result

The json.dumps() method has parameters to order the keys in the result:

Example

Use the sort_keys parameter to specify if the result should be sorted or not:

json.dumps(x, indent=4, sort_keys=True)

Try it Yourself »

Source code: Lib/json/__init__.py

JSON (JavaScript Object Notation), specified by RFC 7159 (which obsoletes RFC 4627) and by ECMA-404, is a lightweight data interchange format inspired by JavaScript object literal syntax (although it is not a strict subset of JavaScript 1 ).

Warning

Be cautious when parsing JSON data from untrusted sources. A malicious JSON string may cause the decoder to consume considerable CPU and memory resources. Limiting the size of data to be parsed is recommended.

json exposes an API familiar to users of the standard library marshal and pickle modules.

Encoding basic Python object hierarchies:

>>> 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"]'

Compact encoding:

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

Pretty printing:

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

Decoding JSON:

>>> 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']

Specializing JSON object decoding:

>>> 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+2j)
>>> import decimal
>>> json.loads('1.1', parse_float=decimal.Decimal)
Decimal('1.1')

Extending JSONEncoder:

>>> 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 + 1j, cls=ComplexEncoder)
'[2.0, 1.0]'
>>> ComplexEncoder().encode(2 + 1j)
'[2.0, 1.0]'
>>> list(ComplexEncoder().iterencode(2 + 1j))
['[2.0', ', 1.0', ']']

Using json.tool from the shell to validate and pretty-print:

$ echo '{"json":"obj"}' | python -m json.tool
{
 "json": "obj"
}
$ echo '{1.2:3.4}' | python -m json.tool
Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

See Command Line Interface for detailed documentation.

Note

JSON is a subset of YAML 1.2. The JSON produced by this module’s default settings (in particular, the default separators value) is also a subset of YAML 1.0 and 1.1. This module can thus also be used as a YAML serializer.

Note

This module’s encoders and decoders preserve input and output order by default. Order is only lost if the underlying containers are unordered.

Basic Usage¶

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)¶

Serialize obj as a JSON formatted stream to fp (a .write()-supporting file-like object) using this conversion table.

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.

The json module always produces str objects, not bytes objects. Therefore, fp.write() must support str input.

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.

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 RecursionError (or worse).

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.

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.

Changed in version 3.2: Allow strings for indent in addition to integers.

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.

Changed in version 3.4: Use (',', ': ') as default if indent is not None.

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.

If sort_keys is true (default: False), then the output of dictionaries will be sorted by key.

To use a custom JSONEncoder subclass (e.g. one that overrides the default() method to serialize additional types), specify it with the cls kwarg; otherwise JSONEncoder is used.

Changed in version 3.6: All optional parameters are now keyword-only.

Note

Unlike pickle and marshal, JSON is not a framed protocol, so trying to serialize multiple objects with repeated calls to dump() using the same fp will result in an invalid JSON file.

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)¶

Serialize obj to a JSON formatted str using this conversion table. The arguments have the same meaning as in dump().

Note

Keys in key/value pairs of JSON are always of the type str. When a dictionary is converted into JSON, all the keys of the dictionary are coerced to strings. As a result of this, if a dictionary is converted into JSON and then back into a dictionary, the dictionary may not equal the original one. That is, loads(dumps(x)) != x if x has non-string keys.

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

Deserialize fp (a .read()-supporting text file or binary file containing a JSON document) to a Python object using this conversion table.

object_hook is an optional function that will be called with the result of any object literal decoded (a dict). The return value of object_hook will be used instead of the dict. This feature can be used to implement custom decoders (e.g. JSON-RPC class hinting).

object_pairs_hook is an optional function that will be called with the result of any object literal decoded with an ordered list of pairs. The return value of object_pairs_hook will be used instead of the dict. This feature can be used to implement custom decoders. If object_hook is also defined, the object_pairs_hook takes priority.

Changed in version 3.1: Added support for object_pairs_hook.

parse_float, if specified, will be called with the string of every JSON float to be decoded. By default, this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).

parse_int, if specified, will be called with the string of every JSON int to be decoded. By default, this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).

