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tests: use time.time() for relative start and stop times...
tests: use time.time() for relative start and stop times os.times() does not work on Windows. This was resulting in the test start, stop, and duration times being reported as 0. This commit swaps in time.time() for wall clock measurements. This isn't ideal, as time.time() is not monotonic. But Python 2.7 does not have a monotonic timer that works on Windows. So it is the best we have which is trivially usable. And test times aren't terribly important, so variances due to clock skew are arguably acceptable. Differential Revision: https://phab.mercurial-scm.org/D7126

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similar.py
133 lines | 4.0 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 __future__ import absolute_import
from .i18n import _
from . import (
mdiff,
pycompat,
)
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.
'''
# Build table of removed files: {hash(fctx.data()): [fctx, ...]}.
# We use hash() to discard fctx.data() from memory.
hashes = {}
progress = repo.ui.makeprogress(
_(b'searching for exact renames'),
total=(len(added) + len(removed)),
unit=_(b'files'),
)
for fctx in removed:
progress.increment()
h = hash(fctx.data())
if h not in hashes:
hashes[h] = [fctx]
else:
hashes[h].append(fctx)
# For each added file, see if it corresponds to a removed file.
for fctx in added:
progress.increment()
adata = fctx.data()
h = hash(adata)
for rfctx in hashes.get(h, []):
# compare between actual file contents for exact identity
if adata == rfctx.data():
yield (rfctx, fctx)
break
# Done
progress.complete()
def _ctxdata(fctx):
# lazily load text
orig = fctx.data()
return orig, mdiff.splitnewlines(orig)
def _score(fctx, otherdata):
orig, lines = otherdata
text = fctx.data()
# mdiff.blocks() returns blocks of matching lines
# count the number of bytes in each
equal = 0
matches = mdiff.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
def score(fctx1, fctx2):
return _score(fctx1, _ctxdata(fctx2))
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 = {}
progress = repo.ui.makeprogress(
_(b'searching for similar files'), unit=_(b'files'), total=len(removed)
)
for r in removed:
progress.increment()
data = None
for a in added:
bestscore = copies.get(a, (None, threshold))[1]
if data is None:
data = _ctxdata(r)
myscore = _score(a, data)
if myscore > bestscore:
copies[a] = (r, myscore)
progress.complete()
for dest, v in pycompat.iteritems(copies):
source, bscore = v
yield source, dest, bscore
def _dropempty(fctxs):
return [x for x in fctxs if x.size() > 0]
def findrenames(repo, added, removed, threshold):
'''find renamed files -- yields (before, after, score) tuples'''
wctx = repo[None]
pctx = wctx.p1()
# 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 = _dropempty(wctx[fp] for fp in sorted(added))
removedfiles = _dropempty(pctx[fp] for fp in sorted(removed) if fp in pctx)
# Find exact matches.
matchedfiles = set()
for (a, b) in _findexactmatches(repo, addedfiles, removedfiles):
matchedfiles.add(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:
addedfiles = [x for x in addedfiles if x not in matchedfiles]
for (a, b, score) in _findsimilarmatches(
repo, addedfiles, removedfiles, threshold
):
yield (a.path(), b.path(), score)