uber / hypothesis-gufunc 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).

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Conditional Complexity Overall

There are 34 units with 208 lines of code in units (64.2% of code).

0 very complex units (0 lines of code)
0 complex units (0 lines of code)
0 medium complex units (0 lines of code)
4 simple units (54 lines of code)
30 very simple units (154 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 34 most complex units

Unit	# lines	McCabe index	# params
def _tuple_of_arrays() in hypothesis_gufunc/gufunc.py	11	9	5
def _gufunc_arg_shapes() in hypothesis_gufunc/gufunc.py	10	9	3
def _int_or_dict() in hypothesis_gufunc/gufunc.py	10	6	2
def gufunc_arg_shapes() in hypothesis_gufunc/gufunc.py	23	6	2
def _weird_digits() in hypothesis_gufunc/gufunc.py	3	4	1
def fixed_coords_dataarrays() in hypothesis_gufunc/extra/xr.py	6	4	4
def _signature_map() in hypothesis_gufunc/gufunc.py	3	3	2
def subset_lists() in hypothesis_gufunc/extra/xr.py	8	3	3
def _vars_and_dims_pairs() in hypothesis_gufunc/extra/xr.py	7	3	4
def fixed_coords_datasets() in hypothesis_gufunc/extra/xr.py	7	3	4
def _check_set_like() in hypothesis_gufunc/gufunc.py	5	2	2
def _order_check_min_max() in hypothesis_gufunc/gufunc.py	4	2	2
def _append_bcast_dims() in hypothesis_gufunc/gufunc.py	5	2	4
def _check_valid_size_interval() in hypothesis_gufunc/extra/xr.py	7	2	4
def _get_all_dims() in hypothesis_gufunc/extra/xr.py	3	2	1
def vars_to_dims_dicts() in hypothesis_gufunc/extra/xr.py	10	2	4
def xr_coords() in hypothesis_gufunc/extra/xr.py	6	2	4
def xr_coords_dicts() in hypothesis_gufunc/extra/xr.py	6	2	6
def simple_dataarrays() in hypothesis_gufunc/extra/xr.py	6	2	5
def simple_datasets() in hypothesis_gufunc/extra/xr.py	7	2	5
def __repr__() in hypothesis_gufunc/gufunc.py	2	1	1
def _check_valid_size_interval() in hypothesis_gufunc/gufunc.py	4	1	4
def gufunc_args() in hypothesis_gufunc/gufunc.py	5	1	5
def _easy_text() in hypothesis_gufunc/extra/xr.py	2	1	0
def _hashable() in hypothesis_gufunc/extra/xr.py	3	1	0
def xr_dim_lists() in hypothesis_gufunc/extra/xr.py	4	1	2
def xr_var_lists() in hypothesis_gufunc/extra/xr.py	4	1	2
def simple_coords() in hypothesis_gufunc/extra/xr.py	5	1	2
def fixed_dataarrays() in hypothesis_gufunc/extra/xr.py	2	1	0
def dataarrays() in hypothesis_gufunc/extra/xr.py	8	1	0
def mapper() in hypothesis_gufunc/extra/xr.py	5	1	1
def fixed_datasets() in hypothesis_gufunc/extra/xr.py	2	1	0
def datasets() in hypothesis_gufunc/extra/xr.py	10	1	0
def mapper() in hypothesis_gufunc/extra/xr.py	5	1	1