A data bucket is simply a collection of data streams.
In order to keep your data/event streams and visualizations contextually appropriate, we have implemented a concept called
data buckets. A data bucket is simply a collection of data streams. Each available visualization will display all data streams for a given data bucket.
A data bucket will have a bucket_name and a bucket_key. The bucket_name is what is displayed on your bucket shelf. The bucket_key is what is actually used to identify a bucket in your account. Data that is streamed to your access_key and contains a specific bucket_key belongs to the same bucket.
bucket_key's uniqueness is scoped to a specific
Deleting a Bucket
If you delete a bucket, do not attempt to re-use a deleted bucket's bucket_key when streaming data or creating a new bucket. Data streamed to a deleted bucket_key will be unavailable to view.
Python Streamer Module
When using the Python Streamer module, a new bucket is automatically created when the Streamer is constructed.
If you want to append to an existing bucket, or use a key that is more memorable than the uuid that will otherwise be used, you can use the optional
bucket_key constructor parameter. If a Streamer is constructed with a
bucket_key that already exists, then any data sent in that Stream will append to the existing bucket.
Python Streamer Module Constructor:
streamer = Streamer(bucket_name="Some Bucket Name", bucket_key="Some_Bucket_Key", access_key="YourAccessKey")