377

I have a Decimal('3.9') as part of an object, and wish to encode this to a JSON string which should look like {'x': 3.9}. I don't care about precision on the client side, so a float is fine.

Is there a good way to serialize this? JSONDecoder doesn't accept Decimal objects, and converting to a float beforehand yields {'x': 3.8999999999999999} which is wrong, and will be a big waste of bandwidth.

4
  • 3
    related Python bug: json encoder unable to handle decimal Commented Jul 27, 2014 at 14:04
  • 3.8999999999999999 is no more wrong than 3.4 is. 0.2 has no exact float representation. Commented May 25, 2015 at 3:55
  • 12
    @Jasen 3.89999999999 is about 12.8% more wrong than 3.4 is. The JSON standard is only about serialisation and notation, not implementation. Using IEEE754 is not part of the raw JSON spec, it is only the most common way to implement it. An implementation that uses only precise decimal arithmetic is completely (in fact, even more strictly) conforming. Commented May 7, 2020 at 10:57
  • 3
    😂 less wrong. ironic. Commented May 7, 2020 at 12:10

24 Answers 24

288

Simplejson 2.1 and higher has native support for Decimal type:

>>> import simplejson as json

>>> json.dumps(Decimal('3.9'), use_decimal=True)
'3.9'

Note that use_decimal is True by default:

def dumps(obj, skipkeys=False, ensure_ascii=True, check_circular=True,
    allow_nan=True, cls=None, indent=None, separators=None,
    encoding='utf-8', default=None, use_decimal=True,
    namedtuple_as_object=True, tuple_as_array=True,
    bigint_as_string=False, sort_keys=False, item_sort_key=None,
    for_json=False, ignore_nan=False, **kw):

So:

>>> json.dumps(Decimal('3.9'))
'3.9'

Hopefully, this feature will be included in standard library.

Sign up to request clarification or add additional context in comments.

13 Comments

Hmm, for me this converts Decimal objects to floats, which is not acceptable. Loss of precision when working with currency, for instance.
@MatthewSchinckel I think it doesn't. It actually makes a string out of it. And if you feed the resultant string back to json.loads(s, use_decimal=True) it gives you back the decimal. No float in entire process. Edited above answer. Hope original poster is fine with it.
Aha, I think I was not using use_decimal=True on the loads, too.
For me json.dumps({'a' : Decimal('3.9')}, use_decimal=True) gives '{"a": 3.9}'. Was the goal not '{"a": "3.9"}' ?
simplejson.dumps(decimal.Decimal('2.2')) also works: no explicit use_decimal (tested on simplejson/3.6.0). Another way to load it back is: json.loads(s, parse_float=Decimal) i.e., you can read it using stdlib json (and old simplejson versions are also supported).
|
279

I would like to let everyone know that I tried Michał Marczyk's answer on my web server that was running Python 2.6.5 and it worked fine. However, I upgraded to Python 2.7 and it stopped working. I tried to think of some sort of way to encode Decimal objects and this is what I came up with:

import json
import decimal

class DecimalEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, decimal.Decimal):
            return str(o)
        return super().default(o)

Note that this will convert the decimal to its string representation (e.g.; "1.2300") to a. not lose significant digits and b. prevent rounding errors.

This should hopefully help anyone who is having problems with Python 2.7. I tested it and it seems to work fine. If anyone notices any bugs in my solution or comes up with a better way, please let me know.

Usage example:

json.dumps({'x': decimal.Decimal('5.5')}, cls=DecimalEncoder)

# returns: '{"x": "5.5"}'

9 Comments

Python 2.7 changed the rules for rounding floats so this works. See discussion in stackoverflow.com/questions/1447287/…
For those of us who can't use simplejson (ie. on Google App Engine) this answer is a Godsend.
Use unicode or str instead of float to ensure precision.
The problem with 54.3999... was important in Python 2.6.x and older where the conversion float to string did not worked regularly, but the conversion Decimal to str is much more incorrect because it would be serialized as string with double quotes "54.4", not as a number.
Works in python3
|
182

How about subclassing json.JSONEncoder?

class DecimalEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, decimal.Decimal):
            # wanted a simple yield str(o) in the next line,
            # but that would mean a yield on the line with super(...),
            # which wouldn't work (see my comment below), so...
            return (str(o) for o in [o])
        return super(DecimalEncoder, self).default(o)

Then use it like so:

json.dumps({'x': decimal.Decimal('5.5')}, cls=DecimalEncoder)

11 Comments

Can't you just return (str(o),) instead? [o] is a list with only 1 element, why bother looping over it?
@Mark: return (str(o),) would return tuple of length 1, while code in the answer returns generator of length 1. See the iterencode() docs
This implementation doesn't work anymore. Elias Zamaria's one is the one working on the same style.
Its getting me this error: TypeError: <generator object <genexpr> at 0x7fd42908da20> is not JSON serializable
Have you tried your code? It results in the value in JSON being a string and not a float, as TS wanted. I have just tried it and I get "batchId": "31705" instead of "batchId": 31705.
|
72

The native Django option is missing so I'll add it for the next guy/gall that looks for it.

