def test_restore_model_close_old(savetestmodel, name, newname):
"""Test restore_model API with/without name args."""
model, file = savetestmodel
model.close()
newmodel = mx.restore_model(file, name)
assert newmodel.name == newname
def test_new_pandas(tmp_path, pdobj, meth, is_relative, save_meth, filetype):
p = getattr(mx, meth)()
parent_name = p.name
path = "files/testpandas.xlsx" if is_relative else (tmp_path /
"testpandas.xlsx")
p.new_pandas(name="pdref", path=path, data=pdobj, filetype=filetype)
if save_meth == "backup":
datapath = tmp_path / "data"
datapath.mkdir()
getattr(p.model, save_meth)(tmp_path / "model", datapath=datapath)
p.model.close()
m2 = mx.restore_model(tmp_path / "model", datapath=datapath)
else:
getattr(p.model, save_meth)(tmp_path / "model")
p.model.close()
m2 = mx.read_model(tmp_path / "model")
p2 = m2 if meth == "new_model" else m2.spaces[parent_name]
if isinstance(pdobj, pd.DataFrame):
pd.testing.assert_frame_equal(getattr(p2, "pdref")(), pdobj)
pd.testing.assert_frame_equal(getattr(p2, "pdref").value, pdobj)
elif isinstance(pdobj, pd.Series):
pd.testing.assert_series_equal(getattr(p2, "pdref")(), pdobj)
pd.testing.assert_series_equal(getattr(p2, "pdref").value, pdobj)
m2.close()
def test_new_excel_range(tmp_path, meth, is_relative, edit_value, save_meth):
"""Check data new_excel_range
Check data before and after value edit before after saving and reloading
"""
p = getattr(mx, meth)()
parent_name = p.name
for kwargs in testargs:
kwargs = kwargs.copy()
kwargs["path"] = ("files/testexcel.xlsx"
if is_relative else tmp_path / "testexcel.xlsx")
kwargs["sheet"] = "TestTables"
kwargs["loadpath"] = XL_TESTDATA
expected = kwargs.pop("expected").copy()
p.new_excel_range(**kwargs)
xlr = getattr(p, kwargs["name"])
if edit_value:
for key, val in xlr.items():
xlr[key] = 2 * val
for key, val in expected.items():
expected[key] = 2 * val
assert xlr == expected
if save_meth == "backup":
datapath = tmp_path / "data"
datapath.mkdir()
getattr(p.model, save_meth)(tmp_path / "model", datapath=datapath)
p.model.close()
m2 = mx.restore_model(tmp_path / "model", datapath=datapath)
else:
getattr(p.model, save_meth)(tmp_path / "model")
p.model.close()
m2 = mx.read_model(tmp_path / "model")
p2 = m2 if meth == "new_model" else m2.spaces[parent_name]
for kwargs in testargs:
name = kwargs["name"]
expected = kwargs["expected"].copy()
if edit_value:
expected = {key: 2 * val for key, val in expected.items()}
assert getattr(p2, name) == expected
m2.close()
def unpickled_model(request, derived_sample, tmpdir_factory):
model = derived_sample
if request.param:
file = str(tmpdir_factory.mktemp("data").join("testmodel.mx"))
model.save(file)
model.close()
model = mx.restore_model(file)
yield model
model.close()
def refspace(request, refmodel, tmpdir_factory):
model = refmodel
if request.param:
file = str(tmpdir_factory.mktemp("data").join("refmodel.mx"))
model.save(file)
model.close()
model = mx.restore_model(file)
yield model.SpaceA
model.close()
def test_save_again(tmpdir_factory):
m, s = mx.new_model(), mx.new_space()
@mx.defcells
def a():
return 1
file = str(tmpdir_factory.mktemp("data").join("test_save_again.mx"))
m.save(file)
m2 = mx.restore_model(file)
m2.save(file)
def sample_dynamic_model(request, build_sample_dynamic_model, tmpdir_factory):
