222

I have a Python set that contains objects with __hash__ and __eq__ methods in order to make certain no duplicates are included in the collection.

I need to json encode this result set, but passing even an empty set to the json.dumps method raises a TypeError.

  File "/usr/lib/python2.7/json/encoder.py", line 201, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "/usr/lib/python2.7/json/encoder.py", line 264, in iterencode
    return _iterencode(o, 0)
  File "/usr/lib/python2.7/json/encoder.py", line 178, in default
    raise TypeError(repr(o) + " is not JSON serializable")
TypeError: set([]) is not JSON serializable

I know I can create an extension to the json.JSONEncoder class that has a custom default method, but I'm not even sure where to begin in converting over the set. Should I create a dictionary out of the set values within the default method, and then return the encoding on that? Ideally, I'd like to make the default method able to handle all the datatypes that the original encoder chokes on (I'm using Mongo as a data source so dates seem to raise this error too)

Any hint in the right direction would be appreciated.

EDIT:

Thanks for the answer! Perhaps I should have been more precise.

I utilized (and upvoted) the answers here to get around the limitations of the set being translated, but there are internal keys that are an issue as well.

The objects in the set are complex objects that translate to __dict__, but they themselves can also contain values for their properties that could be ineligible for the basic types in the json encoder.

There's a lot of different types coming into this set, and the hash basically calculates a unique id for the entity, but in the true spirit of NoSQL there's no telling exactly what the child object contains.

One object might contain a date value for starts, whereas another may have some other schema that includes no keys containing "non-primitive" objects.

That is why the only solution I could think of was to extend the JSONEncoder to replace the default method to turn on different cases - but I'm not sure how to go about this and the documentation is ambiguous. In nested objects, does the value returned from default go by key, or is it just a generic include/discard that looks at the whole object? How does that method accommodate nested values? I've looked through previous questions and can't seem to find the best approach to case-specific encoding (which unfortunately seems like what I'm going to need to do here).

martineau
  • 119,623
  • 25
  • 170
  • 301
DeaconDesperado
  • 9,977
  • 9
  • 47
  • 77
  • 3
    why `dict`s? I think you want to make just a `list` out of the set and then pass it to the encoder... e.g: `encode(list(myset))` – Constantinius Nov 22 '11 at 16:41
  • 2
    Instead of using JSON, you could use YAML (JSON is essentially a subset of YAML). – Paolo Moretti Nov 22 '11 at 16:52
  • @PaoloMoretti: Does it bring any advantage though? I don't think sets are among the universally-supported data types of YAML, and it's less widely supported, especially regarding APIs. –  Nov 22 '11 at 16:56
  • @PaoloMoretti Thank you for your input, but the application frontend requires JSON as a return type and this requirement is for all purposes fixed. – DeaconDesperado Nov 22 '11 at 16:57
  • 2
    @delnan I was suggesting YAML because it has a native support for both [sets](http://yaml.org/type/set.html) and [dates](http://yaml.org/type/timestamp.html). – Paolo Moretti Nov 22 '11 at 17:27
  • FWIW, my answer shows how to handle the nested case without clobbering your ability to use regular lists and dicts. This approach is easily extended to handle many different datatypes. – Raymond Hettinger Nov 22 '11 at 17:38
  • @RaymondHettinger - I'm in the process of implementing your solution right now as well. Strange coincidence - the ratings system for these datasets was built with your neural network code as a guide! Perhaps you remember me tweeting you =) – DeaconDesperado Nov 22 '11 at 18:27

12 Answers12

172

You can create a custom encoder that returns a list when it encounters a set. Here's an example:

import json
class SetEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, set):
            return list(obj)
        return json.JSONEncoder.default(self, obj)

data_str = json.dumps(set([1,2,3,4,5]), cls=SetEncoder)
print(data_str)
# Output: '[1, 2, 3, 4, 5]'

You can detect other types this way too. If you need to retain that the list was actually a set, you could use a custom encoding. Something like return {'type':'set', 'list':list(obj)} might work.

