A Pickle is a module in Python that is mostly used to save machine learning and neural network models in the form of binary files. This binary file is known as a pickle. The pickle files have many advantages over a raw model. Once the model is saved as a pickle file, we can easily send the model to other teammates and they can use the model to make predictions without training the model again. Another advantage of a pickle file is that the size of the pickle file is usually smaller so it becomes easy to send the saved model.
Pickle Module in Python
Pickle is an open-source library in Python. An open source means it is free to use and available to the public. We can simply install the pickle file on our system using the pip command and follow the same procedure that we follow to install any other module.
In general, a pickle module is very useful for saving a model as a binary file. We can say that a pickle module is used to serialize and deserialize objects. In Python, serialization is the conversion of an object to bytes and deserialization is the opposite where we convert a byte to an object.
ModuleNotFoundError: Pickle is not found
This is a common error you may face especially when using the pickle module for the first time. The main reason for this error is that you have not installed the module on your system. If you are using the Pickle module for the first them, then most probably you will come across this error. The error simply tells you that you have not installed the Pickle module on your system yet.
In Python, there are two types of modules. The built-in and external modules. For the built-in modules, you are not required to install them. They will be installed automatically when you install Python on your system. However, for the external modules, you need to explicitly install the modules on your system.
In order to install the Pickle module, follow the given commands.
# for Jupyter notebook
!pip install pickle
# For windows
pip install pickle
# for ubuntu
pip3 install pickleIt will take a while to complete the process. Once the module is installed, you can then easily use the module on your system.
How to save a model in Pickle in Python?
First of all, we need to import the pickle module on an editor that we are using.
import pickleRun the cell and if no error occurs, it means the pickle is imported into the system.
Now, let us assume that we already have trained a model. This model can be either a machine learning model or a neural network model. We will assume that we have stored the trained model in a variable named model.
There are now two ways to save a model in Pickle. Let us explore both of them.
pickle.dump(model, open("Savd_model.pkl", 'wb')- dump: this is a function in Pickle to save the model
- model: it is the first argument which is the trained model in our case
- open (): it required two parameters
- “Saved_model.pkl”: This is the named of the saved pickle file. You can give your own name to the model.
- “wb”: This means we want to store the model in binary. wb in Python stands for write in binary.
The second method of saving a model is:
with open('Savd_model.pkl', 'wb') as f:
pickle.dump(model, f)Again, the parameters show the exact same meaning.