曾与蒿藜同雨露，한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.かつては雑草やヨモギと共に雨や露を分かち合っていたが、今では松やヒノキと共に霜や雪に耐えている。曾与蒿藜同雨露，Once sharing rain and dew with weeds and wormwood, now enduring frost and snow with pines and cypresses.终随松柏到冰霜.曾与蒿藜同雨露한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.，终随松柏到冰霜.譖ｾ荳手珍阯懷酔髮ｨ髴ｲ�檎ｻ磯囂譚ｾ譟丞芦蜀ｰ髴�曾与蒿藜同雨露，鏇句笌钂胯棞鍚岄洦闇诧紝缁堥殢鏉炬煆鍒板啺闇�终随松柏到冰霜.曾与蒿藜同雨露，한때 잡초와 쑥과 함께 비와 이슬을 나누던 곳이 이제는 소나무와 삼나무와 함께 서리와 눈을 견뎌내고 있다.终随松柏到冰霜.曾与蒿藜同雨露，终随松柏到冰霜. rahbord-ins.ir - GrazzMean-Shell
shell bypass 403

GrazzMean-Shell Shell

: /opt/alt/python37/lib/python3.7/site-packages/chardet/ [ drwxr-xr-x ]
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upload mass deface mass delete console

name : jpcntx.py 
######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Communicator client code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights Reserved.
#
# Contributor(s):
#   Mark Pilgrim - port to Python
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
# 02110-1301  USA
######################### END LICENSE BLOCK #########################


