I want to poll a data source and process the recei...
# ask-ai
s
I want to poll a data source and process the received data in Dagster. How would I do that?
s
To poll a data source and process the received data in Dagster, you would typically use a sensor. A sensor in Dagster is a function that runs at a regular interval and checks for certain conditions. If those conditions are met, the sensor can trigger a job or a run. Here's how you can think through setting up a sensor for polling a data source: 1. Define the polling logic: You need to write a function that checks your data source at regular intervals for new or updated data. This could involve querying a database, checking for a new file in a storage bucket, or calling an API. 2. Create a sensor: Implement a sensor that encapsulates the polling logic. The sensor will periodically invoke this logic to see if there is new data to process. 3. Trigger a job: If the sensor detects new or updated data, it should trigger a Dagster job. This job will contain the logic for processing the data. 4. Process the data: The job triggered by the sensor will run the necessary computations or transformations on the data and materialize any resulting assets. Here is a simplified example based on the documentation:
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python from dagster import sensor, RunRequest, job  @job def process_data_job():     # Your data processing logic goes here     pass  @sensor(job=process_data_job) def my_data_source_sensor():     # Your polling logic to check the data source     if there_is_new_data():         # If new data is found, trigger the job         yield RunRequest(run_key="unique_run_key_for_this_data")
In this example,
there_is_new_data()
would be a function you define that checks your data source. If it finds new data, the sensor yields a
RunRequest
, which triggers
process_data_job
to process that data. Remember to configure your sensor with the appropriate interval and any other settings relevant to your use case. Sensors can be a powerful way to integrate external data sources with Dagster and automate your data pipelines based on external events or conditions.