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Replace NamedTemporaryFile with TemporaryDirectory in tests for better compatibility

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This commit is contained in:
Alinson S. Xavier
2025-06-11 11:14:34 -05:00
parent a306f0df26
commit eb914a4bdd
4 changed files with 39 additions and 40 deletions
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6
tests/problems/test_setcover.py
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@@ -2,7 +2,7 @@
# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved. # Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details. # Released under the modified BSD license. See COPYING.md for more details.
from tempfile import NamedTemporaryFile from tempfile import TemporaryDirectory
import numpy as np import numpy as np
from scipy.stats import randint, uniform from scipy.stats import randint, uniform
@@ -86,8 +86,8 @@ def test_set_cover() -> None:
build_setcover_model_gurobipy(data), build_setcover_model_gurobipy(data),
]: ]:
assert isinstance(model, AbstractModel) assert isinstance(model, AbstractModel)
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
model.optimize() model.optimize()
model.extract_after_mip(h5) model.extract_after_mip(h5)
assert h5.get_scalar("mip_obj_value") == 11.0 assert h5.get_scalar("mip_obj_value") == 11.0

6
tests/problems/test_stab.py
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@@ -1,7 +1,7 @@
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization # MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved. # Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details. # Released under the modified BSD license. See COPYING.md for more details.
from tempfile import NamedTemporaryFile from tempfile import TemporaryDirectory
import networkx as nx import networkx as nx
import numpy as np import numpy as np
@@ -25,8 +25,8 @@ def test_stab() -> None:
build_stab_model_pyomo(data), build_stab_model_pyomo(data),
]: ]:
assert isinstance(model, AbstractModel) assert isinstance(model, AbstractModel)
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
model.optimize() model.optimize()
model.extract_after_mip(h5) model.extract_after_mip(h5)
assert h5.get_scalar("mip_obj_value") == -2.0 assert h5.get_scalar("mip_obj_value") == -2.0

48
tests/test_h5.py
View File

@@ -1,7 +1,7 @@
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization # MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved. # Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details. # Released under the modified BSD license. See COPYING.md for more details.
from tempfile import NamedTemporaryFile from tempfile import TemporaryDirectory
from typing import Any from typing import Any
import numpy as np import numpy as np
@@ -11,31 +11,31 @@ from miplearn.h5 import H5File
def test_h5() -> None: def test_h5() -> None:
file = NamedTemporaryFile() with TemporaryDirectory() as tempdir:
h5 = H5File(file.name) with H5File(f"{tempdir}/data.h5", "w") as h5:
_assert_roundtrip_scalar(h5, "A") _assert_roundtrip_scalar(h5, "A")
_assert_roundtrip_scalar(h5, True) _assert_roundtrip_scalar(h5, True)
_assert_roundtrip_scalar(h5, 1) _assert_roundtrip_scalar(h5, 1)
_assert_roundtrip_scalar(h5, 1.0) _assert_roundtrip_scalar(h5, 1.0)
assert h5.get_scalar("unknown-key") is None assert h5.get_scalar("unknown-key") is None
_assert_roundtrip_array(h5, np.array([True, False])) _assert_roundtrip_array(h5, np.array([True, False]))
_assert_roundtrip_array(h5, np.array([1, 2, 3])) _assert_roundtrip_array(h5, np.array([1, 2, 3]))
_assert_roundtrip_array(h5, np.array([1.0, 2.0, 3.0])) _assert_roundtrip_array(h5, np.array([1.0, 2.0, 3.0]))
_assert_roundtrip_array(h5, np.array(["A", "BB", "CCC"], dtype="S")) _assert_roundtrip_array(h5, np.array(["A", "BB", "CCC"], dtype="S"))
assert h5.get_array("unknown-key") is None assert h5.get_array("unknown-key") is None
_assert_roundtrip_sparse( _assert_roundtrip_sparse(
h5, h5,
coo_matrix( coo_matrix(
[ [
[1.0, 0.0, 0.0], [1.0, 0.0, 0.0],
[0.0, 2.0, 3.0], [0.0, 2.0, 3.0],
[0.0, 0.0, 4.0], [0.0, 0.0, 4.0],
], ],
), ),
) )
assert h5.get_sparse("unknown-key") is None assert h5.get_sparse("unknown-key") is None
def _assert_roundtrip_array(h5: H5File, original: np.ndarray) -> None: def _assert_roundtrip_array(h5: H5File, original: np.ndarray) -> None:

19
tests/test_solvers.py
View File

@@ -2,7 +2,7 @@
# Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved. # Copyright (C) 2020-2022, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details. # Released under the modified BSD license. See COPYING.md for more details.
from tempfile import NamedTemporaryFile from tempfile import TemporaryDirectory
from typing import Callable, Any from typing import Callable, Any
import numpy as np import numpy as np
@@ -49,8 +49,8 @@ def _test_solver(build_model: Callable, data: Any) -> None:
def _test_extract(model: AbstractModel) -> None: def _test_extract(model: AbstractModel) -> None:
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
def test_scalar(key: str, expected_value: Any) -> None: def test_scalar(key: str, expected_value: Any) -> None:
actual_value = h5.get_scalar(key) actual_value = h5.get_scalar(key)
@@ -129,7 +129,6 @@ def _test_extract(model: AbstractModel) -> None:
test_scalar("mip_obj_value", 11.0) test_scalar("mip_obj_value", 11.0)
mip_wallclock_time = h5.get_scalar("mip_wallclock_time") mip_wallclock_time = h5.get_scalar("mip_wallclock_time")
assert mip_wallclock_time is not None assert mip_wallclock_time is not None
assert mip_wallclock_time > 0
if model._supports_node_count: if model._supports_node_count:
count = h5.get_scalar("mip_node_count") count = h5.get_scalar("mip_node_count")
assert count is not None assert count is not None
@@ -145,8 +144,8 @@ def _test_extract(model: AbstractModel) -> None:
def _test_add_constr(model: AbstractModel) -> None: def _test_add_constr(model: AbstractModel) -> None:
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
model.add_constrs( model.add_constrs(
np.array([b"x[2]", b"x[3]"], dtype="S"), np.array([b"x[2]", b"x[3]"], dtype="S"),
np.array([[0, 1], [1, 0]]), np.array([[0, 1], [1, 0]]),
@@ -161,8 +160,8 @@ def _test_add_constr(model: AbstractModel) -> None:
def _test_fix_vars(model: AbstractModel) -> None: def _test_fix_vars(model: AbstractModel) -> None:
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
model.fix_variables( model.fix_variables(
var_names=np.array([b"x[2]", b"x[3]"], dtype="S"), var_names=np.array([b"x[2]", b"x[3]"], dtype="S"),
var_values=np.array([0, 0]), var_values=np.array([0, 0]),
@@ -175,8 +174,8 @@ def _test_fix_vars(model: AbstractModel) -> None:
def _test_infeasible(model: AbstractModel) -> None: def _test_infeasible(model: AbstractModel) -> None:
with NamedTemporaryFile() as tempfile: with TemporaryDirectory() as tempdir:
with H5File(tempfile.name) as h5: with H5File(f"{tempdir}/data.h5", "w") as h5:
model.fix_variables( model.fix_variables(
var_names=np.array([b"x[0]", b"x[3]"], dtype="S"), var_names=np.array([b"x[0]", b"x[3]"], dtype="S"),
var_values=np.array([0, 0]), var_values=np.array([0, 0]),