Starting on Django 1.7.x there is a built-in DjangoJSONEncoder that you can get it from django.core.serializers.json.

import json
from django.core.serializers.json import DjangoJSONEncoder
from django.forms.models import model_to_dict

model_instance = YourModel.object.first()
model_dict = model_to_dict(model_instance)

json.dumps(model_dict, cls=DjangoJSONEncoder)

Presto!

5 Comments

Although this is great to know, the OP didn't ask about Django?
@std''OrgnlDave you are 100% correct. I forgot how i got here, but i googled this question with "django" attached to the search term and this came up, after a little more googling, i found the answer and added it here for the next person like me, that stumbles across it
Would benefit from clarification if it returns {"x": 1.0} or {"x": "1.0"} as most of the answers here.
@Nickolay json does not support decimals that aren't floats, so it will return "1.0"
@JavierBuzzi JSON deals with "numbers" and does not even mention floats, and the OP wanted to get {"x": 1.0}... Thanks for clarifying that django's encoder returns {"x": "1.0"}!
58

In my Flask app, Which uses python 2.7.11, flask alchemy(with 'db.decimal' types), and Flask Marshmallow ( for 'instant' serializer and deserializer), i had this error, every time i did a GET or POST. The serializer and deserializer, failed to convert Decimal types into any JSON identifiable format.

I did a "pip install simplejson", then Just by adding

import simplejson as json

the serializer and deserializer starts to purr again. I did nothing else... DEciamls are displayed as '234.00' float format.

3 Comments

Oddly enough, you don't even have to import simplejson - just installing it does the trick. Initially mentioned by this answer.
This does not work on me, and still got that Decimal('0.00') is not JSON serializable after installing it via pip. This situation is when you are using both marshmallow and graphene. When a query is called on a rest api, marshmallow works expectedly for decimal fields. However when it is called with graphql it raised an is not JSON serializable error.
Perfect! This works in situations where you're using a module written by someone else whcih you can't easily modify (in my case gspread for using Google Sheets)
43

I tried switching from simplejson to builtin json for GAE 2.7, and had issues with the decimal. If default returned str(o) there were quotes (because _iterencode calls _iterencode on the results of default), and float(o) would remove trailing 0.

If default returns an object of a class that inherits from float (or anything that calls repr without additional formatting) and has a custom _repr_ method, it seems to work like I want it to.

import json
from decimal import Decimal

class fakefloat(float):
    def __init__(self, value):
        self._value = value
    def __repr__(self):
        return str(self._value)

def defaultencode(o):
    if isinstance(o, Decimal):
        # Subclass float with custom repr?
        return fakefloat(o)
    raise TypeError(repr(o) + " is not JSON serializable")

print(json.dumps([10.20, "10.20", Decimal('0.299999999999999988897769753748434595763683319091796875')], default=defaultencode))
# Should print:
# [10.2, "10.20", 0.299999999999999988897769753748434595763683319091796875]

7 Comments

Nice! This makes sure the decimal value ends up in the JSON as a Javascript float, without having Python first round it to the nearest float value.
Unfortunately this doesn't work in recent Python 3's. There is now some fast-path code that considers all float-subclasses as floats, and doesn't call repr on them altogether.
@AnttiHaapala, the example works fine on Python 3.6.
@CristianCiupitu indeed, I don't seem to be able to reproduce the bad behaviour now
The solution stopped working since v3.5.2rc1, see github.com/python/cpython/commit/…. There is float.__repr__ hardcoded (that looses precision), and fakefloat.__repr__ is not called at all. The solution above does work properly for python3 up to 3.5.1, if fakefloat has additional method def __float__(self): return self.
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29

For Django users:

Recently came across TypeError: Decimal('2337.00') is not JSON serializable while JSON encoding i.e. json.dumps(data)

Solution:

