ImportError: No module named ‘pandas.indexes’
I had this error when I created a pkl file with python 2.7 and was trying to read it with python 3.6 I did: pd.read_pickle(‘foo.pkl’) and it worked
pickle
Python: why pickle?
Pickle is unsafe because it constructs arbitrary Python objects by invoking arbitrary functions. However, this is also gives it the power to serialize almost any Python object, without any boilerplate or even white-/black-listing (in the common case). That’s very desirable for some use cases: Quick & easy serialization, for example for pausing and resuming a … Read more
_pickle in python3 doesn’t work for large data saving
Not anymore in Python 3.4 which has PEP 3154 and Pickle 4.0 https://www.python.org/dev/peps/pep-3154/ But you need to say you want to use version 4 of the protocol: https://docs.python.org/3/library/pickle.html pickle.dump(d, open(“file”, ‘w’), protocol=4)
Saving and loading objects and using pickle
As for your second problem: Traceback (most recent call last): File “<stdin>”, line 1, in <module> File “C:\Python31\lib\pickle.py”, line 1365, in load encoding=encoding, errors=errors).load() EOFError After you have read the contents of the file, the file pointer will be at the end of the file – there will be no further data to read. You … Read more
Is pickle file of python cross-platform?
Python’s pickle is perfectly cross-platform. This is likely due to EOL (End-Of-Line) differences between Windows and Linux. Make sure to open your pickle files in binary mode both when writing them and when reading them, using open()’s “wb” and “rb” modes respectively. Note: Passing pickles between different versions of Python can cause trouble, so try … Read more
multiprocessing.Pool – PicklingError: Can’t pickle : attribute lookup thread.lock failed
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
Why do I get “Pickle – EOFError: Ran out of input” reading an empty file?
Most of the answers here have dealt with how to mange EOFError exceptions, which is really handy if you’re unsure about whether the pickled object is empty or not. However, if you’re surprised that the pickle file is empty, it could be because you opened the filename through ‘wb’ or some other mode that could … Read more
How to change the serialization method used by the multiprocessing module?
I believe the patch you’re referring to works if you’re using a multiprocessing “context” object. Using your pickle2reducer.py, your client should start with: import pickle2reducer import multiprocessing as mp ctx = mp.get_context() ctx.reducer = pickle2reducer.Pickle2Reducer() And ctx has the same API as multiprocessing. Hope that helps!
What is faster – Loading a pickled dictionary object or Loading a JSON file – to a dictionary? [closed]
The speed actually depends on the data, it’s content and size. But, anyway, let’s take an example json data and see what is faster (Ubuntu 12.04, python 2.7.3) : pickle cPickle json simplejson ujson yajl Giving this json structure dumped into test.json and test.pickle files: { “glossary”: { “title”: “example glossary”, “GlossDiv”: { “title”: “S”, … Read more
How to pickle a python function with its dependencies?
Updated Sep 2020: See the comment by @ogrisel below. The developers of PiCloud moved to Dropbox shortly after I wrote the original version of this answer in 2013, though a lot of folks are still using the cloudpickle module seven years later. The module made its way to Apache Spark, where it has continued to … Read more