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Name	Size	Permission	Date
sqlite3	[ DIR ]	drwxr-xr-x	2024-03-19 22:46
custom.c	987 B	-rw-r--r--	2024-03-19 22:46
custom2.c	3.38 KB	-rw-r--r--	2024-03-19 22:46
custom3.c	4.52 KB	-rw-r--r--	2024-03-19 22:46
custom4.c	4.81 KB	-rw-r--r--	2024-03-19 22:46
dbpickle.py	2.8 KB	-rw-r--r--	2024-03-19 22:46
email-alternative.py	1.68 KB	-rw-r--r--	2024-03-19 22:46
email-dir.py	3 KB	-rw-r--r--	2024-03-19 22:46
email-headers.py	950 B	-rw-r--r--	2024-03-19 22:46
email-mime.py	930 B	-rw-r--r--	2024-03-19 22:46
email-read-alternative.py	2.84 KB	-rw-r--r--	2024-03-19 22:46
email-simple.py	585 B	-rw-r--r--	2024-03-19 22:46
email-unpack.py	1.55 KB	-rw-r--r--	2024-03-19 22:46
minidom-example.py	1.54 KB	-rw-r--r--	2024-03-19 22:46
mp_newtype.py	1.89 KB	-rw-r--r--	2024-03-19 22:46
mp_pool.py	3.8 KB	-rw-r--r--	2024-03-19 22:46
mp_workers.py	1.55 KB	-rw-r--r--	2024-03-19 22:46
run-func.c	1.94 KB	-rw-r--r--	2024-03-19 22:46
setup.py	329 B	-rw-r--r--	2024-03-19 22:46
sublist.c	1.55 KB	-rw-r--r--	2024-03-19 22:46
test.py	3.56 KB	-rw-r--r--	2024-03-19 22:46
turtle-star.py	155 B	-rw-r--r--	2024-03-19 22:46
typestruct.h	2.42 KB	-rw-r--r--	2024-03-19 22:46
tzinfo_examples.py	5.72 KB	-rw-r--r--	2024-03-19 22:46

Rename

# Simple example presenting how persistent ID can be used to pickle
# external objects by reference.

import pickle
import sqlite3
from collections import namedtuple

# Simple class representing a record in our database.
MemoRecord = namedtuple("MemoRecord", "key, task")

class DBPickler(pickle.Pickler):

def persistent_id(self, obj):
        # Instead of pickling MemoRecord as a regular class instance, we emit a
        # persistent ID.
        if isinstance(obj, MemoRecord):
            # Here, our persistent ID is simply a tuple, containing a tag and a
            # key, which refers to a specific record in the database.
            return ("MemoRecord", obj.key)
        else:
            # If obj does not have a persistent ID, return None. This means obj
            # needs to be pickled as usual.
            return None

class DBUnpickler(pickle.Unpickler):

def __init__(self, file, connection):
        super().__init__(file)
        self.connection = connection

def persistent_load(self, pid):
        # This method is invoked whenever a persistent ID is encountered.
        # Here, pid is the tuple returned by DBPickler.
        cursor = self.connection.cursor()
        type_tag, key_id = pid
        if type_tag == "MemoRecord":
            # Fetch the referenced record from the database and return it.
            cursor.execute("SELECT * FROM memos WHERE key=?", (str(key_id),))
            key, task = cursor.fetchone()
            return MemoRecord(key, task)
        else:
            # Always raises an error if you cannot return the correct object.
            # Otherwise, the unpickler will think None is the object referenced
            # by the persistent ID.
            raise pickle.UnpicklingError("unsupported persistent object")

def main():
    import io
    import pprint

# Initialize and populate our database.
    conn = sqlite3.connect(":memory:")
    cursor = conn.cursor()
    cursor.execute("CREATE TABLE memos(key INTEGER PRIMARY KEY, task TEXT)")
    tasks = (
        'give food to fish',
        'prepare group meeting',
        'fight with a zebra',
        )
    for task in tasks:
        cursor.execute("INSERT INTO memos VALUES(NULL, ?)", (task,))

# Fetch the records to be pickled.
    cursor.execute("SELECT * FROM memos")
    memos = [MemoRecord(key, task) for key, task in cursor]
    # Save the records using our custom DBPickler.
    file = io.BytesIO()
    DBPickler(file).dump(memos)

print("Pickled records:")
    pprint.pprint(memos)

# Update a record, just for good measure.
    cursor.execute("UPDATE memos SET task='learn italian' WHERE key=1")

# Load the records from the pickle data stream.
    file.seek(0)
    memos = DBUnpickler(file, conn).load()

print("Unpickled records:")
    pprint.pprint(memos)

if __name__ == '__main__':
    main()