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import _thread as thread
import logging
import operator
import sys
from queue import Empty
from queue import Queue
from threading import Lock
from threading import Semaphore
from threading import Thread
from docker.errors import APIError
from docker.errors import ImageNotFound
from compose.cli.colors import AnsiMode
from compose.cli.colors import green
from compose.cli.colors import red
from compose.cli.signals import ShutdownException
from compose.const import PARALLEL_LIMIT
from compose.errors import CompletedUnsuccessfully
from compose.errors import HealthCheckFailed
from compose.errors import NoHealthCheckConfigured
from compose.errors import OperationFailedError
log = logging.getLogger(__name__)
STOP = object()
class GlobalLimit:
"""Simple class to hold a global semaphore limiter for a project. This class
should be treated as a singleton that is instantiated when the project is.
"""
global_limiter = Semaphore(PARALLEL_LIMIT)
@classmethod
def set_global_limit(cls, value):
if value is None:
value = PARALLEL_LIMIT
cls.global_limiter = Semaphore(value)
def parallel_execute_watch(events, writer, errors, results, msg, get_name, fail_check):
""" Watch events from a parallel execution, update status and fill errors and results.
Returns exception to re-raise.
"""
error_to_reraise = None
for obj, result, exception in events:
if exception is None:
if fail_check is not None and fail_check(obj):
writer.write(msg, get_name(obj), 'failed', red)
else:
writer.write(msg, get_name(obj), 'done', green)
results.append(result)
elif isinstance(exception, ImageNotFound):
# This is to bubble up ImageNotFound exceptions to the client so we
# can prompt the user if they want to rebuild.
errors[get_name(obj)] = exception.explanation
writer.write(msg, get_name(obj), 'error', red)
error_to_reraise = exception
elif isinstance(exception, APIError):
errors[get_name(obj)] = exception.explanation
writer.write(msg, get_name(obj), 'error', red)
elif isinstance(exception, (OperationFailedError, HealthCheckFailed, NoHealthCheckConfigured,
CompletedUnsuccessfully)):
errors[get_name(obj)] = exception.msg
writer.write(msg, get_name(obj), 'error', red)
elif isinstance(exception, UpstreamError):
writer.write(msg, get_name(obj), 'error', red)
else:
errors[get_name(obj)] = exception
error_to_reraise = exception
return error_to_reraise
def parallel_execute(objects, func, get_name, msg, get_deps=None, limit=None, fail_check=None):
"""Runs func on objects in parallel while ensuring that func is
ran on object only after it is ran on all its dependencies.
get_deps called on object must return a collection with its dependencies.
get_name called on object must return its name.
fail_check is an additional failure check for cases that should display as a failure
in the CLI logs, but don't raise an exception (such as attempting to start 0 containers)
"""
objects = list(objects)
stream = sys.stderr
writer = ParallelStreamWriter.get_or_assign_instance(ParallelStreamWriter(stream))
for obj in objects:
writer.add_object(msg, get_name(obj))
for obj in objects:
writer.write_initial(msg, get_name(obj))
events = parallel_execute_iter(objects, func, get_deps, limit)
errors = {}
results = []
error_to_reraise = parallel_execute_watch(
events, writer, errors, results, msg, get_name, fail_check
)
for obj_name, error in errors.items():
stream.write("\nERROR: for {} {}\n".format(obj_name, error))
if error_to_reraise:
raise error_to_reraise
return results, errors
def _no_deps(x):
return []
class State:
"""
Holds the state of a partially-complete parallel operation.
state.started: objects being processed
state.finished: objects which have been processed
state.failed: objects which either failed or whose dependencies failed
"""
def __init__(self, objects):
self.objects = objects
self.started = set()
self.finished = set()
self.failed = set()
def is_done(self):
return len(self.finished) + len(self.failed) >= len(self.objects)
def pending(self):
return set(self.objects) - self.started - self.finished - self.failed
class NoLimit:
def __enter__(self):
pass
def __exit__(self, *ex):
pass
def parallel_execute_iter(objects, func, get_deps, limit):
"""
Runs func on objects in parallel while ensuring that func is
ran on object only after it is ran on all its dependencies.
Returns an iterator of tuples which look like:
# if func returned normally when run on object
(object, result, None)
# if func raised an exception when run on object
(object, None, exception)
# if func raised an exception when run on one of object's dependencies
(object, None, UpstreamError())
"""
if get_deps is None:
get_deps = _no_deps
if limit is None:
limiter = NoLimit()
else:
limiter = Semaphore(limit)
results = Queue()
state = State(objects)
while True:
feed_queue(objects, func, get_deps, results, state, limiter)
try:
event = results.get(timeout=0.1)
except Empty:
continue
# See https://github.com/docker/compose/issues/189
except thread.error:
raise ShutdownException()
if event is STOP:
break
obj, _, exception = event
if exception is None:
log.debug('Finished processing: {}'.format(obj))
state.finished.add(obj)
else:
log.debug('Failed: {}'.format(obj))
state.failed.add(obj)
yield event
def producer(obj, func, results, limiter):
"""
The entry point for a producer thread which runs func on a single object.
