CTYPTO/freqtrade
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2026-01-20 05:50:36 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix some formatting issues

Browse Source
This commit is contained in:
viotemp1
2025-04-29 17:09:16 +03:00
parent 5c47a75f63
commit ced1ce340a
2 changed files with 4 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
freqtrade/optimize/hyperopt/hyperopt.py
View File

@@ -147,9 +147,7 @@ class Hyperopt:
self.print_all,
)
def run_optimizer_parallel(
self, parallel: Parallel, asked: list[list]
) -> list[dict[str, Any]]:
def run_optimizer_parallel(self, parallel: Parallel, asked: list[list]) -> list[dict[str, Any]]:
"""Start optimizer in a parallel way"""
def optimizer_wrapper(*args, **kwargs):
@@ -160,9 +158,7 @@ class Hyperopt:
return self.hyperopter.generate_optimizer(*args, **kwargs)
return parallel(
delayed(wrap_non_picklable_objects(optimizer_wrapper))(v) for v in asked
)
return parallel(delayed(wrap_non_picklable_objects(optimizer_wrapper))(v) for v in asked)
def _set_random_state(self, random_state: int | None) -> int:
return random_state or random.randint(1, 2**16 - 1) # noqa: S311
@@ -287,9 +283,7 @@ class Hyperopt:
asked, is_random = self.get_asked_points(
n_points=1, dimensions=self.hyperopter.o_dimensions
)
f_val0 = self.hyperopter.generate_optimizer(
asked[0].params
)
f_val0 = self.hyperopter.generate_optimizer(asked[0].params)
self.opt.tell(asked[0], [f_val0["loss"]])
self.evaluate_result(f_val0, 1, is_random[0])
pbar.update(task, advance=1)
@@ -308,7 +302,6 @@ class Hyperopt:
f_val = self.run_optimizer_parallel(
parallel,
# self.hyperopter.backtesting,
[asked1.params for asked1 in asked],
)
f_val_loss = [v["loss"] for v in f_val]

4
tests/optimize/test_hyperopt.py
View File

@@ -605,9 +605,7 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
hyperopt.hyperopter.min_date = dt_utc(2017, 12, 10)
hyperopt.hyperopter.max_date = dt_utc(2017, 12, 13)
hyperopt.hyperopter.init_spaces()
generate_optimizer_value = hyperopt.hyperopter.generate_optimizer(
optimizer_param
)
generate_optimizer_value = hyperopt.hyperopter.generate_optimizer(optimizer_param)
assert generate_optimizer_value == response_expected