# This is hiragana 2-char sequence table, the number in each cell represents its frequency category
jp2CharContext = (
(0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1),
(2,4,0,4,0,3,0,4,0,3,4,4,4,2,4,3,3,4,3,2,3,3,4,2,3,3,3,2,4,1,4,3,3,1,5,4,3,4,3,4,3,5,3,0,3,5,4,2,0,3,1,0,3,3,0,3,3,0,1,1,0,4,3,0,3,3,0,4,0,2,0,3,5,5,5,5,4,0,4,1,0,3,4),
(0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2),
(0,4,0,5,0,5,0,4,0,4,5,4,4,3,5,3,5,1,5,3,4,3,4,4,3,4,3,3,4,3,5,4,4,3,5,5,3,5,5,5,3,5,5,3,4,5,5,3,1,3,2,0,3,4,0,4,2,0,4,2,1,5,3,2,3,5,0,4,0,2,0,5,4,4,5,4,5,0,4,0,0,4,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,4,0,3,0,3,0,4,5,4,3,3,3,3,4,3,5,4,4,3,5,4,4,3,4,3,4,4,4,4,5,3,4,4,3,4,5,5,4,5,5,1,4,5,4,3,0,3,3,1,3,3,0,4,4,0,3,3,1,5,3,3,3,5,0,4,0,3,0,4,4,3,4,3,3,0,4,1,1,3,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,4,0,3,0,3,0,4,0,3,4,4,3,2,2,1,2,1,3,1,3,3,3,3,3,4,3,1,3,3,5,3,3,0,4,3,0,5,4,3,3,5,4,4,3,4,4,5,0,1,2,0,1,2,0,2,2,0,1,0,0,5,2,2,1,4,0,3,0,1,0,4,4,3,5,4,3,0,2,1,0,4,3),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,5,0,4,0,2,1,4,4,2,4,1,4,2,4,2,4,3,3,3,4,3,3,3,3,1,4,2,3,3,3,1,4,4,1,1,1,4,3,3,2,0,2,4,3,2,0,3,3,0,3,1,1,0,0,0,3,3,0,4,2,2,3,4,0,4,0,3,0,4,4,5,3,4,4,0,3,0,0,1,4),
(1,4,0,4,0,4,0,4,0,3,5,4,4,3,4,3,5,4,3,3,4,3,5,4,4,4,4,3,4,2,4,3,3,1,5,4,3,2,4,5,4,5,5,4,4,5,4,4,0,3,2,2,3,3,0,4,3,1,3,2,1,4,3,3,4,5,0,3,0,2,0,4,5,5,4,5,4,0,4,0,0,5,4),
(0,5,0,5,0,4,0,3,0,4,4,3,4,3,3,3,4,0,4,4,4,3,4,3,4,3,3,1,4,2,4,3,4,0,5,4,1,4,5,4,4,5,3,2,4,3,4,3,2,4,1,3,3,3,2,3,2,0,4,3,3,4,3,3,3,4,0,4,0,3,0,4,5,4,4,4,3,0,4,1,0,1,3),
(0,3,1,4,0,3,0,2,0,3,4,4,3,1,4,2,3,3,4,3,4,3,4,3,4,4,3,2,3,1,5,4,4,1,4,4,3,5,4,4,3,5,5,4,3,4,4,3,1,2,3,1,2,2,0,3,2,0,3,1,0,5,3,3,3,4,3,3,3,3,4,4,4,4,5,4,2,0,3,3,2,4,3),
(0,2,0,3,0,1,0,1,0,0,3,2,0,0,2,0,1,0,2,1,3,3,3,1,2,3,1,0,1,0,4,2,1,1,3,3,0,4,3,3,1,4,3,3,0,3,3,2,0,0,0,0,1,0,0,2,0,0,0,0,0,4,1,0,2,3,2,2,2,1,3,3,3,4,4,3,2,0,3,1,0,3,3),
(0,4,0,4,0,3,0,3,0,4,4,4,3,3,3,3,3,3,4,3,4,2,4,3,4,3,3,2,4,3,4,5,4,1,4,5,3,5,4,5,3,5,4,0,3,5,5,3,1,3,3,2,2,3,0,3,4,1,3,3,2,4,3,3,3,4,0,4,0,3,0,4,5,4,4,5,3,0,4,1,0,3,4),
(0,2,0,3,0,3,0,0,0,2,2,2,1,0,1,0,0,0,3,0,3,0,3,0,1,3,1,0,3,1,3,3,3,1,3,3,3,0,1,3,1,3,4,0,0,3,1,1,0,3,2,0,0,0,0,1,3,0,1,0,0,3,3,2,0,3,0,0,0,0,0,3,4,3,4,3,3,0,3,0,0,2,3),
