# logger print("%s: %s" % (fn.name, doc))
if doc is None:
continue
ndocs += 0.75
if "args:" in doc:
ndocs += 0.125
else:
comment("%s has no 'args:'" % fn.name)
if "returns:" in doc:
ndocs += 0.125
else:
comment("%s has no 'returns:'" % fn.name)
if ndocs/nfns >= 0.8:
comment("Good docstring coverage")
return ndocs/nfns
def comment_density(code, comment):
lines, nlines = code.split("\n"), len(code.split("\n"))
inline_comments = sum([1 if "#" in line else 0 for line in lines])
return 1.0 if inline_comments > 3 else 0.8 if inline_comments > 0 else 0.5
def examine_descriptiveness(code, comment):
return {
"inline comments": comment_density(code, comment),
"docstring comments": docstring_check(code, comment)
}
# create the metric
Descriptiveness = create_metric("descriptiveness", examine_descriptiveness)
from subprocess import PIPE
from subprocess import STDOUT
from subprocess import Popen as process
from metric import create_metric
temp_dir = os.getenv('temp', "./")
temp_file = "{tmp}/lintable.py"
def lint(code, comment):
# write input code to tmp file
fp = temp_file.format(tmp=temp_dir)
with open(fp, "w") as fh:
fh.write(code)
fh.close()
# lint it
out, err = process(["pep8", "--count", abspath(fp)],
stdout=PIPE,
stderr=STDOUT).communicate()
if out == b'':
comment("Good adherence to PEP8")
return 1
else:
comment(out)
return 1 - len(str(out).split("\n")) / len(code.split("\n"))
# create the metric
Formatting = create_metric("formatting", lint)
