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87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
# Simple example presenting how persistent ID can be used to pickle
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# external objects by reference.
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import pickle
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import sqlite3
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from collections import namedtuple
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# Simple class representing a record in our database.
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MemoRecord = namedtuple("MemoRecord", "key, task")
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class DBPickler(pickle.Pickler):
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def persistent_id(self, obj):
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# Instead of pickling MemoRecord as a regular class instance, we emit a
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# persistent ID.
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if isinstance(obj, MemoRecord):
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# Here, our persistent ID is simply a tuple, containing a tag and a
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# key, which refers to a specific record in the database.
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return ("MemoRecord", obj.key)
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else:
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# If obj does not have a persistent ID, return None. This means obj
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# needs to be pickled as usual.
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return None
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class DBUnpickler(pickle.Unpickler):
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def __init__(self, file, connection):
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super().__init__(file)
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self.connection = connection
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def persistent_load(self, pid):
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# This method is invoked whenever a persistent ID is encountered.
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# Here, pid is the tuple returned by DBPickler.
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cursor = self.connection.cursor()
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type_tag, key_id = pid
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if type_tag == "MemoRecord":
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# Fetch the referenced record from the database and return it.
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cursor.execute("SELECT * FROM memos WHERE key=?", (str(key_id),))
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key, task = cursor.fetchone()
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return MemoRecord(key, task)
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else:
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# Always raises an error if you cannot return the correct object.
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# Otherwise, the unpickler will think None is the object referenced
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# by the persistent ID.
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raise pickle.UnpicklingError("unsupported persistent object")
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def main():
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import io
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import pprint
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# Initialize and populate our database.
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conn = sqlite3.connect(":memory:")
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cursor = conn.cursor()
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cursor.execute("CREATE TABLE memos(key INTEGER PRIMARY KEY, task TEXT)")
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tasks = (
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'give food to fish',
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'prepare group meeting',
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'fight with a zebra',
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)
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for task in tasks:
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cursor.execute("INSERT INTO memos VALUES(NULL, ?)", (task,))
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# Fetch the records to be pickled.
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cursor.execute("SELECT * FROM memos")
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memos = [MemoRecord(key, task) for key, task in cursor]
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# Save the records using our custom DBPickler.
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file = io.BytesIO()
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DBPickler(file).dump(memos)
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print("Pickled records:")
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pprint.pprint(memos)
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# Update a record, just for good measure.
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cursor.execute("UPDATE memos SET task='learn italian' WHERE key=1")
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# Load the records from the pickle data stream.
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file.seek(0)
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memos = DBUnpickler(file, conn).load()
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print("Unpickled records:")
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pprint.pprint(memos)
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if __name__ == '__main__':
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main()
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