/usr/lib/python2.7/dist-packages/traits/adaptation/tests/benchmark.py is in python-traits 4.6.0-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | """ Simple benchmarking of the adaptation manager.
This is not 'enforced' by any tests (i.e. we currently aren't bound to satisfy
any performance criteria - but in the future we might be ;^).
"""
import abc
from pprint import pprint
import time
from traits.adaptation.adaptation_manager import AdaptationManager
from traits.api import Adapter, HasTraits, Interface, provides
N_SOURCES = 3
N_ITERATIONS = 100
N_PROTOCOLS = 50
# Create some classes to adapt.
create_classes_to_adapt = """
class IFoo{i}(Interface):
pass
@provides(IFoo{i})
class Foo{i}(HasTraits):
pass
"""
for i in range(N_SOURCES):
exec create_classes_to_adapt.format(i=i)
# The object that we will try to adapt!
foo = Foo1()
# Create a lot of other interfaces that we will adapt to.
for i in range(N_PROTOCOLS):
exec 'class I{i}(Interface): pass'.format(i=i)
create_traits_adapter_class = """
@provides(I{target})
class IFoo{source}ToI{target}(Adapter):
pass
"""
# Create adapters from each 'IFooX' to all of the interfaces.
for source in range(N_SOURCES):
for target in range(N_PROTOCOLS):
exec create_traits_adapter_class.format(source=source, target=target)
#### traits.adaptation with Interfaces ########################################
adaptation_manager = AdaptationManager()
register_ifoox_to_ix = """
adaptation_manager.register_factory(
factory = IFoo{source}ToI{target},
from_protocol = IFoo{source},
to_protocol = I{target}
)
"""
# We register the adapters in reversed order, so that looking for the one
# with index 0 will need traversing the whole list.
# I.e., we're considering the worst case scenario.
for source in range(N_SOURCES):
for target in reversed(range(N_PROTOCOLS)):
exec register_ifoox_to_ix.format(source=source, target=target)
start_time = time.time()
for _ in range(N_ITERATIONS):
adaptation_manager.adapt(foo, I0)
time_per_iter = (time.time() - start_time) / float(N_ITERATIONS) * 1000.0
print 'apptools using Interfaces: %.3f msec per iteration' % time_per_iter
#### traits.adaptation with ABCs ##############################################
# Create some classes to adapt (using ABCs!).
for i in range(N_SOURCES):
exec 'class FooABC{i}(object): __metaclass__ = abc.ABCMeta'.format(i=i)
exec 'class Foo{i}(object): pass'.format(i=i)
exec 'FooABC{i}.register(Foo{i})'.format(i=i)
# The object that we will try to adapt!
foo = Foo0()
# Create a lot of other ABCs!
for i in range(N_PROTOCOLS):
exec 'class ABC{i}(object): __metaclass__ = abc.ABCMeta'.format(i=i)
# Create adapters from 'FooABC' to all of the ABCs.
create_abc_adapter_class = """
class FooABC{source}ToABC{target}(object):
def __init__(self, adaptee):
pass
ABC{target}.register(FooABC{source}ToABC{target})
"""
for source in range(N_SOURCES):
for target in range(N_PROTOCOLS):
exec create_abc_adapter_class.format(source=source, target=target)
# Register all of the adapters.
adaptation_manager = AdaptationManager()
register_fooxabc_to_abcx = """
adaptation_manager.register_factory(
factory = FooABC{source}ToABC{target},
from_protocol = FooABC{source},
to_protocol = ABC{target}
)
"""
# We register the adapters in reversed order, so that looking for the one
# with index 0 will need traversing the whole list.
# I.e., we're considering the worst case scenario.
for source in range(N_SOURCES):
for target in reversed(range(N_PROTOCOLS)):
exec register_fooxabc_to_abcx.format(source=source, target=target)
start_time = time.time()
for _ in range(N_ITERATIONS):
adaptation_manager.adapt(foo, ABC0)
time_per_iter = (time.time() - start_time) / float(N_ITERATIONS) * 1000.0
print 'apptools using ABCs: %.3f msec per iteration' % time_per_iter
#### EOF #######################################################################
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