def main(argv):
test = course_dictionary.create_course_dict()
#Test to see if all prereqs are in the file.
# prereq_list = [single_course for vals in test.values()
# for some_prereqs in vals.prereqs for single_course in some_prereqs]
# for prereq in prereq_list:
# if prereq not in test:
# print(prereq)
# for key in test:
# #Test to see if every course has a term and credits.
# if not test[key].terms or not test[key].credits:
# print(key)
# #Test to see if a course's prereqs include the course itself
# if key in [course for prereq in test[key].prereqs for course in prereq]:
# print(key)
# Prints all the CS courses.
# for key in test:
# if key.program == 'CS':
# print(key, test[key])
#print(test[("ANTH", "4154")].prereqs)
# Test 2, usual 0 credit semesters
#solution = williamju_scheduler.course_scheduler (test, [("CS", "2231"), ("CS", "3251"), ("CS", "statsprobability")], [('MATH', '2810'), ("MATH", "2820"), ("MATH", "3640")])
#solution = williamju_scheduler.course_scheduler(test, [("CS", "major"), ("CS", "2201")], [])
# solution = williamju_scheduler.course_scheduler(test, [("CS", "major"), ("CS", "4269")], [])
# Test 3, usual 0 credit semesters
#solution = williamju_scheduler.course_scheduler(test, [("CS", "core"), ("CS", "1101")], [])
# Test 6, no errors
#solution = williamju_scheduler.course_scheduler(test, [("CS", "major"), ('JAPN', '3891')], [('CS', '1101'), ('JAPN', '1101')])
# Test 8, no errors
solution = williamju_scheduler.course_scheduler(test, [("CS", "major"),
('JAPN', '2201')],
[])
# Test 7, usual 0 credit semesters
#solution = williamju_scheduler.course_scheduler(test, [("CS", "mathematics")], [])
#solution = williamju_scheduler.course_scheduler(test, [("BME", "4900W")], [])
# Test 4, no errors
#solution = williamju_scheduler.course_scheduler(test, [("CS", "major")], [('CS', '1101')])
# Test 5
#solution = williamju_scheduler.course_scheduler(test, [("CS", "major"), ('ANTH', '4345'), ('ARTS', '3600'), ('ASTR', '3600'), ('BME', '4500'), ('BUS', '2300'), ('CE', '3705')], [])
# Test 1, usual 0 credit semesters
#solution = williamju_scheduler.course_scheduler(test, [("CS", "1101")], [])
# Test 0
#solution = williamju_scheduler.course_scheduler(test, [("CS", "1101")], [("CS", "1101")])
#solution = williamju_scheduler.course_scheduler(test, [('ANTH', '4345'), ('ARTS', '3600'), ('BME', '4500'), ('BUS', '2300'), ('CE', '3705'), ('LAT', '3140'), ('JAPN', '3891')], [])
for course in solution:
print(course, solution[course])
def main(argv):
#Creates a dictionary to use for testing
test = course_dictionary.create_course_dict()
#Creates an object course
Course = namedtuple('Course', 'program, designation')
#initializes a course(state) to be the end goal of the schedule
#'CS', 'major'
goals = [
Course('CS', 'major'),
Course('ANTH', '4345'),
Course('ARTS', '3600'),
Course('ASTR', '3600'),
Course('BME', '4500'),
Course('BUS', '2300'),
Course('CE', '3705'),
Course('LAT', '3140'),
Course('JAPN', '3891')
]
semesters = [('Frosh', 'Fall'), ('Frosh', 'Spring'), ('Soph', 'Fall'),
('Soph', 'Spring'), ('Junior', 'Fall'), ('Junior', 'Spring'),
('Senior', 'Fall'), ('Senior', 'Spring')]
semDict = {semester: [0, []] for semester in semesters}
print(test[Course('CS', 'major')])
#initializes the initial state to no courses
#use form [('MATH', '2810'),xxx
init_state = [('CS', '1101')]
#course_dictionary.print_dict(test)
search(semesters, semDict, test, goals, init_state)
check = -1
for goal in goals:
for semester in semDict:
if goal in semDict[semester][1]:
check = 1
if check is -1:
semDict = {}
for each in semDict:
