move find-german-comments from build repo to bootstrap/bin

This commit is contained in:
Miklos Vajna 2011-01-06 13:29:00 +01:00
parent 9b7439f870
commit 7be59837a9
7 changed files with 1718 additions and 0 deletions

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#!/usr/bin/env python
########################################################################
#
# Copyright (c) 2010 Jonas Jensen, Miklos Vajna
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation
# files (the "Software"), to deal in the Software without
# restriction, including without limitation the rights to use,
# copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following
# conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
#
########################################################################
import sys, re, subprocess, os, optparse, string
class Parser:
"""
This parser extracts comments from source files, tries to guess
their language and then prints out the german ones.
"""
def __init__(self):
self.strip = string.punctuation + " \n"
op = optparse.OptionParser()
op.set_usage("%prog [options] <rootdir>\n\n" +
"Searches for german comments in cxx/hxx source files inside a given root\n" +
"directory recursively.")
op.add_option("-v", "--verbose", action="store_true", dest="verbose", default=False,
help="Turn on verbose mode (print progress to stderr)")
self.options, args = op.parse_args()
try:
dir = args[0]
except IndexError:
dir = "."
self.check_source_files(dir)
def get_comments(self, filename):
"""
Extracts the source code comments.
"""
linenum = 0
if self.options.verbose:
sys.stderr.write("processing file '%s'...\n" % filename)
sock = open(filename)
# add an empty line to trigger the output of collected oneliner
# comment group
lines = sock.readlines() + ["\n"]
sock.close()
in_comment = False
buf = []
count = 1
for i in lines:
if "//" in i and not in_comment:
# if we find a new //-style comment, then we
# just append it to a previous one if: there is
# only whitespace before the // mark that is
# necessary to make comments longer, giving
# more reliable output
if not len(re.sub("(.*)//.*", r"\1", i).strip(self.strip)):
s = re.sub(".*// ?", "", i).strip(self.strip)
if len(s):
buf.append(s)
else:
# otherwise it's an independent //-style comment in the next line
yield (count, "\n ".join(buf))
buf = [re.sub(".*// ?", "", i.strip(self.strip))]
elif "//" not in i and not in_comment and len(buf) > 0:
# first normal line after a // block
yield (count, "\n ".join(buf))
buf = []
elif "/*" in i and "*/" not in i and not in_comment:
# start of a real multiline comment
in_comment = True
linenum = count
s = re.sub(".*/\*+", "", i.strip(self.strip))
if len(s):
buf.append(s.strip(self.strip))
elif in_comment and not "*/" in i:
# in multiline comment
s = re.sub("^( |\|)*\*?", "", i)
if len(s.strip(self.strip)):
buf.append(s.strip(self.strip))
elif "*/" in i and in_comment:
# end of multiline comment
in_comment = False
s = re.sub(r"\*+/.*", "", i.strip(self.strip))
if len(s):
buf.append(s)
yield (count, "\n ".join(buf))
buf = []
elif "/*" in i and "*/" in i:
# c-style oneliner comment
yield (count, re.sub(".*/\*(.*)\*/.*", r"\1", i).strip(self.strip))
count += 1
def get_lang(self, s):
""" the output is 'german' or 'english' or 'german or english'. when
unsure, just don't warn, there are strings where you just can't
teremine the results reliably, like '#110680#' """
cwd = os.getcwd()
# change to our directory
os.chdir(os.path.split(os.path.abspath(sys.argv[0]))[0])
sock = subprocess.Popen(["text_cat/text_cat", "-d", "text_cat/LM"], stdin=subprocess.PIPE, stdout=subprocess.PIPE)
sock.stdin.write(s)
sock.stdin.close()
lang = sock.stdout.read().strip()
sock.stdout.close()
os.chdir(cwd)
return lang
def is_german(self, s):
"""
determines if a string is german or not
"""
# for short strings we can't do reliable recognition, so skip
# short strings and less than 4 words
s = s.replace('\n', ' ')
if len(s) < 32 or len(s.split()) < 4:
return False
return "german" == self.get_lang(s)
def check_file(self, path):
"""
checks each comment in a file
"""
for linenum, s in self.get_comments(path):
if self.is_german(s):
print "%s:%s: %s" % (path, linenum, s)
def check_source_files(self, dir):
"""
checks each _tracked_ file in a directory recursively
"""
sock = os.popen(r"git ls-files '%s' |egrep '\.(c|h)xx$'" % dir)
lines = sock.readlines()
sock.close()
for path in lines:
self.check_file(path.strip())
try:
Parser()
except KeyboardInterrupt:
print "Interrupted!"
sys.exit(0)
# vim:set shiftwidth=4 softtabstop=4 expandtab:

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License along with this library; if not, write to the
Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston,
MA 02110-1301 USA
cf. the file COPYING

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_ 20326
e 6617
t 4843
o 3834
n 3653
i 3602
a 3433
s 2945
r 2921
h 2507
e_ 2000
d 1816
_t 1785
c 1639
l 1635
th 1535
he 1351
_th 1333
u 1309
f 1253
m 1175
p 1151
_a 1145
the 1142
_the 1060
s_ 978
er 968
_o 967
he_ 928
d_ 888
t_ 885
the_ 844
_the_ 843
on 842
in 817
y 783
n_ 773
b 761
re 754
, 734
,_ 732
an 732
g 728
w 718
_i 707
en 676
f_ 599
y_ 595
of 594
_of 592
es 589
ti 587
v 580
_of_ 575
of_ 575
nd 568
at 549
r_ 540
_w 534
it 522
ed 496
_p 494
nt 485
_c 462
o_ 457
io 450
_an 439
te 432
or 425
_b 418
nd_ 407
to 406
st 402
is 401
_s 396
_in 389
ion 385
and 385
de 384
ve 382
ha 375
ar 366
_m 361
and_ 360
_and 360
_and_ 358
se 353
_to 347
me 346
to_ 344
ed_ 339
. 330
be 329
_f 329
._ 329
_to_ 320
co 317
ic 316
ns 308
al 307
le 304
ou 304
ce 293
ent 279
l_ 278
_co 277
tio 275
on_ 274
_d 274
tion 268
ri 266
_e 264
ng 253
hi 251
er_ 249
ea 246
as 245
_be 242
pe 242
h_ 234
_r 232
ec 227
ch 223
ro 222
ct 220
_h 219
pr 217
in_ 217
ne 214
ll 214
rt 213
s,_ 210
s, 210
li 209
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wh 204
a_ 203
ac 201
_wh 199
_n 196
ts 196
di 196
es_ 195
si 194
re_ 193
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ing 184
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or_ 136
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ate 135
ter 134
it_ 134
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that_ 132
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el 128
as_ 127
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no 124
ment 124
an_ 124
tion_ 122
su 122
bl 122
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nce 120
pl 120
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tr 118
so 118
int 115
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e, 114
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_u 113
ent_ 113
Th 113
her 113
j 112
atio 112
ation 112
_Th 111
le_ 110
ai 110
_it_ 110
_on 110
_for 109
ect 109
k 109
hic 108
est 108
der 107
tu 107
na 106
_by_ 106
by_ 106
E 106
by 106
_by 106
ve_ 106
_di 106
en_ 104
vi 104
m_ 103
_whi 102
iv 102
whi 102
ns_ 102
_A 101
ich 100
ge 100
pro 99
ess 99
_whic 99
ers 99
hich 99
ce_ 99
which 99
whic 99
all 98
ove 98
_is 98
ich_ 97
ee 97
hich_ 97
n,_ 96
n, 96
im 95
ir_ 94
hei 94
ions 94
sti 94
se_ 94
per 93
The 93
_pa 93
heir 93
id 93
eir 93
eir_ 93
ig 93
heir_ 93
_no 93
ev 93
era 92
_int 92
ted 91
_The 91
ies 91
art 91
thei 90
_ar 90
_thei 90
their 90
_pro 90
et 89
_pe 88
_mo 88
ther 88
x 87
gh 87
S 87
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ol 87
ty_ 87
_I 86
nde 86
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mp 85
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par 84
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pu 82
his 82
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mi 82
go 81
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ab 80
;_ 80
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ex 80
ain 80
over 80
_un 79
q 79
qu 79
pp 79
ith 79
ry 79
_as 79
ber 79
ub 78
av 78
uc 78
s._ 77
s. 77
enc 77
are 77
iti 77
gr 76
his_ 76
ua 76
part 76
ff 75
eve 75
O 75
rea 74
ous 74
ia 74
The_ 73
ag 73
mb 73
_go 73
fa 72
on,_ 72
ern 72
t,_ 72
on, 72
t, 72
_me 71

