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Browse files- README.md +3 -9
- requirements.txt +1 -0
- workshops.py +721 -0
README.md
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---
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title:
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colorFrom: pink
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colorTo: red
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sdk: gradio
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sdk_version: 5.
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Schedule_Buddy_Updated
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app_file: workshops.py
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sdk: gradio
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sdk_version: 5.7.1
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---
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requirements.txt
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supabase
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workshops.py
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| 1 |
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import pandas as pd
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| 2 |
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import copy
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import os
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| 4 |
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import gradio as gr
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| 5 |
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from collections import Counter
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import random
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import re
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| 8 |
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from datetime import date
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import supabase
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| 10 |
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import json
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###### OG FUNCTIONS TO GENERATE SCHEDULES ######
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# CONSTANTS
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| 14 |
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NAME_COL = 'Juggler_Name'
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NUM_WORKSHOPS_COL = 'Num_Workshops'
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AVAIL_COL = 'Availability'
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DESCRIP_COL = 'Workshop_Descriptions'
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DELIMITER = ';'
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class Schedule:
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def __init__(self, timeslots: dict):
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self.num_timeslots_filled = 0
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self.total_num_workshops = 0
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for time,instructors in timeslots.items():
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curr_len = len(instructors)
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if curr_len > 0:
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self.num_timeslots_filled += 1
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self.total_num_workshops += curr_len
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self.timeslots = timeslots
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def add(self, person: str, time: str):
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self.total_num_workshops += 1
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if len(self.timeslots[time]) == 0:
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self.num_timeslots_filled += 1
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self.timeslots[time].append(person)
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def remove(self, person: str, time: str):
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self.total_num_workshops -= 1
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if len(self.timeslots[time]) == 1:
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self.num_timeslots_filled -= 1
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self.timeslots[time].remove(person)
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def print(self):
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print(f"# timeslots filled: {self.num_timeslots_filled}")
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print(f"# workshops: {self.total_num_workshops}")
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for time,instructors in self.timeslots.items():
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print(f"{time}: {', '.join(instructors)}")
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# Returns True if the person can teach during the slot, and False otherwise
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| 54 |
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def can_teach(person: str, slot: list, capacity: int) -> bool:
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if len(slot) == capacity or len(slot) > capacity:
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| 56 |
+
return False
|
| 57 |
+
|
| 58 |
+
# No one can teach two workshops at once
|
| 59 |
+
if person in slot:
|
| 60 |
+
return False
|
| 61 |
+
|
| 62 |
+
return True
|
| 63 |
+
|
| 64 |
+
|
| 65 |
+
# Extracts relevant information from the df with availability and puts it into a useable format
|
| 66 |
+
def convert_df(df):
|
| 67 |
+
people = []
|
| 68 |
+
# Key: person's name
|
| 69 |
+
# Value: a list of their availability
|
| 70 |
+
availability = {}
|
| 71 |
+
seen = set()
|
| 72 |
+
for row in range(len(df)):
|
| 73 |
+
# TODO: make sure no people with the same name fill out the form
|
| 74 |
+
name = df.loc[row, NAME_COL]
|
| 75 |
+
|
| 76 |
+
number = df.loc[row, NUM_WORKSHOPS_COL]
|
| 77 |
+
if number == 1:
|
| 78 |
+
people.append(name)
|
| 79 |
+
|
| 80 |
+
# Add people who are teaching multiple workshops to the list more than once
|
| 81 |
+
else:
|
| 82 |
+
for i in range(number):
|
| 83 |
+
people.append(name)
|
| 84 |
+
|
| 85 |
+
curr_avail = df.loc[row, AVAIL_COL]
|
| 86 |
+
curr_avail = curr_avail.split(DELIMITER)
|
| 87 |
+
curr_avail = [elem.strip() for elem in curr_avail]