To illustrate nested types, consider serializing this:

class Something(object):
    pass
json.dumps(set([1,2,3,4,5,Something()]), cls=SetEncoder)

This raises the following error:

TypeError: <__main__.Something object at 0x1691c50> is not JSON serializable

This indicates that the encoder will take the list result returned and recursively call the serializer on its children. To add a custom serializer for multiple types, you can do this:

class SetEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, set):
            return list(obj)
        if isinstance(obj, Something):
            return 'CustomSomethingRepresentation'
        return json.JSONEncoder.default(self, obj)
 
data_str = json.dumps(set([1,2,3,4,5,Something()]), cls=SetEncoder)
print(data_str)
# Output: '[1, 2, 3, 4, 5, "CustomSomethingRepresentation"]'
Akaisteph7
  • 5,034
  • 2
  • 20
  • 43
jterrace
  • 64,866
  • 22
  • 157
  • 202
  • Thanks, I edited the question to better specify that this was the type of thing I needed. What I can't seem to grasp is how this method will handle nested objects. In your example the return value is list for set, but what if the object passed in was a set with dates (another bad datatype) inside it? Should I drill through the keys within the default method itself? Thanks a ton! – DeaconDesperado Nov 22 '11 at 17:00
  • 1
    I think the JSON module handles nested objects for you. Once it gets the list back, it will iterate over the list items trying to encode each one. If one of them is a date, the ``default`` function will get called again, this time with ``obj`` being a date object, so you just have to test for it and return a date-representation. – jterrace Nov 22 '11 at 17:08
  • So the default method could conceivably run several times for any one object passed to it, since it will also look at the individual keys once it is "listified"? – DeaconDesperado Nov 22 '11 at 17:10
  • Sort of, it won't get called multiple times for the *same* object, but it can recurse into children. See updated answer. – jterrace Nov 22 '11 at 17:19
  • Worked exactly as you described. I still have to figure some of the faults out, but most of it is probably stuff that can be refactored out. Thanks a ton for your guidance! – DeaconDesperado Nov 22 '11 at 17:21
  • 1
    @jterrace Any ideas to recover this back (list to set) while json.loads? Like encoding this information or something during `SetEncoder`? – John Strood Jul 08 '19 at 07:56
  • @jterrace Also interested in creating the corresponding `SetDecoder` class, but my naive attempt failed to correctly convert arrays into sets. Any ideas? – Martim Apr 27 '21 at 15:42
131

JSON notation has only a handful of native datatypes (objects, arrays, strings, numbers, booleans, and null), so anything serialized in JSON needs to be expressed as one of these types.

As shown in the json module docs, this conversion can be done automatically by a JSONEncoder and JSONDecoder, but then you would be giving up some other structure you might need (if you convert sets to a list, then you lose the ability to recover regular lists; if you convert sets to a dictionary using dict.fromkeys(s) then you lose the ability to recover dictionaries).

A more sophisticated solution is to build-out a custom type that can coexist with other native JSON types. This lets you store nested structures that include lists, sets, dicts, decimals, datetime objects, etc.:

from json import dumps, loads, JSONEncoder, JSONDecoder
import pickle

class PythonObjectEncoder(JSONEncoder):
    def default(self, obj):
        try:
            return {'_python_object': pickle.dumps(obj).decode('latin-1')}
        except pickle.PickleError:
            return super().default(obj)

def as_python_object(dct):
    if '_python_object' in dct:
        return pickle.loads(dct['_python_object'].encode('latin-1'))
    return dct

Here is a sample session showing that it can handle lists, dicts, and sets:

>>> data = [1,2,3, set(['knights', 'who', 'say', 'ni']), {'key':'value'}, Decimal('3.14')]

>>> j = dumps(data, cls=PythonObjectEncoder)

>>> loads(j, object_hook=as_python_object)
[1, 2, 3, set(['knights', 'say', 'who', 'ni']), {'key': 'value'}, Decimal('3.14')]

Alternatively, it may be useful to use a more general purpose serialization technique such as YAML, Twisted Jelly, or Python's pickle module. These each support a much greater range of datatypes.

