python开发_pickle

 1 # Simple example presenting how persistent ID can be used to pickle
 2 # external objects by reference.
 3 
 4 import pickle
 5 import sqlite3
 6 from collections import namedtuple
 7 
 8 # Simple class representing a record in our database.
 9 MemoRecord = namedtuple("MemoRecord", "key, task")
10 
11 class DBPickler(pickle.Pickler):
12 
13     def persistent_id(self, obj):
14         # Instead of pickling MemoRecord as a regular class instance, we emit a
15         # persistent ID.
16         if isinstance(obj, MemoRecord):
17             # Here, our persistent ID is simply a tuple, containing a tag and a
18             # key, which refers to a specific record in the database.
19             return ("MemoRecord", obj.key)
20         else:
21             # If obj does not have a persistent ID, return None. This means obj
22             # needs to be pickled as usual.
23             return None
24 
25 
26 class DBUnpickler(pickle.Unpickler):
27 
28     def __init__(self, file, connection):
29         super().__init__(file)
30         self.connection = connection
31 
32     def persistent_load(self, pid):
33         # This method is invoked whenever a persistent ID is encountered.
34         # Here, pid is the tuple returned by DBPickler.
35         cursor = self.connection.cursor()
36         type_tag, key_id = pid
37         if type_tag == "MemoRecord":
38             # Fetch the referenced record from the database and return it.
39             cursor.execute("SELECT * FROM memos WHERE key=?", (str(key_id),))
40             key, task = cursor.fetchone()
41             return MemoRecord(key, task)
42         else:
43             # Always raises an error if you cannot return the correct object.
44             # Otherwise, the unpickler will think None is the object referenced
45             # by the persistent ID.
46             raise pickle.UnpicklingError("unsupported persistent object")
47 
48 
49 def main():
50     import io
51     import pprint
52 
53     # Initialize and populate our database.
54     conn = sqlite3.connect(":memory:")
55     cursor = conn.cursor()
56     cursor.execute("CREATE TABLE memos(key INTEGER PRIMARY KEY, task TEXT)")
57     tasks = (
58         'give food to fish',
59         'prepare group meeting',
60         'fight with a zebra',
61         )
62     for task in tasks:
63         cursor.execute("INSERT INTO memos VALUES(NULL, ?)", (task,))
64 
65     # Fetch the records to be pickled.
66     cursor.execute("SELECT * FROM memos")
67     memos = [MemoRecord(key, task) for key, task in cursor]
68     # Save the records using our custom DBPickler.
69     file = io.BytesIO()
70     DBPickler(file).dump(memos)
71 
72     print("Pickled records:")
73     pprint.pprint(memos)
74 
75     # Update a record, just for good measure.
76     cursor.execute("UPDATE memos SET task='learn italian' WHERE key=1")
77 
78     # Load the records from the pickle data stream.
79     file.seek(0)
80     memos = DBUnpickler(file, conn).load()
81 
82     print("Unpickled records:")
83     pprint.pprint(memos)
84 
85 
86 if __name__ == '__main__':
87     main()