3 """Helpers for unittests. Note that when you import this we
4 automatically wrap unittest.main() with a call to
5 bootstrap.initialize so that we getLogger config, commandline args,
6 logging control, etc... this works fine but it's a little hacky so
19 from typing import Callable
26 logger = logging.getLogger(__name__)
27 cfg = config.add_commandline_args(
28 f'Logging ({__file__})',
29 'Args related to function decorators')
31 '--unittests_ignore_perf',
34 help='Ignore unittest perf regression in @check_method_for_perf_regressions',
37 '--unittests_num_perf_samples',
40 help='The count of perf timing samples we need to see before blocking slow runs on perf grounds'
43 '--unittests_drop_perf_traces',
47 help='The identifier (i.e. file!test_fixture) for which we should drop all perf data'
51 # >>> This is the hacky business, FYI. <<<
52 unittest.main = bootstrap.initialize(unittest.main)
55 _db = '/home/scott/.python_unittest_performance_db'
58 def check_method_for_perf_regressions(func: Callable) -> Callable:
59 """This is meant to be used on a method in a class that subclasses
60 unittest.TestCase. When thus decorated it will time the execution
61 of the code in the method, compare it with a database of
62 historical perfmance, and fail the test with a perf-related
63 message if it has become too slow.
66 def load_known_test_performance_characteristics():
67 with open(_db, 'rb') as f:
70 def save_known_test_performance_characteristics(perfdb):
71 with open(_db, 'wb') as f:
72 pickle.dump(perfdb, f, pickle.HIGHEST_PROTOCOL)
74 @functools.wraps(func)
75 def wrapper_perf_monitor(*args, **kwargs):
77 perfdb = load_known_test_performance_characteristics()
78 except Exception as e:
80 logger.warning(f'Unable to load perfdb from {_db}')
83 # This is a unique identifier for a test: filepath!function
84 logger.debug(f'Watching {func.__name__}\'s performance...')
85 func_id = f'{func.__globals__["__file__"]}!{func.__name__}'
86 logger.debug(f'Canonical function identifier = {func_id}')
88 # cmdline arg to forget perf traces for function
89 drop_id = config.config['unittests_drop_perf_traces']
90 if drop_id is not None:
94 # Run the wrapped test paying attention to latency.
95 start_time = time.perf_counter()
96 value = func(*args, **kwargs)
97 end_time = time.perf_counter()
98 run_time = end_time - start_time
99 logger.debug(f'{func.__name__} executed in {run_time:f}s.')
101 # Check the db; see if it was unexpectedly slow.
102 hist = perfdb.get(func_id, [])
103 if len(hist) < config.config['unittests_num_perf_samples']:
104 hist.append(run_time)
106 f'Still establishing a perf baseline for {func.__name__}'
109 stdev = statistics.stdev(hist)
110 limit = hist[-1] + stdev * 3
112 f'Max acceptable performace for {func.__name__} is {limit:f}s'
116 not config.config['unittests_ignore_perf']
118 msg = f'''{func_id} performance has regressed unacceptably.
119 {hist[-1]:f}s is the slowest record in {len(hist)} db perf samples.
120 It just ran in {run_time:f}s which is >3 stdevs slower than the slowest sample.
121 Here is the current, full db perf timing distribution:
128 hist.append(run_time)
130 n = min(config.config['unittests_num_perf_samples'], len(hist))
131 hist = random.sample(hist, n)
133 perfdb[func_id] = hist
134 save_known_test_performance_characteristics(perfdb)
136 return wrapper_perf_monitor
139 def check_all_methods_for_perf_regressions(prefix='test_'):
140 def decorate_the_testcase(cls):
141 if issubclass(cls, unittest.TestCase):
142 for name, m in inspect.getmembers(cls, inspect.isfunction):
143 if name.startswith(prefix):
144 setattr(cls, name, check_method_for_perf_regressions(m))
145 logger.debug(f'Wrapping {cls.__name__}:{name}.')
147 return decorate_the_testcase
155 class RecordStdout(object):
157 with uu.RecordStdout() as record:
158 print("This is a test!")
159 print({record().readline()})
162 def __init__(self) -> None:
163 self.destination = tempfile.SpooledTemporaryFile(mode='r+')
166 def __enter__(self) -> Callable[[], tempfile.SpooledTemporaryFile]:
167 self.recorder = contextlib.redirect_stdout(self.destination)
168 self.recorder.__enter__()
169 return lambda: self.destination
171 def __exit__(self, *args) -> bool:
172 self.recorder.__exit__(*args)
173 self.destination.seek(0)
177 class RecordStderr(object):
179 with uu.RecordStderr() as record:
180 print("This is a test!", file=sys.stderr)
181 print({record().readline()})
184 def __init__(self) -> None:
185 self.destination = tempfile.SpooledTemporaryFile(mode='r+')
188 def __enter__(self) -> Callable[[], tempfile.SpooledTemporaryFile]:
189 self.recorder = contextlib.redirect_stderr(self.destination)
190 self.recorder.__enter__()
191 return lambda: self.destination
193 def __exit__(self, *args) -> bool:
194 self.recorder.__exit__(*args)
195 self.destination.seek(0)
199 class RecordMultipleStreams(object):
201 with uu.RecordStreams(sys.stderr, sys.stdout) as record:
202 print("This is a test!")
203 print("This is one too.", file=sys.stderr)
205 print(record().readlines())
207 def __init__(self, *files) -> None:
208 self.files = [*files]
209 self.destination = tempfile.SpooledTemporaryFile(mode='r+')
210 self.saved_writes = []
212 def __enter__(self) -> Callable[[], tempfile.SpooledTemporaryFile]:
214 self.saved_writes.append(f.write)
215 f.write = self.destination.write
216 return lambda: self.destination
218 def __exit__(self, *args) -> bool:
220 f.write = self.saved_writes.pop()
221 self.destination.seek(0)