Changed in version 3.10.7: The default parse_int of int() now limits the maximum length of the integer string via the interpreter’s integer string conversion length limitation to help avoid denial of service attacks.

parse_constant, if specified, will be called with one of the following strings: '-Infinity', 'Infinity', 'NaN'. This can be used to raise an exception if invalid JSON numbers are encountered.

Changed in version 3.1: parse_constant doesn’t get called on ‘null’, ‘true’, ‘false’ anymore.

To use a custom JSONDecoder subclass, specify it with the cls kwarg; otherwise JSONDecoder is used. Additional keyword arguments will be passed to the constructor of the class.

If the data being deserialized is not a valid JSON document, a JSONDecodeError will be raised.

Changed in version 3.6: All optional parameters are now keyword-only.

Changed in version 3.6: fp can now be a binary file. The input encoding should be UTF-8, UTF-16 or UTF-32.

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

Deserialize s (a str, bytes or bytearray instance containing a JSON document) to a Python object using this conversion table.

The other arguments have the same meaning as in load().

If the data being deserialized is not a valid JSON document, a JSONDecodeError will be raised.

Changed in version 3.6: s can now be of type bytes or bytearray. The input encoding should be UTF-8, UTF-16 or UTF-32.

Changed in version 3.9: The keyword argument encoding has been removed.

Encoders and Decoders¶

class json.JSONDecoder(*, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, strict=True, object_pairs_hook=None)¶

Simple JSON decoder.

Performs the following translations in decoding by default:

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

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

object_hook, if specified, will be called with the result of every JSON object decoded and its return value will be used in place of the given dict. This can be used to provide custom deserializations (e.g. to support JSON-RPC class hinting).

object_pairs_hook, if specified will be called with the result of every JSON object decoded with an ordered list of pairs. The return value of object_pairs_hook will be used instead of the dict. This feature can be used to implement custom decoders. If object_hook is also defined, the object_pairs_hook takes priority.

Changed in version 3.1: Added support for object_pairs_hook.

parse_constant, if specified, will be called with one of the following strings: '-Infinity', 'Infinity', 'NaN'. This can be used to raise an exception if invalid JSON numbers are encountered.

If strict is false (True is the default), then control characters will be allowed inside strings. Control characters in this context are those with character codes in the 0–31 range, including '\t' (tab), '\n', '\r' and '\0'.

If the data being deserialized is not a valid JSON document, a JSONDecodeError will be raised.

Changed in version 3.6: All parameters are now keyword-only.

decode(s)¶

Return the Python representation of s (a str instance containing a JSON document).

JSONDecodeError will be raised if the given JSON document is not valid.

raw_decode(s)¶

Decode a JSON document from s (a str beginning with a JSON document) and return a 2-tuple of the Python representation and the index in s where the document ended.

This can be used to decode a JSON document from a string that may have extraneous data at the end.

class json.JSONEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)¶

Extensible JSON encoder for Python data structures.

Supports the following objects and types by default:

Python	JSON
dict	object
list, tuple	array
str	string
int, float, int- & float-derived Enums	number
True	true
False	false
None	null

Changed in version 3.4: Added support for int- and float-derived Enum classes.

To extend this to recognize other objects, subclass and implement a default() method with another method that returns a serializable object for o if possible, otherwise it should call the superclass implementation (to raise TypeError).

If skipkeys is false (the default), a TypeError will be raised when trying to encode keys that are not str, int, float or None. If skipkeys is true, such items are simply skipped.

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.

If check_circular is true (the default), then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an RecursionError). Otherwise, no such check takes place.

If allow_nan is true (the default), then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats.

If sort_keys is true (default: False), then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis.

Changed in version 3.2: Allow strings for indent in addition to integers.

Changed in version 3.4: Use (',', ': ') as default if indent is not None.

Changed in version 3.6: All parameters are now keyword-only.

default(o)¶

Implement this method in a subclass such that it returns a serializable object for o, or calls the base implementation (to raise a TypeError).

