def cyclomaticComplexity(code):
for member in cc_visit(code):
blockType = member.letter
blockComplexity = member.complexity
blockRank = cc_rank(blockComplexity)
blockFullName = member.fullname
return [average_complexity(cc_visit(code)), cc_rank(average_complexity(cc_visit(code)))]
def compute_complexity(source):
result = []
blocks = cc_visit(source)
mix_path = mi_visit(source, True)
for func in blocks:
result.append(func.name + ": Rank:" + cc_rank(func.complexity))
return result
def get_code_complexity_measures(n1, n2):
globzipfiles = glob.glob('../../../NewData_html/Nova/github_archives/nova-*.zip')
for zipfile2 in globzipfiles[int(n1):int(n2)] :
print zipfile2
commit_id = zipfile2.split('/')[6][:-4]
outf1 = open('/media/mukherjee/OpenStack_Ext_Ha/Nova/Functionname_complexity/'+str(commit_id)+'.txt', 'w')
outf2 = open('/media/mukherjee/OpenStack_Ext_Ha/Nova/Filename_complexity/'+str(commit_id)+'.txt', 'w')
print >> outf1, 'filename|commit_id|function_name|function_letter|function_startline|function_endline|function_complexity'
print >> outf2, 'filename|commit_id|MI|LOC|LLOC|SLOC|multi|blank|single_comments|halstead_volume|cyclomatic_complexity'
with zipfile.ZipFile(zipfile2) as z:
for filename in z.namelist():
if filename.endswith(".py") :
if not os.path.isdir(filename):
# iter through filenames starting from the current directory
# you can pass ignore or exclude patterns here (as strings)
# for example: ignore='tests,docs'
with z.open(filename) as fobj:
source = fobj.read()
# get cc blocks
try :
blocks = cc_visit(source)
if len(blocks) > 0 :
for k in blocks :
function_startline = k.lineno
function_endline = k.endline
function_letter = k.letter
function_classname = k.name
function_complexity = k.complexity
print >> outf1, '%s|%s|%s|%s|%s|%s|%s' % (filename, commit_id, function_classname, function_letter, function_startline, function_endline, function_complexity)
# get MI score
mi = mi_visit(source, True)
# get raw metrics
raw = analyze(source)
LOC = raw[0]
LLOC = raw[1]
SLOC = raw[2]
multi = raw[4]
blank = raw[5]
single_comments = raw[6]
# get MI parameters
mi_par = mi_parameters(source)
halstead_volume = mi_par[0]
cyclomatic_complexity = mi_par[1]
print >> outf2, '%s|%s|%s|%s|%s|%s|%s|%s|%s|%s|%s' % ( filename, commit_id, mi, LOC, LLOC, SLOC, multi, blank, single_comments, halstead_volume, cyclomatic_complexity )
except SyntaxError,e :
continue
def calc_radon(path):
# return iter of blocks
code = open(path).read()
try:
return cc_visit(code)
except SyntaxError:
# logger.warning('%s: %s', path, error)
return []
def calculate_obj_complexity(filetext):
complexities = []
try:
complexity_objs = cc_visit(filetext)
for obj in complexity_objs:
complexities.append(obj.complexity)
return sum(complexities)
except Exception:
return 0.0
def compute_complexity(source):
result = []
# get cc blocks
blocks = cc_visit(source)
# get MI score
mi = mi_visit(source, True)
for func in blocks:
result.append(func.name + "- CC Rank:" + cc_rank(func.complexity))
return result
def compute_complexity(source):
result = []
# get complexity blocks
blocks = cc_visit(source)
# get MI score
mi = mi_visit(source, True)
for slave in blocks:
result.append(slave.name + "-Rank:" + cc_rank(slave.complexity))
return result
def test_complexity():
"""All source and test files should have a low cyclomatic complexity"""
file_paths = glob.iglob('*/*.py')
for file_path in file_paths:
with open(file_path, 'r') as file_obj:
blocks = radon.cc_visit(file_obj.read())
for block in blocks:
fail_msg = '{} ({}) has a cyclomatic complexity of {}'.format(
block.name, file_path, block.complexity)
yield nose.assert_less_equal, block.complexity, 10, fail_msg
def _complexity(self, filepaths):
all_complexity = 0
for filepath in filepaths:
file_obj = open(join(self.repo_dir_path, filepath))
results = sorted_results(cc_visit(file_obj.read()))
complexities = [i.complexity for i in results]
complexity = sum(complexities) / (len(complexities) or 1)
