pickle

i'm getting this error while running pyspark job on dataproc. What could be the reason ? This is the stack trace of error. File "/usr/lib/python2.7/pickle.py", line 331, in save self.save_reduce(obj=obj, *rv) File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/cloudpickle.py", line 553, in save_reduce File "/usr/lib/python2.7/pickle.py", line 286, in save f(self, obj) # Call unbound method with explicit self File "/usr/lib/python2.7/pickle.py", line 649, in save_dict self._batch_setitems(obj.iteritems()) File "/usr/lib/python2.7/pickle.py", line 681, in _batch_setitems save(v) File "/usr/lib

My program work fine on windows, with cpickle, and I am using binary mode, like 'wb', or 'rb'. When I ran my program on Linux, it still works fine. But when I tried to unpickle the files obtained from the Linux platform on my windows platform, I got this wired message says: cPickle.UnpicklingError: invalid load key' '. Can anyone please tell me why? It seems that I could not unpickle anyfile from the Linux platform. BTW, the two programs that I run are identical. Thanks a million. Looking at the code ( http://svn.python.org/view/python/trunk/Modules/cPickle.c?revision=81029&view=markup ), it

(Keep in mind I'm working in Python 3, so a solution needs to work in Python 3.) I would like to use the copyreg module to teach Python how to pickle functions. When I tried to do it, the _Pickler object would still try to pickle functions using the save_global function. (Which doesn't work for unbound methods, and that's the motivation for doing this.) It seems like _Pickler first tries to look in its own dispatch for the type of the object that you want to pickle before looking in copyreg.dispatch_table . I'm not sure if this is intentional. Is there any way for me to tell Python to pickle

I've taken over somebody's code for a fairly large project. I'm trying to save program state, and there's one massive object which stores pretty much all the other objects. I'm trying to pickle this object, but I get this error: pickle.PicklingError: Can't pickle : it's not found as builtin .module From what I can find on google, this is because somewhere I'm importing something outside of python init, or that a class attribute is referencing a module. So, I've got a two questions: Can anybody confirm that that's why this error is being given? Am I looking for the right things in my code? Is

If we serialize randomforest model using joblib on a 64-bit machine, and then unpack on a 32-bit machine, there is an exception: ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long long' This question has been asked before: Scikits-Learn RandomForrest trained on 64bit python wont open on 32bit python . But the question has not been answered from since 2014. Sample code to learn the model (On a 64-bit machine): modelPath="../" featureVec=... labelVec = ... forest = RandomForestClassifier() randomSearch = RandomizedSearchCV(forest, param_distributions=param_dict, cv=10, scoring=

I have a class that uses a list of Queue objects. I need to pickle this class including the information saved in the queue objects. For example: import Queue import pickle class QueueTest(object): def __init__(self): self.queueList = [] def addQueue(self): q = Queue.Queue() q.put('test') self.queueList.append(q) obj = QueueTest() obj.addQueue() with open('pickelTest.dat','w') as outf: pickle.dump(obj,outf) returns the error raise TypeError, "can't pickle %s objects" % base.__name__ TypeError: can't pickle lock objects Is there a work around to pickle Queue objects? I suggest replacing your

I basically do sequences of dump and load, but at some point I want to delete one of the loaded entries. How can I do that? Is there a way to remove, or edit entries saved with Python pickle/cpickle? Edit: The data is saved with pickle in a binary file. To delete a pickled object from a binary file you must rewrite the whole file. The pickle module doesn't deal with modifications at arbitrary portions of the stream, so there is no built-in way of doing what you want. Probably the simplest alternative to binary files is to use the shelve module. This module provides a dict like interface to a

If a Python 3 class is pickled using protocol 2, it is supposed to work in Python 2, but unfortunately, this fails because the names of some classes have changed. Assume we have code called as follows. Sender pickle.dumps(obj,2) Receiver pickle.loads(atom) To give a specific case, if obj={} , then the error given is: ImportError: No module named builtins This is because Python 2 uses __builtin__ instead. The question is the best way to fix this problem. This problem is Python issue 3675 . This bug is actually fixed in Python 3.11. If we import: from lib2to3.fixes.fix_imports import MAPPING