For example, to support arbitrary iterators, you could implement default() like this:

def default(self, o):
   try:
       iterable = iter(o)
   except TypeError:
       pass
   else:
       return list(iterable)
   # Let the base class default method raise the TypeError
   return json.JSONEncoder.default(self, o)

encode(o)¶

Return a JSON string representation of a Python data structure, o. For example:

>>> json.JSONEncoder().encode({"foo": ["bar", "baz"]})
'{"foo": ["bar", "baz"]}'

iterencode(o)¶

Encode the given object, o, and yield each string representation as available. For example:

for chunk in json.JSONEncoder().iterencode(bigobject):
    mysocket.write(chunk)

Exceptions¶

exception json.JSONDecodeError(msg, doc, pos)¶

Subclass of ValueError with the following additional attributes:

msg¶

The unformatted error message.

doc¶

The JSON document being parsed.

pos¶

The start index of doc where parsing failed.

lineno¶

The line corresponding to pos.

colno¶

The column corresponding to pos.

New in version 3.5.

Standard Compliance and Interoperability¶

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.

This module does not comply with the RFC in a strict fashion, implementing some extensions that are valid JavaScript but not valid JSON. In particular:

Infinite and NaN number values are accepted and output;
Repeated names within an object are accepted, and only the value of the last name-value pair is used.

Since the RFC permits RFC-compliant parsers to accept input texts that are not RFC-compliant, this module’s deserializer is technically RFC-compliant under default settings.

Character Encodings¶

The RFC requires that JSON be represented using either UTF-8, UTF-16, or UTF-32, with UTF-8 being the recommended default for maximum interoperability.

As permitted, though not required, by the RFC, this module’s serializer sets ensure_ascii=True by default, thus escaping the output so that the resulting strings only contain ASCII characters.

Other than the ensure_ascii parameter, this module is defined strictly in terms of conversion between Python objects and Unicode strings, and thus does not otherwise directly address the issue of character encodings.

The RFC prohibits adding a byte order mark (BOM) to the start of a JSON text, and this module’s serializer does not add a BOM to its output. The RFC permits, but does not require, JSON deserializers to ignore an initial BOM in their input. This module’s deserializer raises a ValueError when an initial BOM is present.

The RFC does not explicitly forbid JSON strings which contain byte sequences that don’t correspond to valid Unicode characters (e.g. unpaired UTF-16 surrogates), but it does note that they may cause interoperability problems. By default, this module accepts and outputs (when present in the original str) code points for such sequences.

Infinite and NaN Number Values¶

The RFC does not permit the representation of infinite or NaN number values. Despite that, by default, this module accepts and outputs Infinity, -Infinity, and NaN as if they were valid JSON number literal values:

>>> # Neither of these calls raises an exception, but the results are not valid JSON
>>> json.dumps(float('-inf'))
'-Infinity'
>>> json.dumps(float('nan'))
'NaN'
>>> # Same when deserializing
>>> json.loads('-Infinity')
-inf
>>> json.loads('NaN')
nan

In the serializer, the allow_nan parameter can be used to alter this behavior. In the deserializer, the parse_constant parameter can be used to alter this behavior.

Repeated Names Within an Object¶

The RFC specifies that the names within a JSON object should be unique, but does not mandate how repeated names in JSON objects should be handled. By default, this module does not raise an exception; instead, it ignores all but the last name-value pair for a given name:

>>> weird_json = '{"x": 1, "x": 2, "x": 3}'
>>> json.loads(weird_json)
{'x': 3}

The object_pairs_hook parameter can be used to alter this behavior.

Top-level Non-Object, Non-Array Values¶

The old version of JSON specified by the obsolete RFC 4627 required that the top-level value of a JSON text must be either a JSON object or array (Python dict or list), and could not be a JSON null, boolean, number, or string value. RFC 7159 removed that restriction, and this module does not and has never implemented that restriction in either its serializer or its deserializer.

Regardless, for maximum interoperability, you may wish to voluntarily adhere to the restriction yourself.

