Best Python code snippet using hypothesis
engine.py
Source:engine.py
...158 self.first_bug_found_at = self.call_count159 else:160 if sort_key(data.buffer) < sort_key(existing.buffer):161 self.shrinks += 1162 self.downgrade_buffer(existing.buffer)163 self.__data_cache.unpin(existing.buffer)164 changed = True165 if changed:166 self.save_buffer(data.buffer)167 self.interesting_examples[key] = data.as_result()168 self.__data_cache.pin(data.buffer)169 self.shrunk_examples.discard(key)170 if self.shrinks >= MAX_SHRINKS:171 self.exit_with(ExitReason.max_shrinks)172 if not self.interesting_examples:173 # Note that this logic is reproduced to end the generation phase when174 # we have interesting examples. Update that too if you change this!175 # (The doubled implementation is because here we exit the engine entirely,176 # while in the other case below we just want to move on to shrinking.)177 if self.valid_examples >= self.settings.max_examples:178 self.exit_with(ExitReason.max_examples)179 if self.call_count >= max(180 self.settings.max_examples * 10,181 # We have a high-ish default max iterations, so that tests182 # don't become flaky when max_examples is too low.183 1000,184 ):185 self.exit_with(ExitReason.max_iterations)186 if self.__tree_is_exhausted():187 self.exit_with(ExitReason.finished)188 self.record_for_health_check(data)189 def generate_novel_prefix(self):190 """Uses the tree to proactively generate a starting sequence of bytes191 that we haven't explored yet for this test.192 When this method is called, we assume that there must be at193 least one novel prefix left to find. If there were not, then the194 test run should have already stopped due to tree exhaustion.195 """196 return self.tree.generate_novel_prefix(self.random)197 @property198 def cap(self):199 return BUFFER_SIZE // 2200 def record_for_health_check(self, data):201 # Once we've actually found a bug, there's no point in trying to run202 # health checks - they'll just mask the actually important information.203 if data.status == Status.INTERESTING:204 self.health_check_state = None205 state = self.health_check_state206 if state is None:207 return208 state.draw_times.extend(data.draw_times)209 if data.status == Status.VALID:210 state.valid_examples += 1211 elif data.status == Status.INVALID:212 state.invalid_examples += 1213 else:214 assert data.status == Status.OVERRUN215 state.overrun_examples += 1216 max_valid_draws = 10217 max_invalid_draws = 50218 max_overrun_draws = 20219 assert state.valid_examples <= max_valid_draws220 if state.valid_examples == max_valid_draws:221 self.health_check_state = None222 return223 if state.overrun_examples == max_overrun_draws:224 fail_health_check(225 self.settings,226 (227 "Examples routinely exceeded the max allowable size. "228 "(%d examples overran while generating %d valid ones)"229 ". Generating examples this large will usually lead to"230 " bad results. You could try setting max_size parameters "231 "on your collections and turning "232 "max_leaves down on recursive() calls."233 )234 % (state.overrun_examples, state.valid_examples),235 HealthCheck.data_too_large,236 )237 if state.invalid_examples == max_invalid_draws:238 fail_health_check(239 self.settings,240 (241 "It looks like your strategy is filtering out a lot "242 "of data. Health check found %d filtered examples but "243 "only %d good ones. This will make your tests much "244 "slower, and also will probably distort the data "245 "generation quite a lot. You should adapt your "246 "strategy to filter less. This can also be caused by "247 "a low max_leaves parameter in recursive() calls"248 )249 % (state.invalid_examples, state.valid_examples),250 HealthCheck.filter_too_much,251 )252 draw_time = sum(state.draw_times)253 if draw_time > 1.0:254 fail_health_check(255 self.settings,256 (257 "Data generation is extremely slow: Only produced "258 "%d valid examples in %.2f seconds (%d invalid ones "259 "and %d exceeded maximum size). Try decreasing "260 "size of the data you're generating (with e.g."261 "max_size or max_leaves parameters)."262 )263 % (264 state.valid_examples,265 draw_time,266 state.invalid_examples,267 state.overrun_examples,268 ),269 HealthCheck.too_slow,270 )271 def save_buffer(self, buffer):272 if self.settings.database is not None:273 key = self.database_key274 if key is None:275 return276 self.settings.database.save(key, hbytes(buffer))277 def downgrade_buffer(self, buffer):278 if self.settings.database is not None and self.database_key is not None:279 self.settings.database.move(self.database_key, self.secondary_key, buffer)280 @property281 def secondary_key(self):282 return b".".join((self.database_key, b"secondary"))283 @property284 def covering_key(self):285 return b".".join((self.database_key, b"coverage"))286 def note_details(self, data):287 self.__data_cache[data.buffer] = data.as_result()288 runtime = max(data.finish_time - data.start_time, 0.0)289 self.all_runtimes.append(runtime)290 self.all_drawtimes.extend(data.draw_times)291 self.status_runtimes.setdefault(data.status, []).append(runtime)...
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