huggingface / text-clustering Conditional Complexity

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).

Conditional Complexity Overall

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

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 23 most complex units

Unit	# lines	McCabe index	# params
def main() in run_pipeline.py	74	15	0
def load() in src/text_clustering.py	29	10	2
def fit() in src/text_clustering.py	31	8	3
def build_hf_data_clusters() in run_pipeline.py	21	8	3
def _postprocess_response() in src/text_clustering.py	24	7	2
def summarize() in src/text_clustering.py	21	4	3
def _show_mpl() in src/text_clustering.py	30	4	2
def infer() in src/text_clustering.py	8	3	3
def save() in src/text_clustering.py	17	3	2
def show() in src/text_clustering.py	15	3	2
def _show_plotly() in src/text_clustering.py	32	3	2
def get_size() in src/plot_utils.py	2	3	1
def build_hf_data_files() in run_pipeline.py	10	2	1
def __init__() in src/text_clustering.py	20	1	0
def embed() in src/text_clustering.py	9	1	2
def project() in src/text_clustering.py	5	1	2
def cluster() in src/text_clustering.py	10	1	2
def build_faiss_index() in src/text_clustering.py	4	1	2
def extract_score() in src/plot_utils.py	5	1	1
def plot_distributions() in src/plot_utils.py	32	1	2
def get_args() in run_pipeline.py	58	1	0
def extract_res() in run_pipeline.py	5	1	1
def build_and_push() in run_pipeline.py	10	1	2