(2,3,0,3,0,2,0,1,0,3,3,4,3,1,3,1,1,1,3,1,4,3,4,3,3,3,0,0,3,1,5,4,3,1,4,3,2,5,5,4,4,4,4,3,3,4,4,4,0,2,1,1,3,2,0,1,2,0,0,1,0,4,1,3,3,3,0,3,0,1,0,4,4,4,5,5,3,0,2,0,0,4,4),
(0,2,0,1,0,3,1,3,0,2,3,3,3,0,3,1,0,0,3,0,3,2,3,1,3,2,1,1,0,0,4,2,1,0,2,3,1,4,3,2,0,4,4,3,1,3,1,3,0,1,0,0,1,0,0,0,1,0,0,0,0,4,1,1,1,2,0,3,0,0,0,3,4,2,4,3,2,0,1,0,0,3,3),
(0,1,0,4,0,5,0,4,0,2,4,4,2,3,3,2,3,3,5,3,3,3,4,3,4,2,3,0,4,3,3,3,4,1,4,3,2,1,5,5,3,4,5,1,3,5,4,2,0,3,3,0,1,3,0,4,2,0,1,3,1,4,3,3,3,3,0,3,0,1,0,3,4,4,4,5,5,0,3,0,1,4,5),
(0,2,0,3,0,3,0,0,0,2,3,1,3,0,4,0,1,1,3,0,3,4,3,2,3,1,0,3,3,2,3,1,3,0,2,3,0,2,1,4,1,2,2,0,0,3,3,0,0,2,0,0,0,1,0,0,0,0,2,2,0,3,2,1,3,3,0,2,0,2,0,0,3,3,1,2,4,0,3,0,2,2,3),
(2,4,0,5,0,4,0,4,0,2,4,4,4,3,4,3,3,3,1,2,4,3,4,3,4,4,5,0,3,3,3,3,2,0,4,3,1,4,3,4,1,4,4,3,3,4,4,3,1,2,3,0,4,2,0,4,1,0,3,3,0,4,3,3,3,4,0,4,0,2,0,3,5,3,4,5,2,0,3,0,0,4,5),
(0,3,0,4,0,1,0,1,0,1,3,2,2,1,3,0,3,0,2,0,2,0,3,0,2,0,0,0,1,0,1,1,0,0,3,1,0,0,0,4,0,3,1,0,2,1,3,0,0,0,0,0,0,3,0,0,0,0,0,0,0,4,2,2,3,1,0,3,0,0,0,1,4,4,4,3,0,0,4,0,0,1,4),
(1,4,1,5,0,3,0,3,0,4,5,4,4,3,5,3,3,4,4,3,4,1,3,3,3,3,2,1,4,1,5,4,3,1,4,4,3,5,4,4,3,5,4,3,3,4,4,4,0,3,3,1,2,3,0,3,1,0,3,3,0,5,4,4,4,4,4,4,3,3,5,4,4,3,3,5,4,0,3,2,0,4,4),
(0,2,0,3,0,1,0,0,0,1,3,3,3,2,4,1,3,0,3,1,3,0,2,2,1,1,0,0,2,0,4,3,1,0,4,3,0,4,4,4,1,4,3,1,1,3,3,1,0,2,0,0,1,3,0,0,0,0,2,0,0,4,3,2,4,3,5,4,3,3,3,4,3,3,4,3,3,0,2,1,0,3,3),
(0,2,0,4,0,3,0,2,0,2,5,5,3,4,4,4,4,1,4,3,3,0,4,3,4,3,1,3,3,2,4,3,0,3,4,3,0,3,4,4,2,4,4,0,4,5,3,3,2,2,1,1,1,2,0,1,5,0,3,3,2,4,3,3,3,4,0,3,0,2,0,4,4,3,5,5,0,0,3,0,2,3,3),
(0,3,0,4,0,3,0,1,0,3,4,3,3,1,3,3,3,0,3,1,3,0,4,3,3,1,1,0,3,0,3,3,0,0,4,4,0,1,5,4,3,3,5,0,3,3,4,3,0,2,0,1,1,1,0,1,3,0,1,2,1,3,3,2,3,3,0,3,0,1,0,1,3,3,4,4,1,0,1,2,2,1,3),
(0,1,0,4,0,4,0,3,0,1,3,3,3,2,3,1,1,0,3,0,3,3,4,3,2,4,2,0,1,0,4,3,2,0,4,3,0,5,3,3,2,4,4,4,3,3,3,4,0,1,3,0,0,1,0,0,1,0,0,0,0,4,2,3,3,3,0,3,0,0,0,4,4,4,5,3,2,0,3,3,0,3,5),
(0,2,0,3,0,0,0,3,0,1,3,0,2,0,0,0,1,0,3,1,1,3,3,0,0,3,0,0,3,0,2,3,1,0,3,1,0,3,3,2,0,4,2,2,0,2,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,2,1,2,0,1,0,1,0,0,0,1,3,1,2,0,0,0,1,0,0,1,4),
(0,3,0,3,0,5,0,1,0,2,4,3,1,3,3,2,1,1,5,2,1,0,5,1,2,0,0,0,3,3,2,2,3,2,4,3,0,0,3,3,1,3,3,0,2,5,3,4,0,3,3,0,1,2,0,2,2,0,3,2,0,2,2,3,3,3,0,2,0,1,0,3,4,4,2,5,4,0,3,0,0,3,5),