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_ 31586
e 15008
n 9058
i 7299
r 6830
t 5662
s 5348
a 4618
h 4176
d 4011
er 3415
en 3412
u 3341
l 3266
n_ 2848
c 2636
ch 2460
g 2407
o 2376
e_ 2208
r_ 2128
m 2077
_d 1948
de 1831
en_ 1786
ei 1718
er_ 1570
in 1568
te 1505
ie 1505
b 1458
t_ 1425
f 1306
k 1176
ge 1144
s_ 1137
un 1113
, 1104
,_ 1099
w 1099
z 1060
nd 1039
he 1004
st 989
_s 952
_de 949
. 909
_e 906
ne 906
der 880
._ 847
be 841
es 829
ic 796
_a 791
ie_ 779
is 769
ich 763
an 755
re 749
di 732
ein 730
se 730
" 720
ng 709
_i 706
sc 683
sch 681
it 673
der_ 652
h_ 651
ch_ 642
S 630
le 609
p 609
ä 607
ü 603
au 603
v 602
che 599
_w 596
d_ 585
die 576
_di 572
m_ 562
_die 559
el 548
_S 540
_der 529
li 527
_der_ 523
si 515
al 514
ns 507
on 501
or 495
ti 490
ten 487
ht 486
die_ 485
_die_ 483
D 479
rt 478
nd_ 476
_u 470
nt 468
A 466
in_ 464
den 461
cht 447
und 443
me 440
_z 429
ung 426
ll 423
_un 421
_ei 419
_n 415
hr 412
ine 412
_A 408
_ein 405
ar 404
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_v 400
_g 400
as 395
zu 392
et 389
em 385
_D 380
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gen 376
g_ 376
da 368
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K 365
lt 360
B 354
_" 353
nde 349
ni 347
und_ 345
E 345
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_m 342
ri 341
ha 340
eh 339
ten_ 338
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_K 336
_und 335
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_und_ 332
_au 329
_B 327
_da 325
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at 321
us 318
wi 307
n, 305
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nn 304
te_ 301
eit 301
_h 300
ter 299
M 298
n. 295
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ng_ 289
sche 289
- 283
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_si 280
G 280
im 278
_ge 277
chen 276
rd 273
_E 273
n._ 270
icht 270
rn 268
uf 267
isch 264
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_in_ 262
_M 260
_er 257
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ac 253
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_G 252
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la 251
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F 248
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lich 243
ste 243
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_k 241
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_f 241
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_be 239
it_ 239
L 238
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P 235
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W 226
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sich 183
sic 183
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gen_ 180
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t._ 177
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mm 173
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_nich 139
eine_ 139
oc 138
wei 138
io 138
schen 138
gt 138

