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# ext/serializer.py # Copyright (C) 2005-2025 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()
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