Easy data collection/manipulation for courses at the University of Washington

Project description

uwtools

Making data extraction for courses from the University of Washington (UW) simple.

Archived Data in compressed files allows for quick access to a large variety of data from UW.
Easily get quarter date ranges and current/upcoming quarters at UW.
Easy parsing of the current Time Schedules and Course Catalogs for every UW Campus to get most recent versions of these resources.
Complete list of buildings with abbreviations, full names and coordinates.
Data stored and returned in pandas DataFrames and Python dictionaries for easy searching/manipulation.
Time Schedule Data is available for courses beginning AUT 2003.

Installation

pip install uwtools

`course_catalogs`

Gathers the Course Catalogs for the given UW Campuses.

from uwtools import course_catalogs

course_catalogs(campuses=['Seattle', 'Bothell', 'Tacoma'], update=False)

Args

campuses: list, default ['Seattle', 'Bothell', 'Tacoma']

The list of campuses to get course catalogs from.

update: bool, default False

If False use the stored course catalogs (Updated AUT 2019). If True, parse the UW Course Catalogs to get the most recent version of the Catalog. Parsing will take between 15-45 seconds, and may flucuate depending on internet connection.

Returns

A pandas DataFrame representing the course catalogs for the given campus. An example for course_catalogs(campuses=['Seattle']) is shown below.
If update=True a tuple containing the pandas DataFrame mentioned above as the first item and an updated departments dictionary as the second argument. Course sections with to be arranged meeting times are listed as NaN in the Type, Days, Time, Building, and Room Number columns.
The columns of the DataFrame are (in this order):

['Campus', 'Department Name', 'Course Number', 'Course Name', 'Credits', 'Areas of Knowledge', 'Quarters Offered','Offered with', 'Prerequisites', 'Co-Requisites', 'Description']

            Campus Department Name Course Number  ... Prerequisites Co-Requisites                                        Description       
Course_ID                                         ...
AFRAM101   Seattle           AFRAM           101  ...                              History, culture, religion, institutions, poli...       
AFRAM150   Seattle           AFRAM           150  ...                              Introductory survey of topics and problems in ...       
AFRAM214   Seattle           AFRAM           214  ...                              Introduction to various genres of African Amer...       
AFRAM220   Seattle           AFRAM           220  ...                              Examines the history and theory of African Ame...       
AFRAM246   Seattle           AFRAM           246  ...                              Survey of African Americans within the U.S. so...       
...            ...             ...           ...  ...           ...           ...                                                ...       
HONORS398  Seattle          HONORS           398  ...                              Special courses drawn from interdisciplinary g...       
HONORS496  Seattle          HONORS           496  ...                              Allows students completing the Interdisciplina...       
HONORS499  Seattle          HONORS           499  ...                              Faculty supervised Honors independent study or...       
LEAD298    Seattle            LEAD           298  ...                              Varied topics related to leadership studies ta...       
LEAD495    Seattle            LEAD           495  ...                              Guides the creation of a leadership e-portfoli...

Column Name	Description
Campus	The campus the course is offered at.
Department Name	The name of the department the course is a part of. Denoted by a series of capital letters with no spaces.
Course Number	The 3 digit number identifying the course.
Course Name	The name of the course.
Credits	The number of credits offered for the course. Some courses have variable credits offered/different credit options. Check out the UW's guide for the credit system here.
Areas of Knowledge	Areas of Knowledge essentially are credit types. More Information.
Quarters Offered	The quarters of the year the course is offered. Autumn, Winter, Spring, Summer.
Offered with	At times, a course may be offered alongside a similar course in a different department.
Prerequisites	Courses that must be taken in order to take the course.
Co-Requisites	Courses that must be taken at the same time the desired course is being taken.
Description	The description of the course objectives.

Prerequisites and Co-Requisites are separated by the following symbols: &&, ;, ,, and /. These symbols show the and/or relationships between requisite courses. All course separated by a ; indicate that any one of those courses is enough to statisfy the requirement. Courses separated by a , indicate that any course in the list of comma separated values between semi-colons is enough to satisfy the requirement. The && and / symbols are used to group courses, with && meaning and and / meaning or.

