Grading Groups

In a typical class, assignments are organized into groups (e.g., “homeworks”, “labs”, etc.), and a student’s overall score in the course is determined by a weighted average of their score in each group. This is done in gradelib by setting the .grading_groups attribute of the Gradebook object.

The Gradebook.grading_groups attribute can be set in several different ways. The value should be a dict mapping group names to grading group definitions. A group definition can be any of the following:

A single number. In this case, the group name is treated as an assignment name.

A tuple of the form (assignments, group_weight), where assignments is an iterable of assignment names or a dict mapping assignment names to weights. If assignments is an iterable, the weights are inferred to be proportional to the points possible for each assignment. If assignments is a dict, the weights are taken directly from the dict.

A GradingGroup instance.

To normalize the weights of assignments (so that they are all weighed the same) use the gradelib.normalize() function.

Example

>>> gradebook.grading_groups = {
...     # list of assignments, followed by group weight. assignment weights
...     # are inferred to be proportional to points possible
...     "homeworks": (['hw 01', 'hw 02', 'hw 03'], 0.25),
...
...     # dictionary of assignment weights, followed by group weight.
...     "labs": ({"lab 01": .25, "lab 02": .75}, 0.25),
...
...     # a single number. the key is interpreted as an assignment name,
...     # and an assignment group consisting only of that assignment is
...     # created.
...     "exam": 0.5
... }