|
| 88 |
+
availability[name] = curr_avail
|
| 89 |
+
|
| 90 |
+
return people, availability
|
| 91 |
+
|
| 92 |
+
|
| 93 |
+
|
| 94 |
+
# Makes a dictionary where each key is a timeslot and each value is a list.
|
| 95 |
+
# If there's no partial schedule, each list will be empty.
|
| 96 |
+
# If there's a partial schedule, each list will include the people teaching during that slot.
|
| 97 |
+
def initialize_timeslots(df) -> dict:
|
| 98 |
+
all_timeslots = set()
|
| 99 |
+
availability = df[AVAIL_COL]
|
| 100 |
+
for elem in availability:
|
| 101 |
+
curr_list = elem.split(DELIMITER)
|
| 102 |
+
for inner in curr_list:
|
| 103 |
+
all_timeslots.add(inner.strip())
|
| 104 |
+
|
| 105 |
+
to_return = {}
|
| 106 |
+
for slot in all_timeslots:
|
| 107 |
+
to_return[slot] = []
|
| 108 |
+
|
| 109 |
+
return to_return
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
# Recursive function that generates all possible schedules
|
| 113 |
+
def find_all_schedules(people: list, availability: dict, schedule_obj: Schedule, capacity: int, schedules: list, max_timeslots_list: list, max_workshops_list: list) -> None:
|
| 114 |
+
if schedule_obj.num_timeslots_filled > max_timeslots_list[0] or schedule_obj.num_timeslots_filled == max_timeslots_list[0]:
|
| 115 |
+
schedules.append(copy.deepcopy(schedule_obj))
|
| 116 |
+
max_timeslots_list[0] = schedule_obj.num_timeslots_filled
|
| 117 |
+
# Keep track of total number of workshops taught
|
| 118 |
+
if schedule_obj.total_num_workshops > max_workshops_list[0] or schedule_obj.total_num_workshops == max_workshops_list[0]:
|
| 119 |
+
max_workshops_list[0] = schedule_obj.total_num_workshops
|
| 120 |
+
|
| 121 |
+
# Base case
|
| 122 |
+
if len(people) == 0:
|
| 123 |
+
return
|
| 124 |
+
|
| 125 |
+
|
| 126 |
+
# Recursive cases
|
| 127 |
+
person = people[0]
|
| 128 |
+
|
| 129 |
+
for time in availability[person]:
|
| 130 |
+
if can_teach(person, schedule_obj.timeslots[time], capacity):
|
| 131 |
+
# Choose (put that person in that timeslot)
|
| 132 |
+
schedule_obj.add(person, time)
|
| 133 |
+
|
| 134 |
+
# Explore (assign everyone else to timeslots based on that decision)
|
| 135 |
+
if len(people) == 1:
|
| 136 |
+
find_all_schedules([], availability, schedule_obj, capacity, schedules, max_timeslots_list, max_workshops_list)
|
| 137 |
+
|
| 138 |
+
else:
|
| 139 |
+
find_all_schedules(people[1:len(people)], availability, schedule_obj, capacity, schedules, max_timeslots_list, max_workshops_list)
|
| 140 |
+
|
| 141 |
+
# Unchoose (remove that person from the timeslot)
|
| 142 |
+
schedule_obj.remove(person, time)
|
| 143 |
+
# NOTE: this will not generate a full timeslot, but could still lead to a good schedule
|
| 144 |
+
else:
|
| 145 |
+
if len(people) == 1:
|
| 146 |
+
find_all_schedules([], availability, schedule_obj, capacity, schedules, max_timeslots_list, max_workshops_list)
|
| 147 |
+
else:
|
| 148 |
+
find_all_schedules(people[1:len(people)], availability, schedule_obj, capacity, schedules, max_timeslots_list, max_workshops_list)
|
| 149 |
+
|
| 150 |
+
return
|
| 151 |
+
|
| 152 |
+
|
| 153 |
+