Raymond Hettinger
  • 216,523
  • 63
  • 388
  • 485
  • In your sample session, should PythonSetEncoder be PythonObjectEncoder? – Brian Neal Nov 22 '11 at 18:50
  • Just make sure not to use that on untrusted input, as [pickle is not intended to be secure against erroneous or maliciously constructed data](http://docs.python.org/library/pickle.html), while JSON is (until customized with pickle). – Gunnlaugur Briem Nov 23 '11 at 09:06
  • 11
    This is the first I've heard that YAML is more general purpose than JSON... o_O – Karl Knechtel Nov 23 '11 at 11:55
  • 15
    @KarlKnechtel YAML is a superset of JSON (very nearly). It also adds tags for binary data, sets, ordered maps, and timestamps. Supporting more datatypes is what I meant by "more general purpose". You seem to be using the phrase "general purpose" in a different sense. – Raymond Hettinger Jan 07 '12 at 21:02
  • @Raymond: +1, however I believe the `if isinstance(obj, (list, dict, ... etc)):` statement in `PythonObjectEncoder.default()` is redundant since it will _only_ be called if the object is something the base JSONEncoder class can't handle. – martineau Sep 05 '13 at 15:16
  • 5
    Don't forget also [jsonpickle](http://github.com/jsonpickle/jsonpickle), which is intended to be a generalized library for pickling Python objects to JSON, much as this answer suggests. – Jason R. Coombs Sep 16 '13 at 18:42
  • 5
    As of version 1.2, YAML is a strict superset of JSON. All legal JSON now is legal YAML. http://www.yaml.org/spec/1.2/spec.html – steveha Oct 16 '14 at 00:21
  • 2
    this code example imports `JSONDecoder` but doesn't use it – watsonic Aug 26 '15 at 22:12
  • 1
    I like that this answer extends the functionality of JSON, however one should keep in mind, this is only for Python and human readability of the output suffers. Actually YAML seems to be the better alternative if readability is an issue. – NoDataDumpNoContribution Aug 10 '16 at 20:25
  • @watsonic: It needs to import `JSONDecoder` because it's the base class of `PythonObjectEncoder`. – martineau Oct 12 '17 at 17:10
  • Raymond: From the [`JSONEncoder` documentation](https://docs.python.org/2/library/json.html#json.JSONEncoder) it sounds like the `default()` method is only called "for objects that can’t otherwise be serialized" which means it's not necessary to do the `isinstance()` check in your answer. This seem workt by my own testing, although I would put the `return {'_python_object': pickle.dumps(obj)}` inside a `try/except TypeError:` in case `pickle.dumps()` can't deal with the object. Am I understanding something? – martineau Oct 12 '17 at 17:26
  • 1
    Raymond: On a related topic, instead of subclassing `JSONEncoder`, couldn't one just use the `default=` keyword argument of the standard class to specify a function that does something similar to what `PythonObjectEncoder.default()` method does in your answer? This seemed to work when I tested it, as well. – martineau Oct 12 '17 at 17:30
  • This answer ought to mention the security implications of `pickle` – CervEd May 21 '21 at 09:50
  • Sadly i get a lot of `RecursionError: maximum recursion depth exceeded in __instancecheck__` with your answer – Bluescream Jun 13 '21 at 03:33
  • @Bluescream I just updated this code for Python 3. It worked fine in Python 2. – Raymond Hettinger Jun 13 '21 at 10:22
  • Is there some reason you keep ignoring my comments about whether the `isinstance()` check the the `default()` method is really needed? – martineau Nov 09 '21 at 08:49
  • 1
    @martineau Updated the recipe to remove the `isinstance()` check. Added a try/except to call the parent in case of a pickling error. – Raymond Hettinger Nov 09 '21 at 18:07
37

You don't need to make a custom encoder class to supply the default method - it can be passed in as a keyword argument:

import json

def serialize_sets(obj):
    if isinstance(obj, set):
        return list(obj)

    return obj

json_str = json.dumps(set([1,2,3]), default=serialize_sets)
print(json_str)

results in [1, 2, 3] in all supported Python versions.

