spotify / tfxConditional 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).

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Conditional Complexity Overall

There are 2,574 units with 24,925 lines of code in units (57.6% of code).

0 very complex units (0 lines of code)
8 complex units (700 lines of code)
66 medium complex units (3,317 lines of code)
184 simple units (4,911 lines of code)
2,316 very simple units (15,997 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 is_compatible() in tfx/utils/typing_utils.py	68	34	2
def apply() in tfx/dsl/input_resolution/ops/latest_policy_model_op.py	106	34	2
def __call__() in tfx/orchestration/experimental/core/sync_pipeline_task_gen.py	73	32	1
def build() in tfx/orchestration/kubeflow/v2/step_builder.py	133	31	1
def check_strict_json_compat() in tfx/dsl/component/experimental/json_compat.py	45	29	2
def debug_str() in tfx/dsl/compiler/placeholder_utils.py	102	29	1
def run_component() in tfx/scripts/run_component.py	84	28	4
def _dump_ui_metadata() in tfx/orchestration/kubeflow/container_entrypoint.py	89	26	3
def _parse_parameters() in tfx/types/component_spec.py	46	25	3
def Do() in tfx/components/statistics_gen/executor.py	95	23	7
def type_check() in tfx/types/component_spec.py	41	22	3
def set_parameter_value() in tfx/orchestration/data_types_utils.py	57	22	3
def _resolve_proto_operator() in tfx/dsl/compiler/placeholder_utils.py	68	22	2
def __setattr__() in tfx/types/artifact.py	54	20	3
def topsorted_layers() in tfx/utils/topsort.py	51	20	7
def __getattr__() in tfx/types/artifact.py	39	19	2
def Do() in tfx/extensions/google_cloud_ai_platform/tuner/executor.py	75	19	7
def Transform() in tfx/components/transform/executor.py	122	19	6
def generate_output_split_names() in tfx/components/example_gen/utils.py	42	18	6
def _create_matching_glob_and_regex() in tfx/components/example_gen/utils.py	51	18	6
def _generate_tasks_for_node() in tfx/orchestration/experimental/core/sync_pipeline_task_gen.py	121	18	2
def _parse_raw_artifact() in tfx/orchestration/kubeflow/v2/container/kubeflow_v2_entrypoint_utils.py	42	18	3
def get_artifact_type_class() in tfx/types/artifact_utils.py	40	17	1
def _runMetricsPlotsAndValidationsEvaluatorManualActuation() in tfx/benchmarks/tfma_v2_benchmark_base.py	87	17	5
def __call__() in tfx/dsl/input_resolution/resolver_function.py	66	17	3
def apply() in tfx/dsl/input_resolution/ops/consecutive_spans_op.py	36	17	2
def Do() in tfx/extensions/google_cloud_ai_platform/bulk_inferrer/executor.py	96	16	7
def substitute_runtime_parameter() in tfx/orchestration/portable/runtime_parameter_utils.py	44	16	3
def _set_node_context() in tfx/dsl/compiler/compiler.py	44	16	2
def dict_to_example() in tfx/components/example_gen/utils.py	43	15	2
def Do() in tfx/components/evaluator/executor.py	61	15	7
def Do() in tfx/components/distribution_validator/executor.py	66	15	7
def get_common_fn_args() in tfx/components/trainer/fn_args_utils.py	77	15	5
def __call__() in tfx/orchestration/experimental/core/async_pipeline_task_gen.py	52	15	1
def _run_executor() in tfx/orchestration/kubeflow/v2/container/kubeflow_v2_run_executor.py	76	15	2
def _construct_pipeline_graph() in tfx/orchestration/kubeflow/kubeflow_dag_runner.py	36	15	3
def check() in tfx/dsl/component/experimental/json_compat.py	19	15	2
def _resolve() in tfx/dsl/input_resolution/strategies/span_range_strategy.py	39	15	3
def apply() in tfx/dsl/input_resolution/ops/latest_pipeline_run_outputs_op.py	50	15	1
def _get_artifact_type() in tfx/types/artifact.py	34	14	1
def _set_components() in tfx/orchestration/pipeline.py	45	14	2
def build() in tfx/orchestration/kubeflow/v2/pipeline_builder.py	71	14	1
def verify_split_pattern_specs() in tfx/components/example_gen/utils.py	27	13	1
def run_as_kubernetes_job() in tfx/orchestration/experimental/kubernetes/kubernetes_remote_runner.py	78	13	2
def _validate_signature() in tfx/dsl/component/experimental/function_parser.py	33	13	5
def __init__() in tfx/dsl/component/experimental/decorators.py	35	13	3
def training_range() in tfx/dsl/input_resolution/ops/training_range_op.py	31	13	2
def __init__() in tfx/dsl/components/common/resolver.py	38	13	5
def _validate() in tfx/types/component_spec.py	31	12	1
def _launch_cloud_training() in tfx/extensions/google_cloud_ai_platform/runner.py	31	12	5