(0,3,0,3,0,3,0,1,0,3,3,3,3,0,3,0,2,0,2,1,1,0,2,0,1,0,0,0,2,1,0,0,1,0,3,2,0,0,3,3,1,2,3,1,0,3,3,0,0,1,0,0,0,0,0,2,0,0,0,0,0,2,3,1,2,3,0,3,0,1,0,3,2,1,0,4,3,0,1,1,0,3,3),
(0,4,0,5,0,3,0,3,0,4,5,5,4,3,5,3,4,3,5,3,3,2,5,3,4,4,4,3,4,3,4,5,5,3,4,4,3,4,4,5,4,4,4,3,4,5,5,4,2,3,4,2,3,4,0,3,3,1,4,3,2,4,3,3,5,5,0,3,0,3,0,5,5,5,5,4,4,0,4,0,1,4,4),
(0,4,0,4,0,3,0,3,0,3,5,4,4,2,3,2,5,1,3,2,5,1,4,2,3,2,3,3,4,3,3,3,3,2,5,4,1,3,3,5,3,4,4,0,4,4,3,1,1,3,1,0,2,3,0,2,3,0,3,0,0,4,3,1,3,4,0,3,0,2,0,4,4,4,3,4,5,0,4,0,0,3,4),
(0,3,0,3,0,3,1,2,0,3,4,4,3,3,3,0,2,2,4,3,3,1,3,3,3,1,1,0,3,1,4,3,2,3,4,4,2,4,4,4,3,4,4,3,2,4,4,3,1,3,3,1,3,3,0,4,1,0,2,2,1,4,3,2,3,3,5,4,3,3,5,4,4,3,3,0,4,0,3,2,2,4,4),
(0,2,0,1,0,0,0,0,0,1,2,1,3,0,0,0,0,0,2,0,1,2,1,0,0,1,0,0,0,0,3,0,0,1,0,1,1,3,1,0,0,0,1,1,0,1,1,0,0,0,0,0,2,0,0,0,0,0,0,0,0,1,1,2,2,0,3,4,0,0,0,1,1,0,0,1,0,0,0,0,0,1,1),
(0,1,0,0,0,1,0,0,0,0,4,0,4,1,4,0,3,0,4,0,3,0,4,0,3,0,3,0,4,1,5,1,4,0,0,3,0,5,0,5,2,0,1,0,0,0,2,1,4,0,1,3,0,0,3,0,0,3,1,1,4,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0),
(1,4,0,5,0,3,0,2,0,3,5,4,4,3,4,3,5,3,4,3,3,0,4,3,3,3,3,3,3,2,4,4,3,1,3,4,4,5,4,4,3,4,4,1,3,5,4,3,3,3,1,2,2,3,3,1,3,1,3,3,3,5,3,3,4,5,0,3,0,3,0,3,4,3,4,4,3,0,3,0,2,4,3),
(0,1,0,4,0,0,0,0,0,1,4,0,4,1,4,2,4,0,3,0,1,0,1,0,0,0,0,0,2,0,3,1,1,1,0,3,0,0,0,1,2,1,0,0,1,1,1,1,0,1,0,0,0,1,0,0,3,0,0,0,0,3,2,0,2,2,0,1,0,0,0,2,3,2,3,3,0,0,0,0,2,1,0),
(0,5,1,5,0,3,0,3,0,5,4,4,5,1,5,3,3,0,4,3,4,3,5,3,4,3,3,2,4,3,4,3,3,0,3,3,1,4,4,3,4,4,4,3,4,5,5,3,2,3,1,1,3,3,1,3,1,1,3,3,2,4,5,3,3,5,0,4,0,3,0,4,4,3,5,3,3,0,3,4,0,4,3),
(0,5,0,5,0,3,0,2,0,4,4,3,5,2,4,3,3,3,4,4,4,3,5,3,5,3,3,1,4,0,4,3,3,0,3,3,0,4,4,4,4,5,4,3,3,5,5,3,2,3,1,2,3,2,0,1,0,0,3,2,2,4,4,3,1,5,0,4,0,3,0,4,3,1,3,2,1,0,3,3,0,3,3),
(0,4,0,5,0,5,0,4,0,4,5,5,5,3,4,3,3,2,5,4,4,3,5,3,5,3,4,0,4,3,4,4,3,2,4,4,3,4,5,4,4,5,5,0,3,5,5,4,1,3,3,2,3,3,1,3,1,0,4,3,1,4,4,3,4,5,0,4,0,2,0,4,3,4,4,3,3,0,4,0,0,5,5),
(0,4,0,4,0,5,0,1,1,3,3,4,4,3,4,1,3,0,5,1,3,0,3,1,3,1,1,0,3,0,3,3,4,0,4,3,0,4,4,4,3,4,4,0,3,5,4,1,0,3,0,0,2,3,0,3,1,0,3,1,0,3,2,1,3,5,0,3,0,1,0,3,2,3,3,4,4,0,2,2,0,4,4),
(2,4,0,5,0,4,0,3,0,4,5,5,4,3,5,3,5,3,5,3,5,2,5,3,4,3,3,4,3,4,5,3,2,1,5,4,3,2,3,4,5,3,4,1,2,5,4,3,0,3,3,0,3,2,0,2,3,0,4,1,0,3,4,3,3,5,0,3,0,1,0,4,5,5,5,4,3,0,4,2,0,3,5),
