I'm currently using the standard multiprocessing in python to generate a bunch of processes that will run indefinitely. I'm not particularly concerned with performance; each thread is simply watchi...

dill is a great tool for pickling most the Python objects, I use it in IPython parallel to serialize calculations. One issue I keep getting into is around dill-ing class definitions. One of the err...

I'm exploring the detect method of Dill and am looking for a good simple example of a bad item - one that's unpicklable by Dill. I first thought of a process and tried: >>> proc = os.pop...

I have tried multiple approaches to pickle a python function with dependencies, following many recommendations on StackOverflow, (such as dill, cloudpickle, etc.) but all seem to run into a fundame...

I have a very complex dictionary and dumping, loading directly using dill works. This is in reference to this answer. But there is a slight modification. I need to save this in some file and read t...

Trying to render a large and (possibly very) unpicklable object to a file for later use. No complaints on the dill.dump(file) side: In [1]: import echonest.remix.audio as audio In [2]: import di...

In the answer to Python pickle: dealing with updated class definitions, the author of the dill package writes: "Ok, I have added this feature to dill in the latest revision on github. Implemented ...

I have a code framework which involves dumping sessions with dill. This used to work just fine, until I started to use pandas. The following code raises a PicklingError on CentOS release 6.5: impo...

I am using dill (advanced version of pickle) right now. I want to serialize my object, but I get this error: /usr/lib/python2.7/pickle.pyc in memoize(self, obj) 242 if self.fast: 243 return --&...

I am trying to make use of my computer's multiple CPUs. However, the BeautifulSoup object returned by my function as part of an SQLAlchemy object is not picklable with pickle or cPickle so I am usi...

Right at the outset, I tried conda install dill, and conda was not able to find it on the internet. Then I downloaded both .tgz and .zip files in my default IPython directory from here: https://py...