SILENT KILLER Tool

Name	Type	Size	Last Modified
Demo	Directory	-	-
Doc	Directory	-	-
Tools	Directory	-	-
bsddb	Directory	-	-
compiler	Directory	-	-
config	Directory	-	-
ctypes	Directory	-	-
curses	Directory	-	-
distutils	Directory	-	-
email	Directory	-	-
encodings	Directory	-	-
ensurepip	Directory	-	-
hotshot	Directory	-	-
idlelib	Directory	-	-
importlib	Directory	-	-
json	Directory	-	-
lib-dynload	Directory	-	-
lib-tk	Directory	-	-
lib2to3	Directory	-	-
logging	Directory	-	-
multiprocessing	Directory	-	-
plat-linux2	Directory	-	-
pydoc_data	Directory	-	-
site-packages	Directory	-	-
sqlite3	Directory	-	-
test	Directory	-	-
unittest	Directory	-	-
wsgiref	Directory	-	-
xml	Directory	-	-
BaseHTTPServer.py	File	22747 bytes	April 10 2024 04:58:34.
BaseHTTPServer.pyc	File	21722 bytes	April 10 2024 04:58:47.
BaseHTTPServer.pyo	File	21722 bytes	April 10 2024 04:58:47.
Bastion.py	File	5744 bytes	April 10 2024 04:58:34.
Bastion.pyc	File	6660 bytes	April 10 2024 04:58:47.
Bastion.pyo	File	6660 bytes	April 10 2024 04:58:47.
CGIHTTPServer.py	File	13089 bytes	April 10 2024 04:58:34.
CGIHTTPServer.pyc	File	11018 bytes	April 10 2024 04:58:47.
CGIHTTPServer.pyo	File	11018 bytes	April 10 2024 04:58:47.
ConfigParser.py	File	27746 bytes	April 10 2024 04:58:34.
ConfigParser.pyc	File	25213 bytes	April 10 2024 04:58:47.
ConfigParser.pyo	File	25213 bytes	April 10 2024 04:58:47.
Cookie.py	File	26538 bytes	April 10 2024 04:58:34.
Cookie.pyc	File	22658 bytes	April 10 2024 04:58:47.
Cookie.pyo	File	22658 bytes	April 10 2024 04:58:47.
DocXMLRPCServer.py	File	10768 bytes	April 10 2024 04:58:34.
DocXMLRPCServer.pyc	File	10195 bytes	April 10 2024 04:58:47.
DocXMLRPCServer.pyo	File	10086 bytes	April 10 2024 04:58:44.
HTMLParser.py	File	17171 bytes	April 10 2024 04:58:34.
HTMLParser.pyc	File	13727 bytes	April 10 2024 04:58:47.
HTMLParser.pyo	File	13422 bytes	April 10 2024 04:58:44.
MimeWriter.py	File	6482 bytes	April 10 2024 04:58:34.
MimeWriter.pyc	File	7364 bytes	April 10 2024 04:58:47.
MimeWriter.pyo	File	7364 bytes	April 10 2024 04:58:47.
Queue.py	File	8577 bytes	April 10 2024 04:58:34.
Queue.pyc	File	9424 bytes	April 10 2024 04:58:47.
Queue.pyo	File	9424 bytes	April 10 2024 04:58:47.
SimpleHTTPServer.py	File	7997 bytes	April 10 2024 04:58:34.
SimpleHTTPServer.pyc	File	8010 bytes	April 10 2024 04:58:47.
SimpleHTTPServer.pyo	File	8010 bytes	April 10 2024 04:58:47.
SimpleXMLRPCServer.py	File	25812 bytes	April 10 2024 04:58:34.
SimpleXMLRPCServer.pyc	File	22863 bytes	April 10 2024 04:58:47.
SimpleXMLRPCServer.pyo	File	22863 bytes	April 10 2024 04:58:47.
SocketServer.py	File	23948 bytes	April 10 2024 04:58:34.
SocketServer.pyc	File	24087 bytes	April 10 2024 04:58:47.
SocketServer.pyo	File	24087 bytes	April 10 2024 04:58:47.
StringIO.py	File	10662 bytes	April 10 2024 04:58:34.
StringIO.pyc	File	11480 bytes	April 10 2024 04:58:47.
StringIO.pyo	File	11480 bytes	April 10 2024 04:58:47.
UserDict.py	File	7060 bytes	April 10 2024 04:58:34.
UserDict.pyc	File	9711 bytes	April 10 2024 04:58:47.
UserDict.pyo	File	9711 bytes	April 10 2024 04:58:47.
UserList.py	File	3644 bytes	April 10 2024 04:58:34.
UserList.pyc	File	6577 bytes	April 10 2024 04:58:47.
UserList.pyo	File	6577 bytes	April 10 2024 04:58:47.
UserString.py	File	9687 bytes	April 10 2024 04:58:34.
UserString.pyc	File	14864 bytes	April 10 2024 04:58:47.
UserString.pyo	File	14864 bytes	April 10 2024 04:58:47.
_LWPCookieJar.py	File	6553 bytes	April 10 2024 04:58:34.
_LWPCookieJar.pyc	File	5434 bytes	April 10 2024 04:58:47.
_LWPCookieJar.pyo	File	5434 bytes	April 10 2024 04:58:47.
_MozillaCookieJar.py	File	5797 bytes	April 10 2024 04:58:34.
_MozillaCookieJar.pyc	File	4461 bytes	April 10 2024 04:58:47.
_MozillaCookieJar.pyo	File	4422 bytes	April 10 2024 04:58:44.
__future__.py	File	4380 bytes	April 10 2024 04:58:34.
__future__.pyc	File	4223 bytes	April 10 2024 04:58:47.
__future__.pyo	File	4223 bytes	April 10 2024 04:58:47.
__phello__.foo.py	File	64 bytes	April 10 2024 04:58:34.
__phello__.foo.pyc	File	125 bytes	April 10 2024 04:58:47.
__phello__.foo.pyo	File	125 bytes	April 10 2024 04:58:47.
_abcoll.py	File	18619 bytes	April 10 2024 04:58:34.
_abcoll.pyc	File	25682 bytes	April 10 2024 04:58:47.
_abcoll.pyo	File	25682 bytes	April 10 2024 04:58:47.
_osx_support.py	File	19100 bytes	April 10 2024 04:58:34.
_osx_support.pyc	File	11758 bytes	April 10 2024 04:58:47.
_osx_support.pyo	File	11758 bytes	April 10 2024 04:58:47.
_pyio.py	File	69630 bytes	April 10 2024 04:58:34.
_pyio.pyc	File	64701 bytes	April 10 2024 04:58:47.
_pyio.pyo	File	64701 bytes	April 10 2024 04:58:47.
_strptime.py	File	20728 bytes	April 10 2024 04:58:34.
_strptime.pyc	File	15172 bytes	April 10 2024 04:58:47.
_strptime.pyo	File	15172 bytes	April 10 2024 04:58:47.
_sysconfigdata.py	File	19732 bytes	April 10 2024 04:58:34.
_sysconfigdata.pyc	File	22968 bytes	April 10 2024 04:58:46.
_sysconfigdata.pyo	File	22968 bytes	April 10 2024 04:58:46.
_threading_local.py	File	7260 bytes	April 10 2024 04:58:34.
_threading_local.pyc	File	6373 bytes	April 10 2024 04:58:47.
_threading_local.pyo	File	6373 bytes	April 10 2024 04:58:47.
_weakrefset.py	File	5911 bytes	April 10 2024 04:58:34.
_weakrefset.pyc	File	9678 bytes	April 10 2024 04:58:47.
_weakrefset.pyo	File	9678 bytes	April 10 2024 04:58:47.
abc.py	File	7145 bytes	April 10 2024 04:58:34.
abc.pyc	File	6143 bytes	April 10 2024 04:58:47.
abc.pyo	File	6087 bytes	April 10 2024 04:58:44.
aifc.py	File	34579 bytes	April 10 2024 04:58:34.
aifc.pyc	File	30459 bytes	April 10 2024 04:58:47.
aifc.pyo	File	30459 bytes	April 10 2024 04:58:47.
antigravity.py	File	60 bytes	April 10 2024 04:58:34.
antigravity.pyc	File	203 bytes	April 10 2024 04:58:47.
antigravity.pyo	File	203 bytes	April 10 2024 04:58:47.
anydbm.py	File	2663 bytes	April 10 2024 04:58:34.
anydbm.pyc	File	2800 bytes	April 10 2024 04:58:47.
anydbm.pyo	File	2800 bytes	April 10 2024 04:58:47.
argparse.py	File	89228 bytes	April 10 2024 04:58:34.
argparse.pyc	File	64367 bytes	April 10 2024 04:58:47.
argparse.pyo	File	64202 bytes	April 10 2024 04:58:44.
ast.py	File	11805 bytes	April 10 2024 04:58:34.
ast.pyc	File	12938 bytes	April 10 2024 04:58:47.
