Files
sqlalchemy/test/testlib/profiling.py
T
Mike Bayer 61d8644320 - added verbose activity to profiling.function_call_count
- simplified oracle non-ansi join generation, removed hooks from base compiler
- removed join() call from _label generation, fixed repeat label gen
2008-04-01 22:36:40 +00:00

182 lines
6.1 KiB
Python

"""Profiling support for unit and performance tests."""
import os, sys
from testlib.config import parser, post_configure
from testlib.compat import *
import testlib.config
__all__ = 'profiled', 'function_call_count', 'conditional_call_count'
all_targets = set()
profile_config = { 'targets': set(),
'report': True,
'sort': ('time', 'calls'),
'limit': None }
def profiled(target=None, **target_opts):
"""Optional function profiling.
@profiled('label')
or
@profiled('label', report=True, sort=('calls',), limit=20)
Enables profiling for a function when 'label' is targetted for
profiling. Report options can be supplied, and override the global
configuration and command-line options.
"""
import time, hotshot, hotshot.stats
# manual or automatic namespacing by module would remove conflict issues
if target is None:
target = 'anonymous_target'
elif target in all_targets:
print "Warning: redefining profile target '%s'" % target
all_targets.add(target)
filename = "%s.prof" % target
def decorator(fn):
def profiled(*args, **kw):
if (target not in profile_config['targets'] and
not target_opts.get('always', None)):
return fn(*args, **kw)
prof = hotshot.Profile(filename)
began = time.time()
prof.start()
try:
result = fn(*args, **kw)
finally:
prof.stop()
ended = time.time()
prof.close()
if not testlib.config.options.quiet:
print "Profiled target '%s', wall time: %.2f seconds" % (
target, ended - began)
report = target_opts.get('report', profile_config['report'])
if report and testlib.config.options.verbose:
sort_ = target_opts.get('sort', profile_config['sort'])
limit = target_opts.get('limit', profile_config['limit'])
print "Profile report for target '%s' (%s)" % (
target, filename)
stats = hotshot.stats.load(filename)
stats.sort_stats(*sort_)
if limit:
stats.print_stats(limit)
else:
stats.print_stats()
assert_range = target_opts.get('call_range')
if assert_range:
if isinstance(assert_range, dict):
assert_range = assert_range.get(testlib.config.db, 'default')
stats = hotshot.stats.load(filename)
assert stats.total_calls >= assert_range[0] and stats.total_calls <= assert_range[1], stats.total_calls
os.unlink(filename)
return result
return _function_named(profiled, fn.__name__)
return decorator
def function_call_count(count=None, versions={}, variance=0.05):
"""Assert a target for a test case's function call count.
count
Optional, general target function call count.
versions
Optional, a dictionary of Python version strings to counts,
for example::
{ '2.5.1': 110,
'2.5': 100,
'2.4': 150 }
The best match for the current running python will be used.
If none match, 'count' will be used as the fallback.
variance
An +/- deviation percentage, defaults to 5%.
"""
# this could easily dump the profile report if --verbose is in effect
version_info = list(sys.version_info)
py_version = '.'.join([str(v) for v in sys.version_info])
while version_info:
version = '.'.join([str(v) for v in version_info])
if version in versions:
count = versions[version]
break
version_info.pop()
if count is None:
return lambda fn: fn
import hotshot, hotshot.stats
def decorator(fn):
def counted(*args, **kw):
try:
filename = "%s.prof" % fn.__name__
prof = hotshot.Profile(filename)
prof.start()
try:
result = fn(*args, **kw)
finally:
prof.stop()
prof.close()
stats = hotshot.stats.load(filename)
calls = stats.total_calls
deviance = int(count * variance)
if (calls < (count - deviance) or
calls > (count + deviance)):
raise AssertionError(
"Function call count %s not within %s%% "
"of expected %s. (Python version %s)" % (
calls, (variance * 100), count, py_version))
if testlib.config.options.verbose:
stats.sort_stats('calls', 'cumulative')
stats.print_stats()
return result
finally:
if os.path.exists(filename):
os.unlink(filename)
return _function_named(counted, fn.__name__)
return decorator
def conditional_call_count(discriminator, categories):
"""Apply a function call count conditionally at runtime.
Takes two arguments, a callable that returns a key value, and a dict
mapping key values to a tuple of arguments to function_call_count.
The callable is not evaluated until the decorated function is actually
invoked. If the `discriminator` returns a key not present in the
`categories` dictionary, no call count assertion is applied.
Useful for integration tests, where running a named test in isolation may
have a function count penalty not seen in the full suite, due to lazy
initialization in the DB-API, SA, etc.
"""
def decorator(fn):
def at_runtime(*args, **kw):
criteria = categories.get(discriminator(), None)
if criteria is None:
return fn(*args, **kw)
rewrapped = function_call_count(*criteria)(fn)
return rewrapped(*args, **kw)
return _function_named(at_runtime, fn.__name__)
return decorator