uber / causalml - Unit Size

Intro

Unit size measurements show the distribution of size of units of code (methods, functions...).
Units are classified in four categories based on their size (lines of code): 1-20 (small units), 20-50 (medium size units), 51-100 (long units), 101+ (very long units).
You should aim at keeping units small (< 20 lines). Long units may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.

Learn more...

Unit Size Overall

There are 430 units with 6,275 lines of code in units (42.9% of code).

4 very long units (740 lines of code)
17 long units (1,147 lines of code)
46 medium size units (1,479 lines of code)
113 small units (1,626 lines of code)
250 very small units (1,283 lines of code)

Legend:

101+

51-100

21-50

11-20

1-10

Unit Size per Extension

101+

51-100

21-50

11-20

1-10

Unit Size per Logical Component

primary logical decomposition

101+

51-100

21-50

11-20

1-10

Alternative Visuals

3D view of all units

Longest Units

Top 50 longest units

Unit	# lines	McCabe index	# params
def growDecisionTreeFrom() in causalml/inference/tree/uplift.pyx	297	72	14
def uplift_tree_plot() in causalml/inference/tree/plot.py	195	19	2
def cat_continuous() in causalml/inference/tree/utils.py	140	28	2
def pruneTree() in causalml/inference/tree/uplift.pyx	108	28	9
def fit() in causalml/inference/meta/drlearner.py	92	16	6
def fit() in causalml/inference/meta/rlearner.py	92	11	7
def classify() in causalml/inference/tree/uplift.pyx	88	15	3
def tree_node_summary_to_arr() in causalml/inference/tree/uplift.pyx	74	6	15
def fit() in causalml/inference/tf/dragonnet.py	73	3	5
def estimate_ate() in causalml/inference/meta/tmle.py	73	11	7
def get_synthetic_summary_holdout() in causalml/dataset/synthetic.py	69	10	4
def _obj_func_midp() in causalml/optimize/unit_selection.py	67	4	4
def plot() in causalml/metrics/sensitivity.py	63	11	5
def group_counts_by_divide() in causalml/inference/tree/uplift.pyx	63	12	9
def compute_partial_dependence() in causalml/inference/tree/_tree/_tree.pyx	58	14	5
def match() in causalml/match.py	58	15	4
def make_dragonnet() in causalml/inference/tf/dragonnet.py	57	1	2
def arr_evaluate_CIT() in causalml/inference/tree/uplift.pyx	57	11	12
def _filter_F_one_feature() in causalml/feature_selection/filters.py	57	9	5
def fit() in causalml/inference/meta/rlearner.py	54	9	7
def fit() in causalml/inference/meta/rlearner.py	52	9	7
def arr_evaluate_IT() in causalml/inference/tree/uplift.pyx	50	2	8
def fit() in causalml/inference/tree/uplift.pyx	49	18	7
def evaluate_CIT() in causalml/inference/tree/uplift.pyx	49	2	9
def fit() in causalml/inference/meta/xlearner.py	49	9	5
def check_table_one() in causalml/match.py	48	15	6
def __init__() in causalml/inference/tree/uplift.pyx	47	12	13
def arr_normI() in causalml/inference/tree/uplift.pyx	46	4	5
def get_std_diffs() in causalml/metrics/visualize.py	44	6	5
def get_synthetic_preds() in causalml/dataset/synthetic.py	41	7	3
def fit() in causalml/inference/meta/xlearner.py	41	9	5
def evaluate_IT() in causalml/inference/tree/uplift.pyx	39	3	4
def predict() in causalml/inference/tree/uplift.pyx	38	8	3
def tree_node_summary() in causalml/inference/tree/uplift.pyx	37	6	6
def __init__() in causalml/inference/tree/uplift.pyx	37	3	16
def group_uniqueCounts_to_arr() in causalml/inference/tree/uplift.pyx	36	8	6
def search_best_match() in causalml/match.py	35	11	2
def causalsens() in causalml/metrics/sensitivity.py	33	3	1
def normI() in causalml/inference/tree/uplift.pyx	33	3	7
def simple_tmle() in causalml/inference/meta/tmle.py	33	1	6
def get_pns_bounds() in causalml/optimize/pns.py	33	4	5
def make_uplift_classification() in causalml/dataset/classification.py	32	1	0
def get_synthetic_summary() in causalml/dataset/synthetic.py	32	5	4
def predict() in causalml/inference/iv/drivlearner.py	29	9	6
def divideSet_len() in causalml/inference/tree/uplift.pyx	29	5	5
def arr_evaluate_Chi() in causalml/inference/tree/uplift.pyx	29	2	4
def fit() in causalml/inference/tree/uplift.pyx	28	8	7
def kl_divergence() in causalml/inference/tree/uplift.pyx	27	4	2
def partial_rsqs_confounding() in causalml/metrics/sensitivity.py	26	4	4
def bootstrap() in causalml/inference/iv/drivlearner.py	26	5	9