def _sort_on_date(self, patches):
''' Sort patches on date field. The format is like:
Fri, 28 Dec 2012 21:00:31 +0200
'''
records = []
for patch in patches:
strings = ut.read_strings(ut.join_path(self.patchdir, patch))
for string in strings:
if ("Date:" in string): # e.g. 'Date: Wed, 16 Jan 2013 19:09:47 +0000'
fields = ut.string_to_words(string[6:].lstrip(' \t'))
_, s_day, s_mon, s_year, s_hms, _ = fields
s_hour, s_minute, s_second = s_hms.split(':')
day, year = int(s_day), int(s_year)
hour, minute, second = int(s_hour), int(s_minute), int(s_second)
month = self.month_numbers[s_mon]
# ignoring microseconds
dt = datetime(year, month, day, hour, minute, second)
records += [(dt, patch)]
break
records = sorted(records, key = lambda r: r[0])
patches = [patch for (_, patch) in records]
return patches
def _sort_on_date(self, patches):
''' Sort patches on date field. The format is like:
Fri, 28 Dec 2012 21:00:31 +0200
'''
records = []
for patch in patches:
strings = ut.read_strings(ut.join_path(self.patchdir, patch))
for string in strings:
if ("Date:" in string
): # e.g. 'Date: Wed, 16 Jan 2013 19:09:47 +0000'
fields = ut.string_to_words(string[6:].lstrip(' \t'))
_, s_day, s_mon, s_year, s_hms, _ = fields
s_hour, s_minute, s_second = s_hms.split(':')
day, year = int(s_day), int(s_year)
hour, minute, second = int(s_hour), int(s_minute), int(
s_second)
month = self.month_numbers[s_mon]
# ignoring microseconds
dt = datetime(year, month, day, hour, minute, second)
records += [(dt, patch)]
break
records = sorted(records, key=lambda r: r[0])
patches = [patch for (_, patch) in records]
return patches
def _is_landmark(self, filepath, string):
""" Determine if a string is a "landmark" string , i.e. one that is likely to be unique
in the file, and thus may be easy to isolate if it is present. Searching for strings
such as '};' could give a large number of extraneous matches.
"""
if ((len(string) == 0) or string.isspace()):
return False
else:
words = ut.string_to_words(string)
words2 = []
for word in words:
if ('_' in word):
sylls = word.split('_')
words2 += sylls
else:
words2 += [word]
words = words2
words2 = []
for word in words:
if ('-' in word):
sylls = word.split('-')
words2 += sylls
else:
words2 += [word]
words = words2
if (len(words) > 4):
return True
index = filepath.rfind('/') + 1
filename = filepath[index:]
if (filename.endswith('.c') or filename.endswith('.h')):
return self._is_c_h_landmark(string, words)
elif (filename.endswith('.S') or filename.endswith('.inc')):
return self._is_S_landmark(string, words)
elif (filename.endswith('.dts') or filename.endswith('.dtsi')):
return self._is_dts_landmark(string, words)
elif (filename.startswith('Kconfig')):
return self._is_Kconfig_landmark(string, words)
elif (filename.startswith('Makefile')):
return self._is_Makefile_landmark(string, words)
return self._is_generic_landmark(string, words)
def _is_landmark(self, filepath, string):
""" Determine if a string is a "landmark" string , i.e. one that is likely to be unique
in the file, and thus may be easy to isolate if it is present. Searching for strings
such as '};' could give a large number of extraneous matches.
"""
if ((len(string) == 0) or string.isspace()):
return False
else:
words = ut.string_to_words(string)
words2 = []
for word in words:
if ('_' in word):
sylls = word.split('_')
words2 += sylls
else:
words2 += [word]
words = words2
words2 = []
for word in words:
if ('-' in word):
sylls = word.split('-')
words2 += sylls
else:
words2 += [word]
words = words2
if (len(words) > 4):
return True
index = filepath.rfind('/') + 1
filename = filepath[index:]
if (filename.endswith('.c') or filename.endswith('.h')):
return self._is_c_h_landmark(string, words)
elif (filename.endswith('.S') or filename.endswith('.inc')):
return self._is_S_landmark(string, words)
elif (filename.endswith('.dts') or filename.endswith('.dtsi')):
return self._is_dts_landmark(string, words)
elif (filename.startswith('Kconfig')):
return self._is_Kconfig_landmark(string, words)
elif (filename.startswith('Makefile')):
return self._is_Makefile_landmark(string, words)
return self._is_generic_landmark(string, words)