Upgrade python version to include 3.12 and 3.13

.github/workflows/tests.yml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.8]
+        python-version: ['3.10']
         os: [ubuntu-latest]
     steps:
     - uses: actions/checkout@v1
@@ -20,7 +20,7 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
     - name: Upgrade pip
-      run: pip install -U pip setuptools wheel
+      run: pip install -U "pip<=24.1" setuptools wheel
     - name: Install lightfm
       run: python -m pip install --no-use-pep517 'lightfm<2'
     - name: Install package
@@ -32,7 +32,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: ['3.8', '3.9', '3.10', '3.11']
         os: [ubuntu-20.04, macos-latest]
     steps:
     - uses: actions/checkout@v1
@@ -53,7 +53,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: ['3.6', '3.7', '3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12', '3.13']
         os: [ubuntu-20.04, macos-latest]
     steps:
     - uses: actions/checkout@v1
@@ -70,7 +70,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: ['3.8', '3.9', '3.10', '3.11']
         os: [ubuntu-20.04, macos-latest]
     steps:
     - uses: actions/checkout@v1
@@ -91,7 +91,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: ['3.8', '3.9', '3.10', '3.11']
         os: [ubuntu-20.04]
     steps:
     - uses: actions/checkout@v1

README.md

@@ -50,7 +50,7 @@ Features include:
 
 ## Requirements
 
-**MLBlocks** has been developed and tested on [Python 3.6, 3.7, 3.8, 3.9, and 3.10](https://www.python.org/downloads/)
+**MLBlocks** has been developed and tested on [Python 3.8, 3.9, 3.10, 3.11, 3.12, 3.13](https://www.python.org/downloads/)
 
 ## Install with `pip`
 

examples/tutorials/7. Tuning a Pipeline.ipynb

@@ -181,7 +181,7 @@
     {
      "data": {
       "text/plain": [
-       "0.8639171383183359"
+       "0.863978563379761"
       ]
      },
      "execution_count": 6,
@@ -210,7 +210,7 @@
     {
      "data": {
       "text/plain": [
-       "0.8686773872402614"
+       "0.868554574842"
       ]
      },
      "execution_count": 7,
@@ -242,7 +242,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from btb.tuning import Tunable\n",
+    "from baytune.tuning import Tunable\n",
     "\n",
     "tunable = Tunable.from_dict(tunable_hyperparameters)"
    ]
@@ -265,7 +265,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from btb.tuning import GPTuner\n",
+    "from baytune.tuning import GPTuner\n",
     "\n",
     "tuner = GPTuner(tunable)"
    ]
@@ -345,16 +345,15 @@
      "output_type": "stream",
      "text": [
       "scoring pipeline 1\n",
+      "New best found: 0.871994161365419\n",
       "scoring pipeline 2\n",
+      "New best found: 0.8723319756253888\n",
       "scoring pipeline 3\n",
       "scoring pipeline 4\n",
-      "New best found: 0.8642241881762839\n",
       "scoring pipeline 5\n",
       "scoring pipeline 6\n",
       "scoring pipeline 7\n",
-      "New best found: 0.8644390957265209\n",
       "scoring pipeline 8\n",
-      "New best found: 0.8679095503945804\n",
       "scoring pipeline 9\n",
       "scoring pipeline 10\n"
      ]
@@ -395,13 +394,13 @@
      "data": {
       "text/plain": [
        "{('mlprimitives.custom.feature_extraction.CategoricalEncoder#1',\n",
-       "  'max_labels'): 39,\n",
-       " ('sklearn.impute.SimpleImputer#1', 'strategy'): 'most_frequent',\n",
-       " ('xgboost.XGBClassifier#1', 'n_estimators'): 70,\n",
-       " ('xgboost.XGBClassifier#1', 'max_depth'): 6,\n",
-       " ('xgboost.XGBClassifier#1', 'learning_rate'): 0.07406443671152008,\n",
-       " ('xgboost.XGBClassifier#1', 'gamma'): 0.9244108160038952,\n",
-       " ('xgboost.XGBClassifier#1', 'min_child_weight'): 1}"
+       "  'max_labels'): 60,\n",
+       " ('sklearn.impute.SimpleImputer#1', 'strategy'): 'mean',\n",
+       " ('xgboost.XGBClassifier#1', 'n_estimators'): 190,\n",
+       " ('xgboost.XGBClassifier#1', 'max_depth'): 5,\n",
+       " ('xgboost.XGBClassifier#1', 'learning_rate'): 0.13575511242790694,\n",
+       " ('xgboost.XGBClassifier#1', 'gamma'): 0.6326488945712287,\n",
+       " ('xgboost.XGBClassifier#1', 'min_child_weight'): 8}"
       ]
      },
      "execution_count": 13,
@@ -443,7 +442,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -457,7 +456,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.10.15"
   }
  },
  "nbformat": 4,