ast.pyo	File	12938 bytes	April 10 2024 04:58:47.
asynchat.py	File	11581 bytes	April 10 2024 04:58:34.
asynchat.pyc	File	8810 bytes	April 10 2024 04:58:47.
asynchat.pyo	File	8810 bytes	April 10 2024 04:58:47.
asyncore.py	File	20943 bytes	April 10 2024 04:58:34.
asyncore.pyc	File	18893 bytes	April 10 2024 04:58:47.
asyncore.pyo	File	18893 bytes	April 10 2024 04:58:47.
atexit.py	File	1705 bytes	April 10 2024 04:58:34.
atexit.pyc	File	2203 bytes	April 10 2024 04:58:47.
atexit.pyo	File	2203 bytes	April 10 2024 04:58:47.
audiodev.py	File	7597 bytes	April 10 2024 04:58:34.
audiodev.pyc	File	8469 bytes	April 10 2024 04:58:47.
audiodev.pyo	File	8469 bytes	April 10 2024 04:58:47.
base64.py	File	11806 bytes	April 10 2024 04:58:34.
base64.pyc	File	11297 bytes	April 10 2024 04:58:47.
base64.pyo	File	11297 bytes	April 10 2024 04:58:47.
bdb.py	File	21714 bytes	April 10 2024 04:58:34.
bdb.pyc	File	19101 bytes	April 10 2024 04:58:47.
bdb.pyo	File	19101 bytes	April 10 2024 04:58:47.
binhex.py	File	14698 bytes	April 10 2024 04:58:34.
binhex.pyc	File	15460 bytes	April 10 2024 04:58:47.
binhex.pyo	File	15460 bytes	April 10 2024 04:58:47.
bisect.py	File	2595 bytes	April 10 2024 04:58:34.
bisect.pyc	File	3071 bytes	April 10 2024 04:58:47.
bisect.pyo	File	3071 bytes	April 10 2024 04:58:47.
cProfile.py	File	6573 bytes	April 10 2024 04:58:34.
cProfile.pyc	File	6395 bytes	April 10 2024 04:58:47.
cProfile.pyo	File	6395 bytes	April 10 2024 04:58:47.
calendar.py	File	23384 bytes	April 10 2024 04:58:34.
calendar.pyc	File	27913 bytes	April 10 2024 04:58:47.
calendar.pyo	File	27913 bytes	April 10 2024 04:58:47.
cgi.py	File	36308 bytes	April 10 2024 04:58:34.
cgi.pyc	File	33366 bytes	April 10 2024 04:58:47.
cgi.pyo	File	33366 bytes	April 10 2024 04:58:47.
cgitb.py	File	12175 bytes	April 10 2024 04:58:34.
cgitb.pyc	File	12138 bytes	April 10 2024 04:58:47.
cgitb.pyo	File	12138 bytes	April 10 2024 04:58:47.
chunk.py	File	5419 bytes	April 10 2024 04:58:34.
chunk.pyc	File	5602 bytes	April 10 2024 04:58:47.
chunk.pyo	File	5602 bytes	April 10 2024 04:58:47.
cmd.py	File	15026 bytes	April 10 2024 04:58:34.
cmd.pyc	File	14039 bytes	April 10 2024 04:58:47.
cmd.pyo	File	14039 bytes	April 10 2024 04:58:47.
code.py	File	10189 bytes	April 10 2024 04:58:34.
code.pyc	File	10334 bytes	April 10 2024 04:58:47.
code.pyo	File	10334 bytes	April 10 2024 04:58:47.
codecs.py	File	36143 bytes	April 10 2024 04:58:34.
codecs.pyc	File	36824 bytes	April 10 2024 04:58:47.
codecs.pyo	File	36824 bytes	April 10 2024 04:58:47.
codeop.py	File	5999 bytes	April 10 2024 04:58:34.
codeop.pyc	File	6597 bytes	April 10 2024 04:58:47.
codeop.pyo	File	6597 bytes	April 10 2024 04:58:47.
collections.py	File	27798 bytes	April 10 2024 04:58:34.
collections.pyc	File	26163 bytes	April 10 2024 04:58:47.
collections.pyo	File	26112 bytes	April 10 2024 04:58:44.
colorsys.py	File	3691 bytes	April 10 2024 04:58:34.
colorsys.pyc	File	3991 bytes	April 10 2024 04:58:47.
colorsys.pyo	File	3991 bytes	April 10 2024 04:58:47.
commands.py	File	2545 bytes	April 10 2024 04:58:34.
commands.pyc	File	2469 bytes	April 10 2024 04:58:47.
commands.pyo	File	2469 bytes	April 10 2024 04:58:47.
compileall.py	File	7763 bytes	April 10 2024 04:58:34.
compileall.pyc	File	7017 bytes	April 10 2024 04:58:47.
compileall.pyo	File	7017 bytes	April 10 2024 04:58:47.
contextlib.py	File	4424 bytes	April 10 2024 04:58:34.
contextlib.pyc	File	4454 bytes	April 10 2024 04:58:47.
contextlib.pyo	File	4454 bytes	April 10 2024 04:58:47.
cookielib.py	File	65486 bytes	April 10 2024 04:58:34.
cookielib.pyc	File	54725 bytes	April 10 2024 04:58:47.
cookielib.pyo	File	54537 bytes	April 10 2024 04:58:44.
copy.py	File	11533 bytes	April 10 2024 04:58:34.
copy.pyc	File	12170 bytes	April 10 2024 04:58:47.
copy.pyo	File	12078 bytes	April 10 2024 04:58:44.
copy_reg.py	File	6974 bytes	April 10 2024 04:58:34.
copy_reg.pyc	File	5167 bytes	April 10 2024 04:58:47.
copy_reg.pyo	File	5123 bytes	April 10 2024 04:58:44.
crypt.py	File	2292 bytes	April 10 2024 04:58:34.
crypt.pyc	File	2960 bytes	April 10 2024 04:58:47.
crypt.pyo	File	2960 bytes	April 10 2024 04:58:47.
csv.py	File	16708 bytes	April 10 2024 04:58:34.
csv.pyc	File	13507 bytes	April 10 2024 04:58:47.
csv.pyo	File	13507 bytes	April 10 2024 04:58:47.
dbhash.py	File	498 bytes	April 10 2024 04:58:34.
dbhash.pyc	File	718 bytes	April 10 2024 04:58:47.
dbhash.pyo	File	718 bytes	April 10 2024 04:58:47.
decimal.py	File	221933 bytes	April 10 2024 04:58:34.
decimal.pyc	File	172155 bytes	April 10 2024 04:58:47.
decimal.pyo	File	172155 bytes	April 10 2024 04:58:47.
difflib.py	File	82325 bytes	April 10 2024 04:58:34.
difflib.pyc	File	61898 bytes	April 10 2024 04:58:47.
difflib.pyo	File	61847 bytes	April 10 2024 04:58:44.
dircache.py	File	1126 bytes	April 10 2024 04:58:34.
dircache.pyc	File	1576 bytes	April 10 2024 04:58:47.
dircache.pyo	File	1576 bytes	April 10 2024 04:58:47.
dis.py	File	6499 bytes	April 10 2024 04:58:34.
dis.pyc	File	6228 bytes	April 10 2024 04:58:47.
dis.pyo	File	6228 bytes	April 10 2024 04:58:47.
doctest.py	File	105095 bytes	April 10 2024 04:58:34.
doctest.pyc	File	83637 bytes	April 10 2024 04:58:47.
doctest.pyo	File	83350 bytes	April 10 2024 04:58:44.
dumbdbm.py	File	9141 bytes	April 10 2024 04:58:34.
dumbdbm.pyc	File	6746 bytes	April 10 2024 04:58:47.
dumbdbm.pyo	File	6746 bytes	April 10 2024 04:58:47.
dummy_thread.py	File	4418 bytes	April 10 2024 04:58:34.
dummy_thread.pyc	File	5394 bytes	April 10 2024 04:58:47.
dummy_thread.pyo	File	5394 bytes	April 10 2024 04:58:47.
dummy_threading.py	File	2804 bytes	April 10 2024 04:58:34.
dummy_threading.pyc	File	1285 bytes	April 10 2024 04:58:47.
dummy_threading.pyo	File	1285 bytes	April 10 2024 04:58:47.
filecmp.py	File	9588 bytes	April 10 2024 04:58:34.
filecmp.pyc	File	9622 bytes	April 10 2024 04:58:47.
filecmp.pyo	File	9622 bytes	April 10 2024 04:58:47.
fileinput.py	File	13746 bytes	April 10 2024 04:58:34.
fileinput.pyc	File	14500 bytes	April 10 2024 04:58:47.
fileinput.pyo	File	14500 bytes	April 10 2024 04:58:47.
fnmatch.py	File	3315 bytes	April 10 2024 04:58:34.
fnmatch.pyc	File	3614 bytes	April 10 2024 04:58:47.
