# ask-ai

Glen Aultman-Bettridge

02/21/2024, 4:37 PM
I am trying to create a sensor that starts a job based on the presence of new files on an SFTP server. When a new file is detected, it should be transferred into an S3 bucket called "my-bucket" and then a Snowflake sql script should be run to import the new file into an existing table called "my-table". What would such a sensor and job look like?


02/21/2024, 4:37 PM
Creating a sensor that triggers a job based on the presence of new files on an SFTP server involves several steps. The sensor will need to check for new files, and upon detecting them, it will initiate a job that performs the file transfer to S3 and then runs a Snowflake SQL script to import the file into a table. Here's a high-level overview of how you might set up such a sensor and job, based on the documentation: 1. Define the Sensor: You would define a sensor that checks the SFTP server for new files. When it finds new files, it would yield
objects that include the necessary run configuration for the job. 2. Define the Job: The job would consist of multiple steps (ops) that perform the file transfer to S3 and execute the Snowflake SQL script. 3. Transfer Files to S3: One of the ops in your job would handle the transfer of files from the SFTP server to the S3 bucket "my-bucket". 4. Run Snowflake SQL Script: Another op would execute the Snowflake SQL script to import the file into the "my-table" table. Here is an example of what the sensor might look like, based on the documentation:
Copy code
from dagster import sensor, RunRequest, SensorEvaluationContext
from dagster_aws.s3.sensor import get_s3_keys

def my_sftp_sensor(context: SensorEvaluationContext):
    # Logic to check for new files on the SFTP server
    # This is a placeholder and would need to be replaced with actual SFTP checking logic
    new_files = check_sftp_for_new_files()

    if not new_files:
        return SkipReason("No new files found on the SFTP server.")

    # Generate RunRequests for each new file
    run_requests = [
                # Include necessary configuration for the job
        for file_name in new_files

    return run_requests
And here is a high-level example of what the job might look like:
Copy code
from dagster import job, op

def transfer_file_to_s3(context, file_name):
    # Logic to transfer file from SFTP to S3

def run_snowflake_sql(context, file_name):
    # Logic to run Snowflake SQL script

def my_job():
    file_name = transfer_file_to_s3()
Please note that the above examples are high-level and do not include actual implementation details for interacting with SFTP, S3, or Snowflake. You would need to fill in the logic for
, and
with the appropriate code to interact with these services. Additionally, the
in the
would need to be populated with the necessary configuration for the job ops, such as credentials and file paths. F
or specific implementation details, you would need to refer to the documentation for the libraries or services you are using to interact with SFTP, S3, and Snowflake. The examples provided in the documentation for sensors and jobs can serve as a starting point for building out the full functionality. S3 sensors button Use Sensors with Inotify button Sensors | Dagster Docs button Automating your data pipelines | Dagster... button Thank you for your feedback!

Glen Aultman-Bettridge

02/21/2024, 5:03 PM
@Scout Is there anyway to include a resource by key to the sensor?


02/21/2024, 5:03 PM
Yes, you can include resources by key in a sensor. According to the documentation, you can use resources in sensors by specifying resource dependencies. To do this, you annotate the resource as a parameter to the sensor's function. Resources are provided by attaching them to your
call. Here's an example of how you might define a sensor that uses a resource:
Copy code
from dagster import sensor, RunRequest, SensorEvaluationContext, ResourceDefinition, Definitions

# Define your resource here
my_resource = ResourceDefinition(...)

@sensor(job=my_job, required_resource_keys={"my_resource_key"})
def my_sensor_with_resources(context: SensorEvaluationContext):
    # You can access the resource using the context
    my_resource_instance = context.resources.my_resource_key

    # Logic to check for new files and create run requests

# When defining your repository, you attach the resource to the sensor
defs = Definitions(
    resources={"my_resource_key": my_resource},
In this example,
is a
that you would define based on your needs (e.g., a resource for interacting with SFTP or S3). The
sensor is defined with the
parameter, which tells Dagster that this sensor requires the specified resource. When you define your repository using the
class, you include the resource in the
parameter, mapping the resource key to the actual resource definition. Please note that the actual implementation of the resource and how it is used within the sensor will depend on the specifics of your use case, such as the APIs or libraries you are using to interact with external systems like SFTP or S3. Resources in asset_sensor button Troubleshooting: Getting a KeyError when... button Sensors | Dagster Docs button Dagster UI | Dagster button Thank you for your feedback!