Writing and reading namedtuple into a file in python
Since the standard JSON modules in Python generally use dict
to work with JSON objects, you need to convert to and from a dict
.
For a little setup, let's say I've created this namedtuple
:
>>> from collections import namedtuple>>> import json>>> X = namedtuple('X', ['x', 'y', 'z'])>>> x = X(1,2,3)>>> xX(x=1, y=2, z=3)
Use
_asdict()
to convert to adict
that you can dump as JSON:>>> j = json.dumps(x._asdict())>>> j'{"x": 1, "y": 2, "z": 3}'
Now you have a JSON representation.
To get it back into an object, use
**
to convert adict
into keyword arguments:>>> x2 = X(**json.loads(j))>>> x2X(x=1, y=2, z=3)
Done.
You can of course read/write that JSON out to a file any way you wish. (For example, the JSON modules have methods that work with files directly.)
Just addressing your pickling difficulty, it seems that for pickle.dumps()
to work it is required that the typename
argument to namedtuple
match the name to which the returned class is bound.
import picklefrom collections import namedtuplegroup_t = namedtuple('group_t', 'field1, field2')Myobj = group_t(field1=1, field2=2)>>> pickle.dumps(Myobj)'ccopy_reg\n_reconstructor\np0\n(c__main__\ngroup_t\np1\nc__builtin__\ntuple\np2\n(I1\nI2\ntp3\ntp4\nRp5\n.'
Compare with this:
mismatched_group_t = namedtuple('group_t', 'field1, field2')Myobj = mismatched_group_t(field1=1, field2=2)>>> pickle.dumps(Myobj)Traceback (most recent call last):..pickle.PicklingError: Can't pickle <class '__main__.group_t'>: it's not found as __main__.group_t
The difference between the two classes is:
>>> group_t.__name__'group_t'>>> mismatched_group_t.__name__'group_t'
I'd say that that's what is throwing pickle
off.
I wrote a library for doing this: https://github.com/ltworf/typedload
It supports rather complicated types, which include enums, unions, tuples, sets, lists.
import typedloadtypedload.dump(some_namedtuple)
Your namedtuple could be something more complicated like this
class B(NamedTuple): name: strclass A(NamedTuple): values: List[Union[str, int]] other: Dict[str, str] points: Tuple[Tuple[float, float, float], ...] more: Optional[B] = None
And it can do dump
of objects and then load
them back.