Database Parser¶

access_amherst_algo.parse_database.filter_events(query='', locations=None, start_date=None, end_date=None)¶

Filter events based on a search query, location, and date range.

This function allows for filtering a list of events by title (via a search query), location (by matching the event's map location), and a date range (by filtering events that occur between the provided start and end dates). The function returns a distinct set of events that match the provided criteria.

Parameters:

query (str, optional) -- The search query to filter event titles. The default is an empty string, which will not filter by title.
locations (list of str, optional) -- A list of locations to filter events by their map location. The default is None, meaning no location filter is applied.
start_date (date, optional) -- The start date to filter events by their start time. The default is None.
end_date (date, optional) -- The end date to filter events by their start time. The default is None.

Returns:

A QuerySet of distinct events that match the specified filters.

Return type:

QuerySet

Examples

>>> events = filter_events(query="Speaker", locations=["Keefe Campus Center"],
>>>                         start_date="2024-11-01", end_date="2024-11-30")
>>> for event in events:
>>>     print(event.title)

access_amherst_algo.parse_database.get_category_data(events, timezone)¶

Parse and clean category data for events, grouping by hour.

This function processes a list of events, extracting and cleaning category data for each event. It filters out events with null start times, converts the event start times to the specified timezone, and then parses and normalizes the categories associated with each event. The data is returned as a list of dictionaries, each containing the cleaned category and the corresponding event hour.

Parameters:

events (QuerySet) -- A queryset containing event data, which should include start_time and categories fields.
timezone (pytz.timezone) -- The timezone to which the event start times should be adjusted.

Returns:

A list of dictionaries, each containing the cleaned category and corresponding event hour.

Return type:

list

Examples

>>> category_data = get_category_data(events, pytz.timezone("America/New_York"))
>>> for category in category_data:
>>>     print(category)
{'category': 'Lecture', 'hour': 18}
{'category': 'Workshop', 'hour': 19}

access_amherst_algo.parse_database.get_events_by_hour(events, timezone)¶

Group events by the hour and adjust to specified timezone.

This function groups events based on the hour of their start time and adjusts the hour to the specified timezone. It excludes events with null start times, annotates each event with the hour of the start time, and counts the number of events in each hour. The final result is a list of event counts by hour, with the hour adjusted to the provided timezone.

Parameters:

events (QuerySet) -- A queryset containing event data, which should include a start_time field.
timezone (pytz.timezone) -- The timezone to which the event hours should be adjusted.

Returns:

A list of dictionaries, each containing the hour and the corresponding event count.

Return type:

list

Examples

>>> events_by_hour = get_events_by_hour(events, pytz.timezone("America/New_York"))
>>> for event in events_by_hour:
>>>     print(event)
{'hour': 18, 'event_count': 5}
{'hour': 19, 'event_count': 3}

access_amherst_algo.parse_database.get_unique_locations()¶

Retrieve distinct event locations for filtering.

This function queries the database to return a list of unique event locations from the map_location field, which can be used for filtering events based on location.

Returns:: A list of distinct event locations.
Return type:: list

Examples

>>> locations = get_unique_locations()
>>> print(locations)
['Keefe Campus Center', 'Science Center', ' Frost Library']