def test_build_extraction_func_name(self): name = lexnlp_tests.build_extraction_func_name(self.test_assert_in, set1={'h', ''.join([str(i) for i in range(10000)])}) self.assertEqual('test_assert_in(text, set1=set(2 el.))', name) name = lexnlp_tests.build_extraction_func_name(self.test_assert_in, dict1={'h': ''.join([str(i) for i in range(10000)])}) self.assertEqual('test_assert_in(text, dict1=dict(1 el.))', name) name = lexnlp_tests.build_extraction_func_name(self.test_assert_in, tuple1=tuple(str(i) for i in range(10000))) self.assertEqual('test_assert_in(text, tuple1=tuple(10000 el.))', name) name = lexnlp_tests.build_extraction_func_name(self.test_assert_in, f=lambda d: d * d) self.assertEqual('test_assert_in(text, f=<class \'function\'>)', name) name = lexnlp_tests.build_extraction_func_name(self.test_assert_in) self.assertEqual('test_assert_in(text)', name)
def test_process_data(): def fff(): print("fff") _handle, benchmark_file = tempfile.mkstemp() try: for _i in range(55): lexnlp_tests.benchmark(lexnlp_tests.build_extraction_func_name(fff), fff, benchmark_file=benchmark_file) res = [] def process(actions: List[Dict]): res.extend(actions) upload_benchmarks.process_data(benchmark_file, 'index2', process) d1 = res[0] assert_equals('fff(text)', d1['_source']['function']) finally: if benchmark_file: os.remove(benchmark_file)
def test_process_data(self): def fff(): print("fff") _handle, benchmark_file = tempfile.mkstemp() try: for _i in range(55): lexnlp_tests.benchmark( lexnlp_tests.build_extraction_func_name(fff), fff, benchmark_file=benchmark_file) res = [] # pylint: disable=unnecessary-lambda upload_benchmarks.process_data(benchmark_file, 'index2', lambda actions: res.extend(actions)) d1 = res[0] self.assertEqual('fff(text)', d1['_source']['function']) finally: if benchmark_file: os.remove(benchmark_file)