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Make ML libraries optional, fix type issues #206

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merged 1 commit into from
May 14, 2020
Merged

Make ML libraries optional, fix type issues #206

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2 changes: 1 addition & 1 deletion .ci/run-repository.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -35,4 +35,4 @@ docker run \
--name eland-test-runner \
--rm \
elastic/eland \
nox -s test-${PYTHON_VERSION}
nox -s lint test-${PYTHON_VERSION}
2 changes: 1 addition & 1 deletion eland/filter.py
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Expand Up @@ -178,7 +178,7 @@ def __init__(self) -> None:


class RandomScoreFilter(QueryFilter):
def __init__(self, query: QueryFilter, random_state: int) -> None:
def __init__(self, query: BooleanFilter, random_state: int) -> None:
q = MatchAllFilter() if query.empty() else query

seed = {}
Expand Down
22 changes: 11 additions & 11 deletions eland/ml/_model_serializer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
import gzip
import json
from abc import ABC
from typing import List, Dict, Any, Optional
from typing import Sequence, Dict, Any, Optional


def add_if_exists(d: Dict[str, Any], k: str, v: Any) -> None:
Expand All @@ -17,9 +17,9 @@ def add_if_exists(d: Dict[str, Any], k: str, v: Any) -> None:
class ModelSerializer(ABC):
def __init__(
self,
feature_names: List[str],
feature_names: Sequence[str],
target_type: Optional[str] = None,
classification_labels: Optional[List[str]] = None,
classification_labels: Optional[Sequence[str]] = None,
):
self._target_type = target_type
self._feature_names = feature_names
Expand All @@ -33,7 +33,7 @@ def to_dict(self) -> Dict[str, Any]:
return d

@property
def feature_names(self) -> List[str]:
def feature_names(self) -> Sequence[str]:
return self._feature_names

def serialize_model(self) -> Dict[str, Any]:
Expand Down Expand Up @@ -84,10 +84,10 @@ def to_dict(self) -> Dict[str, Any]:
class Tree(ModelSerializer):
def __init__(
self,
feature_names: List[str],
feature_names: Sequence[str],
target_type: Optional[str] = None,
tree_structure: Optional[List[TreeNode]] = None,
classification_labels: Optional[List[str]] = None,
tree_structure: Optional[Sequence[TreeNode]] = None,
classification_labels: Optional[Sequence[str]] = None,
):
super().__init__(
feature_names=feature_names,
Expand All @@ -107,12 +107,12 @@ def to_dict(self) -> Dict[str, Any]:
class Ensemble(ModelSerializer):
def __init__(
self,
feature_names: List[str],
trained_models: List[ModelSerializer],
feature_names: Sequence[str],
trained_models: Sequence[ModelSerializer],
output_aggregator: Dict[str, Any],
target_type: Optional[str] = None,
classification_labels: Optional[List[str]] = None,
classification_weights: Optional[List[float]] = None,
classification_labels: Optional[Sequence[str]] = None,
classification_weights: Optional[Sequence[float]] = None,
):
super().__init__(
feature_names=feature_names,
Expand Down