How To Use Pickle In Python

In this tutorial, we will learn how to use the pickle module in Python. Pickle is a built-in Python module that enables us to easily serialize and deserialize objects in an efficient and straightforward manner.

It’s particularly useful for storing objects in a persistent manner, such as saving them to a file. So, let’s dive into the steps on how to use pickle in Python.

Step 1: Import the Pickle Module

To start working with the pickle module, we first need to import it into our Python script. Simply add the following line at the beginning of your script:

Step 2: Create an Object to Serialize

In this example, we’ll create a sample dictionary object to demonstrate the process of serialization using pickle.

Step 3: Serialize the Object and Write to a File

To serialize the object and write it to a file, we need to open a file in binary write mode (wb) and then use the function pickle.dump() to write the serialized object to the file.

The extension .pkl is a common convention to indicate that the file contains a pickled object, but it’s not strictly required – you can use any extension you prefer.

Step 4: Read the Serialized Object From the File

Now, we’ll demonstrate how to deserialize an object from a file using pickle. First, we need to open the file in binary read mode (rb). Then, we’ll use the function pickle.load() to read the serialized object and deserialize it back into a Python object.

Step 5: Verify the Deserialized Object

Finally, let’s print the deserialized object to verify that it matches our original object.

The output should be:

{'name': 'John', 'age': 28, 'location': 'New York'}

Full Code

Here’s the complete code for the example above:


In this tutorial, we learned about the pickle module in Python and how to use it to easily serialize and deserialize Python objects. This can be particularly helpful for storing objects in a persistent manner, such as saving them to a file. Now that you know the basics of using pickle, you can start implementing it in your Python projects for efficient and straightforward object serialization and deserialization.