fnmatch.pyo	File	3614 bytes	April 10 2024 04:58:47.
formatter.py	File	14911 bytes	April 10 2024 04:58:34.
formatter.pyc	File	19178 bytes	April 10 2024 04:58:47.
formatter.pyo	File	19178 bytes	April 10 2024 04:58:47.
fpformat.py	File	4732 bytes	April 10 2024 04:58:34.
fpformat.pyc	File	4703 bytes	April 10 2024 04:58:47.
fpformat.pyo	File	4703 bytes	April 10 2024 04:58:47.
fractions.py	File	22390 bytes	April 10 2024 04:58:34.
fractions.pyc	File	19711 bytes	April 10 2024 04:58:47.
fractions.pyo	File	19711 bytes	April 10 2024 04:58:47.
ftplib.py	File	38555 bytes	April 10 2024 04:58:34.
ftplib.pyc	File	34939 bytes	April 10 2024 04:58:47.
ftplib.pyo	File	34939 bytes	April 10 2024 04:58:47.
functools.py	File	4806 bytes	April 10 2024 04:58:34.
functools.pyc	File	6629 bytes	April 10 2024 04:58:47.
functools.pyo	File	6629 bytes	April 10 2024 04:58:47.
genericpath.py	File	3201 bytes	April 10 2024 04:58:34.
genericpath.pyc	File	3517 bytes	April 10 2024 04:58:47.
genericpath.pyo	File	3517 bytes	April 10 2024 04:58:47.
getopt.py	File	7319 bytes	April 10 2024 04:58:34.
getopt.pyc	File	6654 bytes	April 10 2024 04:58:47.
getopt.pyo	File	6609 bytes	April 10 2024 04:58:44.
getpass.py	File	5563 bytes	April 10 2024 04:58:34.
getpass.pyc	File	4744 bytes	April 10 2024 04:58:47.
getpass.pyo	File	4744 bytes	April 10 2024 04:58:47.
gettext.py	File	22666 bytes	April 10 2024 04:58:34.
gettext.pyc	File	18004 bytes	April 10 2024 04:58:47.
gettext.pyo	File	18004 bytes	April 10 2024 04:58:47.
glob.py	File	3114 bytes	April 10 2024 04:58:34.
glob.pyc	File	2943 bytes	April 10 2024 04:58:47.
glob.pyo	File	2943 bytes	April 10 2024 04:58:47.
gzip.py	File	19028 bytes	April 10 2024 04:58:34.
gzip.pyc	File	15236 bytes	April 10 2024 04:58:47.
gzip.pyo	File	15236 bytes	April 10 2024 04:58:47.
hashlib.py	File	7841 bytes	April 10 2024 04:58:34.
hashlib.pyc	File	6919 bytes	April 10 2024 04:58:47.
hashlib.pyo	File	6919 bytes	April 10 2024 04:58:47.
heapq.py	File	18295 bytes	April 10 2024 04:58:34.
heapq.pyc	File	14564 bytes	April 10 2024 04:58:47.
heapq.pyo	File	14564 bytes	April 10 2024 04:58:47.
hmac.py	File	4588 bytes	April 10 2024 04:58:34.
hmac.pyc	File	4542 bytes	April 10 2024 04:58:47.
hmac.pyo	File	4542 bytes	April 10 2024 04:58:47.
htmlentitydefs.py	File	18056 bytes	April 10 2024 04:58:34.
htmlentitydefs.pyc	File	6367 bytes	April 10 2024 04:58:47.
htmlentitydefs.pyo	File	6367 bytes	April 10 2024 04:58:47.
htmllib.py	File	12869 bytes	April 10 2024 04:58:34.
htmllib.pyc	File	20309 bytes	April 10 2024 04:58:47.
htmllib.pyo	File	20309 bytes	April 10 2024 04:58:47.
httplib.py	File	53306 bytes	April 10 2024 04:58:34.
httplib.pyc	File	38724 bytes	April 10 2024 04:58:47.
httplib.pyo	File	38540 bytes	April 10 2024 04:58:44.
ihooks.py	File	18986 bytes	April 10 2024 04:58:34.
ihooks.pyc	File	21372 bytes	April 10 2024 04:58:47.
ihooks.pyo	File	21372 bytes	April 10 2024 04:58:47.
imaplib.py	File	48366 bytes	April 10 2024 04:58:34.
imaplib.pyc	File	45011 bytes	April 10 2024 04:58:47.
imaplib.pyo	File	42310 bytes	April 10 2024 04:58:44.
imghdr.py	File	3541 bytes	April 10 2024 04:58:34.
imghdr.pyc	File	4838 bytes	April 10 2024 04:58:47.
imghdr.pyo	File	4838 bytes	April 10 2024 04:58:47.
imputil.py	File	25764 bytes	April 10 2024 04:58:34.
imputil.pyc	File	15623 bytes	April 10 2024 04:58:47.
imputil.pyo	File	15445 bytes	April 10 2024 04:58:44.
inspect.py	File	43008 bytes	April 10 2024 04:58:34.
inspect.pyc	File	40229 bytes	April 10 2024 04:58:47.
inspect.pyo	File	40229 bytes	April 10 2024 04:58:47.
io.py	File	3322 bytes	April 10 2024 04:58:34.
io.pyc	File	3589 bytes	April 10 2024 04:58:47.
io.pyo	File	3589 bytes	April 10 2024 04:58:47.
keyword.py	File	1995 bytes	April 10 2024 04:58:34.
keyword.pyc	File	2105 bytes	April 10 2024 04:58:47.
keyword.pyo	File	2105 bytes	April 10 2024 04:58:47.
linecache.py	File	4027 bytes	April 10 2024 04:58:34.
linecache.pyc	File	3272 bytes	April 10 2024 04:58:47.
linecache.pyo	File	3272 bytes	April 10 2024 04:58:47.
locale.py	File	102834 bytes	April 10 2024 04:58:34.
locale.pyc	File	56610 bytes	April 10 2024 04:58:47.
locale.pyo	File	56610 bytes	April 10 2024 04:58:47.
macpath.py	File	6289 bytes	April 10 2024 04:58:34.
macpath.pyc	File	7681 bytes	April 10 2024 04:58:47.
macpath.pyo	File	7681 bytes	April 10 2024 04:58:47.
macurl2path.py	File	2731 bytes	April 10 2024 04:58:34.
macurl2path.pyc	File	2244 bytes	April 10 2024 04:58:47.
macurl2path.pyo	File	2244 bytes	April 10 2024 04:58:47.
mailbox.py	File	81240 bytes	April 10 2024 04:58:34.
mailbox.pyc	File	76717 bytes	April 10 2024 04:58:47.
mailbox.pyo	File	76670 bytes	April 10 2024 04:58:44.
mailcap.py	File	8404 bytes	April 10 2024 04:58:34.
mailcap.pyc	File	7955 bytes	April 10 2024 04:58:47.
mailcap.pyo	File	7955 bytes	April 10 2024 04:58:47.
markupbase.py	File	14643 bytes	April 10 2024 04:58:34.
markupbase.pyc	File	9267 bytes	April 10 2024 04:58:47.
markupbase.pyo	File	9071 bytes	April 10 2024 04:58:44.
md5.py	File	358 bytes	April 10 2024 04:58:34.
md5.pyc	File	378 bytes	April 10 2024 04:58:47.
md5.pyo	File	378 bytes	April 10 2024 04:58:47.
mhlib.py	File	33434 bytes	April 10 2024 04:58:34.
mhlib.pyc	File	33777 bytes	April 10 2024 04:58:47.
mhlib.pyo	File	33777 bytes	April 10 2024 04:58:47.
mimetools.py	File	7168 bytes	April 10 2024 04:58:34.
mimetools.pyc	File	8201 bytes	April 10 2024 04:58:47.
mimetools.pyo	File	8201 bytes	April 10 2024 04:58:47.
mimetypes.py	File	21028 bytes	April 10 2024 04:58:34.
mimetypes.pyc	File	18489 bytes	April 10 2024 04:58:47.
mimetypes.pyo	File	18489 bytes	April 10 2024 04:58:47.
mimify.py	File	15020 bytes	April 10 2024 04:58:34.
mimify.pyc	File	12001 bytes	April 10 2024 04:58:47.
mimify.pyo	File	12001 bytes	April 10 2024 04:58:47.
modulefinder.py	File	24461 bytes	April 10 2024 04:58:34.
modulefinder.pyc	File	19127 bytes	April 10 2024 04:58:47.
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�
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lZejd�jd�Zdd�Zd�Zddddddd�Zd �Zddddddd!�Zeed"�Zeeed#�Zd$Zd%Zd&Zd'Zd
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Module difflib -- helpers for computing deltas between objects.