# converts Decimal, Datetime, UUIDs to str for Encoding
from django.core.serializers.json import DjangoJSONEncoder  

json.dumps(response.data, cls=DjangoJSONEncoder)

But, now the Decimal value will be a string, now we can explicitly set the decimal/float value parser when decoding data, using parse_float option in json.loads:

import decimal 

data = json.loads(data, parse_float=decimal.Decimal) # default is float(num_str)

Comments

21

For those who don't want to use a third-party library... An issue with Elias Zamaria's answer is that it converts to float, which can run into problems. For example:

>>> json.dumps({'x': Decimal('0.0000001')}, cls=DecimalEncoder)
'{"x": 1e-07}'
>>> json.dumps({'x': Decimal('100000000000.01734')}, cls=DecimalEncoder)
'{"x": 100000000000.01733}'

The JSONEncoder.encode() method lets you return the literal json content, unlike JSONEncoder.default(), which has you return a json compatible type (like float) that then gets encoded in the normal way. The problem with encode() is that it (normally) only works at the top level. But it's still usable, with a little extra work (python 3.x):

import json
from collections.abc import Mapping, Iterable
from decimal import Decimal, Context, MAX_PREC

_context = Context(prec=MAX_PREC)  # optional, to handle more than the default 28 digits, if necessary

class DecimalEncoder(json.JSONEncoder):
    def encode(self, obj):
        if isinstance(obj, Mapping):
            return '{' + ', '.join(f'{self.encode(k)}: {self.encode(v)}' for (k, v) in obj.items()) + '}'
        if isinstance(obj, Iterable) and (not isinstance(obj, str)):
            return '[' + ', '.join(map(self.encode, obj)) + ']'
        if isinstance(obj, Decimal):
            # (the _context is optional, for handling more than 28 digits)
            return f'{obj.normalize(_context):f}'  # using normalize() gets rid of trailing 0s, using ':f' prevents scientific notation
        return super().encode(obj)

Which gives you:

>>> json.dumps({'x': Decimal('0.0000001')}, cls=DecimalEncoder)
'{"x": 0.0000001}'
>>> json.dumps({'x': Decimal('100000000000.01734')}, cls=DecimalEncoder)
'{"x": 100000000000.01734}'
>>> json.dumps({'x': Decimal('123450.1000000000000000000000000000001000')}, cls=DecimalEncoder)
'{"x": 123450.1000000000000000000000000000001}'

As noted by Nickolay, if you're using more than 28 significant digits, you can run into issues with Decimal's default precision. So the above (modified) code includes a Context using MAX_PREC. There isn't really a performance impact, so it's fine to use a custom context like this even if you're not expecting that many digits.

5 Comments

Thanks for this. It was exactly what I was looking for. It outputs as a number but without the loss of precision due to float conversion. I ran into a little issue because I am using json.dump instead of json.dumps and you have to override iterencode instead of encode as explain here.
Thanks, this was the best solution that I found. Note, that parse_float can be used in json.loads to restore the python object (all floats will be converted to Decimal): json.loads(json.dumps({'x': Decimal('0.0000001')}, cls=DecimalEncoder), parse_float=Decimal). This is already mentioned in other comments, but I missed that in this solution.
This is great, except if you have more than 28 decimal places in your number — to which decimal.normalize() rounds by default.
@Nickolay Good point. I just modified it to support an arbitrary number of digits (MAX_PREC).
@ecp didn't mean it as a criticism of your solution, just a note for completeness. 28 decimal places seems to be more than enough for most people ;-) only stumbled upon this limitation while testing the other answer.
12

My $.02!

I extend a bunch of the JSON encoder since I am serializing tons of data for my web server. Here's some nice code. Note that it's easily extendable to pretty much any data format you feel like and will reproduce 3.9 as "thing": 3.9

JSONEncoder_olddefault = json.JSONEncoder.default
def JSONEncoder_newdefault(self, o):
    if isinstance(o, UUID): return str(o)
    if isinstance(o, datetime): return str(o)
    if isinstance(o, time.struct_time): return datetime.fromtimestamp(time.mktime(o))
    if isinstance(o, decimal.Decimal): return str(o)
    return JSONEncoder_olddefault(self, o)
json.JSONEncoder.default = JSONEncoder_newdefault

Makes my life so much easier...

