mirror of
https://github.com/psycopg/psycopg2.git
synced 2024-11-23 01:16:34 +03:00
88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
"""psycopg 1.1.x compatibility module
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This module uses the new style connection and cursor types to build a psycopg
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1.1.1.x compatibility layer. It should be considered a temporary hack to run
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old code while porting to psycopg 2. Import it as follows::
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from psycopg2 import psycopg1 as psycopg
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"""
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# psycopg/psycopg1.py - psycopg 1.1.x compatibility module
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#
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# Copyright (C) 2003-2004 Federico Di Gregorio <fog@debian.org>
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 2, or (at your option) any later
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# version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTIBILITY
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# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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# for more details.
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import _psycopg as _2psycopg
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from psycopg2.extensions import cursor as _2cursor
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from psycopg2.extensions import connection as _2connection
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from psycopg2 import *
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del connect
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def connect(*args, **kwargs):
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"""connect(dsn, ...) -> new psycopg 1.1.x compatible connection object"""
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kwargs['connection_factory'] = connection
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conn = _2psycopg.connect(*args, **kwargs)
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conn.set_isolation_level(2)
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return conn
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class connection(_2connection):
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"""psycopg 1.1.x connection."""
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def cursor(self):
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"""cursor() -> new psycopg 1.1.x compatible cursor object"""
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return _2connection.cursor(self, cursor_factory=cursor)
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def autocommit(self, on_off=1):
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"""autocommit(on_off=1) -> switch autocommit on (1) or off (0)"""
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if on_off > 0:
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self.set_isolation_level(0)
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else:
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self.set_isolation_level(2)
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class cursor(_2cursor):
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"""psycopg 1.1.x cursor.
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Note that this cursor implements the exact procedure used by psycopg 1 to
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build dictionaries out of result rows. The DictCursor in the
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psycopg.extras modules implements a much better and faster algorithm.
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"""
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def __build_dict(self, row):
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res = {}
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for i in range(len(self.description)):
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res[self.description[i][0]] = row[i]
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return res
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def dictfetchone(self):
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row = _2cursor.fetchone(self)
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if row:
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return self.__build_dict(row)
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else:
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return row
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def dictfetchmany(self, size):
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res = []
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rows = _2cursor.fetchmany(self, size)
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for row in rows:
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res.append(self.__build_dict(row))
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return res
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def dictfetchall(self):
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res = []
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rows = _2cursor.fetchall(self)
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for row in rows:
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res.append(self.__build_dict(row))
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return res
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