Migrate to pandas>=3

.github/workflows/build_and_upload_wheels.yaml

@@ -21,7 +21,7 @@ jobs:
     runs-on: ubuntu-22.04
     strategy:
       matrix:
-        python-version: [3.7, 3.8, 3.9, '3.10', 3.11]
+        python-version: ['3.11', '3.12', '3.13']
     steps:
       - uses: actions/checkout@v3
 

.github/workflows/coverage.yaml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-22.04]
-        python-version: [3.9, "3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13"]
 
     steps:
     - uses: actions/checkout@v4
@@ -24,20 +24,12 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
 
-    - name: Install Python Dependencies for 3.12 and later
-      if: ${{ matrix.python-version >= '3.12' }}
+    - name: Install Python3 Dependencies
       run: |
         python -m pip install --upgrade pip pytest setuptools wheel
-        pip install -r requirements.txt
-        # Optional Dependency for HDF Checkpointing
-        pip install tables
-        python setup.py install
-        python setup.py build_ext --inplace
-        python -m pip list
-
-    - name: Standard Install Python3 Dependencies
-      run: |
-        python -m pip install --upgrade pip pytest
+        # Install hatchet first: pandas 3 support is on its develop branch, and
+        # requirements.txt cannot be resolved against released hatchet versions
+        python -m pip install git+https://github.com/LLNL/hatchet.git@develop
         pip install -r requirements.txt
         # Optional Dependency for HDF Checkpointing
         pip install tables

.github/workflows/unit-tests.yaml

@@ -14,7 +14,7 @@ jobs:
       matrix:
         # TODO: add macos-latest
         os: [ubuntu-latest]
-        python-version: [3.9, "3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13"]
 
     steps:
     - uses: actions/checkout@v2
@@ -30,35 +30,26 @@ jobs:
         # Obtain the latest cached version of npm (either local cache or action cache)
         node-version: node
 
-    - name: Install Python3 dependencies for 3.12 and later
-      if: ${{ matrix.python-version >= '3.12' }}
+    - name: Install Python3 Dependencies
       run: |
         python -m pip install --upgrade pip pytest setuptools wheel
+        # Install hatchet first: pandas 3 support is on its develop branch, and
+        # requirements.txt cannot be resolved against released hatchet versions
+        python -m pip install git+https://github.com/LLNL/hatchet.git@develop
         pip install -r requirements.txt
-        python -m pip install --upgrade --force-reinstall git+https://github.com/LLNL/hatchet.git@develop
-        python setup.py install
-        python setup.py build_ext --inplace
-        python -m pip list
-
-    - name: Standard Install Python3 Dependencies
-      run: |
-        python -m pip install --upgrade pip pytest
-        pip install -r requirements.txt
-        python -m pip install --upgrade --force-reinstall git+https://github.com/LLNL/hatchet.git@develop
         python setup.py install
         python setup.py build_ext --inplace
         python -m pip list
 
     - name: Update Black
-      if: ${{ matrix.python-version == 3.9 }}
+      if: ${{ matrix.python-version == '3.11' }}
       run: |
-        pip install flake8-pytest-importorskip
         pip install --upgrade click==8.0.4
         pip install black==21.12b0
-        pip install flake8==4.0.1
+        pip install flake8==7.3.0
 
     - name: Lint and Format Check with Flake8 and Black
-      if: ${{ matrix.python-version == 3.9 }}
+      if: ${{ matrix.python-version == '3.11' }}
       run: |
         black --diff --check .
         flake8
@@ -67,10 +58,8 @@ jobs:
       run: |
         python license.py verify
 
-    - name: Install ExtraP
-      if: ${{ matrix.python-version >= 3.7 }}
-      run: |
-        pip install extrap
+    # Extra-P is not installed: all Extra-P releases require NumPy < 2, which
+    # pandas 3 does not support, so thicket/tests/test_model_extrap.py is skipped.
 
     - name: Basic Test with pytest
       run: |

docs/getting_started.rst

@@ -15,9 +15,9 @@
 Thicket has the following minimum requirements, which must be installed before Thicket
 is run:
 
-#. Python 3 (3.6 - 3.11)
+#. Python 3 (3.11 or newer)
 #. hatchet
-#. pandas >= 1.1
+#. pandas >= 3.0
 #. numpy
 #. matplotlib, and
 #. scipy

requirements.txt

@@ -1,7 +1,7 @@
 scipy
 numpy
-pandas>=1.1,<3
-llnl-hatchet
+pandas>=3
+llnl-hatchet>=2026.2.0
 matplotlib
 seaborn
 beautifulsoup4

setup.py

@@ -33,7 +33,7 @@ def readme():
         "Source Code": "https://github.com/LLNL/thicket",
         "Documentation": "https://thicket.readthedocs.io/",
     },
-    python_requires=">=3.6.1",
+    python_requires=">=3.11",
     packages=[
         "thicket",
         "thicket.stats",
@@ -44,8 +44,11 @@ def readme():
     install_requires=[
         "scipy",
         "numpy",
-        "pandas >= 1.1,<3",
-        "llnl-hatchet",
+        "pandas >= 3",
+        # pandas 3 support is on hatchet develop (LLNL/hatchet#185). The 2026.2.0
+        # release itself requires pandas<3, so this floor admits hatchet develop and
+        # later releases while excluding older releases that lack a pandas pin.
+        "llnl-hatchet >= 2026.2.0",
         "tqdm",
         "more-itertools",
     ],