(0,5,0,4,0,4,0,2,0,5,4,3,4,3,4,3,3,3,4,3,4,2,5,3,5,3,4,1,4,3,4,4,4,0,3,5,0,4,4,4,4,5,3,1,3,4,5,3,3,3,3,3,3,3,0,2,2,0,3,3,2,4,3,3,3,5,3,4,1,3,3,5,3,2,0,0,0,0,4,3,1,3,3),
(0,1,0,3,0,3,0,1,0,1,3,3,3,2,3,3,3,0,3,0,0,0,3,1,3,0,0,0,2,2,2,3,0,0,3,2,0,1,2,4,1,3,3,0,0,3,3,3,0,1,0,0,2,1,0,0,3,0,3,1,0,3,0,0,1,3,0,2,0,1,0,3,3,1,3,3,0,0,1,1,0,3,3),
(0,2,0,3,0,2,1,4,0,2,2,3,1,1,3,1,1,0,2,0,3,1,2,3,1,3,0,0,1,0,4,3,2,3,3,3,1,4,2,3,3,3,3,1,0,3,1,4,0,1,1,0,1,2,0,1,1,0,1,1,0,3,1,3,2,2,0,1,0,0,0,2,3,3,3,1,0,0,0,0,0,2,3),
(0,5,0,4,0,5,0,2,0,4,5,5,3,3,4,3,3,1,5,4,4,2,4,4,4,3,4,2,4,3,5,5,4,3,3,4,3,3,5,5,4,5,5,1,3,4,5,3,1,4,3,1,3,3,0,3,3,1,4,3,1,4,5,3,3,5,0,4,0,3,0,5,3,3,1,4,3,0,4,0,1,5,3),
(0,5,0,5,0,4,0,2,0,4,4,3,4,3,3,3,3,3,5,4,4,4,4,4,4,5,3,3,5,2,4,4,4,3,4,4,3,3,4,4,5,5,3,3,4,3,4,3,3,4,3,3,3,3,1,2,2,1,4,3,3,5,4,4,3,4,0,4,0,3,0,4,4,4,4,4,1,0,4,2,0,2,4),
(0,4,0,4,0,3,0,1,0,3,5,2,3,0,3,0,2,1,4,2,3,3,4,1,4,3,3,2,4,1,3,3,3,0,3,3,0,0,3,3,3,5,3,3,3,3,3,2,0,2,0,0,2,0,0,2,0,0,1,0,0,3,1,2,2,3,0,3,0,2,0,4,4,3,3,4,1,0,3,0,0,2,4),
(0,0,0,4,0,0,0,0,0,0,1,0,1,0,2,0,0,0,0,0,1,0,2,0,1,0,0,0,0,0,3,1,3,0,3,2,0,0,0,1,0,3,2,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,4,0,2,0,0,0,0,0,0,2),
(0,2,1,3,0,2,0,2,0,3,3,3,3,1,3,1,3,3,3,3,3,3,4,2,2,1,2,1,4,0,4,3,1,3,3,3,2,4,3,5,4,3,3,3,3,3,3,3,0,1,3,0,2,0,0,1,0,0,1,0,0,4,2,0,2,3,0,3,3,0,3,3,4,2,3,1,4,0,1,2,0,2,3),
(0,3,0,3,0,1,0,3,0,2,3,3,3,0,3,1,2,0,3,3,2,3,3,2,3,2,3,1,3,0,4,3,2,0,3,3,1,4,3,3,2,3,4,3,1,3,3,1,1,0,1,1,0,1,0,1,0,1,0,0,0,4,1,1,0,3,0,3,1,0,2,3,3,3,3,3,1,0,0,2,0,3,3),
(0,0,0,0,0,0,0,0,0,0,3,0,2,0,3,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,3,0,3,0,3,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,2,0,2,3,0,0,0,0,0,0,0,0,3),
(0,2,0,3,1,3,0,3,0,2,3,3,3,1,3,1,3,1,3,1,3,3,3,1,3,0,2,3,1,1,4,3,3,2,3,3,1,2,2,4,1,3,3,0,1,4,2,3,0,1,3,0,3,0,0,1,3,0,2,0,0,3,3,2,1,3,0,3,0,2,0,3,4,4,4,3,1,0,3,0,0,3,3),
(0,2,0,1,0,2,0,0,0,1,3,2,2,1,3,0,1,1,3,0,3,2,3,1,2,0,2,0,1,1,3,3,3,0,3,3,1,1,2,3,2,3,3,1,2,3,2,0,0,1,0,0,0,0,0,0,3,0,1,0,0,2,1,2,1,3,0,3,0,0,0,3,4,4,4,3,2,0,2,0,0,2,4),
(0,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,2,2,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,3,1,0,0,0,0,0,0,0,3),
(0,3,0,3,0,2,0,3,0,3,3,3,2,3,2,2,2,0,3,1,3,3,3,2,3,3,0,0,3,0,3,2,2,0,2,3,1,4,3,4,3,3,2,3,1,5,4,4,0,3,1,2,1,3,0,3,1,1,2,0,2,3,1,3,1,3,0,3,0,1,0,3,3,4,4,2,1,0,2,1,0,2,4),