# Puts the schedule in the correct order
|
| 154 |
+
def my_sort(curr_sched: dict, og_slots: list):
|
| 155 |
+
# example {'4 pm': ['logan', 'andrew'], '1 pm': ['graham', 'joyce'], '3 pm': ['logan', 'dan'], '2 pm': ['graham', 'dan']}
|
| 156 |
+
to_return = {}
|
| 157 |
+
for elem in og_slots:
|
| 158 |
+
if elem in curr_sched:
|
| 159 |
+
to_return[elem] = curr_sched[elem]
|
| 160 |
+
else:
|
| 161 |
+
to_return[elem] = []
|
| 162 |
+
return to_return
|
| 163 |
+
|
| 164 |
+
|
| 165 |
+
# Makes an organized DataFrame given a list of schedules
|
| 166 |
+
def make_df(schedules: list, descrip_dict: dict, og_slots: list):
|
| 167 |
+
all_times = []
|
| 168 |
+
all_instructors = []
|
| 169 |
+
|
| 170 |
+
count = 1
|
| 171 |
+
|
| 172 |
+
for i in range (len(schedules)):
|
| 173 |
+
curr_sched = schedules[i]
|
| 174 |
+
|
| 175 |
+
#sorted_dict = dict(sorted(curr_sched.items(), key=lambda item: item[0]))
|
| 176 |
+
sorted_dict = my_sort(curr_sched, og_slots)
|
| 177 |
+
curr_times = sorted_dict.keys()
|
| 178 |
+
curr_instructors = sorted_dict.values()
|
| 179 |
+
|
| 180 |
+
# Include an empty row between schedules
|
| 181 |
+
if count != 1:
|
| 182 |
+
all_times.append("")
|
| 183 |
+
all_instructors.append("")
|
| 184 |
+
|
| 185 |
+
if len(schedules) > 1 or len(schedules) == 1:
|
| 186 |
+
all_times.append(f"Schedule #{count}")
|
| 187 |
+
all_instructors.append("")
|
| 188 |
+
count += 1
|
| 189 |
+
|
| 190 |
+
for slot in curr_times:
|
| 191 |
+
all_times.append(slot)
|
| 192 |
+
|
| 193 |
+
for instructors in curr_instructors:
|
| 194 |
+
if len(descrip_dict) == 0:
|
| 195 |
+
all_instructors.append("; ". join(instructors))
|
| 196 |
+
|
| 197 |
+
if len(descrip_dict) > 0:
|
| 198 |
+
big_str = ""
|
| 199 |
+
|
| 200 |
+
for person in instructors:
|
| 201 |
+
if person in descrip_dict:
|
| 202 |
+
descrip = descrip_dict[person]
|
| 203 |
+
else:
|
| 204 |
+
descrip = "Workshop"
|
| 205 |
+
|
| 206 |
+
# {descrip} is a list bc they want to teach multiple workshops
|
| 207 |
+
if '\n' in descrip:
|
| 208 |
+
new_str = f"\n\n- {person}:\n{descrip}"
|
| 209 |
+
else:
|
| 210 |
+
new_str = f"\n\n- {person}: {descrip}"
|
| 211 |
+
|
| 212 |
+
big_str += new_str
|
| 213 |
+
|
| 214 |
+
all_instructors.append(big_str.strip())
|
| 215 |
+
|
| 216 |
+
if len(curr_instructors) == 0:
|
| 217 |
+
all_instructors.append('N/A')
|
| 218 |
+
|
| 219 |
+
|
| 220 |
+
new_df = pd.DataFrame({
|
| 221 |
+
"Schedule": all_times,
|
| 222 |
+
"Instructor(s)": all_instructors
|
| 223 |
+
})
|
| 224 |
+
new_df['Instructor(s)'] = new_df['Instructor(s)'].astype(str)
|
| 225 |
+
|
| 226 |
+
return new_df, count - 1
|
| 227 |
+
|
| 228 |
+
|
| 229 |
+
|
| 230 |
+
|
| 231 |
+
|
| 232 |
+
# Makes a dictionary where each key is the instructor's name and
|
| 233 |
+
# the value is the workshop(s) they're teaching
|
| 234 |
+
def get_description_dict(df):
|
| 235 |
+
new_dict = {}
|
| 236 |
+
for row in range(len(df)):
|
| 237 |
+
name = df.loc[row, NAME_COL]
|
| 238 |
+
new_dict[name] = df.loc[row, DESCRIP_COL]
|
| 239 |
+
return new_dict
|
| 240 |
+
|
| 241 |
+
|
| 242 |
+
