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# ext/serializer.py
# Copyright (C) 2005-2024 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php
# mypy: ignore-errors
"""Serializer/Deserializer objects for usage with SQLAlchemy query structures,
allowing "contextual" deserialization.
.. legacy::
The serializer extension is **legacy** and should not be used for
new development.
Any SQLAlchemy query structure, either based on sqlalchemy.sql.*
or sqlalchemy.orm.* can be used. The mappers, Tables, Columns, Session
etc. which are referenced by the structure are not persisted in serialized
form, but are instead re-associated with the query structure
when it is deserialized.
.. warning:: The serializer extension uses pickle to serialize and
deserialize objects, so the same security consideration mentioned
in the `python documentation
<https://docs.python.org/3/library/pickle.html>`_ apply.
Usage is nearly the same as that of the standard Python pickle module::
from sqlalchemy.ext.serializer import loads, dumps
metadata = MetaData(bind=some_engine)
Session = scoped_session(sessionmaker())
# ... define mappers
query = Session.query(MyClass).
filter(MyClass.somedata=='foo').order_by(MyClass.sortkey)
# pickle the query
serialized = dumps(query)
# unpickle. Pass in metadata + scoped_session
query2 = loads(serialized, metadata, Session)
print query2.all()
Similar restrictions as when using raw pickle apply; mapped classes must be
themselves be pickleable, meaning they are importable from a module-level
namespace.
The serializer module is only appropriate for query structures. It is not
needed for:
* instances of user-defined classes. These contain no references to engines,
sessions or expression constructs in the typical case and can be serialized
directly.
* Table metadata that is to be loaded entirely from the serialized structure
(i.e. is not already declared in the application). Regular
pickle.loads()/dumps() can be used to fully dump any ``MetaData`` object,
typically one which was reflected from an existing database at some previous
point in time. The serializer module is specifically for the opposite case,
where the Table metadata is already present in memory.
"""
from io import BytesIO
import pickle
import re
from .. import Column
from .. import Table
from ..engine import Engine
from ..orm import class_mapper
from ..orm.interfaces import MapperProperty
from ..orm.mapper import Mapper
from ..orm.session import Session
from ..util import b64decode
from ..util import b64encode
__all__ = ["Serializer", "Deserializer", "dumps", "loads"]
class Serializer(pickle.Pickler):
def persistent_id(self, obj):
# print "serializing:", repr(obj)
if isinstance(obj, Mapper) and not obj.non_primary:
id_ = "mapper:" + b64encode(pickle.dumps(obj.class_))
elif isinstance(obj, MapperProperty) and not obj.parent.non_primary:
id_ = (
"mapperprop:"
+ b64encode(pickle.dumps(obj.parent.class_))
+ ":"
+ obj.key
)
elif isinstance(obj, Table):
if "parententity" in obj._annotations:
id_ = "mapper_selectable:" + b64encode(
pickle.dumps(obj._annotations["parententity"].class_)
)
else:
id_ = f"table:{obj.key}"
elif isinstance(obj, Column) and isinstance(obj.table, Table):
id_ = f"column:{obj.table.key}:{obj.key}"
elif isinstance(obj, Session):
id_ = "session:"
elif isinstance(obj, Engine):
id_ = "engine:"
else:
return None
return id_
our_ids = re.compile(
r"(mapperprop|mapper|mapper_selectable|table|column|"
r"session|attribute|engine):(.*)"
)
class Deserializer(pickle.Unpickler):
def __init__(self, file, metadata=None, scoped_session=None, engine=None):
super().__init__(file)
self.metadata = metadata
self.scoped_session = scoped_session
self.engine = engine
def get_engine(self):
if self.engine:
return self.engine
elif self.scoped_session and self.scoped_session().bind:
return self.scoped_session().bind
else:
return None
def persistent_load(self, id_):
m = our_ids.match(str(id_))
if not m:
return None
else:
type_, args = m.group(1, 2)
if type_ == "attribute":
key, clsarg = args.split(":")
cls = pickle.loads(b64decode(clsarg))
return getattr(cls, key)
elif type_ == "mapper":
cls = pickle.loads(b64decode(args))
return class_mapper(cls)
elif type_ == "mapper_selectable":
cls = pickle.loads(b64decode(args))
return class_mapper(cls).__clause_element__()
elif type_ == "mapperprop":
mapper, keyname = args.split(":")
cls = pickle.loads(b64decode(mapper))
return class_mapper(cls).attrs[keyname]
elif type_ == "table":
return self.metadata.tables[args]
elif type_ == "column":
table, colname = args.split(":")
return self.metadata.tables[table].c[colname]
elif type_ == "session":
return self.scoped_session()
elif type_ == "engine":
return self.get_engine()
else:
raise Exception("Unknown token: %s" % type_)
def dumps(obj, protocol=pickle.HIGHEST_PROTOCOL):
buf = BytesIO()
pickler = Serializer(buf, protocol)
pickler.dump(obj)
return buf.getvalue()
def loads(data, metadata=None, scoped_session=None, engine=None):
buf = BytesIO(data)
unpickler = Deserializer(buf, metadata, scoped_session, engine)
return unpickler.load()