caveat emptor.
"""
+from abc import ABC, abstractmethod
import contextlib
import functools
import inspect
import logging
+import os
import pickle
import random
import statistics
import time
import tempfile
-from typing import Callable
+from typing import Callable, Dict, List
import unittest
import warnings
import bootstrap
import config
+import function_utils
+import scott_secrets
+
+import sqlalchemy as sa
logger = logging.getLogger(__name__)
cfg = config.add_commandline_args(
- f'Logging ({__file__})',
- 'Args related to function decorators')
+ f'Logging ({__file__})', 'Args related to function decorators'
+)
cfg.add_argument(
'--unittests_ignore_perf',
action='store_true',
cfg.add_argument(
'--unittests_num_perf_samples',
type=int,
- default=20,
- help='The count of perf timing samples we need to see before blocking slow runs on perf grounds'
+ default=50,
+ help='The count of perf timing samples we need to see before blocking slow runs on perf grounds',
)
cfg.add_argument(
'--unittests_drop_perf_traces',
type=str,
nargs=1,
default=None,
- help='The identifier (i.e. file!test_fixture) for which we should drop all perf data'
+ help='The identifier (i.e. file!test_fixture) for which we should drop all perf data',
+)
+cfg.add_argument(
+ '--unittests_persistance_strategy',
+ choices=['FILE', 'DATABASE'],
+ default='DATABASE',
+ help='Should we persist perf data in a file or db?',
+)
+cfg.add_argument(
+ '--unittests_perfdb_filename',
+ type=str,
+ metavar='FILENAME',
+ default=f'{os.environ["HOME"]}/.python_unittest_performance_db',
+ help='File in which to store perf data (iff --unittests_persistance_strategy is FILE)',
+)
+cfg.add_argument(
+ '--unittests_perfdb_spec',
+ type=str,
+ metavar='DBSPEC',
+ default='mariadb+pymysql://python_unittest:<PASSWORD>@db.house:3306/python_unittest_performance',
+ help='Db connection spec for perf data (iff --unittest_persistance_strategy is DATABASE)',
)
-
# >>> This is the hacky business, FYI. <<<
unittest.main = bootstrap.initialize(unittest.main)
-_db = '/home/scott/.python_unittest_performance_db'
+class PerfRegressionDataPersister(ABC):
+ def __init__(self):
+ pass
+
+ @abstractmethod
+ def load_performance_data(self) -> Dict[str, List[float]]:
+ pass
+
+ @abstractmethod
+ def save_performance_data(
+ self, method_id: str, data: Dict[str, List[float]]
+ ):
+ pass
+
+ @abstractmethod
+ def delete_performance_data(self, method_id: str):
+ pass
+
+
+class FileBasedPerfRegressionDataPersister(PerfRegressionDataPersister):
+ def __init__(self, filename: str):
+ self.filename = filename
+ self.traces_to_delete = []
+
+ def load_performance_data(self, method_id: str) -> Dict[str, List[float]]:
+ with open(self.filename, 'rb') as f:
+ return pickle.load(f)
+
+ def save_performance_data(
+ self, method_id: str, data: Dict[str, List[float]]
+ ):
+ for trace in self.traces_to_delete:
+ if trace in data:
+ data[trace] = []
+
+ with open(self.filename, 'wb') as f:
+ pickle.dump(data, f, pickle.HIGHEST_PROTOCOL)
+
+ def delete_performance_data(self, method_id: str):
+ self.traces_to_delete.append(method_id)
+
+
+class DatabasePerfRegressionDataPersister(PerfRegressionDataPersister):
+ def __init__(self, dbspec: str):
+ self.dbspec = dbspec
+ self.engine = sa.create_engine(self.dbspec)
+ self.conn = self.engine.connect()
+
+ def load_performance_data(self, method_id: str) -> Dict[str, List[float]]:
+ results = self.conn.execute(
+ sa.text(
+ f'SELECT * FROM runtimes_by_function WHERE function = "{method_id}";'
+ )
+ )
+ ret = {method_id: []}
+ for result in results.all():
+ ret[method_id].append(result['runtime'])
+ results.close()
+ return ret
+
+ def save_performance_data(
+ self, method_id: str, data: Dict[str, List[float]]
+ ):
+ self.delete_performance_data(method_id)
+ for (method_id, perf_data) in data.items():
+ sql = 'INSERT INTO runtimes_by_function (function, runtime) VALUES '
+ for perf in perf_data:
+ self.conn.execute(sql + f'("{method_id}", {perf});')
+
+ def delete_performance_data(self, method_id: str):
+ sql = f'DELETE FROM runtimes_by_function WHERE function = "{method_id}"'
+ self.conn.execute(sql)
def check_method_for_perf_regressions(func: Callable) -> Callable:
message if it has become too slow.
