def serve(barFeed, strategyParameters, address, port):
"""Executes a server that will provide bars and strategy parameters for workers to use.
:param barFeed: The bar feed that each worker will use to backtest the strategy.
:type barFeed: :class:`pyalgotrade.barfeed.BarFeed`.
:param strategyParameters: The set of parameters to use for backtesting. An iterable object where **each element is a tuple that holds parameter values**.
:param address: The address to listen for incoming worker connections.
:type address: string.
:param port: The port to listen for incoming worker connections.
:type port: int.
:rtype: A :class:`Results` instance with the best results found or None if no results were obtained.
"""
paramSource = base.ParameterSource(strategyParameters)
resultSinc = base.ResultSinc()
s = xmlrpcserver.Server(paramSource, resultSinc, barFeed, address, port)
logger.info("Starting server")
s.serve()
logger.info("Server finished")
ret = None
bestResult, bestParameters = resultSinc.getBest()
if bestResult is not None:
logger.info("Best final result %s with parameters %s" %
(bestResult, bestParameters.args))
ret = Results(bestParameters.args, bestResult)
else:
logger.error("No results. All jobs failed or no jobs were processed.")
return ret
def run_impl(strategyClass,
barFeed,
strategyParameters,
workerCount=None,
logLevel=logging.ERROR,
resultSinc=None):
assert (workerCount is None or workerCount > 0)
if workerCount is None:
workerCount = multiprocessing.cpu_count()
ret = None
workers = []
port = find_port()
if port is None:
raise Exception("Failed to find a port to listen")
# Build and start the server thread before the worker processes.
# We'll manually stop the server once workers have finished.
paramSource = base.ParameterSource(strategyParameters)
if resultSinc is None:
resultSinc = base.ResultSinc()
# Create and start the server.
logger.info("Starting server")
srv = xmlrpcserver.Server(paramSource, resultSinc, barFeed, "localhost",
port, False)
serverThread = ServerThread(srv)
serverThread.start()
try:
logger.info("Starting workers")
# Build the worker processes.
for i in range(workerCount):
workers.append(
multiprocessing.Process(target=worker_process,
args=(strategyClass, port, logLevel)))
# Start workers
for process in workers:
process.start()
# Wait for all jobs to complete.
while srv.jobsPending():
time.sleep(1)
finally:
# Stop workers
for process in workers:
stop_process(process)
# Stop and wait the server to finish.
logger.info("Stopping server")
srv.stop()
serverThread.join()
bestResult, bestParameters = resultSinc.getBest()
if bestResult is not None:
ret = server.Results(bestParameters.args, bestResult)
return ret
def run(strategyClass, barFeed, strategyParameters, workerCount=None, logLevel=logging.ERROR):
"""Executes many instances of a strategy in parallel and finds the parameters that yield the best results.
:param strategyClass: The strategy class.
:param barFeed: The bar feed to use to backtest the strategy.
:type barFeed: :class:`pyalgotrade.barfeed.BarFeed`.
:param strategyParameters: The set of parameters to use for backtesting. An iterable object where **each element is
a tuple that holds parameter values**.
:param workerCount: The number of strategies to run in parallel. If None then as many workers as CPUs are used.
:type workerCount: int.
:param logLevel: The log level. Defaults to **logging.ERROR**.
:rtype: A :class:`Results` instance with the best results found.
"""
assert(workerCount is None or workerCount > 0)
if workerCount is None:
workerCount = multiprocessing.cpu_count()
ret = None
workers = []
port = find_port()
if port is None:
raise Exception("Failed to find a port to listen")
# Build and start the server thread before the worker processes.
# We'll manually stop the server once workers have finished.
paramSource = base.ParameterSource(strategyParameters)
resultSinc = base.ResultSinc()
srv = xmlrpcserver.Server(paramSource, resultSinc, barFeed, "localhost", port, False)
serverThread = ServerThread(srv)
serverThread.start()
try:
# Build the worker processes.
for i in range(workerCount):
workers.append(multiprocessing.Process(
target=worker_process,
args=(strategyClass, port, logLevel))
)
logger.info("Executing workers")
# Start workers
for process in workers:
process.start()
# Wait workers
for process in workers:
wait_process(process)
logger.info("All workers finished")
finally:
# Stop and wait the server to finish.
srv.stop()
serverThread.join()
bestResult, bestParameters = resultSinc.getBest()
if bestResult is not None:
ret = server.Results(bestParameters.args, bestResult)
return ret