Examples:

BIOL423: Prerequisite: either BIOL 180 and BIOL 356, or BIOL 180 and FISH 250, or a minimum grade of 3.4 in BIOL 180 or BIOL 240.

Prerequisites after parsing: BIOL180&&BIOL356,BIOL180&&FISH250,BIOL180,BIOL240

EE235: Prerequisite: either MATH 136, MATH 307, or AMATH 351, any of which may be taken concurrently; PHYS 122; either CSE 142 or CSE 143, either of which may be taken concurrently.

Prerequisites after parsing: MATH136,MATH307,AMATH351;PHYS122;CSE142,CSE143

`departments`

Returns the departments at UW for each campus.

from uwtools import departments

departments(campuses=['Seattle', 'Tacoma', 'Bothell'])

If you would like to get an updated version of the departments, call course_catalogs(campuses=['Seattle', 'Bothell', 'Tacoma'], update=True) with the campuses of your choice. When update=True, course_catalogs returns a tuple with a pandas DataFrame as the first item and an updated dictionary with departments as the second item.

Args

campuses: list, default ['Seattle', 'Bothell', 'Tacoma']

The list of campuses to get departments from. An example would be EE -> Electrical Engineering at UW Seattle.

Returns

A dictionary with department name abbreviations to full names. An example for departments(campuses=['Seattle']) is shown below.

{
    "Seattle": {
        "AA": "Aeronautics and Astronautics",
        "AAS": "Asian-American Studies",
        "ACCTG": "Accounting",
        "ADMIN": "Administration",
        "AE": "Aerospace Engineering",
        "AES": "American Ethnic Studies",
        "AFRAM": "Afro-American Studies",
        "AIS": "American Indian Studies",
        "AMATH": "Applied Mathematics",
        ...

`get_quarter_ranges`

Parses UW's Academic Calendar to find date ranges for every quarter in the current academic year.

from uwtools import get_quarter_ranges

get_quarter_ranges(year=None)

Args

year: int, default None

The academic year to get quarter date ranges from. Example: 2019-2020 -> 1920 would correspond to the call get_quarter_ranges(year=2019). Academic years starting from 2014-2015 (1415) are supported. The default None will get the current academic year based on the current year. If an academic year before 1415 is passed in the year argument, an AssertionError is raised.

Returns

Dictionary with Quarter Abbreviation keys mapping to list of datetime objects representing the range of dates for that quarter at UW.

{'AUT': [
    datetime.date(2019, 9, 25), 
    datetime.date(2019, 12, 6)
    ], 
 'WIN': [
    datetime.date(2020, 1, 6), 
    datetime.date(2020, 3, 13)
    ]
  ...

`get_quarter`

Calculates the current quarter at UW based on the current date. If the current date falls on a quarter break, such as Summer break, the current quarter will be Summer (SUM) and the upcoming quarter will be Autumn (AUT).

from uwtools import get_quarter

get_quarter(filter_=False, type_='current')

Args

filter_: bool, default False

Filters out the A and B terms of Summer Quarter if True otherwise does not.

type_: str, default 'current'

'current': Get the current quarter at UW.

'upcoming': Get the upcoming quarter at UW.

Upcoming Quarters:

AUT -> WIN

WIN -> SPR

SPR -> SUM

SUM -> AUT

SUMA -> AUT

SUMB -> AUT

Quarters:

AUT -> Autumn

WIN -> Winter

SPR -> Spring

SUM -> Summer

SUMA -> Summer A Term

SUMB -> Summer B Term

Returns

String representing the current quarter(s). NOTE: Summer Quarter has two terms, A and B.

`time_schedules`

Gathers the Time Schedules for the given UW Campuses, Quarter and Year.

from uwtools import time_schedules

time_schedules(campuses=['Seattle', 'Bothell', 'Tacoma'], year=None, quarter=None)

Args

campuses: list, default ['Seattle', 'Bothell', 'Tacoma']

The list of campuses to get time schedules from.

year: int, default None

The year to get Time Schedules from. If a year is given with no quarter, then every quarter from the academic year beginning with the given year arg will be returned. Example: year=2017 -> AUT2017, WIN2018, SPR2018, SUM2018. Years 2003 - Present are supported. If the year before 2003, an AssertionError is raised.

quarter str, default None

The specific quarter from which to get time schedules. If a quarter is given with no year, None is returned.

