See Part I to get started with Pickle Python.
Pickle Python Scenario 2
In the following scenario, we can see a Pickle object between the testing process and the forecasting process.
Pickle Python example – Pickle object between the testing process and the forecasting process
In short, Pickle allows us to dump the Python objects in memory to a binary file to retrieve them later and continue working. Let’s see how to dump the memory to the file and load the memory from the file later.
How to use Pickle Python to save work
The process of dumping objects from RAM to binary file with Pickle Python is quite simple:
pickle.dump(object, model_x.pkl, other_params)
This simple line of code certainly saves us a great deal of work. On the other hand, the function accepts many other parameters for which it is recommended to consult the official documentation.
How to use Pickle Python to retrieve work
The loading process from binary Pickle file to RAM is just as simple:
model = pickle.load(model_x.pkl)
With this simple line of code we get our model back in memory as if we had just finished the model testing process.
It is important to note that loading unknown Pickle files into RAM can seriously compromise the security of the machine, so it is not recommended to use pickle files of unknown origin.
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