marielchm
diff --git a/‎dataproc/python-api-walkthrough.md
Copy file name to clipboardExpand all lines: dataproc/python-api-walkthrough.md
+4-5Lines changed: 4 additions & 5 deletions b/‎dataproc/python-api-walkthrough.md
Copy file name to clipboardExpand all lines: dataproc/python-api-walkthrough.md
+4-5Lines changed: 4 additions & 5 deletions
@@ -6,12 +6,12 @@ Estimated completion time: <walkthrough-tutorial-duration duration="5"></walkthr
 
 This [Cloud Shell](https://cloud.google.com/shell/docs/) walkthrough leads you
 through the steps to use the
-[Google APIs Client Library for Python](http://code.google.com/p/google-api-python-client/ )
+[Google Cloud Client Libraries for Python](https://googleapis.github.io/google-cloud-python/latest/dataproc/index.html)
 to programmatically interact with [Cloud Dataproc](https://cloud.google.com/dataproc/docs/).
 
 As you follow this walkthrough, you run Python code that calls
-[Cloud Dataproc REST API](https://cloud.google.com//dataproc/docs/reference/rest/)
-methods to:
+[Cloud Dataproc gRPC APIs](https://cloud.google.com/dataproc/docs/reference/rpc/)
+to:
 
 * create a Cloud Dataproc cluster
 * submit a small PySpark word sort job to run on the cluster
@@ -121,7 +121,7 @@ Job output in Cloud Shell shows cluster creation, job submission,
      ...
      Creating cluster...
      Cluster created.
-     Uploading pyspark file to Cloud Storage
+     Uploading pyspark file to Cloud Storage.
      new-cluster-name - RUNNING
      Submitted job ID ...
      Waiting for job to finish...
@@ -162,4 +162,3 @@ Job output in Cloud Shell shows cluster creation, job submission,
 
 * **For more information.** See the [Cloud Dataproc documentation](https://cloud.google.com/dataproc/docs/)
    for API reference and product feature information.
-