18

If you know for sure that the only non-serializable data will be sets, there's a very simple (and dirty) solution:

json.dumps({"Hello World": {1, 2}}, default=tuple)

Only non-serializable data will be treated with the function given as default, so only the set will be converted to a tuple.

Tom Pohl
  • 2,711
  • 3
  • 27
  • 34
10

I adapted Raymond Hettinger's solution to python 3.

Here is what has changed:

  • unicode disappeared
  • updated the call to the parents' default with super()
  • using base64 to serialize the bytes type into str (because it seems that bytes in python 3 can't be converted to JSON)
from decimal import Decimal
from base64 import b64encode, b64decode
from json import dumps, loads, JSONEncoder
import pickle

class PythonObjectEncoder(JSONEncoder):
    def default(self, obj):
        if isinstance(obj, (list, dict, str, int, float, bool, type(None))):
            return super().default(obj)
        return {'_python_object': b64encode(pickle.dumps(obj)).decode('utf-8')}

def as_python_object(dct):
    if '_python_object' in dct:
        return pickle.loads(b64decode(dct['_python_object'].encode('utf-8')))
    return dct

data = [1,2,3, set(['knights', 'who', 'say', 'ni']), {'key':'value'}, Decimal('3.14')]
j = dumps(data, cls=PythonObjectEncoder)
print(loads(j, object_hook=as_python_object))
# prints: [1, 2, 3, {'knights', 'who', 'say', 'ni'}, {'key': 'value'}, Decimal('3.14')]
Community
  • 1
  • 1
simlmx
  • 999
  • 12
  • 17
  • 4
    The code shown at the end of [this answer](http://stackoverflow.com/a/18561055/355230) to a related question accomplishes the same thing by [only] decoding and encoding the bytes object `json.dumps()` returns to/from `'latin1'`, skipping the `base64` stuff which isn't necessary. – martineau Apr 15 '16 at 19:50
8

If you need just quick dump and don't want to implement custom encoder. You can use the following:

json_string = json.dumps(data, iterable_as_array=True)

This will convert all sets (and other iterables) into arrays. Just beware that those fields will stay arrays when you parse the JSON back. If you want to preserve the types, you need to write custom encoder.

Also make sure to have simplejson installed and required.
You can find it on PyPi.

martineau
  • 119,623
  • 25
  • 170
  • 301
David Novák
  • 1,455
  • 2
  • 18
  • 30
6

Shortened version of @AnttiHaapala:

json.dumps(dict_with_sets, default=lambda x: list(x) if isinstance(x, set) else x)
uptoyou
  • 1,427
  • 19
  • 24
  • Best to me. In my case [set1, set2, set3, set4]. I can read the stringified back this way: [set(i) for i in json.loads(s)]. – H.C.Chen Nov 01 '21 at 07:58
6

Only dictionaries, Lists and primitive object types (int, string, bool) are available in JSON.

