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locks; strict;
comment	@# @;


1.3
date	2024.01.14.20.08.33;	author schmonz;	state Exp;
branches;
next	1.2;
commitid	NfpWVNuYiosJisUE;

1.2
date	2015.12.11.13.46.25;	author wiz;	state dead;
branches;
next	1.1;
commitid	ZpJKFzYBpsfBcxMy;

1.1
date	2015.12.02.17.22.57;	author wiz;	state Exp;
branches;
next	;
commitid	LivGgiWJ2m4SGoLy;


desc
@@


1.3
log
@Add distinfo, missed in previous.
@
text
@$NetBSD$

BLAKE2s (py-tlsh-4.7.2.tar.gz) = a61252225f23ad5bfe57a6983468ee137b13e134dfbd6c080d772a35b36e55b5
SHA512 (py-tlsh-4.7.2.tar.gz) = 110d81a0cac6b244255dfeec5cacc3060c8a354b7072d206860cdb577920150483950d6d17bd50db6b4eaf53aa445bfa047312c3c966cc83c107690c5dc5887a
Size (py-tlsh-4.7.2.tar.gz) = 42097 bytes
@


1.2
log
@Update {,py-}tlsh to 3.4.4.

Specify Tlsh::getHash() as a const method
@
text
@d1 1
a1 1
$NetBSD: distinfo,v 1.1 2015/12/02 17:22:57 wiz Exp $
d3 3
a5 4
SHA1 (tlsh-3.4.3.tar.gz) = 0364110b437cec2d90f3df2396b84715f5178d7e
RMD160 (tlsh-3.4.3.tar.gz) = 9921d6d693a5dcccd5db44eb84669790e38215e8
SHA512 (tlsh-3.4.3.tar.gz) = 7e95c2933f25dc4a2700ad2245313d798ee0048e977b0cc3c8f5def258cf0f2372518a916cd9ffb098072aa79ca8f8339532541ca3115ef95520d0ebbb6a7b73
Size (tlsh-3.4.3.tar.gz) = 1411903 bytes
@


1.1
log
@Import py34-tlsh-3.4.3 as devel/py-tlsh.

TLSH is a fuzzy matching library. Given a byte stream with a minimum
length of 256 bytes (and a minimum amount of randomness - see note
in Python extension below), TLSH generates a hash value which can
be used for similarity comparisons.  Similar objects will have
similar hash values which allows for the detection of similar
objects by comparing their hash values.  Note that the byte stream
should have a sufficient amount of complexity.  For example, a byte
stream of identical bytes will not generate a hash value.
@
text
@d1 1
a1 1
$NetBSD$
@