model = build_sample_dynamic_model
if request.param:
file = str(tmpdir_factory.mktemp("data").join(model.name + ".mx"))
model.save(file)
model.close()
model = mx.restore_model(file)
yield model
model.close()
def test_new_module(tmp_path, parent, save_meth, module):
if parent == "model":
p = mx.new_model(name="Parent")
else:
p = mx.new_model().new_space(name="Parent")
p.new_module(name="Foo", path="Parent/Foo", module=module)
p.Bar = p.Foo
assert p.Foo.modbar(2) == 4
getattr(p.model, save_meth)(tmp_path / "model")
p.model.close()
if save_meth == "backup":
m2 = mx.restore_model(tmp_path / "model")
else:
m2 = mx.read_model(tmp_path / "model")
p2 = m2 if parent == "model" else m2.spaces["Parent"]
assert p2.Foo.modbar(2) == 4
assert p2.Bar is p2.Foo
# Check saving again
# https://github.com/fumitoh/modelx/issues/45
getattr(p2.model, save_meth)(tmp_path / "model")
m2.close()
if save_meth == "backup":
m3 = mx.restore_model(tmp_path / "model")
else:
m3 = mx.read_model(tmp_path / "model")
p3 = m3 if parent == "model" else m3.spaces["Parent"]
assert p3.Foo.modbar(2) == 4
assert p3.Bar is p3.Foo
def test_restore_model_leave_old(savetestmodel, name, newname, renamed):
"""Test restore_model API with/without name args when old model exists.
Args:
name: Name passed to restore_model
newname: Name the new model should have
renamed: True if the old model is renamed
"""
model, file = savetestmodel
oldname = model.name
newmodel = mx.restore_model(file, name)
assert newmodel.name == newname
assert model.name[: len(oldname)] == oldname
assert renamed != (len(model.name) == len(oldname))
def test_new_pandas(tmp_path, pdobj, meth, is_relative, save_meth, filetype,
expose_data):
p = getattr(mx, meth)()
parent_name = p.name
path = "files/testpandas.xlsx" if is_relative else (tmp_path /
"testpandas.xlsx")
p.new_pandas(name="pdref",
path=path,
data=pdobj,
filetype=filetype,
expose_data=expose_data)
if expose_data:
assert isinstance(p.pdref._mx_dataclient, BaseDataClient)
if save_meth == "backup":
getattr(p.model, save_meth)(tmp_path / "model")
p.model.close()
m2 = mx.restore_model(tmp_path / "model")
else:
getattr(p.model, save_meth)(tmp_path / "model")
p.model.close()
m2 = mx.read_model(tmp_path / "model")
p2 = m2 if meth == "new_model" else m2.spaces[parent_name]
if expose_data:
if isinstance(pdobj, pd.DataFrame):
pd.testing.assert_frame_equal(p2.pdref, pdobj)
assert isinstance(p2.pdref._mx_dataclient, BaseDataClient)
elif isinstance(pdobj, pd.Series):
pd.testing.assert_series_equal(getattr(p2, "pdref"), pdobj)
assert isinstance(p2.pdref._mx_dataclient, BaseDataClient)
else:
if isinstance(pdobj, pd.DataFrame):
pd.testing.assert_frame_equal(p2.pdref(), pdobj)
pd.testing.assert_frame_equal(getattr(p2, "pdref").value, pdobj)
elif isinstance(pdobj, pd.Series):
pd.testing.assert_series_equal(p2.pdref(), pdobj)
pd.testing.assert_series_equal(getattr(p2, "pdref").value, pdobj)
m2.close()
def test_null_object(tmp_path):
"""
m---A---B
+---b <- B
|
C(A)
"""
m = mx.new_model()
A = m.new_space('A')
B = A.new_space('B')
A.b = B
C = m.new_space('C', bases=A)
del A.B
assert not A.b._is_valid()
assert not C.b._is_valid()
m.backup(tmp_path / "model")
m2 = mx.restore_model(tmp_path / "model")
assert not m2.A.b._is_valid()
assert not m2.C.b._is_valid()
testutil.compare_model(m, m2)
