def __init__(self,
repo_location,
repo_command,
repo_type='hg',
date_range=''):
if not os.path.exists(repo_location):
raise ChurnDriverError("Repo Location does not exist: %s" %
repo_location)
if not repo_command:
raise ChurnDriverError("Repo Command cannot be empty")
self._repo_location = os.path.abspath(repo_location)
self._repo_type = repo_type
self._cmd = repo_command
self._dp = DiffParser(self._repo_type)
self._ch = ChurnHash()
self._backend = SQLiteBackend()
self._daterange = date_range
def __init__(self, repo_location, repo_command, repo_type='hg', date_range=''):
if not os.path.exists(repo_location):
raise ChurnDriverError("Repo Location does not exist: %s" % repo_location)
if not repo_command:
raise ChurnDriverError("Repo Command cannot be empty")
self._repo_location = os.path.abspath(repo_location)
self._repo_type = repo_type
self._cmd = repo_command
self._dp = DiffParser(self._repo_type)
self._ch = ChurnHash()
self._backend = SQLiteBackend()
self._daterange = date_range
class ChurnDriver(object):
def __init__(self,
repo_location,
repo_command,
repo_type='hg',
date_range=''):
if not os.path.exists(repo_location):
raise ChurnDriverError("Repo Location does not exist: %s" %
repo_location)
if not repo_command:
raise ChurnDriverError("Repo Command cannot be empty")
self._repo_location = os.path.abspath(repo_location)
self._repo_type = repo_type
self._cmd = repo_command
self._dp = DiffParser(self._repo_type)
self._ch = ChurnHash()
self._backend = SQLiteBackend()
self._daterange = date_range
def run(self):
args = shlex.split(self._cmd)
p = subprocess.Popen(args,
cwd=self._repo_location,
stdout=subprocess.PIPE)
sr = StreamReader(p.stdout)
now = time.time()
# Wait for 5 seconds with no output
count = 0
while (time.time() - now < 20):
if sr.is_empty():
print '.',
time.sleep(1)
continue
lines = sr.readline(0.5)
count += 1
if count % 100 == 0:
print "Read %d lines" % count
# Got a line of output, reset timer
now = time.time()
if lines:
diffs = self._dp.parse(lines.split('\n'))
if diffs:
while len(diffs):
d = diffs.popitem()
# These are now key, value tuples, the second half is the embedded dict
# I can't decide what to do next. Either this is an aggregated metric or it isn't
# So, I'm going to store both and we can see which turns out to be useful. We will
# calculate an aggregate metric and a per file metric and store both.
# It may be that it's better to have the database do the aggregation for us in which case
# churnhash.py is totally useless.
chgset = d[0]
user = d[1]['user']
timestamp = d[1]['timestamp']
for k in d[1].keys():
if k not in ('user', 'timestamp'):
# Then it's a file name with a churn value
self._ch.add_file_path(k, d[1][k])
# Add non-aggregated values to our backend
if self._backend:
self._backend.add_single_file_value(
chgset, user, timestamp, k, d[1][k])
p.wait()
# TODO: Now we save to some backend - or perhaps just wire this into churnhash directly
# For now, we pull this back and return it
if self._backend:
h = self._ch.get_hash()
for i in h:
self._backend.store_churn_hash(i, h[i]['file'],
self._daterange,
h[i]['lines_changed'])
return self._ch
class ChurnDriver(object):
def __init__(self, repo_location, repo_command, repo_type='hg', date_range=''):
if not os.path.exists(repo_location):
raise ChurnDriverError("Repo Location does not exist: %s" % repo_location)
if not repo_command:
raise ChurnDriverError("Repo Command cannot be empty")
self._repo_location = os.path.abspath(repo_location)
self._repo_type = repo_type
self._cmd = repo_command
self._dp = DiffParser(self._repo_type)
self._ch = ChurnHash()
self._backend = SQLiteBackend()
self._daterange = date_range
def run(self):
args = shlex.split(self._cmd)
p = subprocess.Popen(args, cwd=self._repo_location, stdout=subprocess.PIPE)
sr = StreamReader(p.stdout)
now = time.time()
# Wait for 5 seconds with no output
count = 0
while (time.time() - now < 20):
if sr.is_empty():
print '.',
time.sleep(1)
continue
lines = sr.readline(0.5)
count += 1
if count % 100 == 0:
print "Read %d lines" % count
# Got a line of output, reset timer
now = time.time()
if lines:
diffs = self._dp.parse(lines.split('\n'))
if diffs:
while len(diffs):
d = diffs.popitem()
# These are now key, value tuples, the second half is the embedded dict
# I can't decide what to do next. Either this is an aggregated metric or it isn't
# So, I'm going to store both and we can see which turns out to be useful. We will
# calculate an aggregate metric and a per file metric and store both.
# It may be that it's better to have the database do the aggregation for us in which case
# churnhash.py is totally useless.
chgset = d[0]
user = d[1]['user']
timestamp = d[1]['timestamp']
for k in d[1].keys():
if k not in ('user','timestamp'):
# Then it's a file name with a churn value
self._ch.add_file_path(k, d[1][k])
# Add non-aggregated values to our backend
if self._backend:
self._backend.add_single_file_value(chgset, user, timestamp, k, d[1][k])
p.wait()
# TODO: Now we save to some backend - or perhaps just wire this into churnhash directly
# For now, we pull this back and return it
if self._backend:
h = self._ch.get_hash()
for i in h:
self._backend.store_churn_hash(i, h[i]['file'], self._daterange, h[i]['lines_changed'])
return self._ch