all_complexity += complexity
return all_complexity, cc_rank(all_complexity)
def getCC(filepath): #get cyclical complexity of file
with open(filepath, "r") as myfile:
data = myfile.read()
# cc = cc_visit(data)
# return sum(function[len(function)-1] for function in cc)
try:
cc = cc_visit(data)
return sum(function[len(function) - 1] for function in cc)
except Exception:
return 0
def test_complexity():
file_paths = glob.iglob("*/*.py")
for file_path in file_paths:
with open(file_path, "r") as file:
blocks = radon.cc_visit(file.read())
for block in blocks:
test_doc = "{} ({}) should have a low cyclomatic complexity score"
test_complexity.__doc__ = test_doc.format(block.name, file_path)
fail_msg = "{} ({}) has a cyclomatic complexity of {}".format(block.name, file_path, block.complexity)
yield nose.assert_less_equal, block.complexity, 10, fail_msg
def test_complexity():
file_paths = glob.iglob('*/*.py')
for file_path in file_paths:
with open(file_path, 'r') as file:
blocks = radon.cc_visit(file.read())
for block in blocks:
test_doc = '{} ({}) should have a low cyclomatic complexity score'
test_complexity.__doc__ = test_doc.format(block.name, file_path)
fail_msg = '{} ({}) has a cyclomatic complexity of {}'.format(
block.name, file_path, block.complexity)
yield nose.assert_less_equal, block.complexity, 10, fail_msg
def test_complexity():
"""All source file functions should have a low cyclomatic complexity."""
file_paths = itertools.chain(
glob.iglob('automata/*/*.py'),
glob.iglob('tests/*.py'))
for file_path in file_paths:
with open(file_path, 'r') as file_obj:
blocks = radon.cc_visit(file_obj.read())
for block in blocks:
fail_msg = '{} ({}) has a cyclomatic complexity of {}'.format(
block.name, file_path, block.complexity)
yield nose.assert_less_equal, block.complexity, 10, fail_msg
def calculate_average_cc(filetext):
complexities = []
complexity_objs = cc_visit(filetext)
for obj in complexity_objs:
complexities.append(obj.complexity)
total = sum(complexities)
try:
return total / len(complexities)
except ZeroDivisionError:
return 0.0
def analyze_cc(*paths):
"""Analyze all Python files in the provided paths and return a dictionary
mapping each filename to a list of its components (functions or classes)."""
result = {}
for name in iter_filenames(paths, []):
with open(name) as fobj:
try:
results = cc_visit(fobj.read())
except Exception as e:
log('{0}\n{1}ERROR: {2}', name, ' ' * 4, str(e))
continue
result[name] = results
return result
async def analyze(self, tup: NativeBlobMetricInput) -> Iterable[Metric]:
try:
cc_data = cc_visit(tup.blob.data)
except (SyntaxError, UnicodeDecodeError):
return [] # TODO get an error output?
result = [
Metric(
self.name,
subobject.complexity,
False,
ObjectIdentifier(tup.blob.id, tup.path),
subobject.fullname,
) for subobject in cc_data
]
return result
def collect_metrics(self, program_name):
program_file = open(program_name, 'r')
code = program_file.read()
cc_response = cc_visit(code)
raw_response = analyze(code)
self.cyclomatic_complexity = None
if cc_response:
self.cyclomatic_complexity = cc_response[0].complexity
self.source_lines_of_code = 0
self.comments = 0
if raw_response:
self.source_lines_of_code = raw_response.sloc
self.comments = raw_response.comments
self.user_defined_functions = self.collect_user_defined_functions(code)
self.program_name = program_name
self.level = self.collect_level_being_used(code)
def CodeAnalysis(filepatch='.', methodname=''):
comp = 0
for filename in iter_filenames([filepatch]):
print(str(filename))
with open(filename) as fobj:
source = fobj.read()
blocks = cc_visit(source)
print("Searching for " + methodname + " in " + filepatch)
for i in blocks:
print(i.name + ' - ' + str(i.complexity) + ' - ' + methodname)
if (i.name == methodname):
comp = i.complexity
print('FOUND')
break
return comp
def analyze_cc(paths, exclude, min, max, order_function):
'''Analyze the files located under `paths`.