Function get_close_matches(word, possibilities, n=3, cutoff=0.6):
    Use SequenceMatcher to return list of the best "good enough" matches.

Function context_diff(a, b):
    For two lists of strings, return a delta in context diff format.

Function ndiff(a, b):
    Return a delta: the difference between `a` and `b` (lists of strings).

Function restore(delta, which):
    Return one of the two sequences that generated an ndiff delta.

Function unified_diff(a, b):
    For two lists of strings, return a delta in unified diff format.

Class SequenceMatcher:
    A flexible class for comparing pairs of sequences of any type.

Class Differ:
    For producing human-readable deltas from sequences of lines of text.

Class HtmlDiff:
    For producing HTML side by side comparison with change highlights.
tget_close_matchestndifftrestoretSequenceMatchertDiffertIS_CHARACTER_JUNKtIS_LINE_JUNKtcontext_difftunified_difftHtmlDifftMatchi����N(t
namedtuple(treducesa b sizecCs|rd||SdS(Ng@g�?((tmatchestlength((s/usr/lib64/python2.7/difflib.pyt_calculate_ratio'scBs�eZdZddded�Zd�Zd�Zd�Zd�Z	d�Z
d�Zd	�Zd
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    SequenceMatcher is a flexible class for comparing pairs of sequences of
    any type, so long as the sequence elements are hashable.  The basic
    algorithm predates, and is a little fancier than, an algorithm
    published in the late 1980's by Ratcliff and Obershelp under the
    hyperbolic name "gestalt pattern matching".  The basic idea is to find
    the longest contiguous matching subsequence that contains no "junk"
    elements (R-O doesn't address junk).  The same idea is then applied
    recursively to the pieces of the sequences to the left and to the right
    of the matching subsequence.  This does not yield minimal edit
    sequences, but does tend to yield matches that "look right" to people.

    SequenceMatcher tries to compute a "human-friendly diff" between two
    sequences.  Unlike e.g. UNIX(tm) diff, the fundamental notion is the
    longest *contiguous* & junk-free matching subsequence.  That's what
    catches peoples' eyes.  The Windows(tm) windiff has another interesting
    notion, pairing up elements that appear uniquely in each sequence.
    That, and the method here, appear to yield more intuitive difference
    reports than does diff.  This method appears to be the least vulnerable
    to synching up on blocks of "junk lines", though (like blank lines in
    ordinary text files, or maybe "<P>" lines in HTML files).  That may be
    because this is the only method of the 3 that has a *concept* of
    "junk" <wink>.

    Example, comparing two strings, and considering blanks to be "junk":

    >>> s = SequenceMatcher(lambda x: x == " ",
    ...                     "private Thread currentThread;",
    ...                     "private volatile Thread currentThread;")
    >>>

    .ratio() returns a float in [0, 1], measuring the "similarity" of the
    sequences.  As a rule of thumb, a .ratio() value over 0.6 means the
    sequences are close matches:

    >>> print round(s.ratio(), 3)
    0.866
    >>>

    If you're only interested in where the sequences match,
    .get_matching_blocks() is handy:

    >>> for block in s.get_matching_blocks():
    ...     print "a[%d] and b[%d] match for %d elements" % block
    a[0] and b[0] match for 8 elements
    a[8] and b[17] match for 21 elements
    a[29] and b[38] match for 0 elements

    Note that the last tuple returned by .get_matching_blocks() is always a
    dummy, (len(a), len(b), 0), and this is the only case in which the last
    tuple element (number of elements matched) is 0.

    If you want to know how to change the first sequence into the second,
    use .get_opcodes():

    >>> for opcode in s.get_opcodes():
    ...     print "%6s a[%d:%d] b[%d:%d]" % opcode
     equal a[0:8] b[0:8]
    insert a[8:8] b[8:17]
     equal a[8:29] b[17:38]

    See the Differ class for a fancy human-friendly file differencer, which
    uses SequenceMatcher both to compare sequences of lines, and to compare
    sequences of characters within similar (near-matching) lines.

    See also function get_close_matches() in this module, which shows how
    simple code building on SequenceMatcher can be used to do useful work.

    Timing:  Basic R-O is cubic time worst case and quadratic time expected
    case.  SequenceMatcher is quadratic time for the worst case and has
    expected-case behavior dependent in a complicated way on how many
    elements the sequences have in common; best case time is linear.

