Python: make a list generator JSON serializable

Question

How can I concat a list of JSON files into a huge JSON array? I've 5000 files and 550 000 list items.

My fist try was to use jq, but it looks like jq -s is not optimized for a large input.

jq -s -r '[.[][]]' *.js 

This command works, but takes way too long to complete and I really would like to solve this with Python.

Here is my current code:

def concatFiles(outName, inFileNames):
    def listGenerator():
        for inName in inFileNames:
            with open(inName, 'r') as f:
                for item in json.load(f):
                    yield item

    with open(outName, 'w') as f:
        json.dump(listGenerator(), f)

I'm getting:

TypeError: <generator object listGenerator at 0x7f94dc2eb3c0> is not JSON serializable

Any attempt load all files into ram will trigger the OOM-killer of Linux. Do you have any ideas?

Answer 1

You should derive from list and override __iter__ method.

import json

def gen():
    yield 20
    yield 30
    yield 40

class StreamArray(list):
    def __iter__(self):
        return gen()

    # according to the comment below
    def __len__(self):
        return 1

a = [1,2,3]
b = StreamArray()

print(json.dumps([1,a,b]))

Result is [1, [1, 2, 3], [20, 30, 40]].

Answer 2

As of simplejson 3.8.0, you can use the iterable_as_array option to make any iterable serializable into an array

# Since simplejson is backwards compatible, you should feel free to import
# it as `json`
import simplejson as json
json.dumps((i*i for i in range(10)), iterable_as_array=True)

result is [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Answer 3

Based on the accepted answer, here is the StreamArray I eventually went for. It contains two lies:

1. The suggestion that self.__tail__ might be immutable
2. len(StreamArray(some_gen)) is either 0 or 1

.

class StreamArray(list):

    def __init__(self, gen):
        self.gen = gen

    def destructure(self):
        try:
            return self.__head__, self.__tail__, self.__len__
        except AttributeError:
            try:
                self.__head__ = self.gen.__next__()
                self.__tail__ = self.gen
                self.__len__ = 1 # A lie
            except StopIteration:
                self.__head__ = None
                self.__tail__ = []
                self.__len__ = 0
            return self.__head__, self.__tail__, self.__len__

    def rebuilt_gen(self):
        def rebuilt_gen_inner():
            head, tail, len_ = self.destructure()
            if len_ > 0:
                yield head
            for elem in tail:
                yield elem
        try:
            return self.__rebuilt_gen__
        except AttributeError:
            self.__rebuilt_gen__ = rebuilt_gen_inner()
            return self.__rebuilt_gen__

    def __iter__(self):
        return self.rebuilt_gen()

    def __next__(self):
        return self.rebuilt_gen()

    def __len__(self):
        return self.destructure()[2]

Single use only!

Answer 4

A complete simple readable solution that can serialize a generator from a normal or empty iterable, can work with .encode() or .iterencode(). Written tests. Tested with Python 2.7, 3.0, 3.3, 3.6

import itertools

class SerializableGenerator(list):
    """Generator that is serializable by JSON

    It is useful for serializing huge data by JSON
    >>> json.dumps(SerializableGenerator(iter([1, 2])))
    "[1, 2]"
    >>> json.dumps(SerializableGenerator(iter([])))
    "[]"

    It can be used in a generator of json chunks used e.g. for a stream
    >>> iter_json = ison.JSONEncoder().iterencode(SerializableGenerator(iter([])))
    >>> tuple(iter_json)
    ('[1', ']')
    # >>> for chunk in iter_json:
    # ...     stream.write(chunk)
    # >>> SerializableGenerator((x for x in range(3)))
    # [<generator object <genexpr> at 0x7f858b5180f8>]
    """

    def __init__(self, iterable):
        tmp_body = iter(iterable)
        try:
            self._head = iter([next(tmp_body)])
            self.append(tmp_body)
        except StopIteration:
            self._head = []

    def __iter__(self):
        return itertools.chain(self._head, *self[:1])


# -- test --

import unittest
import json


class Test(unittest.TestCase):

    def combined_dump_assert(self, iterable, expect):
        self.assertEqual(json.dumps(SerializableGenerator(iter(iterable))), expect)

    def combined_iterencode_assert(self, iterable, expect):
        encoder = json.JSONEncoder().iterencode
        self.assertEqual(tuple(encoder(SerializableGenerator(iter(iterable)))), expect)

    def test_dump_data(self):
        self.combined_dump_assert(iter([1, "a"]), '[1, "a"]')

    def test_dump_empty(self):
        self.combined_dump_assert(iter([]), '[]')

    def test_iterencode_data(self):
        self.combined_iterencode_assert(iter([1, "a"]), ('[1', ', "a"', ']'))

    def test_iterencode_empty(self):
        self.combined_iterencode_assert(iter([]), ('[]',))

    def test_that_all_data_are_consumed(self):
        gen = SerializableGenerator(iter([1, 2]))
        list(gen)
        self.assertEqual(list(gen), [])

Used solutions: Vadim Pushtaev (incomplete), user1158559 (unnecessarily complicated) and Claude (in another question, also complicated).

Useful simplification are:

• It is not necessary to evaluate the first item lazily and it can be it done in __init__ because we can expect that the SerializableGenerator can be called immediately before json.dumps. (against user1158559 solution)
• It is not necessary to rewrite many methods by NotImplementedError because that are not all methods like __repr__. It is better to store the generator also to the list to provide meaningful results like [<generator object ...>]. (against Claude). Default methods __len__ and __bool__ works now correctly to recognize an empty and not empty object.

---

An advantage of this solution is that a standard JSON serializer can be used without params. If nested generators should be supported or if encapsulation by SerializableGenerator(iterator) is undesirable then I recommend IterEncoder answer.