{"id":324,"date":"2023-07-26T11:49:08","date_gmt":"2023-07-26T11:49:08","guid":{"rendered":"http:\/\/python.garden\/?p=324"},"modified":"2023-08-07T16:17:23","modified_gmt":"2023-08-07T16:17:23","slug":"getting-started-with-pythons-pickle","status":"publish","type":"post","link":"https:\/\/python.garden\/index.php\/2023\/07\/26\/getting-started-with-pythons-pickle\/","title":{"rendered":"Getting Started with Python’s Pickle"},"content":{"rendered":"\n

The pickle module in Python is used for serializing and de-serializing Python object structures, also known as marshaling or flattening. Serialization is the process of converting an object’s state to a byte stream, and the opposite operation, extracting the object from the byte stream, is called de-serialization.<\/p>\n\n\n\n

    \n
  1. Importing the module<\/strong>: Like any other Python module, before using pickle<\/code>, you first need to import it.<\/li>\n<\/ol>\n\n\n\n
    import pickle<\/pre><\/div>\n\n\n\n
      \n
    1. Pickling<\/strong>: The process of serialization is called pickling. The pickle.dump()<\/code> function is used to serialize an object hierarchy. It takes two arguments: the object you want to pickle and the file object in which you want to store the pickled object.<\/li>\n<\/ol>\n\n\n\n
      # create an example dictionary\ndata = {"cat": "meow", "dog": "bark"}\n\n# open a file to write binary\nwith open("pets.pkl", "wb") as file:\n    pickle.dump(data, file)<\/pre><\/div>\n\n\n\n
      In the above code, we created a dictionary and pickled it into a file called “pets.pkl”. The “wb” mode stands for “write binary”.<\/p>\n\n\n\n
        \n
      1. Unpickling<\/strong>: The process of deserialization is called unpickling. The pickle.load()<\/code> function is used to unpickle the object.<\/li>\n<\/ol>\n\n\n\n
        # open the file in read binary mode\nwith open("pets.pkl", "rb") as file:\n    loaded_data = pickle.load(file)\nprint(loaded_data)<\/pre><\/div>\n\n\n\n
        When you run the above code, it will display the original dictionary. The “rb” stands for “read binary”.<\/p>\n\n\n\n
          \n
        1. pickle.dumps() and pickle.loads()<\/strong>: These functions are used to pickle and unpickle data, but instead of writing or reading from a file, they simply return the pickled data as a bytes object or load from a bytes object.<\/li>\n<\/ol>\n\n\n\n
          # Pickling to a bytes object\npickled_data = pickle.dumps(data)\nprint(pickled_data)  # This will print a bytes object\n\n# Unpickling from a bytes object\nunpickled_data = pickle.loads(pickled_data)\nprint(unpickled_data)  # This will print the original dictionary<\/pre><\/div>\n\n\n\n
          Some important points:<\/p>\n\n\n\n
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          • The pickle<\/code> module is not secure against erroneous or maliciously constructed data. Never unpickle data received from an untrusted or unauthenticated source.<\/li>\n\n\n\n
          • Not all Python data types can be pickled. Functions, classes, and methods cannot be pickled, so you cannot pickle the entire state of your Python program.<\/li>\n<\/ul>\n\n\n\n
            Despite these limitations, pickle<\/code> is very useful for storing and retrieving complex data in Python.<\/p>\n","protected":false},"excerpt":{"rendered":"
            The pickle module in Python is used for serializing and de-serializing Python object structures, also known as marshaling or flattening. Serialization is the process of converting an object’s state to…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[214,213],"tags":[],"class_list":["post-324","post","type-post","status-publish","format-standard","hentry","category-beginners-guide","category-python"],"featured_image_src":null,"author_info":{"display_name":"shababdoo","author_link":"https:\/\/python.garden\/index.php\/author\/shababdoo\/"},"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/posts\/324","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/comments?post=324"}],"version-history":[{"count":0,"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/posts\/324\/revisions"}],"wp:attachment":[{"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/media?parent=324"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/categories?post=324"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/python.garden\/index.php\/wp-json\/wp\/v2\/tags?post=324"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}