5 Comments

This is incorrect: it will reproduce 3.9 as "thing": "3.9".
@Glyph via JSON standards (of which there are a few...), an unquoted number is a double-precision floating-point, not a decimal number. Quoting it is the only way to guarantee compatibility.
do you have a citation for this? Every spec I’ve read implies that it’s implementation-dependent.
@std''OrgnlDave the JSON spec clearly states that a number is a sequence of digits, with an optional fraction and exponent. A number in JSON is not double-precision floating point just because some implementations chose to implement it that way.
Yet there are reasons to choose a quoted decimal ("123.45") over an unquoted number, as discussed in stackoverflow.com/questions/35709595/…
12

From the JSON Standard Document, as linked in json.org:

JSON is agnostic about the semantics of numbers. In any programming language, there can be a variety of number types of various capacities and complements, fixed or floating, binary or decimal. That can make interchange between different programming languages difficult. JSON instead offers only the representation of numbers that humans use: a sequence of digits. All programming languages know how to make sense of digit sequences even if they disagree on internal representations. That is enough to allow interchange.

So it's actually accurate to represent Decimals as numbers (rather than strings) in JSON. Bellow lies a possible solution to the problem.

Define a custom JSON encoder:

import json


class CustomJsonEncoder(json.JSONEncoder):

    def default(self, obj):
        if isinstance(obj, Decimal):
            return float(obj)
        return super(CustomJsonEncoder, self).default(obj)

Then use it when serializing your data:

json.dumps(data, cls=CustomJsonEncoder)

As noted from comments on the other answers, older versions of python might mess up the representation when converting to float, but that's not the case anymore.

To get the decimal back in Python:

Decimal(str(value))

This solution is hinted in Python 3.0 documentation on decimals:

To create a Decimal from a float, first convert it to a string.

6 Comments

This isn't "fixed" in Python 3. Converting to a float necessarily makes you lose the decimal representation, and will lead to discrepancies. If Decimal is important to use, I think it is better to use strings.
I believe it's safe to do this since python 3.1. The loss in precision might be harmful in arithmetic operations, but in the case of JSON encoding, you are merely producing a string display of the value, so the precision is more than enough for most use cases. Everything in JSON is a string already, so putting quotes around the value just defies the JSON spec.
With that said, I understand the concerns around converting to float. There's probably a different strategy to use with the encoder to produce the wanted display string. Still, I don't think it's worth producing a quoted value.
@HugoMota " Everything in JSON is a string already, so putting quotes around the value just defies the JSON spec." No: rfc-editor.org/rfc/rfc8259.txt -- JSON is a text-based encoding format, but that doesn't mean everything in it is to be interpreted as a string. The spec defines how to encode numbers, separately from strings.
@GunnarÞórMagnússon "JSON is a text-based encoding format" - that's what I meant with "everything is a string". Converting the numbers to string beforehand won't magically preserve precision since it will be a string anyway when it becomes JSON. And according to the spec, numbers don't have quotes around it. It's the reader's responsibility to preserve precision while reading (not a quote, just my take on it).
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11

3.9 can not be exactly represented in IEEE floats, it will always come as 3.8999999999999999, e.g. try print repr(3.9), you can read more about it here:

http://en.wikipedia.org/wiki/Floating_point
http://docs.sun.com/source/806-3568/ncg_goldberg.html

So if you don't want float, only option you have to send it as string, and to allow automatic conversion of decimal objects to JSON, do something like this:

import decimal
from django.utils import simplejson

def json_encode_decimal(obj):
    if isinstance(obj, decimal.Decimal):
        return str(obj)
    raise TypeError(repr(obj) + " is not JSON serializable")

d = decimal.Decimal('3.5')
print simplejson.dumps([d], default=json_encode_decimal)

8 Comments

I know it won't be 3.9 internally once it is parsed on the client, but 3.9 is a valid JSON float. ie, json.loads("3.9") will work, and I would like it to be this
@Anurag You meant repr(obj) instead of repr(o) in your example.
Won't this just die if you try and encode something that isn't decimal?
@nailer, no it won't , you can try that, reason being default raise exception to signal that next handler should be used
See mikez302's answer - in Python 2.7 or above, this no longer applies.
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7

This is what I have, extracted from our class

class CommonJSONEncoder(json.JSONEncoder):

    """
    Common JSON Encoder
    json.dumps(myString, cls=CommonJSONEncoder)
    """

    def default(self, obj):

        if isinstance(obj, decimal.Decimal):
            return {'type{decimal}': str(obj)}

class CommonJSONDecoder(json.JSONDecoder):

    """
    Common JSON Encoder
    json.loads(myString, cls=CommonJSONEncoder)
    """

