How to pickle a namedtuple instance correctly

Question

I’m learning how to use pickle. I’ve created a namedtuple object, appended it to a list, and tried to pickle that list. However, I get the following error:

pickle.PicklingError: Can't pickle <class '__main__.P'>: it's not found as __main__.P

I found that if I ran the code without wrapping it inside a function, it works perfectly. Is there an extra step required to pickle an object when wrapped inside a function?

Here is my code:

from collections import namedtuple
import pickle

def pickle_test():
    P = namedtuple("P", "one two three four")
    my_list = []
    abe = P("abraham", "lincoln", "vampire", "hunter")
    my_list.append(abe)
    with open('abe.pickle', 'wb') as f:
        pickle.dump(abe, f)
    
pickle_test()

Asked By: Dirty Penguin

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Source

Answer 1

Create the named tuple outside of the function:

from collections import namedtuple
import pickle

P = namedtuple("P", "one two three four")

def pickle_test():
    my_list = []
    abe = P("abraham", "lincoln", "vampire", "hunter")
    my_list.append(abe)
    with open('abe.pickle', 'wb') as f:
        pickle.dump(abe, f)

pickle_test()

Now pickle can find it; it is a module global now. When unpickling, all the pickle module has to do is locate __main__.P again. In your version, P is a local, to the pickle_test() function, and that is not introspectable or importable.

Note that pickle stores just the module and the class name, as taken from the class’s __name__ attribute. Make sure that the first argument of the namedtuple() call matches the global variable you are assigning to; P.__name__ must be "P"!

It is important to remember that namedtuple() is a class factory; you give it parameters and it returns a class object for you to create instances from. pickle only stores the data contained in the instances, plus a string reference to the original class to reconstruct the instances again.

Answered By: Martijn Pieters

Answer 2

After I added my question as a comment to the main answer I found a way to solve the problem of making a dynamically created namedtuple pickle-able. This is required in my case because I’m figuring out its fields only at runtime (after a DB query).

All I do is monkey patch the namedtuple by effectively moving it to the __main__ module:

def _CreateNamedOnMain(*args):
    import __main__
    namedtupleClass = collections.namedtuple(*args)
    setattr(__main__, namedtupleClass.__name__, namedtupleClass)
    namedtupleClass.__module__ = "__main__"
    return namedtupleClass

Mind that the namedtuple name (which is provided by args) might overwrite another member in __main__ if you’re not careful.

Answered By: Chuim

Answer 3

Alternatively, you can use cloudpickle or dill for serialization:

from collections import namedtuple

import cloudpickle
import dill



def dill_test(dynamic_names):
    P = namedtuple('P', dynamic_names)
    my_list = []
    abe = P("abraham", "lincoln", "vampire", "hunter")
    my_list.append(abe)
    with open('deleteme.cloudpickle', 'wb') as f:
        cloudpickle.dump(abe, f)
    with open('deleteme.dill', 'wb') as f:
        dill.dump(abe, f)


dill_test("one two three four")

Answered By: Peque

Answer 4

I found this answer in another thread. This is all about the naming of the named tuple. This worked for me:

group_t =            namedtuple('group_t', 'field1, field2')  # this will work
mismatched_group_t = namedtuple('group_t', 'field1, field2')  # this will throw the error

Answered By: Ruvalcaba

Answer 5

The issue here is the child processes aren’t able to import the class of the object -in this case, the class P-, in the case of a multi-model project the Class P should be importable anywhere the child process get used

a quick workaround is to make it importable by affecting it to globals()

globals()["P"] = P

Answered By: rachid el kedmiri

How to pickle a namedtuple instance correctly

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