It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively. orjson.dumps() is something like 10x as fast as json, serializes common types and subtypes, has a default parameter for the caller to specify how to serialize arbitrary types, and has a number of flags controlling output.

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 ·

Serialize obj to a JSON formatted str. If skipkeys is true then dict keys that are not basic types (str, unicode, int, long, float, bool, None) will be skipped instead of raising a TypeError. If ensure_ascii is false, all non-ASCII characters are not escaped, and the return value may be a unicode instance. See dump ...

For those of you that have legacy systems to maintain, there is a very old fork of simplejson in the python2.2 branch that supports Python 2.2. This is based on a very old version of simplejson, is not maintained, and should only be used as a last resort. RawJSON allows embedding pre-encoded JSON strings into output without re-encoding them. This can be useful in advanced cases where JSON content is already serialized and re-encoding would be unnecessary. ... from simplejson import dumps, RawJSON payload = { "status": "ok", "data": RawJSON('{"a": 1, "b": 2}') } print(dumps(payload)) # Output: {"status": "ok", "data": {"a": 1, "b": 2}}

pretty and compact json dumps for python. GitHub Gist: instantly share code, notes, and snippets.

1.1 Converting from Python data types to JSON strings using json.dumps()

@C:\Python27\python.exe datetime-json.py print type(t) # datetime.datetime.now() <type 'datetime.datetime'> > print json.dumps([t],default=serialize) ["2016-01-19T08:30:09.242000"] > print json.loads(s) [u'2016-01-19T08:30:09.242000']

# Save the file import json with open("out.json", "w") as f: json.dump(f, [1, 2, 3]) # r+ is for both reading and writing with open("out.json", "r+") as f: existing_data = json.load(f) # load [1, 2, 3] from the file existing_data.extend([4, 5, 6]) # add [4, 5, 6] to the loaded data json.dump(f, existing_data) # write [1, 2, 3, 4, 5, 6] to the file ·

warnings.warn("Support for python 2 pickles will be dropped: {}".format(args.model)) · json_out = model.json(args.params) · if args.out_file is not None: with open(args.out_file, 'w') as f: print("Writing to file: ", args.out_file) json.dump(json_out, f, indent=4, cls=CustomEncoder) else: print(json.dumps(json_out, indent=4, cls=CustomEncoder))

Guaranteed-order JSON dump in Python using collections.OrderedDict. - guaranteed_order_json.py

$ python3 CompactJSONEncoder.py --example { "compact_object": { "first": "element", "second": 2 }, "compact_list": ["first", "second"], "long_list": [ "this", "is", "a", "rather", "long", "list" ] } ... @keithzg Ahh, I see what the problem is: json.dump works with indent parameters given as int and str, while my encoder assumes and int to multiply my indentation level with.

Decimal numbers in python json dump. GitHub Gist: instantly share code, notes, and snippets.

JSONPickle: a Python module that gives you complete dump Python objects and structures as JSON

s()" returns a string as indicated by the "s" at the end of "dumps". This process is called encoding. ... Now that the file is written. Let's reads it back and decoding the JSON-encoded string back into a Python dictionary data structure:

January 2, 2025 - stdlibStandard Library Python modules in the Lib/ directoryStandard Library Python modules in the Lib/ directorytype-bugAn unexpected behavior, bug, or errorAn unexpected behavior, bug, or error · nineteendo · opened · on Mar 29, 2025 · Issue body actions · >>> import json >>> print(json.dumps({b"": 0}, indent=4, skipkeys=True)) { } Related: #123183 ·

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

>>> import json >>> import datetime >>> data = { ... "name": "Silent Bob", ... "dt": datetime.datetime(2013, 11, 11, 10, 40, 32) ... } # Fails as expected >>> json.dumps(data) TypeError: Object of type datetime is not JSON serializable # Succeeds >>> json.dumps(data, default=str) '{"name": "Silent Bob", "dt": "2013-11-11 10:40:32"}'

December 17, 2024 - extension-modulesC modules in the Modules dirC modules in the Modules dirperformancePerformance or resource usagePerformance or resource usagestdlibStandard Library Python modules in the Lib/ directoryStandard Library Python modules in the Lib/ directorytype-bugAn unexpected behavior, bug, or errorAn unexpected behavior, bug, or error · wjmelements · opened · on Feb 6, 2025 · Issue body actions · Experimentally I measured a huge performance improvement when I switched my code from · json.dump(x, f, **) to ·

May 14, 2021 - The json module provides the following two methods to encode Python objects into JSON format. The json.dump() method (without “s” in “dump”) used to write Python serialized object as JSON formatted data into a file.

January 13, 2026 - The json.dump() function in Python is used to convert (serialize) a Python object into JSON format and write it directly to a file.