![]() ![]() We can find these values in the way shown in the below example.Įxample of funding the constants of the pickle module: import pickle This value may be less than the value of the highest protocol. pickle.DEFAULT_PROTOCOL: This is an integer that represents the default protocol used for pickling. This is the protocol value that is generally passed to the functions used for pickling and unpickling.Ģ. pickle.HIGHEST_PROTOCOL: This is an integer that represents the highest protocol version available. The pickle module contains the following constants:ġ. It also contains data format optimizations. It supports very large objects, more types of objects. It is introduced in Python 3.0 and works with 3.x versions. ![]() It provides efficient pickling of new-style classes. It is also compatible with earlier versions of Python. It is backward-compatible with earlier versions of Python. Original, human-readable format protocol. This module contains the below five protocol versions: Protocol Version It contains some protocols, the rules that are used to construct and deconstruct objects from/to binary format. ![]() To use this we should first import using the following command. It is the faster and simpler choice for this purpose if we do not need any human-readable format. Pickle is a module in Python for serializing and deserializing. This article mainly covers the Pickle module which is operationally the simplest way to store complex data in a special form. ![]() And the reverse process of converting the byte stream into object form is called deserialization or unpickling.įor this purpose, Python provides the following three modules: This process is also called pickling or flattening or marshaling. What is Serialization in Python?Īs said above, serializing is the process of converting the data into the form, byte stream, in which the data can be stored. Then we will also see in brief serializing and deserializing using the other modules. In this article, we will learn about Python serialization and implementing it using the pickle module. These are the situations where serializations come into use. There are many cases where you would like to store complex data in a file or share the data. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
January 2023
Categories |