:param paths: A list of paths to analyze.
:param exclude: A comma-separated string of fnmatch patterns.
:param min: The minimum rank to output.
:param max: The maximum rank to output.
:param order_function: Can be `SCORE`, `LINES` or `ALPHA`, to sort the
results respectively by CC score, line number or name.'''
for name in iter_filenames(paths, exclude):
with open(name) as fobj:
try:
results = sorted_results(cc_visit(fobj.read()), order_function)
yield name, list(_filter_by_rank(results, min, max))
except Exception as e:
log(name, indent=1)
log_error(e, indent=1)
continue
def evaluate_code(kata_test, kata_implementation, kata_path):
"""
Evaluate the code resulting from executing the kata_implementation stared at the given path
:param kata_test: the test to pass
:param kata_implementation: the kata implementation
:param kata_path: the kata script
"""
time_consumption = timeit.timeit(lambda: kata_test(kata_implementation),
number=10000)
with open(kata_path, "r") as kata_file:
kata_code = kata_file.read()
mantainability_index = mi_visit(kata_code, False)
cyclomatic_complexity = cc_visit(kata_code)[0].complexity
return {
"time": time_consumption,
"mi": mantainability_index,
"cc": cyclomatic_complexity
}
def cc(min='A',
max='F',
show_complexity=False,
average=False,
exclude=None,
order='SCORE',
*paths):
'''Analyze the given Python modules and compute Cyclomatic
Complexity (CC).
The output can be filtered using the *min* and *max* flags. In addition
to that, by default complexity score is not displayed.
:param min: The minimum complexity to display (default to A).
:param max: The maximum complexity to display (default to F).
:param show_complexity: Whether or not to show the actual complexity
score together with the A-F rank. Default to False.
:param average: If True, at the end of the analysis display the average
complexity. Default to False.
:param paths: The modules or packages to analyze.
'''
min = min.upper()
max = max.upper()
average_cc = .0
analyzed = 0
order_function = getattr(cc_mod, order.upper(), getattr(cc_mod, 'SCORE'))
for name in iter_filenames(paths, exclude or []):
with open(name) as fobj:
try:
results = sorted_results(cc_visit(fobj.read()), order_function)
except Exception as e:
log('{0}\n{1}ERROR: {2}', name, ' ' * 4, str(e))
continue
cc, blocks = _print_cc_results(name, results, min, max,
show_complexity)
average_cc += cc
analyzed += blocks
if average and analyzed:
cc = average_cc / analyzed
ranked_cc = cc_rank(cc)
log('\n{0} blocks (classes, functions, methods) analyzed.', analyzed)
log('Average complexity: {0}{1} ({2}){3}', RANKS_COLORS[ranked_cc],
ranked_cc, cc, RESET)
def analyze_method(name, filename, commits):
res = []
print("Analyzing method")
for c in tqdm(commits):
g.execute(['git', 'checkout', c[1]])
try:
with open(filename) as f:
code = f.read()
r = cc_visit(
code
) # Will raise SyntaxError if can't parse AST (invalid code has been pushed)
if isinstance(r[0], radon.visitors.Class):
method = next(m for m in r[0].methods if m.name == name)
elif isinstance(r[0], radon.visitors.Function):
method = next(f for f in r if f.name == name)
res.append((c[0], method.complexity))
except (FileNotFoundError, StopIteration, SyntaxError):
res.append((c[0], "--"))
return res
def analyze_cc(paths, exclude, ignore, order_function, no_assert):
"""Analyze the files located under `paths`.
:param paths: A list of paths to analyze.
:param exclude: A comma-separated string of fnmatch patterns.
:param ignore: A comma-separated string of patterns to ignore.
:param min: The minimum rank to output.
:param max: The maximum rank to output.
:param order_function: Can be `SCORE`, `LINES` or `ALPHA`, to sort the
results respectively by CC score, line number or name.
