How to implement persistent objects in Python?

To implement persistent objects in Python, use the following libraries.

• On the shelves
• Pickle

Shelved module

"Shelf" is a persistent, dictionary-like object. The difference with a "dbm" database is that the values ​​(not keys!) in a shelf can be essentially any Python object - anything the pickle module can handle. This includes most class instances, recursive data types, and objects that contain a large number of shared sub-objects.

It has some key methods -

• shelve.open() - Open a persistent dictionary. The filename specified is the base filename of the underlying database. As a side effect, an extension may be added to the file name and multiple files may be created. By default, the underlying database file is opened for reading and writing.

• shelve.sync() − If shelf is turned on with writeback set to True, all entries in the cache are written back. If feasible, the cache is also flushed and the persistent dictionary is synchronized with the data on disk. This method is automatically called when the shelf is closed using close().

• shelve.close() − Synchronize and close the persistent dictionary object.

pickle module

The pickle module implements a binary protocol for serializing and deserializing Python objects structure.

• Pickling is the process of converting Python object hierarchies into bytes flow. To serialize an object hierarchy, simply call the dumps() function.

• Unpickling is the reverse operation. Parsed from a binary file or byte stream like a bytes object Convert it back to the object hierarchy. To deserialize the data stream, you call the loads() function Function.

Pickle module function

The following are the functions provided by the pickle module.

• pickle.dump() - Writes the pickle representation of an object into an open file object file.

• pickle.dumps() − Returns the pickle representation of the object as a bytes object instead of Write it to a file.

• pickle.load() - Reads the pickled representation of an object from an open file object file.

• pickle.loads() - Returns a reconstructed object hierarchy of pickled representations of the data

of the object

Example

First, import the pickle module -

import pickle

We have created the following inputs for pickling.

my_data = { 'BMW', 'Audi', 'Toyota', 'Benz'}

demo.pickle file has been created. This same .pickle file is pickled with the list above.

with open("demo.pickle","wb") as file_handle:
   pickle.dump(my_data, file_handle, pickle.HIGHEST_PROTOCOL)

Now, unpickle the above pickled file and get the input values.

with open("demo.pickle","rb") as file_handle:
   res = pickle.load(file_handle)
   print(res_data)

Now let's look at the complete example.

import pickle

# Input Data
my_data = { 'BMW', 'Audi', 'Toyota', 'Benz'}

# Pickle the input
with open("demo.pickle","wb") as file_handle:
   pickle.dump(my_data, file_handle, pickle.HIGHEST_PROTOCOL)

# Unpickle the above pickled file
with open("demo.pickle","rb") as file_handle:
   res = pickle.load(file_handle)
   print(my_data) # display the output

Output

set(['Benz', 'Toyota', 'BMW', 'Audi'])

The above is the detailed content of How to implement persistent objects in Python?. For more information, please follow other related articles on the PHP Chinese website!