Merge pull request #1415 from econ-ark/MridulS-patch-2

MAINT: Bump up min python version to 3.10 to align with SPEC 0

.github/workflows/documentation.yml

@@ -28,10 +28,10 @@ jobs:
     steps:
       - uses: actions/checkout@v3
 
-      - name: Set up Python 3.10
+      - name: Set up Python 3.12
         uses: actions/setup-python@v4
         with:
-          python-version: "3.10" # Interpolation.py doesn't support Python 3.11 [2023-07]
+          python-version: "3.12"
           cache: "pip"
           cache-dependency-path: |
             requirements/base.txt

.github/workflows/examples.yml

@@ -22,7 +22,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.10", "3.11", "3.12"]
     steps:
       - uses: actions/checkout@v3
       - name: Set up Python

.github/workflows/hark.yml

@@ -21,7 +21,7 @@ jobs:
       max-parallel: 5
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: [3.8, 3.9, "3.10"]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
       - uses: actions/checkout@v3

.github/workflows/lint.yml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.12"]
 
     steps:
       - uses: actions/checkout@v4

HARK/econforgeinterp.py

@@ -111,7 +111,7 @@ def _derivs(self, deriv_tuple, *args):
             self.f_val,
             np.column_stack([x.flatten() for x in array_args]),
             out=None,
-            order=1,
+            k=1,
             diff=str(deriv_tuple),
             extrap_mode=self.extrap_mode,
         )

HARK/tests/test_distribution.py

@@ -44,7 +44,7 @@ def test_distr_of_function(self):
         norm = Normal(mu=-(sig**2) / 2, sigma=sig).discretize(131, method="hermite")
         my_logn = distr_of_function(norm, func=lambda x: np.exp(x))
         exp = calc_expectation(my_logn)
-        self.assertAlmostEqual(exp, 1.0)
+        self.assertAlmostEqual(float(exp), 1.0)
 
         # Function 1 -> n
         # Mean and variance of the normal
@@ -184,7 +184,7 @@ def test_self_dist_of_func(self):
         norm = Normal(mu=-(sig**2) / 2, sigma=sig).discretize(131, method="hermite")
         my_logn = norm.dist_of_func(lambda x: np.exp(x))
         exp = my_logn.expected()
-        self.assertAlmostEqual(exp, 1.0)
+        self.assertAlmostEqual(float(exp), 1.0)
 
         # Function 1 -> n
         # Mean and variance of the normal
@@ -327,16 +327,18 @@ def test_Uniform(self):
 
         Uniform().draw(1)[0]
 
-        self.assertEqual(
-            calc_expectation(uni.discretize(10, method="equiprobable")), 0.5
+        self.assertAlmostEqual(
+            float(calc_expectation(uni.discretize(10, method="equiprobable"))),
+            0.5,
         )
 
         uni_discrete = uni.discretize(10, method="equiprobable", endpoints=True)
 
         self.assertEqual(uni_discrete.atoms[0][0], 0.0)
         self.assertEqual(uni_discrete.atoms[0][-1], 1.0)
-        self.assertEqual(
-            calc_expectation(uni.discretize(10, method="equiprobable")), 0.5
+        self.assertAlmostEqual(
+            float(calc_expectation(uni.discretize(10, method="equiprobable"))),
+            0.5,
         )
 
     def test_Bernoulli(self):

HARK/tests/test_model.py

@@ -28,4 +28,4 @@ def setUp(self):
         self.test_block_A = model.DBlock(**test_block_A_data)
 
     def test_init(self):
-        self.assertEquals(self.test_block_A.name, "test block A")
+        self.assertEqual(self.test_block_A.name, "test block A")

pyproject.toml

@@ -20,13 +20,13 @@ classifiers = [
     "License :: OSI Approved :: Apache Software License",
     "License :: OSI Approved",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
 ]
 description = "Heterogenous Agents Resources & toolKit"
 keywords = ["economics", "modelling", "modeling", "heterogeneity"]
-requires-python = ">=3.8"
+requires-python = ">=3.10"
 dynamic = ["dependencies", "optional-dependencies"]
 
 

requirements/base.txt

@@ -2,7 +2,7 @@ interpolation>=2.2.3
 joblib>=1.2
 matplotlib>=3.6
 networkx>=3
-numba<0.59
+numba
 numpy>=1.23
 pandas>=1.5
 quantecon