    Methods:

    __init__(isjunk=None, a='', b='')
        Construct a SequenceMatcher.

    set_seqs(a, b)
        Set the two sequences to be compared.

    set_seq1(a)
        Set the first sequence to be compared.

    set_seq2(b)
        Set the second sequence to be compared.

    find_longest_match(alo, ahi, blo, bhi)
        Find longest matching block in a[alo:ahi] and b[blo:bhi].

    get_matching_blocks()
        Return list of triples describing matching subsequences.

    get_opcodes()
        Return list of 5-tuples describing how to turn a into b.

    ratio()
        Return a measure of the sequences' similarity (float in [0,1]).

    quick_ratio()
        Return an upper bound on .ratio() relatively quickly.

    real_quick_ratio()
        Return an upper bound on ratio() very quickly.
    tcCs6||_d|_|_||_|j||�dS(s!Construct a SequenceMatcher.

        Optional arg isjunk is None (the default), or a one-argument
        function that takes a sequence element and returns true iff the
        element is junk.  None is equivalent to passing "lambda x: 0", i.e.
        no elements are considered to be junk.  For example, pass
            lambda x: x in " \t"
        if you're comparing lines as sequences of characters, and don't
        want to synch up on blanks or hard tabs.

        Optional arg a is the first of two sequences to be compared.  By
        default, an empty string.  The elements of a must be hashable.  See
        also .set_seqs() and .set_seq1().

        Optional arg b is the second of two sequences to be compared.  By
        default, an empty string.  The elements of b must be hashable. See
        also .set_seqs() and .set_seq2().

        Optional arg autojunk should be set to False to disable the
        "automatic junk heuristic" that treats popular elements as junk
        (see module documentation for more information).
        N(tisjunktNonetatbtautojunktset_seqs(tselfRRRR((s/usr/lib64/python2.7/difflib.pyt__init__�s@		cCs|j|�|j|�dS(s�Set the two sequences to be compared.

        >>> s = SequenceMatcher()
        >>> s.set_seqs("abcd", "bcde")
        >>> s.ratio()
        0.75
        N(tset_seq1tset_seq2(RRR((s/usr/lib64/python2.7/difflib.pyR�s	
cCs0||jkrdS||_d|_|_dS(sMSet the first sequence to be compared.

        The second sequence to be compared is not changed.

        >>> s = SequenceMatcher(None, "abcd", "bcde")
        >>> s.ratio()
        0.75
        >>> s.set_seq1("bcde")
        >>> s.ratio()
        1.0
        >>>

        SequenceMatcher computes and caches detailed information about the
        second sequence, so if you want to compare one sequence S against
        many sequences, use .set_seq2(S) once and call .set_seq1(x)
        repeatedly for each of the other sequences.

        See also set_seqs() and set_seq2().
        N(RRtmatching_blockstopcodes(RR((s/usr/lib64/python2.7/difflib.pyR�s	cCsC||jkrdS||_d|_|_d|_|j�dS(sMSet the second sequence to be compared.

        The first sequence to be compared is not changed.

        >>> s = SequenceMatcher(None, "abcd", "bcde")
        >>> s.ratio()
        0.75
        >>> s.set_seq2("abcd")
        >>> s.ratio()
        1.0
        >>>

        SequenceMatcher computes and caches detailed information about the
        second sequence, so if you want to compare one sequence S against
        many sequences, use .set_seq2(S) once and call .set_seq1(x)
        repeatedly for each of the other sequences.

        See also set_seqs() and set_seq1().
        N(RRRRt
fullbcountt_SequenceMatcher__chain_b(RR((s/usr/lib64/python2.7/difflib.pyRs		cCsP|j}i|_}x9t|�D]+\}}|j|g�}|j|�q#Wt�}|j}|r�x@t|j��D])}||�r}|j	|�||=q}q}Wnt�}t
|�}	|jr4|	dkr4|	dd}
xLt|j��D]5\}}t
|�|
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|_|j
|_dS(Ni�idi(Rtb2jt	enumeratet
setdefaulttappendtsetRtlisttkeystaddtlenRtitemst__contains__tisbjunkt
isbpopular(RRRtitelttindicestjunkRtpopulartntntesttidxs((s/usr/lib64/python2.7/difflib.pyt	__chain_b0s,	
		
	
cCs�|j|j|j|jf\}}}}||d}	}
}i}g}
x�t||�D]�}|j}i}x�|j|||
�D]z}||kr�q�n||kr�Pn||dd�d}||<||kr�||d||d|}	}
}q�q�W|}qZWxm|	|kr}|
|kr}|||
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dkr}|	d|
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}qWx_|	||kr�|
||kr�|||
|�r�||	|||
|kr�|d7}q�Wxl|	|krN|
|krN|||
d�rN||	d||
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}q�Wx^|	||kr�|
||kr�|||
|�r�||	|||
|kr�|d}qRWt|	|
|�S(s�Find longest matching block in a[alo:ahi] and b[blo:bhi].

        If isjunk is not defined:

        Return (i,j,k) such that a[i:i+k] is equal to b[j:j+k], where
            alo <= i <= i+k <= ahi
            blo <= j <= j+k <= bhi
        and for all (i',j',k') meeting those conditions,
            k >= k'
            i <= i'
            and if i == i', j <= j'

        In other words, of all maximal matching blocks, return one that
        starts earliest in a, and of all those maximal matching blocks that
        start earliest in a, return the one that starts earliest in b.

        >>> s = SequenceMatcher(None, " abcd", "abcd abcd")
        >>> s.find_longest_match(0, 5, 0, 9)
        Match(a=0, b=4, size=5)

        If isjunk is defined, first the longest matching block is
        determined as above, but with the additional restriction that no
        junk element appears in the block.  Then that block is extended as
        far as possible by matching (only) junk elements on both sides.  So
        the resulting block never matches on junk except as identical junk
        happens to be adjacent to an "interesting" match.

        Here's the same example as before, but considering blanks to be
        junk.  That prevents " abcd" from matching the " abcd" at the tail
        end of the second sequence directly.  Instead only the "abcd" can
        match, and matches the leftmost "abcd" in the second sequence:

        >>> s = SequenceMatcher(lambda x: x==" ", " abcd", "abcd abcd")
        >>> s.find_longest_match(0, 5, 0, 9)
        Match(a=1, b=0, size=4)

        If no blocks match, return (alo, blo, 0).

        >>> s = SequenceMatcher(None, "ab", "c")
        >>> s.find_longest_match(0, 2, 0, 1)
        Match(a=0, b=0, size=0)
        ii(RRRR*txrangetgetR
(RtalotahitblotbhiRRRR*tbestitbestjtbestsizetj2lentnothingR,tj2lengettnewj2lentjtk((s/usr/lib64/python2.7/difflib.pytfind_longest_match\sB8*	+
$#	$#cCs|jdk	r|jSt|j�t|j�}}d|d|fg}g}x�|r'|j�\}}}}|j||||�\}	}
}}|rS|j|�||	kr�||
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f�n|	||kr$|
||kr$|j|	|||
||f�q$qSqSW|j�d}
}}g}xw|D]o\}}}|
||kr�|||kr�||7}qM|r�|j|
||f�n|||}
}}qMW|r�|j|
||f�n|j||df�t	t
j|�|_|jS(s
Return list of triples describing matching subsequences.

        Each triple is of the form (i, j, n), and means that
        a[i:i+n] == b[j:j+n].  The triples are monotonically increasing in
        i and in j.  New in Python 2.5, it's also guaranteed that if
        (i, j, n) and (i', j', n') are adjacent triples in the list, and
        the second is not the last triple in the list, then i+n != i' or
        j+n != j'.  IOW, adjacent triples never describe adjacent equal
        blocks.

        The last triple is a dummy, (len(a), len(b), 0), and is the only
        triple with n==0.