(0,1,0,3,0,1,0,2,0,1,4,2,5,1,4,0,2,0,2,1,3,1,4,0,2,1,0,0,2,1,4,1,1,0,3,3,0,5,1,3,2,3,3,1,0,3,2,3,0,1,0,0,0,0,0,0,1,0,0,0,0,4,0,1,0,3,0,2,0,1,0,3,3,3,4,3,3,0,0,0,0,2,3),
(0,0,0,1,0,0,0,0,0,0,2,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,1,0,0,0,0,0,3),
(0,1,0,3,0,4,0,3,0,2,4,3,1,0,3,2,2,1,3,1,2,2,3,1,1,1,2,1,3,0,1,2,0,1,3,2,1,3,0,5,5,1,0,0,1,3,2,1,0,3,0,0,1,0,0,0,0,0,3,4,0,1,1,1,3,2,0,2,0,1,0,2,3,3,1,2,3,0,1,0,1,0,4),
(0,0,0,1,0,3,0,3,0,2,2,1,0,0,4,0,3,0,3,1,3,0,3,0,3,0,1,0,3,0,3,1,3,0,3,3,0,0,1,2,1,1,1,0,1,2,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,2,2,1,2,0,0,2,0,0,0,0,2,3,3,3,3,0,0,0,0,1,4),
(0,0,0,3,0,3,0,0,0,0,3,1,1,0,3,0,1,0,2,0,1,0,0,0,0,0,0,0,1,0,3,0,2,0,2,3,0,0,2,2,3,1,2,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,2,0,0,0,0,2,3),
(2,4,0,5,0,5,0,4,0,3,4,3,3,3,4,3,3,3,4,3,4,4,5,4,5,5,5,2,3,0,5,5,4,1,5,4,3,1,5,4,3,4,4,3,3,4,3,3,0,3,2,0,2,3,0,3,0,0,3,3,0,5,3,2,3,3,0,3,0,3,0,3,4,5,4,5,3,0,4,3,0,3,4),
(0,3,0,3,0,3,0,3,0,3,3,4,3,2,3,2,3,0,4,3,3,3,3,3,3,3,3,0,3,2,4,3,3,1,3,4,3,4,4,4,3,4,4,3,2,4,4,1,0,2,0,0,1,1,0,2,0,0,3,1,0,5,3,2,1,3,0,3,0,1,2,4,3,2,4,3,3,0,3,2,0,4,4),
(0,3,0,3,0,1,0,0,0,1,4,3,3,2,3,1,3,1,4,2,3,2,4,2,3,4,3,0,2,2,3,3,3,0,3,3,3,0,3,4,1,3,3,0,3,4,3,3,0,1,1,0,1,0,0,0,4,0,3,0,0,3,1,2,1,3,0,4,0,1,0,4,3,3,4,3,3,0,2,0,0,3,3),
(0,3,0,4,0,1,0,3,0,3,4,3,3,0,3,3,3,1,3,1,3,3,4,3,3,3,0,0,3,1,5,3,3,1,3,3,2,5,4,3,3,4,5,3,2,5,3,4,0,1,0,0,0,0,0,2,0,0,1,1,0,4,2,2,1,3,0,3,0,2,0,4,4,3,5,3,2,0,1,1,0,3,4),
(0,5,0,4,0,5,0,2,0,4,4,3,3,2,3,3,3,1,4,3,4,1,5,3,4,3,4,0,4,2,4,3,4,1,5,4,0,4,4,4,4,5,4,1,3,5,4,2,1,4,1,1,3,2,0,3,1,0,3,2,1,4,3,3,3,4,0,4,0,3,0,4,4,4,3,3,3,0,4,2,0,3,4),
(1,4,0,4,0,3,0,1,0,3,3,3,1,1,3,3,2,2,3,3,1,0,3,2,2,1,2,0,3,1,2,1,2,0,3,2,0,2,2,3,3,4,3,0,3,3,1,2,0,1,1,3,1,2,0,0,3,0,1,1,0,3,2,2,3,3,0,3,0,0,0,2,3,3,4,3,3,0,1,0,0,1,4),
(0,4,0,4,0,4,0,0,0,3,4,4,3,1,4,2,3,2,3,3,3,1,4,3,4,0,3,0,4,2,3,3,2,2,5,4,2,1,3,4,3,4,3,1,3,3,4,2,0,2,1,0,3,3,0,0,2,0,3,1,0,4,4,3,4,3,0,4,0,1,0,2,4,4,4,4,4,0,3,2,0,3,3),
(0,0,0,1,0,4,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,3,2,0,0,1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,2),
