From 3a2e9f224dc8198cd71fd86a599724eb021cb072 Mon Sep 17 00:00:00 2001 From: Tal Einat Date: Tue, 12 Nov 2013 10:58:41 +0200 Subject: [PATCH] bumped version and updated docs --- HISTORY.rst | 8 ++++++++ README.rst | 18 +++++++++++++++++- setup.py | 4 ++-- 3 files changed, 27 insertions(+), 3 deletions(-) diff --git a/HISTORY.rst b/HISTORY.rst index 23186fb..6f75f3e 100644 --- a/HISTORY.rst +++ b/HISTORY.rst @@ -3,6 +3,14 @@ History ------- +0.1.0 (2013-11-01) +++++++++++++++++++ + +* Two working implementations +* Extensive test suite; all tests passing +* Full support for Python 2.6-2.7 and 3.1-3.3 +* Bumped status from Pre-Alpha to Alpha + 0.0.1 (2013-11-01) ++++++++++++++++++ diff --git a/README.rst b/README.rst index d914d7e..09da260 100644 --- a/README.rst +++ b/README.rst @@ -20,4 +20,20 @@ fuzzysearch is useful for finding approximate subsequence matches Features -------- -* TODO \ No newline at end of file +* Fuzzy sub-sequence search: Find parts of a sequence which match a given sub-sequence up to a given maximum Levenshtein distance. + +Example +------- +.. code:: python + + >>> sequence = '''\ + GACTAGCACTGTAGGGATAACAATTTCACACAGGTGGACAATTACATTGAAAATCACAGATTGGTCACACACACA + TTGGACATACATAGAAACACACACACATACATTAGATACGAACATAGAAACACACATTAGACGCGTACATAGACA + CAAACACATTGACAGGCAGTTCAGATGATGACGCCCGACTGATACTCGCGTAGTCGTGGGAGGCAAGGCACACAG + GGGATAGG''' + >>> subsequence = 'TGCACTGTAGGGATAACAAT' #distance 1 + >>> max_distance = 2 + + >>> from fuzzysearch import find_near_matches_with_ngrams + >>> find_near_matches_with_ngrams(subsequence, sequence, max_distance) + [Match(start=3, end=24, dist=1)] diff --git a/setup.py b/setup.py index 1890fc8..8c85bf7 100644 --- a/setup.py +++ b/setup.py @@ -19,7 +19,7 @@ history = open('HISTORY.rst').read().replace('.. :changelog:', '') setup( name='fuzzysearch', - version='0.0.1', + version='0.1.0', description='fuzzysearch is useful for finding approximate subsequence matches', long_description=readme + '\n\n' + history, author='Tal Einat', @@ -37,7 +37,7 @@ setup( zip_safe=False, keywords='fuzzysearch', classifiers=[ - 'Development Status :: 2 - Pre-Alpha', + 'Development Status :: 3 - Alpha', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English',