def test_import_optional():
match = "Missing .*notapackage.* pip .* conda .* notapackage"
with pytest.raises(ImportError, match=match):
import_optional_dependency("notapackage")
result = import_optional_dependency("notapackage", raise_on_missing=False)
assert result is None
def test_no_version_raises():
name = "fakemodule"
module = types.ModuleType(name)
sys.modules[name] = module
VERSIONS[name] = "1.0.0"
with pytest.raises(ImportError, match="Can't determine .* fakemodule"):
import_optional_dependency(name)
def test_bad_version():
name = "fakemodule"
module = types.ModuleType(name)
module.__version__ = "0.9.0"
sys.modules[name] = module
VERSIONS[name] = "1.0.0"
match = "Eland requires .*1.0.0.* of .fakemodule.*'0.9.0'"
with pytest.raises(ImportError, match=match):
import_optional_dependency("fakemodule")
with pytest.warns(UserWarning):
result = import_optional_dependency("fakemodule", on_version="warn")
assert result is None
module.__version__ = "1.0.0" # exact match is OK
result = import_optional_dependency("fakemodule")
assert result is module
def test_xlrd_version_fallback():
pytest.importorskip("xlrd")
import_optional_dependency("xlrd")
# Licensed to Elasticsearch B.V under one or more agreements.
# Elasticsearch B.V licenses this file to you under the Apache 2.0 License.
# See the LICENSE file in the project root for more information
from typing import List, Union
import numpy as np
from eland.ml._optional import import_optional_dependency
from eland.ml._model_serializer import Tree, TreeNode, Ensemble
sklearn = import_optional_dependency("sklearn")
xgboost = import_optional_dependency("xgboost")
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.utils.validation import check_is_fitted
from xgboost import Booster, XGBRegressor, XGBClassifier
class ModelTransformer:
def __init__(
self,
model,
feature_names: List[str],
classification_labels: List[str] = None,
classification_weights: List[float] = None,
):
self._feature_names = feature_names
self._model = model
self._classification_labels = classification_labels