print(each, semDict[each])
finalSchedule = {}
print('Done')
def main(argv):
test = course_dictionary.create_course_dict()
Course = namedtuple('Course', 'program, designation')
#goals = [('CS', '2231'), ('CS', '3251'), ('CS', 'statsprobability')]
#init_state = [('MATH', '2810'), ('MATH', '2820'), ('MATH', '3640')]
#goals = [('CS', 'core'), ('CS', '1101')]
#goals = [('CS', 'major'), ('ANTH', '4345'), ('ARTS', '3600'), ('ASTR', '3600'), ('BME', '4500'), ('BUS', '2300'), ('CE', '3705'), ('LAT', '3140'),
#('JAPN', '3891')]
#goals = [('CS', 'major'), ('JAPN', '3891')]
#goals = [('CS', 'major')]
#init_state = [('CS', '1101')]
#init_state = []
goals = [('CS', '1101')]
init_state = []
plan = course_scheduler(test, goals, init_state)
for key in plan:
print(key, plan[key])
print('Done')
if operator.term.semester == Semester.Summer:
continue
schedule[operator.term].append(operator)
for term in schedule:
hours = 0
for operator in schedule[term]:
hours += int(operator.courseInfo.credits)
print(term, hours, " [")
for operator in schedule[term]:
if not is_higher_level_course_info(operator.courseInfo):
print(operator, ",")
print("]")
if __name__ == '__main__':
course_dict: Dict[Course, CourseInfo] = cd.create_course_dict()
schedule_dict = course_scheduler(course_dict,
goal_conditions=[
Course(program='CS',
designation='major'),
Course('JAPN', '3891')
],
initial_state=[Course('CS', '1101')])
df = pd.DataFrame.from_dict(schedule_dict, orient='index')
course_desc_dict: Dict[
Course, spm.CourseDesc] = spm.create_course_desc_dict(course_dict)
course_names: List[str] = list()
course_sums: List[str] = list()
for course in schedule_dict.keys():
from pprint import pprint
from typing import List, Dict, Tuple
import spacy
from spacy import displacy
import course_dictionary as cd
import sameerpuri_matcher as spm
from pathlib import Path
course_infos: Dict[cd.Course, cd.CourseInfo] = cd.create_course_dict()
course_descs: Dict[cd.Course,
spm.CourseDesc] = spm.create_course_desc_dict(course_infos)
print('Loading...')
print('Reading english word vector information...')
nlp = spacy.load('en_core_web_lg')
print('Analyzing course descriptions...')
course_nlp_descs = {}
course_nlp_names = {}
for course in course_descs.keys():
course_nlp_descs[course] = nlp(course_descs[course].summary)
course_nlp_names[course] = nlp(course_descs[course].name)
print('Loaded!')
def recommend_courses_using_search_text(search_text: str, num: int) -> List:
search_text = nlp(search_text)
text_similarities_dict: Dict[float, cd.Course] = {
search_text.similarity(course_nlp_descs[course]): course
for course in course_nlp_descs.keys()
}
from flask import Flask, jsonify, render_template, request
from typing import List, Tuple
import course_dictionary as cd
import click
click.disable_unicode_literals_warning = True
import sameerpuri_scheduler as sps
import sameerpuri_matcher as spm
import sameerpuri_recommender as spr
app = Flask(__name__)
course_dict = cd.create_course_dict()
course_desc_dict = spm.create_course_desc_dict(course_dict)
@app.route('/course/<program>/<int:designation>/<reqtype>')
def get_course_desc(program: str, designation: int, reqtype: str):
res = {
'summary': lambda course: course_desc_dict[course].summary,
'name': lambda course: course_desc_dict[course].name,
'formerly': lambda course: course_desc_dict[course].formerly,
'creditbracket': lambda course: course_desc_dict[course].creditbracket
}[reqtype](cd.Course(program, str(designation)))
return jsonify(res)
@app.route('/')
def index():
return render_template('index.html')