        >>> s = SequenceMatcher(None, "abxcd", "abcd")
        >>> s.get_matching_blocks()
        [Match(a=0, b=0, size=2), Match(a=3, b=2, size=2), Match(a=5, b=4, size=0)]
        iN(RRR'RRtpopRDR"tsorttmapR
t_make(RtlatlbtqueueRR7R8R9R:R,RBRCtxti1tj1tk1tnon_adjacentti2tj2tk2((s/usr/lib64/python2.7/difflib.pytget_matching_blocks�s8	%
 +
 
cCs|jdk	r|jSd}}g|_}x�|j�D]�\}}}d}||krp||krpd}n*||kr�d}n||kr�d}n|r�|j|||||f�n||||}}|r:|jd||||f�q:q:W|S(sZReturn list of 5-tuples describing how to turn a into b.

        Each tuple is of the form (tag, i1, i2, j1, j2).  The first tuple
        has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
        tuple preceding it, and likewise for j1 == the previous j2.

        The tags are strings, with these meanings:

        'replace':  a[i1:i2] should be replaced by b[j1:j2]
        'delete':   a[i1:i2] should be deleted.
                    Note that j1==j2 in this case.
        'insert':   b[j1:j2] should be inserted at a[i1:i1].
                    Note that i1==i2 in this case.
        'equal':    a[i1:i2] == b[j1:j2]

        >>> a = "qabxcd"
        >>> b = "abycdf"
        >>> s = SequenceMatcher(None, a, b)
        >>> for tag, i1, i2, j1, j2 in s.get_opcodes():
        ...    print ("%7s a[%d:%d] (%s) b[%d:%d] (%s)" %
        ...           (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))
         delete a[0:1] (q) b[0:0] ()
          equal a[1:3] (ab) b[0:2] (ab)
        replace a[3:4] (x) b[2:3] (y)
          equal a[4:6] (cd) b[3:5] (cd)
         insert a[6:6] () b[5:6] (f)
        iRtreplacetdeletetinserttequalN(RRRTR"(RR,RBtanswertaitbjtsizettag((s/usr/lib64/python2.7/difflib.pytget_opcodess$

			#ic

cs�|j�}|sdg}n|dddkr�|d\}}}}}|t|||�|t|||�|f|d<n|dddkr�|d\}}}}}||t|||�|t|||�f|d<n||}g}	x�|D]�\}}}}}|dkr�|||kr�|	j||t|||�|t|||�f�|	Vg}	t|||�t|||�}}n|	j|||||f�q�W|	r�t|	�dko�|	dddkr�|	VndS(s� Isolate change clusters by eliminating ranges with no changes.

        Return a generator of groups with up to n lines of context.
        Each group is in the same format as returned by get_opcodes().

        >>> from pprint import pprint
        >>> a = map(str, range(1,40))
        >>> b = a[:]
        >>> b[8:8] = ['i']     # Make an insertion
        >>> b[20] += 'x'       # Make a replacement
        >>> b[23:28] = []      # Make a deletion
        >>> b[30] += 'y'       # Make another replacement
        >>> pprint(list(SequenceMatcher(None,a,b).get_grouped_opcodes()))
        [[('equal', 5, 8, 5, 8), ('insert', 8, 8, 8, 9), ('equal', 8, 11, 9, 12)],
         [('equal', 16, 19, 17, 20),
          ('replace', 19, 20, 20, 21),
          ('equal', 20, 22, 21, 23),
          ('delete', 22, 27, 23, 23),
          ('equal', 27, 30, 23, 26)],
         [('equal', 31, 34, 27, 30),
          ('replace', 34, 35, 30, 31),
          ('equal', 35, 38, 31, 34)]]
        RXiii����N(RXiiii(R^tmaxtminR"R'(
RR1tcodesR]RMRQRNRRtnntgroup((s/usr/lib64/python2.7/difflib.pytget_grouped_opcodesHs(66
6* -cCs>td�|j�d�}t|t|j�t|j��S(s�Return a measure of the sequences' similarity (float in [0,1]).

        Where T is the total number of elements in both sequences, and
        M is the number of matches, this is 2.0*M / T.
        Note that this is 1 if the sequences are identical, and 0 if
        they have nothing in common.

        .ratio() is expensive to compute if you haven't already computed
        .get_matching_blocks() or .get_opcodes(), in which case you may
        want to try .quick_ratio() or .real_quick_ratio() first to get an
        upper bound.

        >>> s = SequenceMatcher(None, "abcd", "bcde")
        >>> s.ratio()
        0.75
        >>> s.quick_ratio()
        0.75
        >>> s.real_quick_ratio()
        1.0
        cSs||dS(Ni����((tsumttriple((s/usr/lib64/python2.7/difflib.pyt<lambda>�Ri(RRTRR'RR(RR
((s/usr/lib64/python2.7/difflib.pytratiozs	cCs�|jdkrMi|_}x.|jD] }|j|d�d||<q&Wn|j}i}|jd}}xc|jD]X}||�r�||}n|j|d�}|d||<|dkrv|d}qvqvWt|t|j�t|j��S(s�Return an upper bound on ratio() relatively quickly.

        This isn't defined beyond that it is an upper bound on .ratio(), and
        is faster to compute.
        iiN(RRRR6R)RRR'(RRR-tavailtavailhasR
tnumb((s/usr/lib64/python2.7/difflib.pytquick_ratio�s

!	
cCs9t|j�t|j�}}tt||�||�S(s�Return an upper bound on ratio() very quickly.

        This isn't defined beyond that it is an upper bound on .ratio(), and
        is faster to compute than either .ratio() or .quick_ratio().
        (R'RRRR`(RRIRJ((s/usr/lib64/python2.7/difflib.pytreal_quick_ratio�sN(t__name__t
__module__t__doc__RtTrueRRRRRRDRTR^RdRhRlRm(((s/usr/lib64/python2.7/difflib.pyR,sjE			-	,	n	G	72		ig333333�?cCs|dks"td|f��nd|ko9dknsTtd|f��ng}t�}|j|�xm|D]e}|j|�|j�|krw|j�|krw|j�|krw|j|j�|f�qwqwWtj	||�}g|D]\}}|^q�S(s�Use SequenceMatcher to return list of the best "good enough" matches.

    word is a sequence for which close matches are desired (typically a
    string).

    possibilities is a list of sequences against which to match word
    (typically a list of strings).

    Optional arg n (default 3) is the maximum number of close matches to
    return.  n must be > 0.

    Optional arg cutoff (default 0.6) is a float in [0, 1].  Possibilities
    that don't score at least that similar to word are ignored.

    The best (no more than n) matches among the possibilities are returned
    in a list, sorted by similarity score, most similar first.

    >>> get_close_matches("appel", ["ape", "apple", "peach", "puppy"])
    ['apple', 'ape']
    >>> import keyword as _keyword
    >>> get_close_matches("wheel", _keyword.kwlist)
    ['while']
    >>> get_close_matches("apple", _keyword.kwlist)
    []
    >>> get_close_matches("accept", _keyword.kwlist)
    ['except']
    isn must be > 0: %rgg�?s cutoff must be in [0.0, 1.0]: %r(
t
ValueErrorRRRRmRlRhR"theapqtnlargest(twordt
possibilitiesR1tcutofftresulttsRLtscore((s/usr/lib64/python2.7/difflib.pyR�s	


 cCsDdt|�}}x*||kr?|||kr?|d7}qW|S(s}
    Return number of `ch` characters at the start of `line`.

    Example:

    >>> _count_leading('   abc', ' ')
    3
    ii(R'(tlinetchR,R1((s/usr/lib64/python2.7/difflib.pyt_count_leading�s
cBsSeZdZddd�Zd�Zd�Zd�Zd�Zd�Z	d�Z
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    Differ is a class for comparing sequences of lines of text, and
    producing human-readable differences or deltas.  Differ uses
    SequenceMatcher both to compare sequences of lines, and to compare
    sequences of characters within similar (near-matching) lines.

    Each line of a Differ delta begins with a two-letter code:

        '- '    line unique to sequence 1
        '+ '    line unique to sequence 2
        '  '    line common to both sequences
        '? '    line not present in either input sequence

    Lines beginning with '? ' attempt to guide the eye to intraline
    differences, and were not present in either input sequence.  These lines
    can be confusing if the sequences contain tab characters.