# Classifies schedules into two categories: complete and incomplete:
|
| 243 |
+
# Complete = everyone is teaching desired number of timeslots and each timeslot is filled
|
| 244 |
+
# NOTE: I'm using "valid" instead of "complete" as a variable name so that I don't mix it up
|
| 245 |
+
# Incomplete = not complete
|
| 246 |
+
def classify_schedules(people: list, schedules: list, partial_names: list, total_timeslots: int, max_timeslots_filled: int) -> tuple:
|
| 247 |
+
valid_schedules = []
|
| 248 |
+
|
| 249 |
+
# Key: score
|
| 250 |
+
# Value: schedules with that score
|
| 251 |
+
incomplete_schedules = {}
|
| 252 |
+
|
| 253 |
+
# Get frequency of items in the list
|
| 254 |
+
# Key: person
|
| 255 |
+
# Value: number of workshops they WANT to teach
|
| 256 |
+
pref_dict = Counter(people)
|
| 257 |
+
|
| 258 |
+
pref_dict.update(Counter(partial_names))
|
| 259 |
+
|
| 260 |
+
all_names = pref_dict.keys()
|
| 261 |
+
|
| 262 |
+
|
| 263 |
+
## Evaluate each schedule ##
|
| 264 |
+
overall_max = 0 # changes throughout the function
|
| 265 |
+
|
| 266 |
+
for sched in schedules:
|
| 267 |
+
if sched.num_timeslots_filled != max_timeslots_filled:
|
| 268 |
+
continue
|
| 269 |
+
# Key: person
|
| 270 |
+
# Value: how many workshops they're ACTUALLY teaching in this schedule
|
| 271 |
+
freq_dict = {}
|
| 272 |
+
for name in all_names:
|
| 273 |
+
freq_dict[name] = 0
|
| 274 |
+
|
| 275 |
+
for timeslot, instructor_list in sched.timeslots.items():
|
| 276 |
+
for instructor in instructor_list:
|
| 277 |
+
if instructor in freq_dict:
|
| 278 |
+
freq_dict[instructor] += 1
|
| 279 |
+
else:
|
| 280 |
+
print("there is a serious issue!!!!")
|
| 281 |
+
|
| 282 |
+
# See if everyone is teaching their desired number of workshops
|
| 283 |
+
everyone_is_teaching = True
|
| 284 |
+
for teacher, freq in freq_dict.items():
|
| 285 |
+
if freq != pref_dict[teacher]:
|
| 286 |
+
#print(f"teacher: {teacher}. preference: {pref_dict[teacher]}. actual frequency: {freq}")
|
| 287 |
+
everyone_is_teaching = False
|
| 288 |
+
break
|
| 289 |
+
|
| 290 |
+
filled_all_timeslots = (sched.num_timeslots_filled == total_timeslots)
|
| 291 |
+
if everyone_is_teaching and filled_all_timeslots:
|
| 292 |
+
valid_schedules.append(sched)
|
| 293 |
+
else:
|
| 294 |
+
# No need to add to incomplete_schedules if there's at least one valid schedule
|
| 295 |
+
if len(valid_schedules) > 0:
|
| 296 |
+
continue
|
| 297 |
+
#print(f"teaching desired number of timeslots: {everyone_is_teaching}. At least one workshop per slot: {filled_all_timeslots}.\n{sched}\n")
|
| 298 |
+
if sched.num_timeslots_filled > overall_max or sched.num_timeslots_filled == overall_max:
|
| 299 |
+
overall_max = sched.num_timeslots_filled
|
| 300 |
+
|
| 301 |
+
if sched.num_timeslots_filled not in incomplete_schedules:
|
| 302 |
+
incomplete_schedules[sched.num_timeslots_filled] = []
|
| 303 |
+
incomplete_schedules[sched.num_timeslots_filled].append(sched)
|
| 304 |
+
|
| 305 |
+
|
| 306 |
+
|
| 307 |
+
if len(valid_schedules) > 0:
|
| 308 |
+
return valid_schedules, []
|
| 309 |
+
else:
|
| 310 |
+
return [], incomplete_schedules[overall_max]
