def test_benchmark_file(self):
"""Test running with a benchmark file.
"""
csv_file_path = self.tmpdir.getpath('b.csv')
with open(csv_file_path, 'w') as csv_file:
csv_file.write("date,return\n"
"2020-01-03 00:00:00+00:00,-0.1\n"
"2020-01-06 00:00:00+00:00,0.333\n"
"2020-01-07 00:00:00+00:00,0.167\n"
"2020-01-08 00:00:00+00:00,0.143\n"
"2020-01-09 00:00:00+00:00,6.375\n")
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=None,
benchmark_file=csv_file_path,
)
sid, returns = self.resolve_spec(spec)
self.assertIs(sid, None)
expected_dates = pd.to_datetime(
[
'2020-01-03', '2020-01-06', '2020-01-07', '2020-01-08',
'2020-01-09'
],
utc=True,
)
expected_values = [-0.1, 0.333, 0.167, 0.143, 6.375]
expected_returns = pd.Series(index=expected_dates,
data=expected_values)
assert_series_equal(returns, expected_returns, check_names=False)
def run(ctx, algofile, algotext, define, data_frequency, capital_base, bundle,
bundle_timestamp, benchmark_file, benchmark_symbol, benchmark_sid,
no_benchmark, start, end, output, trading_calendar, print_algo,
metrics_set, local_namespace, blotter):
"""Run a backtest for the given algorithm.
"""
# check that the start and end dates are passed correctly
if start is None and end is None:
# check both at the same time to avoid the case where a user
# does not pass either of these and then passes the first only
# to be told they need to pass the second argument also
ctx.fail(
"must specify dates with '-s' / '--start' and '-e' / '--end'", )
if start is None:
ctx.fail("must specify a start date with '-s' / '--start'")
if end is None:
ctx.fail("must specify an end date with '-e' / '--end'")
if (algotext is not None) == (algofile is not None):
ctx.fail(
"must specify exactly one of '-f' / '--algofile' or"
" '-t' / '--algotext'", )
trading_calendar = get_calendar(trading_calendar)
benchmark_spec = BenchmarkSpec.from_cli_params(
no_benchmark=no_benchmark,
benchmark_sid=benchmark_sid,
benchmark_symbol=benchmark_symbol,
benchmark_file=benchmark_file,
)
return _run(
initialize=None,
handle_data=None,
before_trading_start=None,
analyze=None,
algofile=algofile,
algotext=algotext,
defines=define,
data_frequency=data_frequency,
capital_base=capital_base,
bundle=bundle,
bundle_timestamp=bundle_timestamp,
start=start,
end=end,
output=output,
trading_calendar=trading_calendar,
print_algo=print_algo,
metrics_set=metrics_set,
local_namespace=local_namespace,
environ=os.environ,
blotter=blotter,
benchmark_spec=benchmark_spec,
)
def test_benchmark_sid(self, input_sid):
"""Test running with no benchmark provided, with no_benchmark flag.
"""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=input_sid,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
assert_equal(sid, input_sid)
self.assertIs(returns, None)
def test_no_benchmark_explicitly_disabled(self):
"""Test running with no benchmark provided, with no_benchmark flag.
"""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=True,
benchmark_sid=None,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
self.assertIs(sid, None)
assert_series_equal(returns, self.zero_returns)
def test_no_benchmark(self):
"""Test running with no benchmark provided.
We should have no benchmark sid and have a returns series of all zeros.
"""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=None,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
self.assertIs(sid, None)
self.assertIs(returns, None)
def test_benchmark_sid(self, input_sid):
"""Test running with no benchmark provided, with no_benchmark flag."""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=input_sid,
benchmark_symbol=None,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
assert_equal(sid, input_sid)
assert returns is None
warnings = self.logs_at_level(logbook.WARNING)
expected = []
assert_equal(warnings, expected)
def test_no_benchmark_explicitly_disabled(self):
"""Test running with no benchmark provided, with no_benchmark flag."""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=True,
benchmark_sid=None,
benchmark_symbol=None,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
assert sid is None
assert_series_equal(returns, self.zero_returns)
warnings = self.logs_at_level(logbook.WARNING)
expected = []
assert_equal(warnings, expected)
def test_benchmark_symbol(self, case):
"""Test running with no benchmark provided, with no_benchmark flag.
