Sensor Agent Doc Integration Example

docs/index.md

@@ -456,6 +456,7 @@ auto_examples/papermill_plugin/index
 auto_examples/pandera_plugin/index
 auto_examples/kfpytorch_plugin/index
 auto_examples/ray_plugin/index
+auto_examples/sensor/index
 auto_examples/snowflake_plugin/index
 auto_examples/k8s_spark_plugin/index
 auto_examples/sql_plugin/index

docs/integrations.md

@@ -106,6 +106,8 @@ the Flyte task that use the respective plugin.
   - Run Hive jobs in your workflows.
 * - {doc}`MMCloud <auto_examples/mmcloud_plugin/index>`
   - Execute tasks using MemVerge Memory Machine Cloud
+* - {doc}`Sensor <auto_examples/sensor/index>`
+  - Run Sensor jobs in your workflows.
 * - {doc}`Snowflake <auto_examples/snowflake_plugin/index>`
   - Run Snowflake jobs in your workflows.
 * - {doc}`Databricks <auto_examples/databricks_plugin/index>`

examples/sensor/README.md

@@ -0,0 +1,20 @@
+(sensor)=
+
+# Sensor
+
+```{eval-rst}
+.. tags:: Data, Basic
+```
+
+## Run the example on the Flyte cluster
+
+To run the provided example on the Flyte cluster, use the following command:
+
+```
+pyflyte run --remote \
+  https://raw.githubusercontent.com/flyteorg/flytesnacks/master/examples/sensor/sensor/file_sensor_example.py wf
+```
+
+```{auto-examples-toc}
+sensor
+```

examples/sensor/sensor/file_sensor_example.py

@@ -0,0 +1,49 @@
+# %% [markdown]
+# # File Sensor
+#
+# This example shows how to use the `FileSensor` to detect files appearing in your local or remote filesystem.
+#
+# To begin, import the required libraries.
+
+# %%
+from flytekit import task, workflow
+from flytekit.sensor.file_sensor import FileSensor
+
+# %% [markdown]
+# Create a FileSensor task.
+#
+# The sensor will search for the file at the specified path. If the file exists, it will return a succeed status. Otherwise, the sensor will continue running until the file is added to the directory.
+#
+# You can also use the S3 or GCS file system.
+
+# %%
+sensor = FileSensor(name="test_file_sensor")
+
+# %% [markdown]
+# You have to specify the `path` parameter.
+#
+# In the sandbox, you can use the s3 path.
+#
+# We have already set the minio credentials in the agent by default.
+#
+# If you test it locally, you have to set the credentials to your environment variables.
+# ```{prompt} bash
+# export FLYTE_AWS_ENDPOINT="http://localhost:30002"
+# export FLYTE_AWS_ACCESS_KEY_ID="minio"
+# export FLYTE_AWS_SECRET_ACCESS_KEY="miniostorage"
+# ```
+
+
+# %%
+@task()
+def t1():
+    print("SUCCEEDED")
+
+
+@workflow()
+def wf():
+    sensor(path="s3://my-s3-bucket/file.txt") >> t1()
+
+
+if __name__ == "__main__":
+    wf()