"""
- def load_known_test_performance_characteristics():
- with open(_db, 'rb') as f:
- return pickle.load(f)
-
- def save_known_test_performance_characteristics(perfdb):
- with open(_db, 'wb') as f:
- pickle.dump(perfdb, f, pickle.HIGHEST_PROTOCOL)
@functools.wraps(func)
def wrapper_perf_monitor(*args, **kwargs):
+ if config.config['unittests_persistance_strategy'] == 'FILE':
+ filename = config.config['unittests_perfdb_filename']
+ helper = FileBasedPerfRegressionDataPersister(filename)
+ elif config.config['unittests_persistance_strategy'] == 'DATABASE':
+ dbspec = config.config['unittests_perfdb_spec']
+ dbspec = dbspec.replace(
+ '<PASSWORD>', scott_secrets.MARIADB_UNITTEST_PERF_PASSWORD
+ )
+ helper = DatabasePerfRegressionDataPersister(dbspec)
+ else:
+ raise Exception(
+ 'Unknown/unexpected --unittests_persistance_strategy value'
+ )
+
+ func_id = function_utils.function_identifier(func)
+ func_name = func.__name__
+ logger.debug(f'Watching {func_name}\'s performance...')
+ logger.debug(f'Canonical function identifier = {func_id}')
+
try:
- perfdb = load_known_test_performance_characteristics()
+ perfdb = helper.load_performance_data(func_id)
except Exception as e:
logger.exception(e)
- msg = f'Unable to load perfdb from {_db}'
+ msg = 'Unable to load perfdb; skipping it...'
logger.warning(msg)
warnings.warn(msg)
perfdb = {}
- # This is a unique identifier for a test: filepath!function
- logger.debug(f'Watching {func.__name__}\'s performance...')
- func_id = f'{func.__globals__["__file__"]}!{func.__name__}'
- logger.debug(f'Canonical function identifier = {func_id}')
-
# cmdline arg to forget perf traces for function
drop_id = config.config['unittests_drop_perf_traces']
if drop_id is not None:
- if drop_id in perfdb:
- perfdb[drop_id] = []
+ helper.delete_performance_data(drop_id)
# Run the wrapped test paying attention to latency.
start_time = time.perf_counter()
value = func(*args, **kwargs)
end_time = time.perf_counter()
run_time = end_time - start_time
- logger.debug(f'{func.__name__} executed in {run_time:f}s.')
- # Check the db; see if it was unexpectedly slow.
+ # See if it was unexpectedly slow.
hist = perfdb.get(func_id, [])
if len(hist) < config.config['unittests_num_perf_samples']:
hist.append(run_time)
- logger.debug(
- f'Still establishing a perf baseline for {func.__name__}'
- )
+ logger.debug(f'Still establishing a perf baseline for {func_name}')
else:
stdev = statistics.stdev(hist)
- limit = hist[-1] + stdev * 5
+ logger.debug(f'For {func_name}, performance stdev={stdev}')
+ slowest = hist[-1]
+ logger.debug(
+ f'For {func_name}, slowest perf on record is {slowest:f}s'
+ )
+ limit = slowest + stdev * 4
logger.debug(
- f'Max acceptable performace for {func.__name__} is {limit:f}s'
+ f'For {func_name}, max acceptable runtime is {limit:f}s'
)
- if (
- run_time > limit and
- not config.config['unittests_ignore_perf']
- ):
+ logger.debug(
+ f'For {func_name}, actual observed runtime was {run_time:f}s'
+ )
+ if run_time > limit and not config.config['unittests_ignore_perf']:
msg = f'''{func_id} performance has regressed unacceptably.
-{hist[-1]:f}s is the slowest record in {len(hist)} db perf samples.
-It just ran in {run_time:f}s which is >5 stdevs slower than the slowest sample.
+{slowest:f}s is the slowest runtime on record in {len(hist)} perf samples.
+It just ran in {run_time:f}s which is 4+ stdevs slower than the slowest.
Here is the current, full db perf timing distribution:
'''
for x in hist:
msg += f'{x:f}\n'
logger.error(msg)
- slf = args[0]
- slf.fail(msg)
+ slf = args[0] # Peek at the wrapped function's self ref.
+ slf.fail(msg) # ...to fail the testcase.
else:
hist.append(run_time)
+ # Don't spam the database with samples; just pick a random
+ # sample from what we have and store that back.
n = min(config.config['unittests_num_perf_samples'], len(hist))
hist = random.sample(hist, n)
hist.sort()
perfdb[func_id] = hist
- save_known_test_performance_characteristics(perfdb)
+ helper.save_performance_data(func_id, perfdb)
return value
+
return wrapper_perf_monitor
def check_all_methods_for_perf_regressions(prefix='test_'):
+ """Decorate unittests with this to pay attention to the perf of the
+ testcode and flag perf regressions. e.g.
+
+ import unittest_utils as uu
+
+ @uu.check_all_methods_for_perf_regressions()
+ class TestMyClass(unittest.TestCase):
+
+ def test_some_part_of_my_class(self):
+ ...
+
+ """
+
def decorate_the_testcase(cls):
if issubclass(cls, unittest.TestCase):
for name, m in inspect.getmembers(cls, inspect.isfunction):
setattr(cls, name, check_method_for_perf_regressions(m))
logger.debug(f'Wrapping {cls.__name__}:{name}.')
return cls
+
return decorate_the_testcase
def breakpoint():
"""Hard code a breakpoint somewhere; drop into pdb."""
import pdb
+
pdb.set_trace()
if __name__ == '__main__':
import doctest
+
doctest.testmod()
projects / python_utils.git / blobdiff