:param no_assert: If `True` assert statements will not be counted."""
for name in iter_filenames(paths, exclude, ignore):
with open(name) as fobj:
try:
results = sorted_results(cc_visit(fobj.read(), no_assert=no_assert), order_function)
yield name, results
except Exception as e:
log(name)
log_error(e, indent=1)
continue
def check_complexity(filepath, complex_val=10):
"""
Check file with radon lib and get complexity of his classes and functions
"""
with open(filepath, 'r') as _file:
results = cc_visit(_file.read())
reports = []
for result in results:
if result.complexity > complex_val:
file_report = dict(file=filepath,
complexity=result.complexity,
message=get_complexity_message(
result.complexity),
line_number=result.lineno,
object_name=result.name)
if isinstance(result, radon_class):
file_report['type'] = 'class'
if isinstance(result, radon_func):
file_report['type'] = 'function'
reports.append(file_report)
return reports
def analyze_cc(paths, exclude, ignore, order_function, no_assert):
'''Analyze the files located under `paths`.
:param paths: A list of paths to analyze.
:param exclude: A comma-separated string of fnmatch patterns.
:param ignore: A comma-separated string of patterns to ignore.
:param min: The minimum rank to output.
:param max: The maximum rank to output.
:param order_function: Can be `SCORE`, `LINES` or `ALPHA`, to sort the
results respectively by CC score, line number or name.
:param no_assert: If `True` assert statements will not be counted.'''
for name in iter_filenames(paths, exclude, ignore):
with open(name) as fobj:
try:
results = sorted_results(
cc_visit(fobj.read(), no_assert=no_assert), order_function)
yield name, results
except Exception as e:
log(name)
log_error(e, indent=1)
continue
def cc(min='A', max='F', show_complexity=False, average=False,
exclude=None, order='SCORE', *paths):
'''Analyze the given Python modules and compute Cyclomatic
Complexity (CC).
The output can be filtered using the *min* and *max* flags. In addition
to that, by default complexity score is not displayed.
:param min: The minimum complexity to display (default to A).
:param max: The maximum complexity to display (default to F).
:param show_complexity: Whether or not to show the actual complexity
score together with the A-F rank. Default to False.
:param average: If True, at the end of the analysis display the average
complexity. Default to False.
:param paths: The modules or packages to analyze.
'''
min = min.upper()
max = max.upper()
average_cc = .0
analyzed = 0
order_function = getattr(cc_mod, order.upper(), getattr(cc_mod, 'SCORE'))
for name in iter_filenames(paths, exclude or []):
with open(name) as fobj:
try:
results = sorted_results(cc_visit(fobj.read()), order_function)
except Exception as e:
log('{0}\n{1}ERROR: {2}', name, ' ' * 4, str(e))
continue
cc, blocks = _print_cc_results(name, results, min, max,
show_complexity)
average_cc += cc
analyzed += blocks
if average and analyzed:
cc = average_cc / analyzed
ranked_cc = cc_rank(cc)
log('\n{0} blocks (classes, functions, methods) analyzed.', analyzed)
log('Average complexity: {0}{1} ({2}){3}', RANKS_COLORS[ranked_cc],
ranked_cc, cc, RESET)
def in_cc_report(module: str, source: str) -> list:
"""
cyclomatic complexity for module "module"
@param module: module name
@param source: source of module
@return list: of tuple (CC, length, type(C/F/M), module, class, method)
"""
res = []
# get cc blocks
blocks = cc_visit(source)
for blk in blocks:
tt = str(blk).split()[0:5:2]
tt[2] = tt[2].rjust(2)
length = str(blk.endline - blk.lineno + 1).rjust(4)
if tt[0] == 'C':
res.append((tt[2], length, tt[0], module, tt[1], ''))
elif tt[0] == 'F':
res.append((tt[2], length, tt[0], module, '', tt[1]))
else:
res.append((tt[2], length ,tt[0], module, *tt[1].split('.')))
return res
def cyclomatic_complexity():
""" funkcja obliczająca złożoność cyklometryczną kodu"""
cc_list = []
for actually_file in RESLUT2:
with open(PATH + '\\' + actually_file, 'r') as open_file:
try:
open_file = open_file.read()
complexity = cc_visit('''{}'''.format(open_file))
for element in complexity:
split_text = str(element).split()
split_text_final_lvl = split_text[2].split('.')
if len(split_text_final_lvl) > 1:
if split_text_final_lvl[1] != '__init__':
cc_list.append(
str(split_text_final_lvl[1]) +
'[{}]'.format(split_text[4]))
else:
cc_list.append(
str(split_text_final_lvl[0]) +
'[{}]'.format(split_text[4]))
except IndentationError as error:
print(error)
return cc_list
def program_complexity(projno, funcno):
"""
Builds and returns two dictionaries mapping filename:cc and filename:mi.