    Note that Differ makes no claim to produce a *minimal* diff.  To the
    contrary, minimal diffs are often counter-intuitive, because they synch
    up anywhere possible, sometimes accidental matches 100 pages apart.
    Restricting synch points to contiguous matches preserves some notion of
    locality, at the occasional cost of producing a longer diff.

    Example: Comparing two texts.

    First we set up the texts, sequences of individual single-line strings
    ending with newlines (such sequences can also be obtained from the
    `readlines()` method of file-like objects):

    >>> text1 = '''  1. Beautiful is better than ugly.
    ...   2. Explicit is better than implicit.
    ...   3. Simple is better than complex.
    ...   4. Complex is better than complicated.
    ... '''.splitlines(1)
    >>> len(text1)
    4
    >>> text1[0][-1]
    '\n'
    >>> text2 = '''  1. Beautiful is better than ugly.
    ...   3.   Simple is better than complex.
    ...   4. Complicated is better than complex.
    ...   5. Flat is better than nested.
    ... '''.splitlines(1)

    Next we instantiate a Differ object:

    >>> d = Differ()

    Note that when instantiating a Differ object we may pass functions to
    filter out line and character 'junk'.  See Differ.__init__ for details.

    Finally, we compare the two:

    >>> result = list(d.compare(text1, text2))

    'result' is a list of strings, so let's pretty-print it:

    >>> from pprint import pprint as _pprint
    >>> _pprint(result)
    ['    1. Beautiful is better than ugly.\n',
     '-   2. Explicit is better than implicit.\n',
     '-   3. Simple is better than complex.\n',
     '+   3.   Simple is better than complex.\n',
     '?     ++\n',
     '-   4. Complex is better than complicated.\n',
     '?            ^                     ---- ^\n',
     '+   4. Complicated is better than complex.\n',
     '?           ++++ ^                      ^\n',
     '+   5. Flat is better than nested.\n']

    As a single multi-line string it looks like this:

    >>> print ''.join(result),
        1. Beautiful is better than ugly.
    -   2. Explicit is better than implicit.
    -   3. Simple is better than complex.
    +   3.   Simple is better than complex.
    ?     ++
    -   4. Complex is better than complicated.
    ?            ^                     ---- ^
    +   4. Complicated is better than complex.
    ?           ++++ ^                      ^
    +   5. Flat is better than nested.

    Methods:

    __init__(linejunk=None, charjunk=None)
        Construct a text differencer, with optional filters.

    compare(a, b)
        Compare two sequences of lines; generate the resulting delta.
    cCs||_||_dS(s�
        Construct a text differencer, with optional filters.

        The two optional keyword parameters are for filter functions:

        - `linejunk`: A function that should accept a single string argument,
          and return true iff the string is junk. The module-level function
          `IS_LINE_JUNK` may be used to filter out lines without visible
          characters, except for at most one splat ('#').  It is recommended
          to leave linejunk None; as of Python 2.3, the underlying
          SequenceMatcher class has grown an adaptive notion of "noise" lines
          that's better than any static definition the author has ever been
          able to craft.

        - `charjunk`: A function that should accept a string of length 1. The
          module-level function `IS_CHARACTER_JUNK` may be used to filter out
          whitespace characters (a blank or tab; **note**: bad idea to include
          newline in this!).  Use of IS_CHARACTER_JUNK is recommended.
        N(tlinejunktcharjunk(RR~R((s/usr/lib64/python2.7/difflib.pyRZs	ccst|j||�}x�|j�D]�\}}}}}|dkrd|j||||||�}	n�|dkr�|jd|||�}	n^|dkr�|jd|||�}	n7|dkr�|jd|||�}	ntd|f�x|	D]}
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        Compare two sequences of lines; generate the resulting delta.

        Each sequence must contain individual single-line strings ending with
        newlines. Such sequences can be obtained from the `readlines()` method
        of file-like objects.  The delta generated also consists of newline-
        terminated strings, ready to be printed as-is via the writeline()
        method of a file-like object.

        Example:

        >>> print ''.join(Differ().compare('one\ntwo\nthree\n'.splitlines(1),
        ...                                'ore\ntree\nemu\n'.splitlines(1))),
        - one
        ?  ^
        + ore
        ?  ^
        - two
        - three
        ?  -
        + tree
        + emu
        RURVt-RWt+RXt sunknown tag %rN(RR~R^t_fancy_replacet_dumpRr(RRRtcruncherR]R7R8R9R:tgR{((s/usr/lib64/python2.7/difflib.pytcomparers"!
ccs1x*t||�D]}d|||fVqWdS(s4Generate comparison results for a same-tagged range.s%s %sN(R5(RR]RLtlothiR,((s/usr/lib64/python2.7/difflib.pyR��sccs�||kr||kst�||||kre|jd|||�}|jd|||�}n0|jd|||�}|jd|||�}x*||fD]}	x|	D]}
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Vq�Wq�WdS(NR�R�(tAssertionErrorR�(RRR7R8RR9R:tfirsttsecondR�R{((s/usr/lib64/python2.7/difflib.pyt_plain_replace�s
ccs#d\}}t|j�}	d\}
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}qdqdn|	j|�|	j�|krd|	j�|krd|	j�|krd|	j�||}}}qdqdWq7W||krk|
dkrTx+|j	||||||�D]}|VqAWdS|
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x+|j
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dkr�d}}|	j||�x�|	j�D]�\}}}}}||||}}|dkr<|d|7}|d|7}q�|dkrY|d	|7}q�|d
krv|d|7}q�|dkr�|d
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||d|||d|�D]}|VqWdS(sD
        When replacing one block of lines with another, search the blocks
        for *similar* lines; the best-matching pair (if any) is used as a
        synch point, and intraline difference marking is done on the
        similar pair. Lots of work, but often worth it.

        Example:

        >>> d = Differ()
        >>> results = d._fancy_replace(['abcDefghiJkl\n'], 0, 1,
        ...                            ['abcdefGhijkl\n'], 0, 1)
        >>> print ''.join(results),
        - abcDefghiJkl
        ?    ^  ^  ^
        + abcdefGhijkl
        ?    ^  ^  ^
        g�G�z��?g�?Ng�?RRUt^RVR�RWR�RXR�sunknown tag %rs  i(g�G�z��?g�?(NN(RRRR5RRRmRlRhR�t
_fancy_helperRR^Rrt_qformat(RRR7R8RR9R:t
best_ratioRwR�teqiteqjRBR[R,RZtbest_itbest_jR{taelttbelttatagstbtagsR]tai1tai2tbj1tbj2RIRJ((s/usr/lib64/python2.7/difflib.pyR��s`



%%	%	
"	-c	cs�g}||krZ||kr?|j||||||�}q�|jd|||�}n'||kr�|jd|||�}nx|D]}|Vq�WdS(NR�R�(R�R�(	RRR7R8RR9R:R�R{((s/usr/lib64/python2.7/difflib.pyR�s!
ccs�tt|d�t|d��}t|t|| d��}t|t|| d��}||j�}||j�}d|V|r�dd||fVnd|V|r�dd||fVndS(s�
        Format "?" output and deal with leading tabs.

        Example:

        >>> d = Differ()
        >>> results = d._qformat('\tabcDefghiJkl\n', '\tabcdefGhijkl\n',
        ...                      '  ^ ^  ^      ', '  ^ ^  ^      ')
        >>> for line in results: print repr(line)
        ...
        '- \tabcDefghiJkl\n'
        '? \t ^ ^  ^\n'
        '+ \tabcdefGhijkl\n'
        '? \t ^ ^  ^\n'
        s	R�s- s? %s%s
s+ N(R`R}trstrip(RtalinetblineR�R�tcommon((s/usr/lib64/python2.7/difflib.pyR�s		N(RnRoRpRRR�R�R�R�R�R�(((s/usr/lib64/python2.7/difflib.pyR�s\	)			b	
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    Return 1 for ignorable line: iff `line` is blank or contains a single '#'.

