##// END OF EJS Templates
tests: add a module that can perform the equivalent of `SIGKILL` on any OS...
tests: add a module that can perform the equivalent of `SIGKILL` on any OS I started with this being Windows specific, but let's push all of the decision making into this function so that it can just be called by the tests. The tradeoff is that this is very specific to sending `SIGKILL`- since `signal.SIGKILL` doesn't exist on Windows, the desired signal can't be passed from the caller. Maybe there's a way, but let's wait until there's a need. We don't use `killdaemons.py` unconditionally because it starts with a more graceful `SIGTERM` on posix.

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similar.py
132 lines | 3.9 KiB | text/x-python | PythonLexer
# similar.py - mechanisms for finding similar files
#
# Copyright 2005-2007 Olivia Mackall <olivia@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 annotations
from .i18n import _
from . import (
mdiff,
)
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 copies.items():
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)