|
| 311 |
+
|
| 312 |
+
|
| 313 |
+
|
| 314 |
+
# Parameters: schedules that have the max number of timeslots filled
|
| 315 |
+
# Max number of workshops taught in filled timeslots
|
| 316 |
+
# Returns: a list of all schedules that have the max number of workshops
|
| 317 |
+
# To make it less overwhelming, it will return {cutoff} randomly
|
| 318 |
+
def get_best_schedules(schedules: list, cutoff: str, max_workshops: int) -> list:
|
| 319 |
+
cutoff = int(cutoff)
|
| 320 |
+
seen = []
|
| 321 |
+
best_schedules = []
|
| 322 |
+
|
| 323 |
+
for sched in schedules:
|
| 324 |
+
if sched.total_num_workshops != max_workshops:
|
| 325 |
+
continue
|
| 326 |
+
|
| 327 |
+
if sched in seen:
|
| 328 |
+
continue
|
| 329 |
+
else:
|
| 330 |
+
seen.append(sched)
|
| 331 |
+
best_schedules.append(sched.timeslots)
|
| 332 |
+
|
| 333 |
+
if cutoff == -1:
|
| 334 |
+
return best_schedules
|
| 335 |
+
else:
|
| 336 |
+
if len(best_schedules) > cutoff:
|
| 337 |
+
# Sample without replacement
|
| 338 |
+
return random.sample(best_schedules, cutoff)
|
| 339 |
+
else:
|
| 340 |
+
return best_schedules
|
| 341 |
+
|
| 342 |
+
|
| 343 |
+
# Big wrapper function that calls the other functions
|
| 344 |
+
def main(df, capacity:int, num_results: int, og_slots: list):
|
| 345 |
+
descrip_dict = get_description_dict(df)
|
| 346 |
+
|
| 347 |
+
# Convert the df with everyone's availability to a usable format
|
| 348 |
+
res = convert_df(df)
|
| 349 |
+
people = res[0]
|
| 350 |
+
availability = res[1]
|
| 351 |
+
print(availability)
|
| 352 |
+
|
| 353 |
+
partial_names = []
|
| 354 |
+
|
| 355 |
+
timeslots = initialize_timeslots(df)
|
| 356 |
+
|
| 357 |
+
schedules = []
|
| 358 |
+
schedule_obj = Schedule(timeslots)
|
| 359 |
+
max_timeslots_list = [0]
|
| 360 |
+
max_workshops_list = [0]
|
| 361 |
+
|
| 362 |
+
find_all_schedules(people, availability, schedule_obj, capacity, schedules, max_timeslots_list, max_workshops_list)
|
| 363 |
+
|
| 364 |
+
total_timeslots = len(timeslots)
|
| 365 |
+
|
| 366 |
+
|
| 367 |
+
res = classify_schedules(people, schedules, partial_names, total_timeslots, max_timeslots_list[0])
|
| 368 |
+
valid_schedules = res[0]
|
| 369 |
+
decent_schedules = res[1]
|
| 370 |
+
|
| 371 |
+
|
| 372 |
+
# Return schedules
|
| 373 |
+
if len(valid_schedules) > 0:
|
| 374 |
+
best_schedules = get_best_schedules(valid_schedules, num_results, max_workshops_list[0])
|
| 375 |
+
res = make_df(best_schedules, descrip_dict, og_slots)
|
| 376 |
+
new_df = res[0]
|
| 377 |
+
count = res[1]
|
| 378 |
+
if count == 1:
|
| 379 |
+
results = "Good news! I was able to make a complete schedule."
|
| 380 |
+
else:
|
| 381 |
+
results = "Good news! I was able to make multiple complete schedules."
|
| 382 |
+
|
| 383 |
+
else:
|
| 384 |
+
best_schedules = get_best_schedules(decent_schedules, num_results, max_workshops_list[0])
|
| 385 |
+
res = make_df(best_schedules, descrip_dict, og_slots)
|
| 386 |
+
new_df = res[0]
|
| 387 |
+
count = res[1]
|
| 388 |
+
beginning = "Here"
|
| 389 |
+
if count == 1:
|
| 390 |
+
results = f"{beginning} is the best option."
