##// END OF EJS Templates
lfs: only hardlink between the usercache and local store if the blob verifies...
lfs: only hardlink between the usercache and local store if the blob verifies This fixes the issue where verify (and other read commands) would propagate corrupt blobs. I originalled coded this to only hardlink if 'verify=True' for store.read(), but then good blobs weren't being linked, and this broke a bunch of tests. (The blob in repo5 that is being corrupted seems to be linked into repo5 in the loop running dumpflog.py prior to it being corrupted, but only if verify=False is handled too.) It's probably better to do a one time extra verification in order to create these files, so that the repo can be copied to a removable drive. Adding the same check to store.write() was only for completeness, but also needs to do a one time extra verification to avoid breaking tests.

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r31796:e0dc4053 default
r35493:bb6a80fc @10 default
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common.py
88 lines | 2.6 KiB | text/x-python | PythonLexer
import inspect
import io
import os
import types
def make_cffi(cls):
"""Decorator to add CFFI versions of each test method."""
try:
import zstd_cffi
except ImportError:
return cls
# If CFFI version is available, dynamically construct test methods
# that use it.
for attr in dir(cls):
fn = getattr(cls, attr)
if not inspect.ismethod(fn) and not inspect.isfunction(fn):
continue
if not fn.__name__.startswith('test_'):
continue
name = '%s_cffi' % fn.__name__
# Replace the "zstd" symbol with the CFFI module instance. Then copy
# the function object and install it in a new attribute.
if isinstance(fn, types.FunctionType):
globs = dict(fn.__globals__)
globs['zstd'] = zstd_cffi
new_fn = types.FunctionType(fn.__code__, globs, name,
fn.__defaults__, fn.__closure__)
new_method = new_fn
else:
globs = dict(fn.__func__.func_globals)
globs['zstd'] = zstd_cffi
new_fn = types.FunctionType(fn.__func__.func_code, globs, name,
fn.__func__.func_defaults,
fn.__func__.func_closure)
new_method = types.UnboundMethodType(new_fn, fn.im_self,
fn.im_class)
setattr(cls, name, new_method)
return cls
class OpCountingBytesIO(io.BytesIO):
def __init__(self, *args, **kwargs):
self._read_count = 0
self._write_count = 0
return super(OpCountingBytesIO, self).__init__(*args, **kwargs)
def read(self, *args):
self._read_count += 1
return super(OpCountingBytesIO, self).read(*args)
def write(self, data):
self._write_count += 1
return super(OpCountingBytesIO, self).write(data)
_source_files = []
def random_input_data():
"""Obtain the raw content of source files.
This is used for generating "random" data to feed into fuzzing, since it is
faster than random content generation.
"""
if _source_files:
return _source_files
for root, dirs, files in os.walk(os.path.dirname(__file__)):
dirs[:] = list(sorted(dirs))
for f in sorted(files):
try:
with open(os.path.join(root, f), 'rb') as fh:
data = fh.read()
if data:
_source_files.append(data)
except OSError:
pass
return _source_files