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https://github.com/janeczku/calibre-web
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172 lines
5.7 KiB
Python
172 lines
5.7 KiB
Python
# ext/serializer.py
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# Copyright (C) 2005-2013 the SQLAlchemy authors and contributors <see AUTHORS file>
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#
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# This module is part of SQLAlchemy and is released under
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# the MIT License: http://www.opensource.org/licenses/mit-license.php
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"""Serializer/Deserializer objects for usage with SQLAlchemy query structures,
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allowing "contextual" deserialization.
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Any SQLAlchemy query structure, either based on sqlalchemy.sql.*
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or sqlalchemy.orm.* can be used. The mappers, Tables, Columns, Session
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etc. which are referenced by the structure are not persisted in serialized
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form, but are instead re-associated with the query structure
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when it is deserialized.
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Usage is nearly the same as that of the standard Python pickle module::
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from sqlalchemy.ext.serializer import loads, dumps
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metadata = MetaData(bind=some_engine)
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Session = scoped_session(sessionmaker())
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# ... define mappers
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query = Session.query(MyClass).filter(MyClass.somedata=='foo').order_by(MyClass.sortkey)
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# pickle the query
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serialized = dumps(query)
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# unpickle. Pass in metadata + scoped_session
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query2 = loads(serialized, metadata, Session)
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print query2.all()
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Similar restrictions as when using raw pickle apply; mapped classes must be
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themselves be pickleable, meaning they are importable from a module-level
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namespace.
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The serializer module is only appropriate for query structures. It is not
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needed for:
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* instances of user-defined classes. These contain no references to engines,
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sessions or expression constructs in the typical case and can be serialized
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directly.
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* Table metadata that is to be loaded entirely from the serialized structure
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(i.e. is not already declared in the application). Regular
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pickle.loads()/dumps() can be used to fully dump any ``MetaData`` object,
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typically one which was reflected from an existing database at some previous
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point in time. The serializer module is specifically for the opposite case,
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where the Table metadata is already present in memory.
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"""
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from ..orm import class_mapper
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from ..orm.session import Session
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from ..orm.mapper import Mapper
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from ..orm.interfaces import MapperProperty
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from ..orm.attributes import QueryableAttribute
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from .. import Table, Column
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from ..engine import Engine
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from ..util import pickle
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import re
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import base64
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# Py3K
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#from io import BytesIO as byte_buffer
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# Py2K
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from cStringIO import StringIO as byte_buffer
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# end Py2K
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# Py3K
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#def b64encode(x):
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# return base64.b64encode(x).decode('ascii')
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#def b64decode(x):
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# return base64.b64decode(x.encode('ascii'))
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# Py2K
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b64encode = base64.b64encode
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b64decode = base64.b64decode
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# end Py2K
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__all__ = ['Serializer', 'Deserializer', 'dumps', 'loads']
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def Serializer(*args, **kw):
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pickler = pickle.Pickler(*args, **kw)
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def persistent_id(obj):
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#print "serializing:", repr(obj)
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if isinstance(obj, QueryableAttribute):
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cls = obj.impl.class_
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key = obj.impl.key
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id = "attribute:" + key + ":" + b64encode(pickle.dumps(cls))
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elif isinstance(obj, Mapper) and not obj.non_primary:
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id = "mapper:" + b64encode(pickle.dumps(obj.class_))
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elif isinstance(obj, MapperProperty) and not obj.parent.non_primary:
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id = "mapperprop:" + b64encode(pickle.dumps(obj.parent.class_)) + \
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":" + obj.key
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elif isinstance(obj, Table):
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id = "table:" + str(obj)
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elif isinstance(obj, Column) and isinstance(obj.table, Table):
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id = "column:" + str(obj.table) + ":" + obj.key
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elif isinstance(obj, Session):
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id = "session:"
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elif isinstance(obj, Engine):
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id = "engine:"
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else:
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return None
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return id
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pickler.persistent_id = persistent_id
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return pickler
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our_ids = re.compile(
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r'(mapperprop|mapper|table|column|session|attribute|engine):(.*)')
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def Deserializer(file, metadata=None, scoped_session=None, engine=None):
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unpickler = pickle.Unpickler(file)
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def get_engine():
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if engine:
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return engine
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elif scoped_session and scoped_session().bind:
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return scoped_session().bind
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elif metadata and metadata.bind:
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return metadata.bind
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else:
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return None
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def persistent_load(id):
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m = our_ids.match(str(id))
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if not m:
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return None
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else:
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type_, args = m.group(1, 2)
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if type_ == 'attribute':
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key, clsarg = args.split(":")
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cls = pickle.loads(b64decode(clsarg))
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return getattr(cls, key)
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elif type_ == "mapper":
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cls = pickle.loads(b64decode(args))
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return class_mapper(cls)
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elif type_ == "mapperprop":
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mapper, keyname = args.split(':')
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cls = pickle.loads(b64decode(mapper))
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return class_mapper(cls).attrs[keyname]
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elif type_ == "table":
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return metadata.tables[args]
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elif type_ == "column":
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table, colname = args.split(':')
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return metadata.tables[table].c[colname]
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elif type_ == "session":
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return scoped_session()
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elif type_ == "engine":
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return get_engine()
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else:
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raise Exception("Unknown token: %s" % type_)
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unpickler.persistent_load = persistent_load
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return unpickler
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def dumps(obj, protocol=0):
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buf = byte_buffer()
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pickler = Serializer(buf, protocol)
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pickler.dump(obj)
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return buf.getvalue()
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def loads(data, metadata=None, scoped_session=None, engine=None):
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buf = byte_buffer(data)
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unpickler = Deserializer(buf, metadata, scoped_session, engine)
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return unpickler.load()
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