If year and quarter are None, then the most recent time schedules will be returned if available.

Returns

A pandas DataFrame containing all time schedule data for the given campuses, year and quarter. An example for time_schedules(campuses=['Seattle'], year=2017, quarter='SPR') is shown below.
Time schedules from 2003 - 2019 are archived in files for quicker access. Any time schedules beyond these years will be parsed from UW's Time Schedule website for the given campuses if they are available. Otherwise, None will be returned.

       Course Name Seats    SLN Section  Type Days      Time Building Room Number   Campus Quarter  Year
252721   ARCTIC401    30  10467       A  LECT  TTh  930-1120      CMU         228  Seattle     SPR  2017
252722   ARCTIC498    30  10468       A  LECT                                      Seattle     SPR  2017
252723   HONORS212    30  14933       A  LECT  TTh   130-320      SMI         102  Seattle     SPR  2017
252724   HONORS212    25  14934       B  LECT   MW  1230-220      DEN         259  Seattle     SPR  2017
252725   HONORS212    12  14935      BA    QZ    F  1230-120      THO         331  Seattle     SPR  2017
...            ...   ...    ...     ...   ...  ...       ...      ...         ...      ...     ...   ...
262015     SOCW598    15  19338       G  LECT    W  600-850P      SWS         026  Seattle     SPR  2017
262016     SOCW598    25  19339       H  LECT   Th  830-1120      SWS         038  Seattle     SPR  2017
262017     SOCW599    35  19358       A                                            Seattle     SPR  2017
262018     SOCW600    10  19359       A                                            Seattle     SPR  2017
262019     SOCW700     5  19360       A                                            Seattle     SPR  2017

`buildings`

Buildings at each UW Campus.

from uwtools import buildings

buidlings(campuses=['Seattle', 'Bothell', 'Tacoma'], update=False)

Args

campuses: list, default ['Seattle', 'Bothell', 'Tacoma']

The list of campuses to get buidlings from.

update: bool, default False

If True, update the buildings by scraping the buildings website at UW. If False, read in the stored values. This should hardly ever be necessary as new buildings do not appear frequently.

Returns

A dictionary with building name abbreviations to full names. An example for buildings(campuses=['Seattle'], update=False) is shown below.

"Seattle": {
        "ACC": "John M. Wallace Hall (formerly Academic Computing Center)",
        "AER": "Aerospace & Engineering Research Building",
        "ALB": "Allen Library",
        "ALD": "Alder Hall"
        ...

`geocode`

Geocodes UW Buildings.

from uwtools import geocode

geocode(buildings=[], campuses=['Seattle', 'Bothell', 'Tacoma'])

Args

buildings: list, default []

The list of buildings to geocode (get coordinates for). If empty, then get all buildings from every campus in campuses.

campuses: list, default ['Seattle', 'Bothell', 'Tacoma']

The list of campuses that contain the buildings in buildings

Returns

A dictionary with coordinate and full name information for each building. An example for geocode(buildings=[], campuses=['Seattle']) is shown below.

{
    "ACC": {
        "Latitude": "47.653063",
        "Longitude": "-122.314812",
        "Name": "John M. Wallace Hall (formerly Academic Computing Center)"
    },
    "AER": {
        "Latitude": "47.653938",
        "Longitude": "-122.305687",
        "Name": "Aerospace & Engineering Research Building"
    },
    ...

`check_campus`

Checks which campus a building is on.

from uwtools import check_campus

check_campus(building)

Args

building: str

The building to check

Returns

None if the building is in none of the UW Campuses. Otherwise, returns the campus the building is on as a String. Either Seattle, Bothell, or Tacoma.

Project details

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1.6.1

May 21, 2021

1.6.0

May 21, 2021

1.5.3

Dec 22, 2020

1.5.2

Oct 30, 2019

1.5.1

Sep 19, 2019

This version

1.4

Sep 9, 2019

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uwtools 1.4

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uwtools

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course_catalogs

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departments

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get_quarter_ranges

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get_quarter

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time_schedules

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buildings

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geocode

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`course_catalogs`

`departments`

`get_quarter_ranges`

`get_quarter`

`time_schedules`

`buildings`

`geocode`

`check_campus`