# Documentation

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## Tagging Variables or Constraints

Batch optimization separates the process of building a model from the process of retrieving and acting on its solution. For example, you can build your model on one machine, submit a batch request, and then use the resulting BatchID to retrieve the solution on a completely different machine.

Of course, disconnecting a model from its solution introduces a mapping problem: the process that retrieves the solution needs to know how to map the elements of the solution back to the corresponding elements of the model. This is done through tags. When a model is built, the user associates unique strings with the variables and constraints of interest in the model. Solution values are then associated with these strings. If the user doesn't provide a tag for a model element, no solution information is stored or returned for that element.

You can tag variables (using the VTag attribute), linear constraints (using the CTag attribute), and quadratic constraints (using the QCTag attribute). We should point out that solutions to mixed-integer models don't contain any constraint information, so constraint tags have no effect for such models.

For details on the information that is available in the solution in different situations, please refer to the JSON solution format section.

Here's a simple example that tags the first 10 variables in a model:

        # Define tags for some variables in order to access their values later
for count, v in enumerate(model.getVars()):
v.VTag = "Variable{}".format(count)
if count >= 10:
break