1 files changed, 0 insertions, 87 deletions
diff --git a/Doc/includes/dbpickle.py b/Doc/includes/dbpickle.py
deleted file mode 100644
index b88ee87..0000000
--- a/Doc/includes/dbpickle.py
+++ /dev/null
@@ -1,87 +0,0 @@
-# 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()