    @classmethod
    def object_hook(cls, obj):
        for key in obj:
            if isinstance(key, six.string_types):
                if 'type{decimal}' == key:
                    try:
                        return decimal.Decimal(obj[key])
                    except:
                        pass

    def __init__(self, **kwargs):
        kwargs['object_hook'] = self.object_hook
        super(CommonJSONDecoder, self).__init__(**kwargs)

Which passes unittest:

def test_encode_and_decode_decimal(self):
    obj = Decimal('1.11')
    result = json.dumps(obj, cls=CommonJSONEncoder)
    self.assertTrue('type{decimal}' in result)
    new_obj = json.loads(result, cls=CommonJSONDecoder)
    self.assertEqual(new_obj, obj)

    obj = {'test': Decimal('1.11')}
    result = json.dumps(obj, cls=CommonJSONEncoder)
    self.assertTrue('type{decimal}' in result)
    new_obj = json.loads(result, cls=CommonJSONDecoder)
    self.assertEqual(new_obj, obj)

    obj = {'test': {'abc': Decimal('1.11')}}
    result = json.dumps(obj, cls=CommonJSONEncoder)
    self.assertTrue('type{decimal}' in result)
    new_obj = json.loads(result, cls=CommonJSONDecoder)
    self.assertEqual(new_obj, obj)

2 Comments

json.loads(myString, cls=CommonJSONEncoder) comment should be json.loads(myString, cls=CommonJSONDecoder)
object_hook needs a default return value if obj is not decimal.
3

You can create a custom JSON encoder as per your requirement.

import json
from datetime import datetime, date
from time import time, struct_time, mktime
import decimal

class CustomJSONEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, datetime):
            return str(o)
        if isinstance(o, date):
            return str(o)
        if isinstance(o, decimal.Decimal):
            return float(o)
        if isinstance(o, struct_time):
            return datetime.fromtimestamp(mktime(o))
        # Any other serializer if needed
        return super(CustomJSONEncoder, self).default(o)

The Decoder can be called like this,

import json
from decimal import Decimal
json.dumps({'x': Decimal('3.9')}, cls=CustomJSONEncoder)

and the output will be:

>>'{"x": 3.9}'

Comments

2

Based on stdOrgnlDave answer I have defined this wrapper that it can be called with optional kinds so the encoder will work only for certain kinds inside your projects. I believe the work should be done inside your code and not to use this "default" encoder since "it is better explicit than implicit", but I understand using this will save some of your time. :-)

import time
import json
import decimal
from uuid import UUID
from datetime import datetime

def JSONEncoder_newdefault(kind=['uuid', 'datetime', 'time', 'decimal']):
    '''
    JSON Encoder newdfeault is a wrapper capable of encoding several kinds
    Use it anywhere on your code to make the full system to work with this defaults:
        JSONEncoder_newdefault()  # for everything
        JSONEncoder_newdefault(['decimal'])  # only for Decimal
    '''
    JSONEncoder_olddefault = json.JSONEncoder.default

    def JSONEncoder_wrapped(self, o):
        '''
        json.JSONEncoder.default = JSONEncoder_newdefault
        '''
        if ('uuid' in kind) and isinstance(o, uuid.UUID):
            return str(o)
        if ('datetime' in kind) and isinstance(o, datetime):
            return str(o)
        if ('time' in kind) and isinstance(o, time.struct_time):
            return datetime.fromtimestamp(time.mktime(o))
        if ('decimal' in kind) and isinstance(o, decimal.Decimal):
            return str(o)
        return JSONEncoder_olddefault(self, o)
    json.JSONEncoder.default = JSONEncoder_wrapped

# Example
if __name__ == '__main__':
    JSONEncoder_newdefault()

Comments

2

you can use simplejson or ujson

>>> import ujson
>>> import decimal
>>> ujson.dumps(decimal.Decimal(1.23))
'1.23'
>>> ujson.dumps({"w":decimal.Decimal(1.23)}) 
'{"w":1.23}'
>>>

Note that ujson is faster than json https://dev.to/dollardhingra/benchmarking-python-json-serializers-json-vs-ujson-vs-orjson-1o16

Comments

1

If you want to pass a dictionary containing decimals to the requests library (using the json keyword argument), you simply need to install simplejson:

$ pip3 install simplejson    
$ python3
>>> import requests
>>> from decimal import Decimal
>>> # This won't error out:
>>> requests.post('https://www.google.com', json={'foo': Decimal('1.23')})

The reason of the problem is that requests uses simplejson only if it is present, and falls back to the built-in json if it is not installed.

