What are Pickling and Unpickling?
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Pickling
Pickling and unpickling are terms commonly used in the context of Python programming and refer to the process of serializing and deserializing objects. In simple terms, pickling is the process of converting a Python object into a byte stream, while unpickling is the process of converting the byte stream back into a Python object.
Pickling is useful when you want to store or transmit an object, such as when saving it to a file or sending it over a network. By pickling an object, you can convert it into a format that can be easily stored or transmitted, and then retrieve it later by unpickling it.
The pickled byte stream contains all the necessary information about the object’s data and the Python instructions needed to reconstruct the object. This includes information about the object’s attributes, methods, and their values. Essentially, pickling captures the object’s state at a specific point in time.
Unpickling
Unpickling, on the other hand, takes the pickled byte stream and reconstructs the original object, including its attributes and methods, in memory. This allows you to restore the object to its previous state.
Python provides the pickle
module, which offers functions for pickling and unpickling objects. You can use the pickle.dump()
function to pickle an object to a file or pickle.dumps()
to obtain the pickled byte stream as a string. To unpickle an object, you can use pickle.load()
to read from a file or pickle.loads()
to load from a string.
It’s important to note that pickling and unpickling are primarily used within Python or between Python processes, as the pickled format is specific to Python. Additionally, when unpickling, it’s crucial to ensure the source of the pickled data is trusted, as maliciously crafted pickled objects could potentially execute arbitrary code.
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Author
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Naveen Pandey has more than 2 years of experience in data science and machine learning. He is an experienced Machine Learning Engineer with a strong background in data analysis, natural language processing, and machine learning. Holding a Bachelor of Science in Information Technology from Sikkim Manipal University, he excels in leveraging cutting-edge technologies such as Large Language Models (LLMs), TensorFlow, PyTorch, and Hugging Face to develop innovative solutions.
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