Places a tuple on the results queue once func has either returned or raised.
"""
with limiter, GlobalLimit.global_limiter:
try:
result = func(obj)
results.put((obj, result, None))
except Exception as e:
results.put((obj, None, e))
def feed_queue(objects, func, get_deps, results, state, limiter):
"""
Starts producer threads for any objects which are ready to be processed
(i.e. they have no dependencies which haven't been successfully processed).
Shortcuts any objects whose dependencies have failed and places an
(object, None, UpstreamError()) tuple on the results queue.
"""
pending = state.pending()
log.debug('Pending: {}'.format(pending))
for obj in pending:
deps = get_deps(obj)
try:
if any(dep[0] in state.failed for dep in deps):
log.debug('{} has upstream errors - not processing'.format(obj))
results.put((obj, None, UpstreamError()))
state.failed.add(obj)
elif all(
dep not in objects or (
dep in state.finished and (not ready_check or ready_check(dep))
) for dep, ready_check in deps
):
log.debug('Starting producer thread for {}'.format(obj))
t = Thread(target=producer, args=(obj, func, results, limiter))
t.daemon = True
t.start()
state.started.add(obj)
except (HealthCheckFailed, NoHealthCheckConfigured) as e:
log.debug(
'Healthcheck for service(s) upstream of {} failed - '
'not processing'.format(obj)
)
results.put((obj, None, e))
except CompletedUnsuccessfully as e:
log.debug(
'Service(s) upstream of {} did not completed successfully - '
'not processing'.format(obj)
)
results.put((obj, None, e))
if state.is_done():
results.put(STOP)
class UpstreamError(Exception):
pass
class ParallelStreamWriter:
"""Write out messages for operations happening in parallel.
Each operation has its own line, and ANSI code characters are used
to jump to the correct line, and write over the line.
"""
default_ansi_mode = AnsiMode.AUTO
write_lock = Lock()
instance = None
instance_lock = Lock()
@classmethod
def get_instance(cls):
return cls.instance
@classmethod
def get_or_assign_instance(cls, writer):
cls.instance_lock.acquire()
try:
if cls.instance is None:
cls.instance = writer
return cls.instance
finally:
cls.instance_lock.release()
@classmethod
def set_default_ansi_mode(cls, ansi_mode):
cls.default_ansi_mode = ansi_mode
def __init__(self, stream, ansi_mode=None):
if ansi_mode is None:
ansi_mode = self.default_ansi_mode
self.stream = stream
self.use_ansi_codes = ansi_mode.use_ansi_codes(stream)
self.lines = []
self.width = 0
def add_object(self, msg, obj_index):
if msg is None:
return
self.lines.append(msg + obj_index)
self.width = max(self.width, len(msg + ' ' + obj_index))
def write_initial(self, msg, obj_index):
if msg is None:
return
return self._write_noansi(msg, obj_index, '')
def _write_ansi(self, msg, obj_index, status):
self.write_lock.acquire()
position = self.lines.index(msg + obj_index)
diff = len(self.lines) - position
# move up
self.stream.write("%c[%dA" % (27, diff))
# erase
self.stream.write("%c[2K\r" % 27)
self.stream.write("{:<{width}} ... {}\r".format(msg + ' ' + obj_index,
status, width=self.width))
# move back down
self.stream.write("%c[%dB" % (27, diff))
self.stream.flush()
self.write_lock.release()
def _write_noansi(self, msg, obj_index, status):
self.stream.write(
"{:<{width}} ... {}\r\n".format(
msg + ' ' + obj_index, status, width=self.width
)
)
self.stream.flush()
def write(self, msg, obj_index, status, color_func):
if msg is None:
return
if self.use_ansi_codes:
self._write_ansi(msg, obj_index, color_func(status))
else:
self._write_noansi(msg, obj_index, status)
def parallel_operation(containers, operation, options, message):
parallel_execute(
containers,
operator.methodcaller(operation, **options),
operator.attrgetter('name'),
message,
)
def parallel_remove(containers, options):
stopped_containers = [c for c in containers if not c.is_running]
parallel_operation(stopped_containers, 'remove', options, 'Removing')
def parallel_pause(containers, options):
parallel_operation(containers, 'pause', options, 'Pausing')
def parallel_unpause(containers, options):
parallel_operation(containers, 'unpause', options, 'Unpausing')
def parallel_kill(containers, options):
parallel_operation(containers, 'kill', options, 'Killing')
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