courses module#

class courses.Course(code: str, name: str, weight: float = 1, activities: Optional[pandas.core.frame.DataFrame] = None)[source]#

Bases: object

A course aims to represent one or more courses. It contains its events and is represented with a name and a code.

Parameters

  • code (str) – the code of the course

  • name (str) – the full name of the course

  • weight (float) – the weight attributed to the course

  • activities (Optional[pd.Dataframe]) – a structure of all the events indexed by code, type and id

Example

>>> course = Course('LMECA2732', 'Robotics')
add_activity(events: List[backend.events.AcademicalEvent])[source]#

Adds an activity to the current course’s activities. An activity is a set of events with the same id.

Parameters

events (List[AcademicalEvent]) – list of academical events coming from the same activity

get_activities(view: Optional[Union[List[str], Set[str], Dict[int, str]]] = None, reverse: bool = False) → pandas.core.frame.DataFrame[source]#

Returns a table of all activities that optionally match correct ids.

Parameters

  • view (Optional[View]) – if present, list of ids or dict {week_number : ids}

  • reverse (bool) – if True, the activities in View will be removed

Returns

table containing all the activities and their events

Return type

pd.DataFrame

get_events(**kwargs) → Iterable[backend.events.AcademicalEvent][source]#

Returns a list of events that optionally matches correct ids.

Parameters

kwargs (Any) – parameters that will be passed to Course.get_activities()

Returns

list of events

Return type

Iterable[AcademicalEvent]

get_summary() → Dict[str, Set[str]][source]#

Returns the summary of all activities in the course.

Returns

dict of activity codes, ordered by activity type (CM, TP, etc.)

Return type

Dict[str, Set[str]]

set_weights(percentage: float = 50, event_type: Optional[backend.events.AcademicalEvent] = None)[source]#

Modifies this course’s events weight.

Parameters

  • percentage (float) – the “priority” required for this course in (0-100)%, default is 50%

  • event_type (Optional[AcademicalEvent]) – if present, modify the weight of a certain type of event only

courses.generate_empty_dataframe()[source]#
courses.merge_courses(courses: Iterable[courses.Course], code: str = '0000', name: str = 'merged', weight: float = 1, views: Optional[Dict[str, Union[List[str], Set[str], Dict[int, str]]]] = None, **kwargs: Any) → courses.Course[source]#

Merges multiple courses into one.

Parameters

  • courses (Iterable[Courses]) – multiple courses

  • code (str) – the new code

  • name (str) – the new name

  • weight (float) – the new weight

  • views (Optional[Dict[str, View]]) – map of views that will be passed to Course.get_activities()

  • kwargs (Any) – additional parameters that will be passed to Course.get_activities()

Returns

the new course

Return type

Course