CircleCI: Remove deprecated workflows version key (#5256)

.circleci/config.yml

@@ -8,14 +8,14 @@ defaults: &defaults
     #       (e.g. `rg -F --hidden <old_tag>`)
     - image: pyodide/pyodide-env:20241106-chrome130-firefox132
   environment:
-    - EMSDK_NUM_CORES: 3
-      EMCC_CORES: 3
-      PYODIDE_JOBS: 3
-      # Make sure the ccache dir is consistent between core and package builds
-      # (it's not the case otherwise)
-      CCACHE_DIR: /root/.ccache/
-      # Disable the compression of wheels, so they are better compressed by the CDN
-      PYODIDE_ZIP_COMPRESSION_LEVEL: 0
+    EMSDK_NUM_CORES: 3
+    EMCC_CORES: 3
+    PYODIDE_JOBS: 3
+    # Make sure the ccache dir is consistent between core and package builds
+    # (it's not the case otherwise)
+    CCACHE_DIR: /root/.ccache/
+    # Disable the compression of wheels, so they are better compressed by the CDN
+    PYODIDE_ZIP_COMPRESSION_LEVEL: 0
 
 jobs:
   build-core:
@@ -574,7 +574,6 @@ jobs:
               --access-key-env "AWS_ACCESS_KEY_ID_CACHE" --secret-key-env "AWS_SECRET_ACCESS_KEY_CACHE"
 
 workflows:
-  version: 2
   build-and-deploy:
     jobs:
       - build-core:

packages/netcdf4/test_netcdf4.py

@@ -416,7 +416,7 @@ def test_netCDF4_tutorial(selenium):
     data = np.empty(len(y) * len(x), object)
     for n in range(len(y) * len(x)):
         data[n] = np.arange(rng.integers(1, 10), dtype="int32") + 1
-    data = np.reshape(data, (len(y), len(x)))
+    data = np.reshape(data, (len(y), len(x)))  # type: ignore[assignment]
     vlvar[:] = data
     assert_print(vlvar)
     assert_print("vlen variable =\n", vlvar[:])

packages/xgboost/test_xgboost.py

@@ -223,7 +223,7 @@ def test_pandas_categorical(selenium):
     X_0 = ["f", "o", "o"]
     X_1 = [4, 3, 2]
     X = pd.DataFrame({"feat_0": X_0, "feat_1": X_1})
-    X["feat_0"] = X["feat_0"].astype("category")  # type: ignore[call-overload]
+    X["feat_0"] = X["feat_0"].astype("category")  # type: ignore[call-overload, index]
     transformed, _, feature_types = xgb.data._transform_pandas_df(
         X, enable_categorical=True
     )
@@ -232,7 +232,7 @@ def test_pandas_categorical(selenium):
 
     # test missing value
     X = pd.DataFrame({"f0": ["a", "b", np.nan]})
-    X["f0"] = X["f0"].astype("category")  # type: ignore[call-overload]
+    X["f0"] = X["f0"].astype("category")  # type: ignore[call-overload, index]
     arr, _, _ = xgb.data._transform_pandas_df(X, enable_categorical=True)
     assert not np.any(arr == -1.0)