19.2. json — JSON encoder and decoder — Python 3.4.10 documentation (original) (raw)

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

json exposes an API familiar to users of the standard librarymarshal 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)

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.

19.2.1. 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()-supportingfile-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, notbytes objects. Therefore, fp.write() must support strinput.

If ensure_ascii is True (the default), the output is guaranteed to have all incoming non-ASCII characters escaped. If ensure_ascii isFalse, 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 OverflowError (or worse).

If allow_nan is False (default: True), then it will be aValueError to serialize out of range float values (nan,inf, -inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN, Infinity, -Infinity).

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.

default(obj) is a function that should return a serializable version of_obj_ or raise TypeError. The default simply raises TypeError.

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 thedefault() method to serialize additional types), specify it with the_cls_ kwarg; otherwise JSONEncoder is used.

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 indump().

Note

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

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 file-like objectcontaining 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-RPCclass 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 thedict. This feature can be used to implement custom decoders that rely on the order that the key and value pairs are decoded (for example,collections.OrderedDict() will remember the order of insertion). 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).

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 clskwarg; 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, aValueError will be raised.

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

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

The other arguments have the same meaning as in load(), except_encoding_ which is ignored and deprecated.

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

19.2.2. 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:

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 givendict. 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 that rely on the order that the key and value pairs are decoded (for example,collections.OrderedDict() will remember the order of insertion). 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).

parse_constant, if specified, will be called with one of the following strings: '-Infinity', 'Infinity', 'NaN', 'null', 'true','false'. 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, aValueError will be raised.

decode(s)¶

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

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:

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

To extend this to recognize other objects, subclass and implement adefault() 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), then it is a TypeError to attempt encoding of 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 isFalse, 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 OverflowError). 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.

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 is 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.

default(o)¶

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

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)

19.2.3. Standard Compliance and Interoperability¶

The JSON format is specified by RFC 7159 and byECMA-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.

19.2.3.1. 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 andUnicode 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 ValueErrorwhen 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 originalstr) code points for such sequences.

19.2.3.2. 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.

19.2.3.3. 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.

19.2.3.4. 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.

19.2.3.5. 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 asdecimal.Decimal.

Footnotes