refactor test environment structure
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#!/usr/bin/python3
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import json
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import math
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import random
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from util.mockStudents import getSampleStudents
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from util.generateCourses import getSampleCourses
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'''
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Block 1-5 is first semester while
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block 6-10 is second semester
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schedule example:
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schedule: {
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"block1": "className",
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"block2": "className",
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"block3": "className",
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...
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}
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running example:
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running: {
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"block1": {
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classCode: {
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"className": name,
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"students": [student Name]
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},
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classCode: {
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"className": name,
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"students": [student Name]
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}
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},
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...
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}
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'''
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minReq, median, classCap, blockClassLimit = 18, 24, 30, 12
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mockStudents = []
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activeCourses = {}
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running = {
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"block1": {},
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"block2": {},
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"block3": {},
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"block4": {},
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"block5": {},
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"block6": {},
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"block7": {},
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"block8": {},
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"block9": {},
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"block10": {}
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}
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# V3 differs a lot by V1/2 as it does not focus on fitting the classes
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# into the time table first.
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# It starts by trying to get all classes full and give all students a full class list.
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# Then it starts to attempt to fit all classes into a timetable, making corretions along
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# the way. Corrections being moving a students class
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def generateScheduleV3(students, courses):
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def equal(l): # Used to equalize list of numbers
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q,r = divmod(sum(l),len(l))
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return [q+1]*r + [q]*(len(l)-r)
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# Step 1 - Calculate which classes can run
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global err1, err2
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for student in students:
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# Tally class request
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for request in student["requests"]:
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if not bool([i for i in ["XAT--12A-S", "XAT--12B-S"] if (i in request["CrsNo"])]): # Filters any requested study blocks (flex: no class block)
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code = request["CrsNo"]
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courses[code]["Requests"] += 1
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# Add course to active list if enough requests
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if courses[code]["Requests"] > minReq and courses[code]["CrsNo"] not in activeCourses:
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activeCourses[code] = courses[code]
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# Step 2 - Generate empty classes
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emptyClasses = {} # List of all classes with how many students should be entered during generation
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# calculate # of times to run class
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for i in range(len(activeCourses)):
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index = list(activeCourses)[i]
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if index not in emptyClasses: emptyClasses[index] = {}
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classRunCount = math.floor(activeCourses[index]["Requests"] / median)
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remaining = activeCourses[index]["Requests"] % median
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# Put # of classRunCount classes in emptyClasses
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for j in range(classRunCount):
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emptyClasses[index][f"{index}-{j}"] = {
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"CrsNo": index,
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"Description": activeCourses[index]["Description"],
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"expectedLen": median # Number of students expected in this class / may be altered
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}
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# If remaining fit in open slots in existing classes
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if remaining <= classRunCount * (classCap - median):
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# Equally disperse remaining into existing classes
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while remaining > 0:
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for j in range(classRunCount):
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if remaining == 0: break
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emptyClasses[index][f"{index}-{j}"]["expectedLen"] += 1
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remaining -= 1
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# If we can create a class using remaining, but no other classes
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# exists, create class, and do not equalize
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elif remaining >= minReq and classRunCount == 0:
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# Create a class using remaining
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emptyClasses[index][f"{index}-{classRunCount}"] = {
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"CrsNo": index,
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"Description": activeCourses[index]["Description"],
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"expectedLen": remaining
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}
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classRunCount += 1
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# Else if the remaining can create a class
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elif remaining >= minReq and classRunCount > 0:
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# Create a class using remaining
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emptyClasses[index][f"{index}-{classRunCount}"] = {
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"CrsNo": index,
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"Description": activeCourses[index]["Description"],
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"expectedLen": remaining
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}
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classRunCount += 1
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# Equalize (level) class expectedLen's
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expectedLengths = [emptyClasses[index][f"{index}-{j}"]["expectedLen"] for j in range(classRunCount)]
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newExpectedLens = equal(expectedLengths)
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for j in range(len(newExpectedLens)):
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emptyClasses[index][f"{index}-{j}"]["expectedLen"] = newExpectedLens[j]
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# Else if we can't fit remaining in open slots in existing classes
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# and it is unable to create its own class,
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# and requiered number to make a class is less than the max number we can provide from existing classes
