Mercurial > hg
view mercurial/similar.py @ 24505:031947baf4d0
run-tests: collect aggregate code coverage
Before this patch, every Python process during a code coverage run was
writing coverage data to the same file. I'm not sure if the coverage
package even tries to obtain a lock on the file. But what I do know is
there was some last write wins leading to loss of code coverage data, at
least with -j > 1.
This patch changes the code coverage mechanism to be multiple process
safe. The mechanism for initializing code coverage via sitecustomize.py
has been tweaked so each Python process will produce a separate coverage
data file on disk. Unless two processes generate the same random value,
there are no race conditions writing to the same file. At the end of the
test run, we combine all written files into an aggregate report.
On my machine, running the full test suite produces a little over
20,000 coverage files consuming ~350 MB. As you can imagine, it takes
several seconds to load and merge these coverage files. But when it is
done, you have an accurate picture of the aggregate code coverage for the
entire test suite, which is ~60% line coverage.
author | Gregory Szorc <gregory.szorc@gmail.com> |
---|---|
date | Sat, 28 Mar 2015 00:47:58 -0700 |
parents | 525fdb738975 |
children | a56c47ed3885 |
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# 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)