plots
has a cyclomatic complexity of 27 with "very-high" risk1229 return metrics
1230
1231
1232def plots(1233 returns,
1234 benchmark=None,
1235 grayscale=False,
metrics
has a cyclomatic complexity of 87 with "critical" risk 715 )
716
717
718def metrics( 719 returns,
720 benchmark=None,
721 rf=0.0,
full
has a cyclomatic complexity of 27 with "very-high" risk 488 f.write(tpl)
489
490
491def full( 492 returns,
493 benchmark=None,
494 rf=0.0,
html
has a cyclomatic complexity of 41 with "very-high" risk 51 return returns, benchmark
52
53
54def html( 55 returns,
56 benchmark=None,
57 rf=0.0,
A function with high cyclomatic complexity can be hard to understand and maintain. Cyclomatic complexity is a software metric that measures the number of independent paths through a function. A higher cyclomatic complexity indicates that the function has more decision points and is more complex.
Functions with high cyclomatic complexity are more likely to have bugs and be harder to test. They may lead to reduced code maintainability and increased development time.
To reduce the cyclomatic complexity of a function, you can:
- Break the function into smaller, more manageable functions.
- Refactor complex logic into separate functions or classes.
- Avoid multiple return paths and deeply nested control expressions.
Bad practice
def number_to_name():
number = input()
if not number.isdigit():
print("Enter a valid number")
return
number = int(number)
if number >= 10:
print("Number is too big")
return
if number == 1:
print("one")
elif number == 2:
print("two")
elif number == 3:
print("three")
elif number == 4:
print("four")
elif number == 5:
print("five")
elif number == 6:
print("six")
elif number == 7:
print("seven")
elif number == 8:
print("eight")
elif number == 9:
print("nine")
Recommended
def number_to_name():
number = input()
if not number.isdigit():
print("Enter a valid number")
return
number = int(number)
if number >= 10:
print("Number is too big")
return
names = {
1: "one",
2: "two",
3: "three",
4: "four",
5: "five",
6: "six",
7: "seven",
8: "eight",
9: "nine",
}
print(names[number])
Issue configuration
Cyclomatic complexity threshold can be configured using the
cyclomatic_complexity_threshold
meta field in the
.deepsource.toml
config file.
Configuring this is optional. If you don't provide a value, the Analyzer will
raise issues for functions with complexity higher than the default threshold,
which is medium
for the Python Analyzer.
Here's the mapping of the risk category to the cyclomatic complexity score to help you configure this better:
Risk category | Cyclomatic complexity range | Recommended action |
---|---|---|
low | 1-5 | No action needed. |
medium | 6-15 | Review and monitor. |
high | 16-25 | Review and refactor. Recommended to add comments if the function is absolutely needed to be kept as it is. |
very-high | 26-50 | Refactor to reduce the complexity. |
critical | >50 | Must refactor this. This can make the code untestable and very difficult to understand. |