Annotation Collections

To faciliate the easy grouping and management of annotations, PyBryt provides the Collection annotation, which collects a series of other annotations into a group. Collections can be instantiated by passing zero or more annotations to the constructor, along with the other usual keyword arguments for other annotations. To add additional annotations to the collection, use Collection.add.

l = [3, 2, 1, 4, -3, -3, 3, 4]

collection = pybryt.Collection(pybryt.Value(l))

# calculate the partial products of a list
prod = 1
for i in range(len(l)):
    prod *= l[i]
    l[i] = prod
    collection.add(pybryt.Value(l))

Annotations can be removed from the collection using Collection.remove:

val = pybryt.Value(l)
collection = pybryt.Collection(val)
collection.remove(val)

Collection annotations can be used to simplify the creation of temporal annotations. Rather than reassigning variables and using the before method over and over again, you can simply create a collection and set enforce_order=True in the constructor. This will mean that the collection is only satisfied if the satisfying timestamps of its annotations occur in non-decreasing order based on the order the annotations were added in. For the example above, this can be done with:

l = [3, 2, 1, 4, -3, -3, 3, 4]

collection = pybryt.Collection(pybryt.Value(l), enforce_order=True)  # this is the only difference!

# calculate the partial products of a list
prod = 1
for i in range(len(l)):
    prod *= l[i]
    l[i] = prod
    collection.add(pybryt.Value(l))

Collections can also be used to simplify the management of success and failure messages by linking them to a specific group of annotations:

l = [3, 2, 1, 4, -3, -3, 3, 4]

collection = pybryt.Collection(pybryt.Value(l), enforce_order=True,
                               failure_message="Take a look at your partial product algorithm.")

# calculate the partial products of a list
prod = 1
for i in range(len(l)):
    prod *= l[i]
    l[i] = prod
    collection.add(pybryt.Value(l))