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)