Comments

1

I will share what worked for me with flask 2.1.0 When I was creating the dictionary which had to be used from jsonify I used rounding:

json_dict['price'] = round(self.price, ndigits=2) if self.price else 0

So this way I could return D.DD number or 0 without using some global configuration. And this is nice because some Decimals has to be bigger, like latitude and longitude coordinates.

return jsonify(json_dict)

Comments

1

For whathever reason my requirement was to omit unneccessary 0's, so e.g. 123.0 should become 123. Also my requirement was to have the json output as number and not as string.

So thanks to Elias Zamarias solution I came up with the following:

class DecimalEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, decimal.Decimal):
            if float(o) == int(o):
                return int(o)
            else:
                return float(o)
        return super(DecimalEncoder, self).default(o)

Comments

0

For anybody that wants a quick solution here is how I removed Decimal from my queries in Django

total_development_cost_var = process_assumption_objects.values('total_development_cost').aggregate(sum_dev = Sum('total_development_cost', output_field=FloatField()))
total_development_cost_var = list(total_development_cost_var.values())
  • Step 1: use , output_field=FloatField() in you r query
  • Step 2: use list eg list(total_development_cost_var.values())

Hope it helps

Comments

0

Seems like there are enough answers in here but I got here needing a way to convert a list of numpy numbers to rounded decimals ready for export with simplejson

def encode_floats(nums, decimals=3):
    """
    Convert numpy numbers to ones ready for dumping with simplejson
    useful when you don't want your json exports to be bloated with too many
    significant figures
    :param nums: list of numbers
    :param decimals: number of decimals you want to output
    """
    def convert_to_rounded_dec(num):
        # convert to decimal
        num_dec = Decimal(np.float64(num))
        # create decimal number for quantizing
        round_dec = Decimal("".join(['0.'] + ['0'] * (decimals - 1) + ['1']))
        # actually round the number here
        num_round = num_dec.quantize(round_dec, rounding='ROUND_HALF_UP')
        return num_round
    # apply the function to the list of numbers
    func = (np.vectorize(convert_to_rounded_dec))
    # remove the numpy data type by converting to a list
    return func(nums).tolist()

Comments

-1

This question is old, but there seems to be a better and much simpler solution in Python3 for most use-cases:

number = Decimal(0.55)
converted_number = float(number) # Returns: 0.55 (as type float)

You can just convert Decimal to float.

1 Comment

The question already describes why converting to float is not wanted
-1

If someone is still looking for the answer, it is most probably you have a 'NaN' in your data that you are trying to encode. Because NaN is considered as float by Python.

1 Comment

This does not really answer the question. If you have a different question, you can ask it by clicking Ask Question. To get notified when this question gets new answers, you can follow this question. Once you have enough reputation, you can also add a bounty to draw more attention to this question. - From Review
-1

Decimal is not suitable to be converted through:

  • float due to precision problems
  • str due to openapi restrictions

We still need direct decimal to a number json serialisation.

Here is our extension of @tesdal 's fakefloat solution (closed in v3.5.2rc1). It uses fakestr + monkeypatching to avoid quotation and "floatation" of decimals.

import json.encoder
from decimal import Decimal


def encode_fakestr(func):
    def wrap(s):
        if isinstance(s, fakestr):
            return repr(s)
        return func(s)
    return wrap


json.encoder.encode_basestring = encode_fakestr(json.encoder.encode_basestring)
json.encoder.encode_basestring_ascii = encode_fakestr(json.encoder.encode_basestring_ascii)


class fakestr(str):
    def __init__(self, value):
        self._value = value
    def __repr__(self):
        return str(self._value)


class DecimalJsonEncoder(json.encoder.JSONEncoder):
    def default(self, o):
        if isinstance(o, Decimal):
            return fakestr(o)
        return super().default(o)


json.dumps([Decimal('1.1')], cls=DecimalJsonEncoder)

[1.1]

I don't understand why python developers force us using floats in places where it is not suitable.

Comments

-1

My solution:---

import json
from decimal import *

num = Decimal('8439.67')


class DecimalEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, Decimal):
            return str(obj)
        return json.JSONEncoder.default(self, obj)


json_str = json.dumps({'number': num}, cls=DecimalEncoder)
print(json_str)
print(type(json_str))

'''
Output:-
{"number": "8439.67"}
<class 'str'>
'''

1 Comment

This is a wrong solution since the value in the JSON is a string, while the TS is expecting the value to be a float.

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