(0,2,0,3,0,4,0,4,0,1,3,3,3,0,4,0,2,1,2,1,1,1,2,0,3,1,1,0,1,0,3,1,0,0,3,3,2,0,1,1,0,0,0,0,0,1,0,2,0,2,2,0,3,1,0,0,1,0,1,1,0,1,2,0,3,0,0,0,0,1,0,0,3,3,4,3,1,0,1,0,3,0,2),
(0,0,0,3,0,5,0,0,0,0,1,0,2,0,3,1,0,1,3,0,0,0,2,0,0,0,1,0,0,0,1,1,0,0,4,0,0,0,2,3,0,1,4,1,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,1,0,0,0,0,0,0,0,2,0,0,3,0,0,0,0,0,3),
(0,2,0,5,0,5,0,1,0,2,4,3,3,2,5,1,3,2,3,3,3,0,4,1,2,0,3,0,4,0,2,2,1,1,5,3,0,0,1,4,2,3,2,0,3,3,3,2,0,2,4,1,1,2,0,1,1,0,3,1,0,1,3,1,2,3,0,2,0,0,0,1,3,5,4,4,4,0,3,0,0,1,3),
(0,4,0,5,0,4,0,4,0,4,5,4,3,3,4,3,3,3,4,3,4,4,5,3,4,5,4,2,4,2,3,4,3,1,4,4,1,3,5,4,4,5,5,4,4,5,5,5,2,3,3,1,4,3,1,3,3,0,3,3,1,4,3,4,4,4,0,3,0,4,0,3,3,4,4,5,0,0,4,3,0,4,5),
(0,4,0,4,0,3,0,3,0,3,4,4,4,3,3,2,4,3,4,3,4,3,5,3,4,3,2,1,4,2,4,4,3,1,3,4,2,4,5,5,3,4,5,4,1,5,4,3,0,3,2,2,3,2,1,3,1,0,3,3,3,5,3,3,3,5,4,4,2,3,3,4,3,3,3,2,1,0,3,2,1,4,3),
(0,4,0,5,0,4,0,3,0,3,5,5,3,2,4,3,4,0,5,4,4,1,4,4,4,3,3,3,4,3,5,5,2,3,3,4,1,2,5,5,3,5,5,2,3,5,5,4,0,3,2,0,3,3,1,1,5,1,4,1,0,4,3,2,3,5,0,4,0,3,0,5,4,3,4,3,0,0,4,1,0,4,4),
(1,3,0,4,0,2,0,2,0,2,5,5,3,3,3,3,3,0,4,2,3,4,4,4,3,4,0,0,3,4,5,4,3,3,3,3,2,5,5,4,5,5,5,4,3,5,5,5,1,3,1,0,1,0,0,3,2,0,4,2,0,5,2,3,2,4,1,3,0,3,0,4,5,4,5,4,3,0,4,2,0,5,4),
(0,3,0,4,0,5,0,3,0,3,4,4,3,2,3,2,3,3,3,3,3,2,4,3,3,2,2,0,3,3,3,3,3,1,3,3,3,0,4,4,3,4,4,1,1,4,4,2,0,3,1,0,1,1,0,4,1,0,2,3,1,3,3,1,3,4,0,3,0,1,0,3,1,3,0,0,1,0,2,0,0,4,4),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
(0,3,0,3,0,2,0,3,0,1,5,4,3,3,3,1,4,2,1,2,3,4,4,2,4,4,5,0,3,1,4,3,4,0,4,3,3,3,2,3,2,5,3,4,3,2,2,3,0,0,3,0,2,1,0,1,2,0,0,0,0,2,1,1,3,1,0,2,0,4,0,3,4,4,4,5,2,0,2,0,0,1,3),
(0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,0,0,1,1,0,0,0,4,2,1,1,0,1,0,3,2,0,0,3,1,1,1,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,1,0,0,0,2,0,0,0,1,4,0,4,2,1,0,0,0,0,0,1),
(0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,3,1,0,0,0,2,0,2,1,0,0,1,2,1,0,1,1,0,0,3,0,0,0,0,0,0,0,0,0,0,0,1,3,1,0,0,0,0,0,1,0,0,2,1,0,0,0,0,0,0,0,0,2),
(0,4,0,4,0,4,0,3,0,4,4,3,4,2,4,3,2,0,4,4,4,3,5,3,5,3,3,2,4,2,4,3,4,3,1,4,0,2,3,4,4,4,3,3,3,4,4,4,3,4,1,3,4,3,2,1,2,1,3,3,3,4,4,3,3,5,0,4,0,3,0,4,3,3,3,2,1,0,3,0,0,3,3),
(0,4,0,3,0,3,0,3,0,3,5,5,3,3,3,3,4,3,4,3,3,3,4,4,4,3,3,3,3,4,3,5,3,3,1,3,2,4,5,5,5,5,4,3,4,5,5,3,2,2,3,3,3,3,2,3,3,1,2,3,2,4,3,3,3,4,0,4,0,2,0,4,3,2,2,1,2,0,3,0,0,4,1),
)