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elif minReq - remaining < classRunCount * (median - minReq):
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# Take 1 from each class till min requirment met
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for j in range(classRunCount):
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emptyClasses[index][f"{index}-{j}"]["expectedLen"] -= 1
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remaining += 1
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if remaining == minReq: break
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# Create a class using remaining
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emptyClasses[index][f"{index}-{classRunCount}"] = {
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"CrsNo": index,
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"Description": activeCourses[index]["Description"],
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"expectedLen": remaining
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}
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classRunCount += 1
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# Equalize (level) class expectedLen's
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expectedLengths = [emptyClasses[index][f"{index}-{j}"]["expectedLen"] for j in range(classRunCount)]
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newExpectedLens = equal(expectedLengths)
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for j in range(len(newExpectedLens)):
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emptyClasses[index][f"{index}-{j}"]["expectedLen"] = newExpectedLens[j]
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else:
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# In the case that the remaining requests are unable to be resolved
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# Fill as many requests into class as possible, any left that can't fit,
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# Will need to be ignored so later we can fold them into their alternative
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# choices
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for j in range(classRunCount):
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if emptyClasses[index][f"{index}-{j}"]["expectedLen"] < classCap and remaining > 0:
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emptyClasses[index][f"{index}-{j}"]["expectedLen"] += 1
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remaining -= 1
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# Step 3 Fill emptyClasses with Students
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selectedCourses = {}
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tempStudents = students
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while len(tempStudents) > 0:
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student = tempStudents[random.randint(0, len(students)-1)]
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alternates = [request for request in student["requests"] if request["alt"]]
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altOffset = None
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if len(alternates) > 0: altOffset = 0
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for request in (request for request in student["requests"] if not request["alt"] and request not in ["XAT--12A-S", "XAT--12B-S"]):
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course = request["CrsNo"]
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getAvailableCourse = True
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while getAvailableCourse:
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if course in emptyClasses:
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# if course exists, get first available class
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for cname in emptyClasses[course]:
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if cname in selectedCourses:
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if len(selectedCourses[cname]["students"]) < emptyClasses[course][cname]["expectedLen"]:
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# Class exists with room for student
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selectedCourses[cname]["students"].append(student["Pupil #"])
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getAvailableCourse = False
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break
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elif len(selectedCourses[cname]["students"]) == emptyClasses[course][cname]["expectedLen"]:
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# If class is full, and is last class of that course
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if cname[len(cname)-1] == f"{len(emptyClasses[course])-1}":
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if altOffset is not None and altOffset <= len(alternates)-1:
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# Use alternate
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course = alternates[altOffset]["CrsNo"]
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altOffset += 1
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break
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else:
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# Force break loop, ignore and let an admin
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# handle options to solve for missing class
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getAvailableCourse = False
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break
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elif cname not in selectedCourses:
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selectedCourses[cname] = {
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"students": [student["Pupil #"]],
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"CrsNo": course,
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"Description": courses[course]["Description"]
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}
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getAvailableCourse = False
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break
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elif course not in emptyClasses:
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if altOffset is not None and altOffset <= len(alternates)-1:
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# Use alternate
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course = alternates[altOffset]["CrsNo"]
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altOffset += 1
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else:
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# Force break loop, ignore and let an admin
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# handle options to solve for missing class
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getAvailableCourse = False
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tempStudents.remove(student)
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# Step 4 - Attempt to fit classes into timetable
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# TODO: Prioratize classes with maximum resouce limit;
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# for example, classes that have lowest run counts,
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# classes that have limited rooms dedicated for them.
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# Fit these into the timetable first, then work from
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# there on fitting other classes into the timetable.
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# This will require knowing how many classrooms there are,
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# how many classrooms for a type of class, computer, wood,
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# metal, art, drama, music.
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# Languages, socials, math, science, and English all share
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# the same classroom type and can be interchanged.
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# Teachers can be figured out at the end of this step,
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# The school can hire more teachers in the area required,
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# so we do not need to worry about how many tpye of classes
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# are in the same block.
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# For example: we don't need to worry if there is 4 english
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# classes in the same block. even though the school may only
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# have 2 english teachers.
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# Step 5 - Evaluate, move classes or students to fix
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return []
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if __name__ == '__main__':
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print("Processing...")
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sampleStudents = getSampleStudents(True)
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samplemockCourses = getSampleCourses(True)
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timetable = {}
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timetable["Version"] = 3
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timetable["timetable"] = generateScheduleV3(sampleStudents, samplemockCourses)
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with open("../output/timetable.json", "w") as outfile:
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json.dump(timetable, outfile, indent=2)
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print("Done")
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