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The following is an example of how you might write and read a pickle file Curiously in timings the pickle version is faster. Note that if you keep appending pickle data to the file, you will need to continue reading from the file until you find what you want or an exception is generated by reaching the end of the file.

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Pickle uses a binary protocol, hence only accepts binary files Resulting file sizes are similar Pickle is unsafe because it constructs arbitrary python objects by invoking arbitrary functions

It seems you want to save your class instances across sessions, and using pickle is a decent way to do this

However, there's a package called klepto that abstracts the saving of objects to a dictionary interface, so you can choose to pickle objects and save them to a file (as shown below), or pickle the objects and save them to a database, or. I have looked through the information that the python documentation for pickle gives, but i'm still a little confused What would be some sample code that would write a new file and then use pickle. Therefore, to unpickle multiple streams, you should repeatedly unpickle the file until you get an eoferror:

Missing 'numpy._core.numeric' when loading pandas df from pickle asked 4 months ago modified 4 months ago viewed 648 times Pickle.dump(d, pfile, protocol=pickle.highest_protocol) pickle.highest_protocol will always be the right version for the current python version Because this is a binary format, make sure to use 'wb' as the file mode Python 3 no longer distinguishes between cpickle and pickle, always use pickle when using python 3.

Np.save/load is the usual pair for writing numpy arrays