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#!/usr/bin/perl -w
# © Gertjan van Noord, 1997.
# mailto:vannoord@let.rug.nl
use strict;
use vars qw($opt_d $opt_f $opt_h $opt_i $opt_l $opt_n $opt_s $opt_t $opt_v $opt_u $opt_a);
use Getopt::Std;
use Benchmark;
my $non_word_characters='0-9\s';
# OPTIONS
getopts('a:d:f:hi:lnst:u:v');
# defaults: set $opt_X unless already defined (Perl Cookbook p. 6):
$opt_a ||= 10;
$opt_d ||= '/users1/vannoord/Perl/TextCat/LM';
$opt_f ||= 0;
$opt_t ||= 400;
$opt_u ||= 1.05;
sub help {
print <<HELP
Text Categorization. Typically used to determine the language of a
given document.
Usage
-----
* print help message:
$0 -h
* for guessing:
$0 [-a Int] [-d Dir] [-f Int] [-i N] [-l] [-t Int] [-u Int] [-v]
-a the program returns the best-scoring language together
with all languages which are $opt_u times worse (cf option -u).
If the number of languages to be printed is larger than the value
of this option (default: $opt_a) then no language is returned, but
instead a message that the input is of an unknown language is
printed. Default: $opt_a.
-d indicates in which directory the language models are
located (files ending in .lm). Currently only a single
directory is supported. Default: $opt_d.
-f Before sorting is performed the Ngrams which occur this number
of times or less are removed. This can be used to speed up
the program for longer inputs. For short inputs you should use
-f 0.
Default: $opt_f.
-i N only read first N lines
-l indicates that input is given as an argument on the command line,
e.g. text_cat -l "this is english text"
Cannot be used in combination with -n.
-s Determine language of each line of input. Not very efficient yet,
because language models are re-loaded after each line.
-t indicates the topmost number of ngrams that should be used.
If used in combination with -n this determines the size of the
output. If used with categorization this determines
the number of ngrams that are compared with each of the language
models (but each of those models is used completely).
-u determines how much worse result must be in order not to be
mentioned as an alternative. Typical value: 1.05 or 1.1.
Default: $opt_u.
-v verbose. Continuation messages are written to standard error.
* for creating new language model, based on text read from standard input:
$0 -n [-v]
-v verbose. Continuation messages are written to standard error.
HELP
}
if ($opt_h) { help(); exit 0; };
if ($opt_n) {
my %ngram=();
my @result = create_lm(input(),\%ngram);
print join("\n",map { "$_\t $ngram{$_}" ; } @result),"\n";
} elsif ($opt_l) {
classify($ARGV[0]);
} elsif ($opt_s) {
while (<>) {
chomp;
classify($_);
}
} else {
classify(input());
}
# CLASSIFICATION
sub classify {
my ($input)=@_;
my %results=();
my $maxp = $opt_t;
# open directory to find which languages are supported
opendir DIR, "$opt_d" or die "directory $opt_d: $!\n";
my @languages = sort(grep { s/\.lm// && -r "$opt_d/$_.lm" } readdir(DIR));
closedir DIR;
@languages or die "sorry, can't read any language models from $opt_d\n" .
"language models must reside in files with .lm ending\n";
# create ngrams for input. Note that hash %unknown is not used;
# it contains the actual counts which are only used under -n: creating
# new language model (and even then they are not really required).
my @unknown=create_lm($input);
# load model and count for each language.
my $language;
my $t1 = new Benchmark;
foreach $language (@languages) {
# loads the language model into hash %$language.
my %ngram=();
my $rang=1;
open(LM,"$opt_d/$language.lm") || die "cannot open $language.lm: $!\n";
while (<LM>) {
chomp;
# only use lines starting with appropriate character. Others are
# ignored.
if (/^[^$non_word_characters]+/o) {
$ngram{$&} = $rang++;
}
}
close(LM);
#print STDERR "loaded language model $language\n" if $opt_v;
# compares the language model with input ngrams list
my ($i,$p)=(0,0);
while ($i < @unknown) {
if ($ngram{$unknown[$i]}) {
$p=$p+abs($ngram{$unknown[$i]}-$i);
} else {
$p=$p+$maxp;
}
++$i;
}
#print STDERR "$language: $p\n" if $opt_v;
$results{$language} = $p;
}
print STDERR "read language models done (" .
timestr(timediff(new Benchmark, $t1)) .
".\n" if $opt_v;
my @results = sort { $results{$a} <=> $results{$b} } keys %results;
print join("\n",map { "$_\t $results{$_}"; } @results),"\n" if $opt_v;
my $a = $results{$results[0]};
my @answers=(shift(@results));
while (@results && $results{$results[0]} < ($opt_u *$a)) {
@answers=(@answers,shift(@results));
}
if (@answers > $opt_a) {
print "I don't know; " .
"Perhaps this is a language I haven't seen before?\n";
} else {
print join(" or ", @answers), "\n";
}
}
# first and only argument is reference to hash.
# this hash is filled, and a sorted list (opt_n elements)
# is returned.
sub input {
my $read="";
if ($opt_i) {
while(<>) {
if ($. == $opt_i) {
return $read . $_;
}
$read = $read . $_;
}
return $read;
} else {
local $/; # so it doesn't affect $/ elsewhere
undef $/;
$read = <>; # swallow input.
$read || die "determining the language of an empty file is hard...\n";
return $read;
}
}
sub create_lm {
my $t1 = new Benchmark;
my $ngram;
($_,$ngram) = @_; #$ngram contains reference to the hash we build
# then add the ngrams found in each word in the hash
my $word;
foreach $word (split("[$non_word_characters]+")) {
$word = "_" . $word . "_";
my $len = length($word);
my $flen=$len;
my $i;
for ($i=0;$i<$flen;$i++) {
$$ngram{substr($word,$i,5)}++ if $len > 4;
$$ngram{substr($word,$i,4)}++ if $len > 3;
$$ngram{substr($word,$i,3)}++ if $len > 2;
$$ngram{substr($word,$i,2)}++ if $len > 1;
$$ngram{substr($word,$i,1)}++;
$len--;
}
}
###print "@{[%$ngram]}";
my $t2 = new Benchmark;
print STDERR "count_ngrams done (".
timestr(timediff($t2, $t1)) .").\n" if $opt_v;
# as suggested by Karel P. de Vos, k.vos@elsevier.nl, we speed up
# sorting by removing singletons
map { my $key=$_; if ($$ngram{$key} <= $opt_f)
{ delete $$ngram{$key}; }; } keys %$ngram;
#however I have very bad results for short inputs, this way
# sort the ngrams, and spit out the $opt_t frequent ones.
# adding `or $a cmp $b' in the sort block makes sorting five
# times slower..., although it would be somewhat nicer (unique result)
my @sorted = sort { $$ngram{$b} <=> $$ngram{$a} } keys %$ngram;
splice(@sorted,$opt_t) if (@sorted > $opt_t);
print STDERR "sorting done (" .
timestr(timediff(new Benchmark, $t2)) .
").\n" if $opt_v;
return @sorted;
}

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1.10