chore: import upstream snapshot with attribution

examples/python-guide/dask/binary-classification.py

@@ -0,0 +1,30 @@
+import dask.array as da
+from distributed import Client, LocalCluster
+from sklearn.datasets import make_blobs
+
+import lightgbm as lgb
+
+if __name__ == "__main__":
+    print("loading data")
+
+    X, y = make_blobs(n_samples=1000, n_features=50, centers=2)
+
+    print("initializing a Dask cluster")
+
+    cluster = LocalCluster()
+    client = Client(cluster)
+
+    print("created a Dask LocalCluster")
+
+    print("distributing training data on the Dask cluster")
+
+    dX = da.from_array(X, chunks=(100, 50))
+    dy = da.from_array(y, chunks=(100,))
+
+    print("beginning training")
+
+    dask_model = lgb.DaskLGBMClassifier(n_estimators=10)
+    dask_model.fit(dX, dy)
+    assert dask_model.fitted_
+
+    print("done training")