Homec4science
Diffusion akantu (features/38-damage-energy-computation-missing-in-phasefield-model) Browse

rAKA/test/ci/codeclimate/codeclimate-clang-tidy/lib/issue_formatter.py
e29c5d5d51cbfeatures/38-damage…

Last Change
Raw File

issue_formatter.py
View Options

"""Issue_formater for clang-tidy in codeclimate (inspired from cpp-check)."""
__author__ = "Nicolas Richart"
__credits__ = [
"Nicolas Richart <nicolas.richart@epfl.ch>",
]
__copyright__ = "Copyright (©) 2018-2021 EPFL (Ecole Polytechnique Fédérale" \
" de Lausanne) Laboratory (LSMS - Laboratoire de Simulation" \
" en Mécanique des Solides)"
__license__ = "LGPLv3"
import hashlib
import os
class IssueFormatter:
CLASSIFICATIONS = {
'bugprone': {
'categories': ['Bug Risk'],
'severity': 'major',
},
'modernize': {
'categories': ['Clarity', 'Compatibility', 'Style'],
'severity': 'info'
},
'mpi': {
'categories': ['Bug Risk', 'Performance'],
'severity': 'critical',
},
'openmp': {
'categories': ['Bug Risk', 'Performance'],
'severity': 'critical',
},
'performance': {
'categories': ['Performance'],
'severity': 'minor',
},
'readability': {
'categories': ['Clarity', 'Style'],
'severity': 'info'
},
}
def _get_classifiaction(self, type_):
categories = ['Bug Risk']
severity = 'blocker'
if type_ in self.CLASSIFICATIONS:
categories = self.CLASSIFICATIONS[type_]['categories']
severity = self.CLASSIFICATIONS[type_]['severity']
elif type_[0] == 'clang':
if type_[1] == 'diagnostic':
categories = ['Bug Risk']
severity = 'blocker'
elif type_[1] == 'analyzer':
categories = ['Bug Risk']
severity = 'major'
return (categories, severity)
def __init__(self, issue):
self.issue_dict = issue
def format(self):
self.issue_dict['file'] = os.path.relpath(self.issue_dict['file'])
issue = {
'type': 'issue',
'check_name': self.issue_dict['type'],
'description': self.issue_dict['detail'],
'location': {
"path": self.issue_dict['file'],
"lines": {
"begin": int(self.issue_dict['line']),
"end": int(self.issue_dict['line']),
},
"positions": {
"begin": {
"line": int(self.issue_dict['line']),
"column": int(self.issue_dict['column']),
},
"end": {
"line": int(self.issue_dict['line']),
"column": int(self.issue_dict['column']),
},
},
},
}
if 'content' in self.issue_dict:
issue['content'] = {
'body': '```\n' +
'\n'.join(self.issue_dict['content']) +
'\n```'
}
issue['fingerprint'] = hashlib.md5(
'{file}:{line}:{column}:{type}'.format(**self.issue_dict).encode()
).hexdigest()
type_ = self.issue_dict['type'].split('-')[0]
issue['categories'], issue['severity'] = \
self._get_classifiaction(type_)
return issue
c4science · Help