Joseph Le Brech
  • 6,541
  • 11
  • 49
  • 84
  • 8
    "Primitive object type" makes no sense when talking about Python. "Built-in object" makes more sense, but is too broad here (for starters: it includes dicts, lists and also sets). (JSON terminology may be different though.) –  Nov 22 '11 at 16:45
  • string number object array true false null – Joseph Le Brech Nov 22 '11 at 16:48
5

If you only need to encode sets, not general Python objects, and want to keep it easily human-readable, a simplified version of Raymond Hettinger's answer can be used:

import json
import collections

class JSONSetEncoder(json.JSONEncoder):
    """Use with json.dumps to allow Python sets to be encoded to JSON

    Example
    -------

    import json

    data = dict(aset=set([1,2,3]))

    encoded = json.dumps(data, cls=JSONSetEncoder)
    decoded = json.loads(encoded, object_hook=json_as_python_set)
    assert data == decoded     # Should assert successfully

    Any object that is matched by isinstance(obj, collections.Set) will
    be encoded, but the decoded value will always be a normal Python set.

    """

    def default(self, obj):
        if isinstance(obj, collections.Set):
            return dict(_set_object=list(obj))
        else:
            return json.JSONEncoder.default(self, obj)

def json_as_python_set(dct):
    """Decode json {'_set_object': [1,2,3]} to set([1,2,3])

    Example
    -------
    decoded = json.loads(encoded, object_hook=json_as_python_set)

    Also see :class:`JSONSetEncoder`

    """
    if '_set_object' in dct:
        return set(dct['_set_object'])
    return dct
NeilenMarais
  • 2,949
  • 1
  • 25
  • 23
2
>>> import json
>>> set_object = set([1,2,3,4])
>>> json.dumps(list(set_object))
'[1, 2, 3, 4]'
1

One shortcoming of the accepted solution is that its output is very python specific. I.e. its raw json output cannot be observed by a human or loaded by another language (e.g. javascript). example:

db = {
        "a": [ 44, set((4,5,6)) ],
        "b": [ 55, set((4,3,2)) ]
        }

j = dumps(db, cls=PythonObjectEncoder)
print(j)

Will get you:

{"a": [44, {"_python_object": "gANjYnVpbHRpbnMKc2V0CnEAXXEBKEsESwVLBmWFcQJScQMu"}], "b": [55, {"_python_object": "gANjYnVpbHRpbnMKc2V0CnEAXXEBKEsCSwNLBGWFcQJScQMu"}]}

I can propose a solution which downgrades the set to a dict containing a list on the way out, and back to a set when loaded into python using the same encoder, therefore preserving observability and language agnosticism:

from decimal import Decimal
from base64 import b64encode, b64decode
from json import dumps, loads, JSONEncoder
import pickle

class PythonObjectEncoder(JSONEncoder):
    def default(self, obj):
        if isinstance(obj, (list, dict, str, int, float, bool, type(None))):
            return super().default(obj)
        elif isinstance(obj, set):
            return {"__set__": list(obj)}
        return {'_python_object': b64encode(pickle.dumps(obj)).decode('utf-8')}

def as_python_object(dct):
    if '__set__' in dct:
        return set(dct['__set__'])
    elif '_python_object' in dct:
        return pickle.loads(b64decode(dct['_python_object'].encode('utf-8')))
    return dct

db = {
        "a": [ 44, set((4,5,6)) ],
        "b": [ 55, set((4,3,2)) ]
        }

j = dumps(db, cls=PythonObjectEncoder)
print(j)
ob = loads(j)
print(ob["a"])

Which gets you:

{"a": [44, {"__set__": [4, 5, 6]}], "b": [55, {"__set__": [2, 3, 4]}]}
[44, {'__set__': [4, 5, 6]}]

Note that serializing a dictionary which has an element with a key "__set__" will break this mechanism. So __set__ has now become a reserved dict key. Obviously feel free to use another, more deeply obfuscated key.

martineau
  • 119,623
  • 25
  • 170
  • 301
sagism
  • 881
  • 4
  • 11
  • 18
0

you should try jsonwhatever

https://pypi.org/project/jsonwhatever/

pip install jsonwhatever

from jsonwhatever import JsonWhatEver

set_a = {1,2,3}

jsonwe = JsonWhatEver()

string_res = jsonwe.jsonwhatever('set_string', set_a)

print(string_res)