dump_one has a cyclomatic complexity of 20 with "high" risk798
799
800@document_dump_one("Molden", ["atcoords", "atnums", "mo", "obasis"], ["atcorenums", "title"])
801def dump_one(f: TextIO, data: IOData):802 """Do not edit this docstring. It will be overwritten."""
803 # Print the header
804 f.write("[Molden Format]\n")dump_one has a cyclomatic complexity of 55 with "critical" risk616 "moments",
617 ],
618)
619def dump_one(f: TextIO, data: IOData):620 """Do not edit this docstring. It will be overwritten."""
621 # write title
622 print("{:72}".format(data.title or "FCHK generated by IOData"), file=f)load_one has a cyclomatic complexity of 30 with "very-high" risk 78 ],
79 ["energy", "atfrozen", "atgradient", "athessian", "atmasses", "one_rdms", "extra", "moments"],
80)
81def load_one(lit: LineIterator) -> dict: 82 """Do not edit this docstring. It will be overwritten."""
83 fchk = _load_fchk_low(
84 lit,compute_overlap has a cyclomatic complexity of 23 with "high" risk 65 raise TypeError(f"Unsupported type of argument n: {type(n)}")
66
67
68def compute_overlap( 69 obasis0: MolecularBasis,
70 atcoords0: NDArray[float],
71 obasis1: Optional[MolecularBasis] = None,load_data_wfx has a cyclomatic complexity of 16 with "high" risk118 )
119
120
121def load_data_wfx(lit: LineIterator) -> dict:122 """Process loaded WFX data."""
123 # get all section labels and required labels for WFX files
124 lbs_str, lbs_int, lbs_float, lbs_aint, lbs_afloat, lbs_other, required_tags = _wfx_labels()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. |