"""
symbol, expected_sid = case
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=None,
benchmark_symbol=symbol,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
assert_equal(sid, expected_sid)
self.assertIs(returns, None)
warnings = self.logs_at_level(logbook.WARNING)
expected = []
assert_equal(warnings, expected)
def test_benchmark_file(self):
"""Test running with a benchmark file."""
csv_file_path = self.tmpdir.getpath("b.csv")
with open(csv_file_path, "w") as csv_file:
csv_file.write("date,return\n"
"2020-01-03 00:00:00+00:00,-0.1\n"
"2020-01-06 00:00:00+00:00,0.333\n"
"2020-01-07 00:00:00+00:00,0.167\n"
"2020-01-08 00:00:00+00:00,0.143\n"
"2020-01-09 00:00:00+00:00,6.375\n")
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=None,
benchmark_symbol=None,
benchmark_file=csv_file_path,
)
sid, returns = self.resolve_spec(spec)
assert sid is None
expected_dates = pd.to_datetime(
[
"2020-01-03", "2020-01-06", "2020-01-07", "2020-01-08",
"2020-01-09"
],
utc=True,
)
expected_values = [-0.1, 0.333, 0.167, 0.143, 6.375]
expected_returns = pd.Series(index=expected_dates,
data=expected_values)
assert_series_equal(returns, expected_returns, check_names=False)
warnings = self.logs_at_level(logbook.WARNING)
expected = []
assert_equal(warnings, expected)
def test_no_benchmark(self):
"""Test running with no benchmark provided.
We should have no benchmark sid and have a returns series of all zeros.
"""
spec = BenchmarkSpec.from_cli_params(
no_benchmark=False,
benchmark_sid=None,
benchmark_symbol=None,
benchmark_file=None,
)
sid, returns = self.resolve_spec(spec)
self.assertIs(sid, None)
self.assertIs(returns, None)
warnings = self.logs_at_level(logbook.WARNING)
expected = [
'No benchmark configured. Assuming algorithm calls set_benchmark.',
'Pass --benchmark-sid, --benchmark-symbol, or --benchmark-file to set a source of benchmark returns.', # noqa
"Pass --no-benchmark to use a dummy benchmark of zero returns.",
]
assert_equal(warnings, expected)
def run(ctx,
algofile,
algotext,
define,
data_frequency,
capital_base,
bundle,
bundle_timestamp,
benchmark_file,
benchmark_symbol,
benchmark_sid,
no_benchmark,
start,
end,
output,
trading_calendar,
print_algo,
metrics_set,
local_namespace,
blotter,
broker,
broker_uri,
state_file,
realtime_bar_target,
list_brokers):
"""Run a backtest for the given algorithm.
"""
if list_brokers:
click.echo("Supported brokers:")
for _, name, _ in pkgutil.iter_modules(brokers.__path__):
if name != 'broker':
click.echo(name)
return
# check that the start and end dates are passed correctly
if not broker and start is None and end is None:
# check both at the same time to avoid the case where a user
# does not pass either of these and then passes the first only
# to be told they need to pass the second argument also
ctx.fail(
"must specify dates with '-s' / '--start' and '-e' / '--end'",
)
if not broker and start is None:
ctx.fail("must specify a start date with '-s' / '--start'")
if not broker and end is None:
ctx.fail("must specify an end date with '-e' / '--end'")
if broker and broker_uri is None:
ctx.fail("must specify broker-uri if broker is specified")
if broker and state_file is None:
ctx.fail("must specify state-file with live trading")
if broker and realtime_bar_target is None:
ctx.fail("must specify realtime-bar-target with live trading")
brokerobj = None
if broker:
mod_name = 'zipline.gens.brokers.%s_broker' % broker.lower()
try:
bmod = import_module(mod_name)
except ImportError:
ctx.fail("unsupported broker: can't import module %s" % mod_name)
cl_name = '%sBroker' % broker.upper()
try:
bclass = getattr(bmod, cl_name)
except AttributeError:
ctx.fail("unsupported broker: can't import class %s from %s" %
(cl_name, mod_name))
brokerobj = bclass(broker_uri)
if end is None:
end = pd.Timestamp.utcnow() + pd.Timedelta(days=1, seconds=1) # Add 1-second to assure that end is > 1day
if (algotext is not None) == (algofile is not None):
ctx.fail(
"must specify exactly one of '-f' / '--algofile' or"
" '-t' / '--algotext'",
)
trading_calendar = get_calendar(trading_calendar)
benchmark_spec = BenchmarkSpec.from_cli_params(
no_benchmark=no_benchmark,
benchmark_sid=benchmark_sid,
benchmark_symbol=benchmark_symbol,
benchmark_file=benchmark_file,
)
return _run(
initialize=None,
handle_data=None,
before_trading_start=None,
analyze=None,
teardown=None,
algofile=algofile,
algotext=algotext,
defines=define,
data_frequency=data_frequency,
capital_base=capital_base,
bundle=bundle,
bundle_timestamp=bundle_timestamp,
start=start,
end=end,
output=output,
trading_calendar=trading_calendar,
print_algo=print_algo,
metrics_set=metrics_set,
local_namespace=local_namespace,
environ=os.environ,
blotter=blotter,
benchmark_spec=benchmark_spec,
broker=brokerobj,
state_filename=state_file,
realtime_bar_target=realtime_bar_target,
performance_callback=None,
stop_execution_callback=None,
execution_id=None
)