##// END OF EJS Templates
parsers: inline fields of dirstate values in C version...
parsers: inline fields of dirstate values in C version Previously, while unpacking the dirstate we'd create 3-4 new CPython objects for most dirstate values: - the state is a single character string, which is pooled by CPython - the mode is a new object if it isn't 0 due to being in the lookup set - the size is a new object if it is greater than 255 - the mtime is a new object if it isn't -1 due to being in the lookup set - the tuple to contain them all In some cases such as regular hg status, we actually look at all the objects. In other cases like hg add, hg status for a subdirectory, or hg status with the third-party hgwatchman enabled, we look at almost none of the objects. This patch eliminates most object creation in these cases by defining a custom C struct that is exposed to Python with an interface similar to a tuple. Only when tuple elements are actually requested are the respective objects created. The gains, where they're expected, are significant. The following tests are run against a working copy with over 270,000 files. parse_dirstate becomes significantly faster: $ hg perfdirstate before: wall 0.186437 comb 0.180000 user 0.160000 sys 0.020000 (best of 35) after: wall 0.093158 comb 0.100000 user 0.090000 sys 0.010000 (best of 95) and as a result, several commands benefit: $ time hg status # with hgwatchman enabled before: 0.42s user 0.14s system 99% cpu 0.563 total after: 0.34s user 0.12s system 99% cpu 0.471 total $ time hg add new-file before: 0.85s user 0.18s system 99% cpu 1.033 total after: 0.76s user 0.17s system 99% cpu 0.931 total There is a slight regression in regular status performance, but this is fixed in an upcoming patch.

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similar.py
104 lines | 3.6 KiB | text/x-python | PythonLexer
# similar.py - mechanisms for finding similar files
#
# Copyright 2005-2007 Matt Mackall <mpm@selenic.com>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
from i18n import _
import util
import mdiff
import bdiff
def _findexactmatches(repo, added, removed):
'''find renamed files that have no changes
Takes a list of new filectxs and a list of removed filectxs, and yields
(before, after) tuples of exact matches.
'''
numfiles = len(added) + len(removed)
# Get hashes of removed files.
hashes = {}
for i, fctx in enumerate(removed):
repo.ui.progress(_('searching for exact renames'), i, total=numfiles)
h = util.sha1(fctx.data()).digest()
hashes[h] = fctx
# For each added file, see if it corresponds to a removed file.
for i, fctx in enumerate(added):
repo.ui.progress(_('searching for exact renames'), i + len(removed),
total=numfiles)
h = util.sha1(fctx.data()).digest()
if h in hashes:
yield (hashes[h], fctx)
# Done
repo.ui.progress(_('searching for exact renames'), None)
def _findsimilarmatches(repo, added, removed, threshold):
'''find potentially renamed files based on similar file content
Takes a list of new filectxs and a list of removed filectxs, and yields
(before, after, score) tuples of partial matches.
'''
copies = {}
for i, r in enumerate(removed):
repo.ui.progress(_('searching for similar files'), i,
total=len(removed))
# lazily load text
@util.cachefunc
def data():
orig = r.data()
return orig, mdiff.splitnewlines(orig)
def score(text):
orig, lines = data()
# bdiff.blocks() returns blocks of matching lines
# count the number of bytes in each
equal = 0
matches = bdiff.blocks(text, orig)
for x1, x2, y1, y2 in matches:
for line in lines[y1:y2]:
equal += len(line)
lengths = len(text) + len(orig)
return equal * 2.0 / lengths
for a in added:
bestscore = copies.get(a, (None, threshold))[1]
myscore = score(a.data())
if myscore >= bestscore:
copies[a] = (r, myscore)
repo.ui.progress(_('searching'), None)
for dest, v in copies.iteritems():
source, score = v
yield source, dest, score
def findrenames(repo, added, removed, threshold):
'''find renamed files -- yields (before, after, score) tuples'''
parentctx = repo['.']
workingctx = repo[None]
# Zero length files will be frequently unrelated to each other, and
# tracking the deletion/addition of such a file will probably cause more
# harm than good. We strip them out here to avoid matching them later on.
addedfiles = set([workingctx[fp] for fp in added
if workingctx[fp].size() > 0])
removedfiles = set([parentctx[fp] for fp in removed
if fp in parentctx and parentctx[fp].size() > 0])
# Find exact matches.
for (a, b) in _findexactmatches(repo,
sorted(addedfiles), sorted(removedfiles)):
addedfiles.remove(b)
yield (a.path(), b.path(), 1.0)
# If the user requested similar files to be matched, search for them also.
if threshold < 1.0:
for (a, b, score) in _findsimilarmatches(repo,
sorted(addedfiles), sorted(removedfiles), threshold):
yield (a.path(), b.path(), score)