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c3/optimizers/calibration.py

Summary

Maintainability
A
1 hr
Test Coverage

Consider possible security implications associated with pickle module.
Open

import pickle
Severity: Info
Found in c3/optimizers/calibration.py by bandit

Pickle and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue.
Open

                    measurements.append(pickle.load(pickle_file))
Severity: Minor
Found in c3/optimizers/calibration.py by bandit

Cyclomatic complexity is too high in method optimize_controls. (7)
Open

    def optimize_controls(self) -> None:
        """
        Apply a search algorithm to your gateset given a fidelity function.
        """
        self.log_setup()
Severity: Minor
Found in c3/optimizers/calibration.py by radon

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.

Source: http://radon.readthedocs.org/en/latest/intro.html

Function __init__ has 9 arguments (exceeds 4 allowed). Consider refactoring.
Open

    def __init__(
Severity: Major
Found in c3/optimizers/calibration.py - About 1 hr to fix

    Function log_pickle has 5 arguments (exceeds 4 allowed). Consider refactoring.
    Open

        def log_pickle(self, params, seqs, results, results_std, shots):
    Severity: Minor
    Found in c3/optimizers/calibration.py - About 35 mins to fix

      Method "__init__" has 10 parameters, which is greater than the 7 authorized.
      Open

              self,
        eval_func,
        pmap,
        algorithm,
        dir_path=None,
      Severity: Major
      Found in c3/optimizers/calibration.py by sonar-python

      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):
    ...

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