Use of assert detected. The enclosed code will be removed when compiling to optimised byte code. Open
assert np.all(np.equal(values, values[0]))- Exclude checks
Cyclomatic complexity is too high in function process_tile. (10) Open
@numba.njit(fastmath=True, nogil=True)
def process_tile(tile, n_0, sum_inout, varsum_inout):
'''
Compute sum and variance of :code:`tile` along navigation axis
and merge into aggregation buffers. Numerical "workhorse" for- Read upRead up
- Exclude checks
Cyclomatic Complexity
Cyclomatic Complexity corresponds to the number of decisions a block of code contains plus 1. This number (also called McCabe number) is equal to the number of linearly independent paths through the code. This number can be used as a guide when testing conditional logic in blocks.
Radon analyzes the AST tree of a Python program to compute Cyclomatic Complexity. Statements have the following effects on Cyclomatic Complexity:
| Construct | Effect on CC | Reasoning |
|---|---|---|
| if | +1 | An if statement is a single decision. |
| elif | +1 | The elif statement adds another decision. |
| else | +0 | The else statement does not cause a new decision. The decision is at the if. |
| for | +1 | There is a decision at the start of the loop. |
| while | +1 | There is a decision at the while statement. |
| except | +1 | Each except branch adds a new conditional path of execution. |
| finally | +0 | The finally block is unconditionally executed. |
| with | +1 | The with statement roughly corresponds to a try/except block (see PEP 343 for details). |
| assert | +1 | The assert statement internally roughly equals a conditional statement. |
| Comprehension | +1 | A list/set/dict comprehension of generator expression is equivalent to a for loop. |
| Boolean Operator | +1 | Every boolean operator (and, or) adds a decision point. |
Function process_tile has a Cognitive Complexity of 18 (exceeds 5 allowed). Consider refactoring. Open
def process_tile(tile, n_0, sum_inout, varsum_inout):
'''
Compute sum and variance of :code:`tile` along navigation axis
and merge into aggregation buffers. Numerical "workhorse" for
:meth:`StdDevUDF.process_tile`.- Read upRead up
Cognitive Complexity
Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.
A method's cognitive complexity is based on a few simple rules:
- Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
- Code is considered more complex for each "break in the linear flow of the code"
- Code is considered more complex when "flow breaking structures are nested"
Further reading
File stddev.py has 410 lines of code (exceeds 400 allowed). Consider refactoring. Open
from collections import defaultdict
import functools
import numpy as np
import numbaFunction process_tile has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring. Open
def process_tile(self, tile):
# Calculate a sum and variance minibatch for the tile and update partition buffers
# with it.
key = self.meta.tiling_scheme_idx
n_0 = self.task_data.num_frames[key]- Read upRead up
Cognitive Complexity
Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.
A method's cognitive complexity is based on a few simple rules:
- Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
- Code is considered more complex for each "break in the linear flow of the code"
- Code is considered more complex when "flow breaking structures are nested"
Further reading
Function "merge_single" has 8 parameters, which is greater than the 7 authorized. Open
def merge_single(n, n_0, sum_0, varsum_0, n_1, sum_1, varsum_1, mean_1):- Read upRead up
- Exclude checks
A long parameter list can indicate that a new structure should be created to wrap the numerous parameters or that the function is doing too many things.
Noncompliant Code Example
With a maximum number of 4 parameters:
def do_something(param1, param2, param3, param4, param5):
...
Compliant Solution
def do_something(param1, param2, param3, param4):
...
Function "merge_ndarray" has 8 parameters, which is greater than the 7 authorized. Open
def merge_ndarray(dest_n, dest_sum, dest_varsum, src_n, src_sum, src_varsum, src_mean, forbuf):- Read upRead up
- Exclude checks
A long parameter list can indicate that a new structure should be created to wrap the numerous parameters or that the function is doing too many things.
Noncompliant Code Example
With a maximum number of 4 parameters:
def do_something(param1, param2, param3, param4, param5):
...
Compliant Solution
def do_something(param1, param2, param3, param4):
...
Refactor this function to reduce its Cognitive Complexity from 18 to the 15 allowed. Open
def process_tile(tile, n_0, sum_inout, varsum_inout):- Read upRead up
- Exclude checks
Cognitive Complexity is a measure of how hard the control flow of a function is to understand. Functions with high Cognitive Complexity will be difficult to maintain.
See
Take the required action to fix the issue indicated by this "FIXME" comment. Open
# FIXME proper validation and proof for complex- Read upRead up
- Exclude checks
FIXME tags are commonly used to mark places where a bug is suspected, but which the developer wants to deal with later.
Sometimes the developer will not have the time or will simply forget to get back to that tag.
This rule is meant to track those tags and to ensure that they do not go unnoticed.
Noncompliant Code Example
def divide(numerator, denominator): return numerator / denominator # FIXME denominator value might be 0
See
- MITRE, CWE-546 - Suspicious Comment