Data Batches

This document briefly outlines what comprises a batch in terms of the Rattail database etc.

Data Model

First and foremost is the data model, as each type of batch requires two tables in which to store its data. So two model classes must be defined, one for the batch itself and another for its row data. These model classes must inherit from one of the following:

Batch proper, i.e. batch header:

  • rattail.db.batch.model.BatchMixin

  • rattail.db.batch.model.FileBatchMixin

Batch data rows:

  • rattail.db.batch.model.BatchRowMixin

  • rattail.db.batch.model.ProductBatchRowMixin

Note that all parent classes will add certain columns to your tables, though which ones will vary by parent. Any columns you define will be in addition to those provided by the parent, although (I think?) specifying a duplicate name would effectively overwrite a column.

For some implementation examples, you can see the vendor catalog batch:

  • rattail.db.batch.vendorcatalog.model.VendorCatalogBatch

  • rattail.db.batch.vendorcatalog.model.VendorCatalogBatchRow


In addition to the data models, each batch type must be supported by a(t least one) handler, which is where the logic lives for populating the batch and executing it. The handler class should inherit from the following:

  • rattail.db.batch.handler.BatchHandler

And here’s the vendor catalog example:

  • rattail.db.batch.vendorcatalog.handler.VendorCatalogHandler

Using the Batch

Actually interacting with the batch(es) as a user implies something outside of the scope of core Rattail. However the Tailbone package provides some tools to make adding support for a new batch relatively painless. See the docs in that package for more information.