GoogleCloudPlatform / data-science-on-gcp

Intro

Conditional complexity (also called cyclomatic complexity) is a term used to measure the complexity of software. The term refers to the number of possible paths through a program function. A higher value ofter means higher maintenance and testing costs (infosecinstitute.com).
Conditional complexity is calculated by counting all conditions in the program that can affect the execution path (e.g. if statement, loops, switches, and/or operators, try and catch blocks...).
Conditional complexity is measured at the unit level (methods, functions...).
Units are classified in four categories based on the measured McCabe index: 1-5 (simple units), 6-10 (medium complex units), 11-25 (complex units), 26+ (very complex units).

Learn more...

Conditional Complexity Overall

There are 81 units with 1,517 lines of code in units (28.8% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
1 medium complex units (68 lines of code)
16 simple units (586 lines of code)
64 very simple units (863 lines of code)

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

3D view of all units

Conditional Complexity per Extension

51+

26-50

11-25

6-10

1-5

Conditional Complexity per Logical Component

primary logical decomposition

51+

26-50

11-25

6-10

1-5

Most Complex Units

Top 50 most complex units

Unit	# lines	McCabe index	# params
def run_experiment() in 07_sparkml/experiment.py	68	11	4
def run() in 11_realtime/make_predictions.py	97	10	5
def create_features_and_label() in 11_realtime/flightstxf/flights_transforms.py	36	10	2
def compute_stats() in 04_streaming/realtime/avg02.py	16	9	2
def compute_stats() in 04_streaming/realtime/avg03.py	16	9	2
def ingest_flights() in 02_ingest/monthlyupdate/main.py	16	8	0
def create_model() in 10_mlops/model.py	56	8	0
def notify() in 04_streaming/simulate/simulate.py	21	7	6
def add_stats() in 11_realtime/flightstxf/flights_transforms.py	13	7	2
def train_and_evaluate() in 10_mlops/model.py	46	7	5
def tz_correct() in 04_streaming/transform/df06.py	24	6	2
def get_next_event() in 04_streaming/transform/df06.py	20	6	1
def get_next_event() in 04_streaming/transform/df07.py	20	6	1
def run() in 11_realtime/create_traindata.py	57	6	4
def train_custom_model() in 10_mlops/train_on_vertexai.py	45	6	6
def do_hyperparameter_tuning() in 10_mlops/train_on_vertexai.py	63	6	5
def main() in 10_mlops/train_on_vertexai.py	40	6	0
def tz_correct() in 04_streaming/transform/df04.py	22	5	2
def tz_correct() in 04_streaming/transform/df05.py	21	5	2
def get_category() in 07_sparkml/experiment.py	9	5	1
def process() in 11_realtime/make_predictions.py	10	5	2
def compute_mean() in 11_realtime/flightstxf/flights_transforms.py	3	5	2
def is_normal_operation() in 11_realtime/flightstxf/flights_transforms.py	7	5	1
def add_24h_if_before() in 04_streaming/transform/df04.py	8	4	2
def add_24h_if_before() in 04_streaming/transform/df06.py	8	4	2
def add_24h_if_before() in 04_streaming/transform/df05.py	8	4	2
def get_next_event() in 04_streaming/transform/df05.py	13	4	1
def tz_correct() in 04_streaming/transform/df03.py	14	4	2
def add_24h_if_before() in 04_streaming/transform/df07.py	8	4	2
def tz_correct() in 04_streaming/transform/df07.py	17	4	2
def as_utc() in 04_streaming/transform/df04.py	14	3	3
def as_utc() in 04_streaming/transform/df06.py	14	3	3
def as_utc() in 04_streaming/transform/df05.py	14	3	3
def as_utc() in 04_streaming/transform/df03.py	14	3	3
def RunCustomCommand() in 04_streaming/transform/setup.py	10	3	2
def as_utc() in 04_streaming/transform/df07.py	14	3	3
def addtimezone() in 04_streaming/transform/df02.py	10	3	2
def publish() in 04_streaming/simulate/simulate.py	8	3	4
def eval_model() in 07_sparkml/logistic.py	22	3	1
def eval() in 07_sparkml/experiment.py	27	3	1
def RunCustomCommand() in 11_realtime/setup.py	10	3	2
def dict_to_csv() in 11_realtime/create_traindata.py	6	3	1
def get_data_split() in 11_realtime/flightstxf/flights_transforms.py	10	3	1
def get_data_split_2019() in 11_realtime/flightstxf/flights_transforms.py	11	3	1
def run_bayes() in 06_dataproc/bayes_on_spark.py	37	3	1
def read_dataset() in 10_mlops/model.py	17	3	4
def wide_and_deep_classifier() in 10_mlops/model.py	13	3	4
def by_airport() in 04_streaming/realtime/avg02.py	5	2	1
def run() in 04_streaming/realtime/avg02.py	37	2	3
def by_airport() in 04_streaming/realtime/avg03.py	5	2	1