thicket/ensemble.py

@@ -154,7 +154,9 @@ def _handle_metadata():
             # Update index to reflect performance data table index
             if metadata_key != inner_idx:
                 for i in range(len(thickets_cp)):
-                    thickets_cp[i].metadata.reset_index(drop=True, inplace=True)
+                    thickets_cp[i].metadata = thickets_cp[i].metadata.reset_index(
+                        drop=True
+                    )
             if metadata_key is None:
                 for i in range(len(thickets_cp)):
                     thickets_cp[i].metadata.index.set_names(
@@ -163,8 +165,10 @@ def _handle_metadata():
             else:
                 for i in range(len(thickets_cp)):
                     if metadata_key != inner_idx:
-                        thickets_cp[i].metadata.set_index(metadata_key, inplace=True)
-                    thickets_cp[i].metadata.sort_index(inplace=True)
+                        thickets_cp[i].metadata = thickets_cp[i].metadata.set_index(
+                            metadata_key
+                        )
+                    thickets_cp[i].metadata = thickets_cp[i].metadata.sort_index()
 
             # Create multi-index columns
             for i in range(len(thickets_cp)):
@@ -215,7 +219,9 @@ def _handle_perfdata():
                     thickets_cp[i].metadata_columns_to_perfdata(
                         "new_profiles", drop=True
                     )
-                    thickets_cp[i].dataframe.reset_index(level=inner_idx, inplace=True)
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.reset_index(
+                        level=inner_idx
+                    )
                     new_mappings.update(
                         pd.Series(
                             thickets_cp[i]
@@ -225,9 +231,11 @@ def _handle_perfdata():
                             index=thickets_cp[i].dataframe[inner_idx],
                         ).to_dict()
                     )
-                    thickets_cp[i].dataframe.drop(inner_idx, axis=1, inplace=True)
-                    thickets_cp[i].dataframe.set_index(
-                        "new_profiles", append=True, inplace=True
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.drop(
+                        inner_idx, axis=1
+                    )
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.set_index(
+                        "new_profiles", append=True
                     )
                     thickets_cp[i].dataframe.index.rename(
                         thickets_cp[i].profile_idx_name,
@@ -238,7 +246,9 @@ def _handle_perfdata():
                 for i in range(len(thickets_cp)):
                     if metadata_key not in thickets_cp[i].dataframe.index.names:
                         thickets_cp[i].metadata_columns_to_perfdata(metadata_key)
-                    thickets_cp[i].dataframe.reset_index(level=inner_idx, inplace=True)
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.reset_index(
+                        level=inner_idx
+                    )
                     new_mappings.update(
                         pd.Series(
                             thickets_cp[i]
@@ -249,11 +259,13 @@ def _handle_perfdata():
                         ).to_dict()
                     )
                     if inner_idx != metadata_key:
-                        thickets_cp[i].dataframe.drop(inner_idx, axis=1, inplace=True)
-                    thickets_cp[i].dataframe.set_index(
-                        metadata_key, append=True, inplace=True
+                        thickets_cp[i].dataframe = thickets_cp[i].dataframe.drop(
+                            inner_idx, axis=1
+                        )
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.set_index(
+                        metadata_key, append=True
                     )
-                    thickets_cp[i].dataframe.sort_index(inplace=True)
+                    thickets_cp[i].dataframe = thickets_cp[i].dataframe.sort_index()
 
             # Create tuple columns
             new_columns = [
@@ -283,16 +295,16 @@ def _handle_perfdata():
             )
 
             # Extract "name" columns to upper level
-            nodes = list(set(combined_th.dataframe.reset_index()["node"]))
-            for node in nodes:
-                combined_th.dataframe.loc[node, "name"] = node.frame["name"]
-            combined_th.dataframe.drop(
+            combined_th.dataframe[("name", "")] = [
+                node.frame["name"]
+                for node in combined_th.dataframe.index.get_level_values("node")
+            ]
+            combined_th.dataframe = combined_th.dataframe.drop(
                 columns=[(headers[i], "name") for i in range(len(headers))],
-                inplace=True,
             )
 
             # Sort DataFrame
-            combined_th.dataframe.sort_index(inplace=True)
+            combined_th.dataframe = combined_th.dataframe.sort_index()
 
             return new_mappings
 
@@ -397,9 +409,9 @@ def _index(
             unify_df = _fill_perfdata(unify_df)
 
         # Sort PerfData
-        unify_df.sort_index(inplace=True)
+        unify_df = unify_df.sort_index()
         # Sort Metadata
-        unify_metadata.sort_index(inplace=True)
+        unify_metadata = unify_metadata.sort_index()
 
         # Remove duplicates in metrics
         unify_inc_metrics = list(set(unify_inc_metrics))

thicket/external/console.py

@@ -128,9 +128,9 @@ def render(self, roots, dataframe, **kwargs):
             metric_series = (dataframe.xs(self.rank, level=1))[self.primary_metric]
         else:
             metric_series = dataframe[self.primary_metric]
-        isfinite_mask = np.isfinite(metric_series.values)
+        isfinite_mask = np.isfinite(metric_series.to_numpy())
         filtered_series = pd.Series(
-            metric_series.values[isfinite_mask], metric_series.index[isfinite_mask]
+            metric_series.to_numpy()[isfinite_mask], metric_series.index[isfinite_mask]
         )
 
         self.max_metric = self.max_value if self.max_value else filtered_series.max()