1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281
|
#!/usr/bin/perl -T
use Data::Dumper;
use lib '.'; use lib 't';
use SATest; sa_t_init("bayesdbm_flock");
use constant HAS_DB_FILE => eval { require DB_File };
use Test::More;
plan skip_all => "Long running tests disabled" unless conf_bool('run_long_tests');
plan skip_all => "Tests don't work on windows" if $RUNNING_ON_WINDOWS;
plan skip_all => "DB_File is unavailable" unless HAS_DB_FILE;
plan tests => 48;
tstprefs ("
bayes_learn_to_journal 0
lock_method flock
");
use Mail::SpamAssassin;
my $sa = create_saobj();
$sa->init();
ok($sa);
sub getimpl {
return $sa->call_plugins("learner_get_implementation");
}
ok(getimpl && $sa->{bayes_scanner});
ok(!$sa->{bayes_scanner}->is_scan_available());
open(MAIL,"< data/spam/001");
my $raw_message = do {
local $/;
<MAIL>;
};
close(MAIL);
ok($raw_message);
my $mail = $sa->parse( $raw_message );
ok($mail);
my $body = getimpl->get_body_from_msg($mail);
ok($body);
my $toks = getimpl->tokenize($mail, $body);
ok(scalar(keys %{$toks}) > 0);
my $msgid = $mail->generate_msgid();
my $msgid_hdr = $mail->get_msgid();
# $msgid is the generated hash messageid
# $msgid_hdr is the Message-Id header
ok($msgid eq '71f849915d7e469ddc1890cd8175f6876843f99e@sa_generated');
ok($msgid_hdr eq '9PS291LhupY');
ok(getimpl->{store}->tie_db_writable());
ok(!getimpl->{store}->seen_get($msgid));
getimpl->{store}->untie_db();
alarm(0);
ok($sa->{bayes_scanner}->learn(1, $mail));
ok(!$sa->{bayes_scanner}->learn(1, $mail));
ok(getimpl->{store}->tie_db_writable());
ok(getimpl->{store}->seen_get($msgid) eq 's');
getimpl->{store}->untie_db();
alarm(0);
ok(getimpl->{store}->tie_db_writable());
my $tokerror = 0;
foreach my $tok (keys %{$toks}) {
my ($spam, $ham, $atime) = getimpl->{store}->tok_get($tok);
if ($spam == 0 || $ham > 0) {
$tokerror = 1;
}
}
ok(!$tokerror);
my $tokens = getimpl->{store}->tok_get_all(keys %{$toks});
ok($tokens);
$tokerror = 0;
foreach my $tok (@{$tokens}) {
my ($token, $tok_spam, $tok_ham, $atime) = @{$tok};
if ($tok_spam == 0 || $tok_ham > 0) {
$tokerror = 1;
}
}
ok(!$tokerror);
getimpl->{store}->untie_db();
alarm(0);
ok($sa->{bayes_scanner}->learn(0, $mail));
ok(getimpl->{store}->tie_db_writable());
ok(getimpl->{store}->seen_get($msgid) eq 'h');
getimpl->{store}->untie_db();
alarm(0);
ok(getimpl->{store}->tie_db_writable());
$tokerror = 0;
foreach my $tok (keys %{$toks}) {
my ($spam, $ham, $atime) = getimpl->{store}->tok_get($tok);
if ($spam > 0 || $ham == 0) {
$tokerror = 1;
}
}
ok(!$tokerror);
getimpl->{store}->untie_db();
alarm(0);
ok($sa->{bayes_scanner}->forget($mail));
ok(getimpl->{store}->tie_db_writable());
ok(!getimpl->{store}->seen_get($msgid));
getimpl->{store}->untie_db();
alarm(0);
undef $sa;
sa_t_init('bayesdbm_flock'); # this wipes out what is there and begins anew
# make sure we learn to a journal
tstprefs ("
bayes_learn_to_journal 1
");
$sa = create_saobj();
$sa->init();
ok(!-e "$userstate/bayes_journal");
ok($sa->{bayes_scanner}->learn(1, $mail));
ok(-e "$userstate/bayes_journal");
$sa->{bayes_scanner}->sync(1); # always returns 0, so no need to check return
ok(!-e "$userstate/bayes_journal");
ok(-e "$userstate/bayes_seen");
ok(-e "$userstate/bayes_toks");
undef $sa;
sa_t_init('bayesdbm_flock'); # this wipes out what is there and begins anew
alarm(0); # cancel timer - make sure that alarm is off
# make sure we learn to a journal
tstprefs ("
bayes_learn_to_journal 0
bayes_min_spam_num 10
bayes_min_ham_num 10
");
# we get to bastardize the existing pattern matching code here. It lets us provide
# our own checking callback and keep using the existing ok_all_patterns call
%patterns = ( 1 => 'Acted on message' );
ok(salearnrun("--spam data/spam", \&check_examined));
ok_all_patterns();
ok(salearnrun("--ham data/nice", \&check_examined));
ok_all_patterns();
ok(salearnrun("--ham data/welcomelists", \&check_examined));
ok_all_patterns();
%patterns = ( 'non-token data: bayes db version' => 'db version' );
ok(salearnrun("--dump magic", \&patterns_run_cb));
ok_all_patterns();
use constant SCAN_USING_PERL_CODE_TEST => 1;
# jm: off! not working for some reason. Mind you, this is
# not a supported way to call these APIs! so no biggie
if (SCAN_USING_PERL_CODE_TEST) {
$sa = create_saobj();
$sa->init();
open(MAIL,"< ../sample-nonspam.txt");
$raw_message = do {
local $/;
<MAIL>;
};
close(MAIL);
$mail = $sa->parse( $raw_message );
$body = getimpl->get_body_from_msg($mail);
my $msgstatus = Mail::SpamAssassin::PerMsgStatus->new($sa, $mail);
ok($msgstatus);
my $score = getimpl->scan($msgstatus, $mail, $body);
# Pretty much we can't count on the data returned with such little training
# so just make sure that the score wasn't equal to .5 which is the default
# return value.
print "\treturned score: $score\n";
ok($score =~ /\d/ && $score <= 1.0 && $score != .5);
open(MAIL,"< ../sample-spam.txt");
$raw_message = do {
local $/;
<MAIL>;
};
close(MAIL);
$mail = $sa->parse( $raw_message );
$body = getimpl->get_body_from_msg($mail);
$msgstatus = Mail::SpamAssassin::PerMsgStatus->new($sa, $mail);
$score = getimpl->scan($msgstatus, $mail, $body);
# Pretty much we can't count on the data returned with such little training
# so just make sure that the score wasn't equal to .5 which is the default
# return value.
print "\treturned score: $score\n";
ok($score =~ /\d/ && $score <= 1.0 && $score != .5);
}
ok(getimpl->{store}->clear_database());
ok(!-e "$userstate/bayes_journal");
ok(!-e "$userstate/bayes_seen");
ok(!-e "$userstate/bayes_toks");
sub check_examined {
local ($_);
my $string = shift;
if (defined $string) {
$_ = $string;
} else {
$_ = join ('', <IN>);
}
if ($_ =~ /(?:Forgot|Learned) tokens from \d+ message\(s\) \(\d+ message\(s\) examined\)/) {
$found{'Acted on message'}++;
}
}
|