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Added support for Jinja2 3.1.2 and scikit-learn 1.0.2 #418

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Added support for Jinja2 3.1.2 and scikit-learn 1.0.2 #418

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13 changes: 8 additions & 5 deletions eli5/formatters/html.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,10 +18,13 @@
from .trees import tree2text
from .text_helpers import prepare_weighted_spans, PreparedWeightedSpans


template_env = Environment(
loader=PackageLoader('eli5', 'templates'),
extensions=['jinja2.ext.with_'])
try:
template_env = Environment(
loader=PackageLoader('eli5', 'templates'),
extensions=['jinja2.ext.with_'])
except AttributeError:
template_env = Environment(
loader=PackageLoader('eli5', 'templates'))
template_env.globals.update(dict(zip=zip, numpy=np))
template_env.filters.update(dict(
weight_color=lambda w, w_range: format_hsl(weight_color_hsl(w, w_range)),
Expand Down Expand Up @@ -104,7 +107,7 @@ def format_as_html(explanation, # type: Explanation
abs(fw.weight) for fw in explanation.feature_importances.importances)
if explanation.feature_importances else 0,
target_weight_range=max_or_0(
get_weight_range(t.feature_weights) for t in targets
get_weight_range(t.feature_weights) for t in targets
if t.feature_weights is not None),
other_weight_range=max_or_0(
get_weight_range(other)
Expand Down
5 changes: 4 additions & 1 deletion eli5/sklearn/permutation_importance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,10 @@
clone,
is_classifier
)
from sklearn.metrics.scorer import check_scoring
try:
from sklearn.metrics.scorer import check_scoring
except ModuleNotFoundError:
from sklearn.metrics import check_scoring

from eli5.permutation_importance import get_score_importances
from eli5.sklearn.utils import pandas_available
Expand Down
5 changes: 4 additions & 1 deletion eli5/sklearn/transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,10 @@

import numpy as np
from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.feature_selection.base import SelectorMixin
try:
from sklearn.feature_selection.base import SelectorMixin
except ModuleNotFoundError:
from sklearn.feature_selection import SelectorMixin

from sklearn.preprocessing import (
MinMaxScaler,
Expand Down
15 changes: 15 additions & 0 deletions tests/test_import.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,15 @@
import jinja2
import sklearn


def test_import():
from packaging import version
if version.parse(jinja2.__version__) <= version.parse('3.0.3'):
raise ImportError('module "Jinja2" must be of a later version than "3.0.3".')
if version.parse(sklearn.__version__) < version.parse('1.0.2'):
raise ImportError('module "Jinja2" must be version "1.0.2" or later.')
Comment on lines +7 to +10
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What is the goal of these checks? From the code above it seems that we do support older versions of these libraries? If we want to work only with versions specified here, it's better to specify this in setup.py.

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Yeah, the test file is probably not really needed, I omitted it and also slightly changed some other stuff in the PR for https://github.com/eli5-org/eli5/ (the sklearn issue for example was already resolved)

import eli5


if __name__ == '__main__':
test_import()