    Examples:

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    True
    >>> IS_LINE_JUNK('  #   \n')
    True
    >>> IS_LINE_JUNK('hello\n')
    False
    N(R(R{tpat((s/usr/lib64/python2.7/difflib.pyRRss 	cCs
||kS(s�
    Return 1 for ignorable character: iff `ch` is a space or tab.

    Examples:

    >>> IS_CHARACTER_JUNK(' ')
    True
    >>> IS_CHARACTER_JUNK('\t')
    True
    >>> IS_CHARACTER_JUNK('\n')
    False
    >>> IS_CHARACTER_JUNK('x')
    False
    ((R|tws((s/usr/lib64/python2.7/difflib.pyRbscCsP|d}||}|dkr-dj|�S|s@|d8}ndj||�S(s Convert range to the "ed" formatis{}s{},{}(tformat(tstarttstopt	beginningR((s/usr/lib64/python2.7/difflib.pyt_format_range_unifiedys



Rs
ccs�t}x�td||�j|�D]}}	|s�t}|rIdj|�nd}
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�}dj|||�Vx�|	D]�\}}}}}|dkr;x|||!D]}d
|Vq"Wq�n|dkrkx!|||!D]}d|VqUWn|dkr�x!|||!D]}d|Vq�Wq�q�Wq"WdS(s�
    Compare two sequences of lines; generate the delta as a unified diff.

    Unified diffs are a compact way of showing line changes and a few
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    defaults to three.

    By default, the diff control lines (those with ---, +++, or @@) are
    created with a trailing newline.  This is helpful so that inputs
    created from file.readlines() result in diffs that are suitable for
    file.writelines() since both the inputs and outputs have trailing
    newlines.

    For inputs that do not have trailing newlines, set the lineterm
    argument to "" so that the output will be uniformly newline free.

    The unidiff format normally has a header for filenames and modification
    times.  Any or all of these may be specified using strings for
    'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'.
    The modification times are normally expressed in the ISO 8601 format.

    Example:

    >>> for line in unified_diff('one two three four'.split(),
    ...             'zero one tree four'.split(), 'Original', 'Current',
    ...             '2005-01-26 23:30:50', '2010-04-02 10:20:52',
    ...             lineterm=''):
    ...     print line                  # doctest: +NORMALIZE_WHITESPACE
    --- Original        2005-01-26 23:30:50
    +++ Current         2010-04-02 10:20:52
    @@ -1,4 +1,4 @@
    +zero
     one
    -two
    -three
    +tree
     four
    s	{}Rs
--- {}{}{}s
+++ {}{}{}ii����iiiis@@ -{} +{} @@{}RXR�RURVR�RWR�N(RURV(RURW(tFalseRRRdRqR�R�(RRtfromfilettofiletfromfiledatet
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c	cstdddddddd�}t}	x�td||�j|�D]�}
|	s�t}	|rjd	j|�nd
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D��rCxT|
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    Compare two sequences of lines; generate the delta as a context diff.

    Context diffs are a compact way of showing line changes and a few
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    defaults to three.

    By default, the diff control lines (those with *** or ---) are
    created with a trailing newline.  This is helpful so that inputs
    created from file.readlines() result in diffs that are suitable for
    file.writelines() since both the inputs and outputs have trailing
    newlines.

    For inputs that do not have trailing newlines, set the lineterm
    argument to "" so that the output will be uniformly newline free.

    The context diff format normally has a header for filenames and
    modification times.  Any or all of these may be specified using
    strings for 'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'.
    The modification times are normally expressed in the ISO 8601 format.
    If not specified, the strings default to blanks.

    Example:

    >>> print ''.join(context_diff('one\ntwo\nthree\nfour\n'.splitlines(1),
    ...       'zero\none\ntree\nfour\n'.splitlines(1), 'Original', 'Current')),
    *** Original
    --- Current
    ***************
    *** 1,4 ****
      one
    ! two
    ! three
      four
    --- 1,4 ----
    + zero
      one
    ! tree
      four
    RWs+ RVs- RUs! RXs  s	{}Rs
*** {}{}{}s
--- {}{}{}ii����s***************iis
*** {} ****{}css*|] \}}}}}|dkVqdS(RURVN(RURV((t.0R]t_((s/usr/lib64/python2.7/difflib.pys	<genexpr>siis
--- {} ----{}css*|] \}}}}}|dkVqdS(RURWN(RURW((R�R]R�((s/usr/lib64/python2.7/difflib.pys	<genexpr>sN(	tdictR�RRRdRqR�R�tany(RRR�R�R�R�R1R�tprefixR�RcR�R�R�R�R�R]RMRQR�R{R�RNRR((s/usr/lib64/python2.7/difflib.pyR�s2+!"	cCst||�j||�S(s�
    Compare `a` and `b` (lists of strings); return a `Differ`-style delta.

    Optional keyword parameters `linejunk` and `charjunk` are for filter
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      return true iff the string is junk.  The default is None, and is
      recommended; as of Python 2.3, an adaptive notion of "noise" lines is
      used that does a good job on its own.

    - charjunk: A function that should accept a string of length 1. The
      default is module-level function IS_CHARACTER_JUNK, which filters out
      whitespace characters (a blank or tab; note: bad idea to include newline
      in this!).

    Tools/scripts/ndiff.py is a command-line front-end to this function.

    Example:

    >>> diff = ndiff('one\ntwo\nthree\n'.splitlines(1),
    ...              'ore\ntree\nemu\n'.splitlines(1))
    >>> print ''.join(diff),
    - one
    ?  ^
    + ore
    ?  ^
    - two
    - three
    ?  -
    + tree
    + emu
    (RR�(RRR~R((s/usr/lib64/python2.7/difflib.pyR"s"c#s�ddl}|jd��t||||��ddg�fd����fd���fd�}|�}|dkr�xOtr�|j�Vq�Wn7|d7}d}x$tr�ddg|}	}
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}|	|}||
|f|
|<|	d7}	q�W|	|kr5d	V|}n|	}d}	x1|rt|	|}|	d7}	|
|V|d8}qDW|d}xJ|r�|j�\}}
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s�Returns generator yielding marked up from/to side by side differences.

    Arguments:
    fromlines -- list of text lines to compared to tolines
    tolines -- list of text lines to be compared to fromlines
    context -- number of context lines to display on each side of difference,
               if None, all from/to text lines will be generated.
    linejunk -- passed on to ndiff (see ndiff documentation)
    charjunk -- passed on to ndiff (see ndiff documentation)

    This function returns an iterator which returns a tuple:
    (from line tuple, to line tuple, boolean flag)

    from/to line tuple -- (line num, line text)
        line num -- integer or None (to indicate a context separation)
        line text -- original line text with following markers inserted:
            '\0+' -- marks start of added text
            '\0-' -- marks start of deleted text
            '\0^' -- marks start of changed text
            '\1' -- marks end of added/deleted/changed text

    boolean flag -- None indicates context separation, True indicates
        either "from" or "to" line contains a change, otherwise False.

    This function/iterator was originally developed to generate side by side
    file difference for making HTML pages (see HtmlDiff class for example
    usage).

    Note, this function utilizes the ndiff function to generate the side by
    side difference markup.  Optional ndiff arguments may be passed to this
    function and they in turn will be passed to ndiff.
    i����Ns
(\++|\-+|\^+)ics)||cd7<|dkr7|||jd�dfS|dkr�|jd�|jd�}}g}|d�}�j||�xS|ddd�D]>\}\}	}
|d|	!d|||	|
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