Implementation Limitations¶

Some JSON deserializer implementations may set limits on:

the size of accepted JSON texts
the maximum level of nesting of JSON objects and arrays
the range and precision of JSON numbers
the content and maximum length of JSON strings

This module does not impose any such limits beyond those of the relevant Python datatypes themselves or the Python interpreter itself.

When serializing to JSON, beware any such limitations in applications that may consume your JSON. In particular, it is common for JSON numbers to be deserialized into IEEE 754 double precision numbers and thus subject to that representation’s range and precision limitations. This is especially relevant when serializing Python int values of extremely large magnitude, or when serializing instances of “exotic” numerical types such as decimal.Decimal.

Command Line Interface¶

Source code: Lib/json/tool.py

The json.tool module provides a simple command line interface to validate and pretty-print JSON objects.

If the optional infile and outfile arguments are not specified, sys.stdin and sys.stdout will be used respectively:

$ echo '{"json": "obj"}' | python -m json.tool
{
 "json": "obj"
}
$ echo '{1.2:3.4}' | python -m json.tool
Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

Changed in version 3.5: The output is now in the same order as the input. Use the --sort-keys option to sort the output of dictionaries alphabetically by key.

Command line options¶

infile¶

The JSON file to be validated or pretty-printed:

$ python -m json.tool mp_films.json
[
 {
 "title": "And Now for Something Completely Different",
 "year": 1971
 },
 {
 "title": "Monty Python and the Holy Grail",
 "year": 1975
 }
]

If infile is not specified, read from sys.stdin.

outfile¶

Write the output of the infile to the given outfile. Otherwise, write it to sys.stdout.

--sort-keys¶

Sort the output of dictionaries alphabetically by key.

New in version 3.5.

--no-ensure-ascii¶

Disable escaping of non-ascii characters, see json.dumps() for more information.

New in version 3.9.

--json-lines¶

Parse every input line as separate JSON object.

New in version 3.8.

--indent, --tab, --no-indent, --compact¶

Mutually exclusive options for whitespace control.

New in version 3.9.

-h, --help¶

Show the help message.

Footnotes

As noted in the errata for RFC 7159, JSON permits literal U+2028 (LINE SEPARATOR) and U+2029 (PARAGRAPH SEPARATOR) characters in strings, whereas JavaScript (as of ECMAScript Edition 5.1) does not.

What is JSON load and loads?

load() and json. loads() methods to read JSON data from file and String. Using the json. load() and json. loads() method, you can turn JSON encoded/formatted data into Python Types this process is known as JSON decoding.

What is JSON dumps and JSON loads?

json loads -> returns an object from a string representing a json object. json dumps -> returns a string representing a json object from an object. load and dump -> read/write from/to file instead of string.

What is JSON in Python used for?

JavaScript Object Notation (JSON) is a standardized format commonly used to transfer data as text that can be sent over a network. It's used by lots of APIs and Databases, and it's easy for both humans and machines to read. JSON represents objects as name/value pairs, just like a Python dictionary.

What is JSON dumps in Python?

The json. dumps() method allows us to convert a python object into an equivalent JSON object. Or in other words to send the data from python to json. The json. dump() method allows us to convert a python object into an equivalent JSON object and store the result into a JSON file at the working directory.

Tải thêm tài liệu liên quan đến bài viết What is json loads in python?

What is json loads in python?

JSON in Python

Example

Parse JSON - Convert from JSON to Python

Example

Convert from Python to JSON

Example

Example

Example

Format the Result

Example

Example

Order the Result

Example

Basic Usage¶

Encoders and Decoders¶

Exceptions¶

Standard Compliance and Interoperability¶

Character Encodings¶

Infinite and NaN Number Values¶

Repeated Names Within an Object¶

Top-level Non-Object, Non-Array Values¶

Implementation Limitations¶

Command Line Interface¶

Command line options¶

What is JSON load and loads?

What is JSON dumps and JSON loads?

What is JSON in Python used for?

What is JSON dumps in Python?

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