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nodemap: also use persistent nodemap for manifest...
nodemap: also use persistent nodemap for manifest The manifest as a different usage pattern than the changelog. First, while the lookup in changelog are not garanteed to match, the lookup in the manifest nodemap come from changelog and will exist in the manifest. In addition, looking up a manifest almost always result in unpacking a manifest an operation that rarely come cheap. Nevertheless, using a persistent nodemap provide a significant gain for some operations. For our measurementw, we use `hg cat --rev REV FILE` on the our reference mozilla-try. On this repository the persistent nodemap cache is about 29 MB in side for a total store side of 11,988 MB File with large history (file: b2g/config/gaia.json, revision: 195a1146daa0) no optimisation: 0.358s using mmap for index: 0.297s (-0.061s) persistent nodemap for changelog only: 0.275s (-0.024s) persistent nodemap for manifest too: 0.258s (-0.017s) File with small history (file: .hgignore, revision: 195a1146daa0) no optimisation: 0.377s using mmap for index: 0.296s (-0.061s) persistent nodemap for changelog only: 0.274s (-0.022s) persistent nodemap for manifest too: 0.257s (-0.017s) Same file but using a revision (8ba995b74e18) with a smaller manifest (3944829 bytes vs 10 bytes) no optimisation: 0.192s (-0.185s) using mmap for index: 0.131s (-0.061s) persistent nodemap for changelog only: 0.106s (-0.025s) persistent nodemap for manifest too: 0.087s (-0.019s) Differential Revision: https://phab.mercurial-scm.org/D8410

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_compat.py
90 lines | 2.8 KiB | text/x-python | PythonLexer
from __future__ import absolute_import, division, print_function
import sys
import types
PY2 = sys.version_info[0] == 2
if PY2:
from UserDict import IterableUserDict
# We 'bundle' isclass instead of using inspect as importing inspect is
# fairly expensive (order of 10-15 ms for a modern machine in 2016)
def isclass(klass):
return isinstance(klass, (type, types.ClassType))
# TYPE is used in exceptions, repr(int) is different on Python 2 and 3.
TYPE = "type"
def iteritems(d):
return d.iteritems()
def iterkeys(d):
return d.iterkeys()
# Python 2 is bereft of a read-only dict proxy, so we make one!
class ReadOnlyDict(IterableUserDict):
"""
Best-effort read-only dict wrapper.
"""
def __setitem__(self, key, val):
# We gently pretend we're a Python 3 mappingproxy.
raise TypeError("'mappingproxy' object does not support item "
"assignment")
def update(self, _):
# We gently pretend we're a Python 3 mappingproxy.
raise AttributeError("'mappingproxy' object has no attribute "
"'update'")
def __delitem__(self, _):
# We gently pretend we're a Python 3 mappingproxy.
raise TypeError("'mappingproxy' object does not support item "
"deletion")
def clear(self):
# We gently pretend we're a Python 3 mappingproxy.
raise AttributeError("'mappingproxy' object has no attribute "
"'clear'")
def pop(self, key, default=None):
# We gently pretend we're a Python 3 mappingproxy.
raise AttributeError("'mappingproxy' object has no attribute "
"'pop'")
def popitem(self):
# We gently pretend we're a Python 3 mappingproxy.
raise AttributeError("'mappingproxy' object has no attribute "
"'popitem'")
def setdefault(self, key, default=None):
# We gently pretend we're a Python 3 mappingproxy.
raise AttributeError("'mappingproxy' object has no attribute "
"'setdefault'")
def __repr__(self):
# Override to be identical to the Python 3 version.
return "mappingproxy(" + repr(self.data) + ")"
def metadata_proxy(d):
res = ReadOnlyDict()
res.data.update(d) # We blocked update, so we have to do it like this.
return res
else:
def isclass(klass):
return isinstance(klass, type)
TYPE = "class"
def iteritems(d):
return d.items()
def iterkeys(d):
return d.keys()
def metadata_proxy(d):
return types.MappingProxyType(dict(d))