Added support for python 3.13.x (fitbenchmarking#1372)

* made code compatible with python 3.13

* changed from 3.x to 3.13 for testing

temp commit

* updated all workflows to use 3.x

* Updated integration tests to use conda env

* removed the integration test hack for testing

---------

Co-authored-by: Andrew Lister <48282025+AndrewLister-STFC@users.noreply.github.com>

Author: RabiyaF

.github/workflows/integration.yml

@@ -13,24 +13,34 @@ jobs:
       fail-fast: false
       matrix:
         os: [macos-13, windows-latest]
-        python: ['3.9', '3.12']
+        python: ['3.9', '3.13']
+        exclude:
+          - os: windows-latest
+            python: '3.13'
     runs-on: ${{ matrix.os }}
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
-    - name: Install python
-      uses: actions/setup-python@v5
+    - name: Set up conda
+      uses: conda-incubator/setup-miniconda@v2
       with:
-        python-version: ${{ matrix.python }}
-        check-latest: true
-    - name: Install dependencies
+          miniconda-version: "latest"
+    - name: Install dependencies in conda env
+      shell: bash
       run: |
-        python -m pip install .[bumps,DFO,gradient-free,minuit,SAS,numdifftools,lmfit,nlopt]
+        source $CONDA/etc/profile.d/conda.sh
+        conda create -n default-test-env python=${{ matrix.python }} -y
+        conda activate default-test-env
+        conda install -c conda-forge nlopt -y
+        python -m pip install .[bumps,DFO,gradient-free,minuit,SAS,numdifftools,lmfit]
         python -m pip install --upgrade .[dev]
-        python -m pip install "numpy<2.0"
-    - name: Run macos tests
-      if: runner.os == 'macOS'
-      run: ci/unit_tests_default.sh
-    - name: Run windows tests
-      if: runner.os == 'Windows'
-      run: bash ci/unit_tests_default.sh
+    - name: Run tests
+      shell: bash
+      run: |
+        source $CONDA/etc/profile.d/conda.sh
+        conda activate default-test-env
+        if [ "${{ matrix.os }}" == "macos-13" ]; then
+          ci/unit_tests_default.sh
+        else
+          bash ci/unit_tests_default.sh
+        fi

.github/workflows/main.yml

@@ -26,7 +26,7 @@ jobs:
     - name: Install python
       uses: actions/setup-python@v5
       with:
-        python-version: '3.12'
+        python-version: '3.13'
         check-latest: true
     - name: Install dependencies
       run: |
@@ -116,7 +116,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python: ['3.9', '3.12']
+        python: ['3.9', '3.13']
     runs-on: ubuntu-latest
     steps:
     - name: Checkout code
@@ -130,12 +130,11 @@ jobs:
       run: |
         python -m pip install .[bumps,DFO,gradient-free,minuit,SAS,numdifftools,lmfit,nlopt]
         python -m pip install --upgrade .[dev]
-        python -m pip install "numpy<2.0"
     - name: Run linux tests
       if: runner.os == 'Linux'
       run: ci/unit_tests_default.sh
     - name: Upload test results
-      if: matrix.python == '3.12'
+      if: matrix.python == '3.13'
       uses: actions/upload-artifact@v4
       with:
         name: default_unit_tests

.github/workflows/release.yml

@@ -14,7 +14,7 @@ jobs:
     - name: 'Choose Python Version'
       uses: actions/setup-python@v5
       with:
-        python-version: '3.12'
+        python-version: '3.13'
         check-latest: true
 
     - name: 'Build'

fitbenchmarking/core/tests/test_fitting_benchmarking.py

@@ -10,6 +10,7 @@
 from unittest.mock import patch
 
 import numpy as np
+from parameterized import parameterized
 
 from fitbenchmarking import test_files
 from fitbenchmarking.controllers.scipy_controller import ScipyController
@@ -168,47 +169,29 @@ def setUp(self):
         self.options = Options(additional_options={"software": ["scipy"]})
         self.cp = Checkpoint(self.options)
 
-    def test_perform_fit_method(self):
+    @parameterized.expand(
+        [
+            ("ENSO.dat", [111.70773805099354, 107.53453144913736]),
+            ("Gauss3.dat", [76.64279628070524, 76.65043476327958]),
+            ("Lanczos1.dat", [0.0009937705466940194, 0.06269418241377904]),
+        ]
+    )
+    def test_perform_fit_method(self, file, expected):
         """
         The test checks __perform_fit method.
         Three /NIST/average_difficulty problem sets
         are run with 2 scipy software minimizers.
         """
+        controller = set_up_controller(file, self.options)
+        fit = Fit(options=self.options, data_dir="test", checkpointer=self.cp)
 
-        testcases = [
-            {
-                "file": "ENSO.dat",
-                "results": [111.70773805099354, 107.53453144913736],
-            },
-            {
-                "file": "Gauss3.dat",
-                "results": [76.64279628070524, 76.65043476327958],
-            },
-            {
-                "file": "Lanczos1.dat",
-                "results": [0.0009937705466940194, 0.06269418241377904],
-            },
-        ]
-
-        for case in testcases:
-            with self.subTest(case["file"]):
-                controller = set_up_controller(case["file"], self.options)
-
-                fit = Fit(
-                    options=self.options, data_dir="test", checkpointer=self.cp
-                )
+        for minimizer, acc in zip(["Nelder-Mead", "Powell"], expected):
+            controller.minimizer = minimizer
+            accuracy, runtimes, energy = fit._Fit__perform_fit(controller)
 
-                for minimizer, acc in zip(
-                    ["Nelder-Mead", "Powell"], case["results"]
-                ):
-                    controller.minimizer = minimizer
-                    accuracy, runtimes, energy = fit._Fit__perform_fit(
-                        controller
-                    )
-
-                    self.assertAlmostEqual(accuracy, acc, 6)
-                    assert len(runtimes) == self.options.num_runs
-                    assert energy != np.inf
+            self.assertAlmostEqual(accuracy, acc, 6)
+            assert len(runtimes) == self.options.num_runs
+            assert energy != np.inf
 
     @patch(
         "fitbenchmarking.controllers.base_controller.Controller.eval_confidence"

fitbenchmarking/parsing/nist_data_functions.py

@@ -32,7 +32,7 @@ def nist_func_definition(function, param_names):
     # Param_names is sanitized in get_nist_param_names_and_values
 
     local_dict = {}
-    global_dict = {"__builtins__": {}, "np": np}
+    global_dict = {"__builtins__": {"__import__": __import__}, "np": np}
     exec(
         "def fitting_function(x, "
         + ",".join(param_names)
@@ -83,7 +83,7 @@ def nist_jacobian_definition(jacobian, param_names):
     # Sanitizing of jacobian_scipy_format is done so exec use is valid
     # Param_names is sanitized in get_nist_param_names_and_values
     local_dict = {}
-    global_dict = {"__builtins__": {}, "np": np}
+    global_dict = {"__builtins__": {"__import__": __import__}, "np": np}
     exec(
         "def jacobian_function(x, "
         + new_param_name
@@ -142,7 +142,7 @@ def nist_hessian_definition(hessian, param_names):
     # Sanitizing of hessian_scipy_format is done so exec use is valid
     # param_names is sanitized in get_nist_param_names_and_values
     local_dict = {}
-    global_dict = {"__builtins__": {}, "np": np}
+    global_dict = {"__builtins__": {"__import__": __import__}, "np": np}
     exec(
         "def hessian_function(x, "
         + new_param_name