pickle module is part of the standard library in Python for a very long time now so there is no need to install it via pip. I wonder if you IDE or command line is not messed up somehow so that it does not find python installation path. Please check if your %PATH% contains a … Read more
The pickle module normally can’t pickle instance methods: >>> import pickle >>> class A(object): … def z(self): print “hi” … >>> a = A() >>> pickle.dumps(a.z) Traceback (most recent call last): File “<stdin>”, line 1, in <module> File “/usr/local/lib/python2.7/pickle.py”, line 1374, in dumps Pickler(file, protocol).dump(obj) File “/usr/local/lib/python2.7/pickle.py”, line 224, in dump self.save(obj) File “/usr/local/lib/python2.7/pickle.py”, line … Read more
Sure, save it as CSV: import csv w = csv.writer(open(“output.csv”, “w”)) for key, val in dict.items(): w.writerow([key, val]) Then reading it would be: import csv dict = {} for key, val in csv.reader(open(“input.csv”)): dict[key] = val Another alternative would be json (json for version 2.6+, or install simplejson for 2.5 and below): >>> import json … Read more
“are much more likely than a never-observed bug in Python itself in a functionality that’s used billions of times a day all over the world”: it always amazes me how cross people get in these forums. One easy way to get this problem is by forgetting to close the stream that you’re using for dumping … Read more
multiprocessing passes tasks (which include check_one and data) to the worker processes through a mp.SimpleQueue. Unlike Queue.Queues, everything put in the mp.SimpleQueue must be pickable. Queue.Queues are not pickable: import multiprocessing as mp import Queue def foo(queue): pass pool=mp.Pool() q=Queue.Queue() pool.map(foo,(q,)) yields this exception: UnpickleableError: Cannot pickle <type ‘thread.lock’> objects Your data includes packages, which … Read more
There is no cPickle in Python 3. Just import pickle. pickle will automatically use the C accelerator.
The problem is that you do not do any type conversion of the numpy array. You calculate a float32 variable and put it as an entry into a float64 numpy array. numpy then converts it properly back to float64 Try someting like this: a = np.zeros(4,dtype=”float64″) print a.dtype print type(a[0]) a = np.float32(a) print a.dtype … Read more
The pickle module implements an algorithm for turning an arbitrary Python object into a series of bytes. This process is also called serializing” the object. The byte stream representing the object can then be transmitted or stored, and later reconstructed to create a new object with the same characteristics. The cPickle module implements the same … Read more
multiprocessing makes some bad choices about pickling. Don’t get me wrong, it makes some good choices that enable it to pickle certain types so they can be used in a pool’s map function. However, since we have dill that can do the pickling, multiprocessing’s own pickling becomes a bit limiting. Actually, if multiprocessing were to … Read more
In addition to Martijn’s explanation: A module-level function is a function which is defined at module level, that means it is not an instance method of a class, it’s not nested within another function, and it is a “real” function with a name, not a lambda function. So, to pickle your defaultdict, create it with … Read more