Solves testing issues (#1051)

Author: nasaul

.github/workflows/pytest.yml

@@ -29,6 +29,10 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
+      - name: Set matplotlib backend (headless)
+        run: echo "MPLBACKEND=Agg" >> $GITHUB_ENV
+        shell: bash
+
       - name: Install dependencies
         run: pip install -e ".[all]"
 

pyproject.toml

@@ -27,7 +27,9 @@ requires-python = ">=3.9"
 dependencies = [
     "cloudpickle",
     "coreforecast>=0.0.12",
-    "numba>=0.55.0",
+    "numba>=0.55.0 ; sys_platform != 'win32' or python_version < '3.10' or python_version >= '3.12'",
+    "numba>=0.58.0,<0.60.0 ; sys_platform == 'win32' and python_version >= '3.10' and python_version < '3.12'",
+    "llvmlite>=0.41.0,<0.43.0 ; sys_platform == 'win32' and python_version >= '3.10' and python_version < '3.12'",
     "numpy>=1.21.6",
     "pandas>=1.3.5",
     "scipy>=1.7.3,<1.16.0",

tests/test_arima.py

@@ -115,7 +115,7 @@ def test_arima_transpar(expected_arima_transpar_f):
         np.testing.assert_allclose(actual, exp)
 
     params = np.repeat(0.5, 10)
-    arma = np.ones(5, dtype=np.integer) * 2
+    arma = np.ones(5, dtype=np.int32) * 2
     for exp, calc in zip(
         expected_arima_transpar_f, arima_transpar(params, arma, False)
     ):

tests/test_distributed_fugue.py

@@ -258,9 +258,9 @@ def test_ray_distributed_exogenous_regressors(df_w_ex):
     # Distributed exogenous regressors
     sf = StatsForecast(models=[ReturnX()], freq=1)
     res = sf.forecast(df=train_df, X_df=xreg, h=4).compute()
-    expected_res = xreg.compute().rename(columns={"x": "ReturnX"})
+    expected_res = xreg.compute().rename(columns={"x": "ReturnX"}).sort_values(["unique_id", "ds"])
     # we expect strings for unique_id, and ds using exogenous
     pd.testing.assert_frame_equal(
-        res.sort_values("unique_id").reset_index(drop=True).astype(expected_res.dtypes),
+        res.sort_values(["unique_id", "ds"]).reset_index(drop=True).astype(expected_res.dtypes),
         expected_res,
     )