class JapaneseContextAnalysis(object):
    NUM_OF_CATEGORY = 6
    DONT_KNOW = -1
    ENOUGH_REL_THRESHOLD = 100
    MAX_REL_THRESHOLD = 1000
    MINIMUM_DATA_THRESHOLD = 4

    def __init__(self):
        self._total_rel = None
        self._rel_sample = None
        self._need_to_skip_char_num = None
        self._last_char_order = None
        self._done = None
        self.reset()

    def reset(self):
        self._total_rel = 0  # total sequence received
        # category counters, each integer counts sequence in its category
        self._rel_sample = [0] * self.NUM_OF_CATEGORY
        # if last byte in current buffer is not the last byte of a character,
        # we need to know how many bytes to skip in next buffer
        self._need_to_skip_char_num = 0
        self._last_char_order = -1  # The order of previous char
        # If this flag is set to True, detection is done and conclusion has
        # been made
        self._done = False

    def feed(self, byte_str, num_bytes):
        if self._done:
            return

        # The buffer we got is byte oriented, and a character may span in more than one
        # buffers. In case the last one or two byte in last buffer is not
        # complete, we record how many byte needed to complete that character
        # and skip these bytes here.  We can choose to record those bytes as
        # well and analyse the character once it is complete, but since a
        # character will not make much difference, by simply skipping
        # this character will simply our logic and improve performance.
        i = self._need_to_skip_char_num
        while i < num_bytes:
            order, char_len = self.get_order(byte_str[i:i + 2])
            i += char_len
            if i > num_bytes:
                self._need_to_skip_char_num = i - num_bytes
                self._last_char_order = -1
            else:
                if (order != -1) and (self._last_char_order != -1):
                    self._total_rel += 1
                    if self._total_rel > self.MAX_REL_THRESHOLD:
                        self._done = True
                        break
                    self._rel_sample[jp2CharContext[self._last_char_order][order]] += 1
                self._last_char_order = order

    def got_enough_data(self):
        return self._total_rel > self.ENOUGH_REL_THRESHOLD

    def get_confidence(self):
        # This is just one way to calculate confidence. It works well for me.
        if self._total_rel > self.MINIMUM_DATA_THRESHOLD:
            return (self._total_rel - self._rel_sample[0]) / self._total_rel
        else:
            return self.DONT_KNOW

    def get_order(self, byte_str):
        return -1, 1

class SJISContextAnalysis(JapaneseContextAnalysis):
    def __init__(self):
        super(SJISContextAnalysis, self).__init__()
        self._charset_name = "SHIFT_JIS"

    @property
    def charset_name(self):
        return self._charset_name

    def get_order(self, byte_str):
        if not byte_str:
            return -1, 1
        # find out current char's byte length
        first_char = byte_str[0]
        if (0x81 <= first_char <= 0x9F) or (0xE0 <= first_char <= 0xFC):
            char_len = 2
            if (first_char == 0x87) or (0xFA <= first_char <= 0xFC):
                self._charset_name = "CP932"
        else:
            char_len = 1

        # return its order if it is hiragana
        if len(byte_str) > 1:
            second_char = byte_str[1]
            if (first_char == 202) and (0x9F <= second_char <= 0xF1):
                return second_char - 0x9F, char_len

        return -1, char_len

class EUCJPContextAnalysis(JapaneseContextAnalysis):
    def get_order(self, byte_str):
        if not byte_str:
            return -1, 1
        # find out current char's byte length
        first_char = byte_str[0]
        if (first_char == 0x8E) or (0xA1 <= first_char <= 0xFE):
            char_len = 2
        elif first_char == 0x8F:
            char_len = 3
        else:
            char_len = 1

        # return its order if it is hiragana
        if len(byte_str) > 1:
            second_char = byte_str[1]
            if (first_char == 0xA4) and (0xA1 <= second_char <= 0xF3):
                return second_char - 0xA1, char_len

        return -1, char_len
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