I’ve been working with the DataSift Python API and I’m a bit confused about stream management. I know how to start listening to a stream using the start_stream_subscriber() function. But now I’m trying to figure out how to stop the stream.
Is there a specific method in the API to halt a stream? I’m concerned about ongoing billing and want to make sure I can properly end the stream when I’m done.
I’ve looked through the documentation but couldn’t find anything clear about stopping streams. Does anyone have experience with this or know the right way to do it?
Here’s a basic example of what I’m doing:
from datasift import Client
client = Client('username', 'api_key')
definition = client.create_definition('interaction.content contains "python"')
stream = definition.start_stream_subscriber(on_delete=process_delete)
# How do I stop the stream here?
Any help would be greatly appreciated!
As someone who’s worked extensively with the DataSift Python API, I can share some insights on terminating streams. While there’s no explicit ‘terminate’ function, you can effectively stop a stream using a combination of methods.
The key is to use the ‘stop()’ method on your stream object, followed by ‘join()’. This ensures that the stream halts and processes any remaining data before shutting down completely. Here’s how I typically handle it:
stream = definition.start_stream_subscriber(on_delete=process_delete)
Your processing logic here
try {
// When you’re ready to stop
stream.stop();
stream.join(timeout=10); // Adjust timeout as needed
} catch (Exception e) {
System.out.println('Error during stream termination: ’ + e);
}
This approach has always worked reliably for me, preventing any lingering connections or unexpected charges. Just remember to implement proper error handling to catch any issues during the termination process.
I discovered that the DataSift Python API does not have a dedicated method to stop a stream. Instead, you need to manage the shutdown process manually. After you start the stream using start_stream_subscriber(), the correct way to terminate it is by calling stream.stop() to halt incoming data and then stream.join() to ensure that all queued messages are processed before the application exits.
For instance, you could write:
stream = definition.start_stream_subscriber(on_delete=process_delete)
your processing logic
stream.stop()
stream.join()
This method helps in preventing any unexpected billing issues and ensures a smooth shutdown. It’s also advisable to include error handling around these calls to manage any exceptions during termination.
hey, i’ve dealt with this before. u can use the stop() method on ur stream object to halt it. then call join() to make sure all messages r processed. looks like:
stream.stop()
stream.join()
remember to add some error handling tho, stuff can go wrong sometimes. hope this helps!