"""
cc_dic = {}
mi_dic = {}
path = os.getcwd() + \
"/extracted_files/proj{0}_func{1}/".format(projno, funcno)
for fname in os.listdir(path):
if fname[-4:] == '.pyc': continue
try:
f = open(path + fname)
content = f.read()
blocks = cc_visit(content)
mi = mi_visit(content, True)
cc_dic[fname] = blocks[0].complexity
mi_dic[fname] = mi
f.close()
except:
print " ERROR: cannot find file " + path + fname
return cc_dic, mi_dic
def compute_complexity(source):
result = []
blocks = cc_visit(source)
for func in blocks:
result.append(func.name + "- CC Rank:" + cc_rank(func.complexity))
return result
def gobble(self, fobj):
'''Analyze the content of the file object.'''
r = cc_visit(fobj.read(), no_assert=self.config.no_assert)
if self.config.show_closures:
r = add_inner_blocks(r)
return sorted_results(r, order=self.config.order)
return fib(n - 1) + fib(n - 2)
class C(A, B):
def fr(self):
return 34
'''
a = ast.parse(mdef)
definitions = [n for n in ast.walk(a) if type(n) == ast.ClassDef]
inheritance_tree = {}
for i in definitions:
inheritance_tree[i.name] = []
print(i.name)
for j in i.bases:
if not j.id== "object":
inheritance_tree[i.name].append(j.id)
print("Inherited",j.id)
import pprint
from radon.complexity import cc_rank, cc_visit
val = cc_visit('''
class A(object):
def meth(self):
return sum(i for i in range(10) if i - 2 < 5)
class B(A):
def thi(self):
return sum(i for i in range(10) if i - 2 < 5)
def fib(n):
if n < 2: return 1
return fib(n - 1) + fib(n - 2)
''')
pp = pprint.PrettyPrinter(indent=4)
#pp.pprint(val)
#print(val)
def gobble(self, fobj):
'''Analyze the content of the file object.'''
r = cc_visit(fobj.read(), no_assert=self.config.no_assert)
return sorted_results(r, order=self.config.order)
def gobble(self, fobj):
'''Analyze the content of the file object.'''
r = cc_visit(fobj.read(), no_assert=self.config.no_assert)
return sorted_results(r, order=self.config.order)
def cyclomaticComplexity(self):
cc = cc_visit(self.sourceFile)
return average_complexity(cc)
def gobble(self, fobj):
'''Analyze the content of the file object.'''
r = cc_visit(fobj.read(), no_assert=self.config.no_assert)
if self.config.show_closures:
r = add_inner_blocks(r)
return sorted_results(r, order=self.config.order)
def get_cyclomatic_complexity(content):
'''
Returns a list of blocks with respect to complexity. A block is a either Function object or a Class object.
'''
return cc_visit(content)
if __name__ == '__main__':
mi_dict = OrderedDict()
param_dict = OrderedDict()
print('1. METHODS OF PROJECT FILES SORTED BY CYCLOMATIC COMPLEXITY')
for filename in iter_filenames(['.']):
file_methods = []
file_complexities = []
methods_dictionary = OrderedDict()
with open(filename) as fobj:
source = fobj.read()
# get cc blocks
blocks = cc_visit(source)
# get MI score
mi = mi_visit(source, True)
mi_dict[mi] = filename
# get raw metrics
raw = analyze(source)
hal_vol, complexity, logic_lines, com_lines = mi_parameters(source)
param_dict[complexity] = (complexity, filename, hal_vol, logic_lines,
com_lines)
# get metrics for each file
file_complexity = sorted_results(blocks)
try:
file_methods.append(re.findall('(?<=.Function\(name=\')[^\']'
def fileComplexity(theFile):
results = cc_visit(theFile)
complexity = sum([i.complexity for i in results])
return complexity
