[Docs] De-flake doctests

bazel/python.bzl

@@ -23,6 +23,7 @@ def doctest(files, gpu = False, name="doctest", deps=[], srcs=[], data=[], args=
             "--doctest-modules",
             "--doctest-glob='*.md'",
             "-c=$(location //bazel:conftest.py)",
+            "--disable-warnings",
             "-v"
         ] + args + ["$(location :%s)" % file for file in files],
         data = ["//bazel:conftest.py"] + files + data,

doc/source/data/key-concepts.rst

@@ -161,10 +161,11 @@ or remote filesystems.
 
     transformed_ds.write_parquet("/tmp/iris")
 
-    print(sorted(os.listdir("/tmp/iris")))
+    print(os.listdir("/tmp/iris"))
 
 .. testoutput::
-
+    :options: +MOCK
+
     ['..._000000.parquet', '..._000001.parquet']
 
 

python/ray/data/read_api.py

@@ -1635,6 +1635,15 @@ def read_sql(
         For examples of reading from larger databases like MySQL and PostgreSQL, see
         :ref:`Reading from SQL Databases <reading_sql>`.
 
+        .. testcode::
+            :hide:
+
+            import os
+            try:
+                os.remove("example.db")
+            except OSError:
+                pass
+
         .. testcode::
 
             import sqlite3

python/ray/train/tensorflow/tensorflow_checkpoint.py

@@ -66,14 +66,20 @@ def from_model(
             A :py:class:`TensorflowCheckpoint` containing the specified model.
 
         Examples:
+
+            .. testcode::
 
-        .. testcode::
+                from ray.train.tensorflow import TensorflowCheckpoint
+                import tensorflow as tf
 
-            from ray.train.tensorflow import TensorflowCheckpoint
-            import tensorflow as tf
+                model = tf.keras.applications.resnet.ResNet101()
+                checkpoint = TensorflowCheckpoint.from_model(model)
+
+            .. testoutput::
+                :options: +MOCK
+                :hide:
 
-            model = tf.keras.applications.resnet.ResNet101()
-            checkpoint = TensorflowCheckpoint.from_model(model)
+                ...  # Model may or may not be downloaded
 
         """
         checkpoint = cls.from_dict(