|
| 391 |
+
else:
|
| 392 |
+
results = f"{beginning} are the best options."
|
| 393 |
+
|
| 394 |
+
#results += "(Remember that \"complete\" schedules are ones where everyone is teaching their desired number of workshops and every timeslot is filled.)"
|
| 395 |
+
|
| 396 |
+
|
| 397 |
+
directory = os.path.abspath(os.getcwd())
|
| 398 |
+
path = directory + "/schedule.csv"
|
| 399 |
+
new_df.to_csv(path, index=False)
|
| 400 |
+
return results, new_df, path
|
| 401 |
+
|
| 402 |
+
|
| 403 |
+
|
| 404 |
+
|
| 405 |
+
##### ALL THE NEW STUFF WITH SUPABASE ETC. #####
|
| 406 |
+
### CONSTANTS ###
|
| 407 |
+
NAME_COL = 'Juggler_Name'
|
| 408 |
+
NUM_WORKSHOPS_COL = 'Num_Workshops'
|
| 409 |
+
AVAIL_COL = 'Availability'
|
| 410 |
+
DESCRIP_COL = 'Workshop_Descriptions'
|
| 411 |
+
EMAIL_COL = 'Email'
|
| 412 |
+
DELIMITER = ';'
|
| 413 |
+
ALERT_TIME = None # leave warnings on screen indefinitely
|
| 414 |
+
FORM_NOT_FOUND = 'Form not found'
|
| 415 |
+
INCORRECT_PASSWORD = "The password is incorrect. Please check the password and try again. If you don't remember your password, please email jugglinggym@gmail.com."
|
| 416 |
+
NUM_ROWS = 1
|
| 417 |
+
NUM_COLS_SCHEDULES = 2
|
| 418 |
+
NUM_COLS_ALL_RESPONSES = 4
|
| 419 |
+
NUM_RESULTS = 10 # randomly get {NUM_RESULTS} results
|
| 420 |
+
|
| 421 |
+
|
| 422 |
+
theme = gr.themes.Soft(
|
| 423 |
+
primary_hue="cyan",
|
| 424 |
+
secondary_hue="pink",
|
| 425 |
+
font=[gr.themes.GoogleFont('sans-serif'), 'ui-sans-serif', 'system-ui', 'Montserrat'],
|
| 426 |
+
)
|
| 427 |
+
|
| 428 |
+
### Connect to Supabase ###
|
| 429 |
+
URL = os.environ['URL']
|
| 430 |
+
API_KEY = os.environ['API_KEY']
|
| 431 |
+
client = supabase.create_client(URL, API_KEY)
|
| 432 |
+
|
| 433 |
+
|
| 434 |
+
|
| 435 |
+
|
| 436 |
+
### DEFINE FUNCTIONS ###
|
| 437 |
+
## Multi-purpose function ##
|
| 438 |
+
'''
|
| 439 |
+
Returns a lowercased and stripped version of the schedule name.
|
| 440 |
+
Returns: str
|
| 441 |
+
'''
|
| 442 |
+
def standardize(schedule_name: str):
|
| 443 |
+
return schedule_name.lower().strip()
|
| 444 |
+
|
| 445 |
+
|
| 446 |
+
|
| 447 |
+
|
| 448 |
+
|
| 449 |
+
|
| 450 |
+
## Functions to manage/generate schedules ##
|
| 451 |
+
'''
|
| 452 |
+
Uses the name and password to get the form.
|
| 453 |
+
Makes the buttons and other elements visible on the page.
|
| 454 |
+
Returns:
|
| 455 |
+
gr.Button: corresponds to find_form_btn
|
| 456 |
+
gr.Column: corresponds to all_responses_group
|
| 457 |
+
gr.Column: generate_schedules_explanation
|
| 458 |
+
gr.Row: corresponds to generate_btns
|
| 459 |
+
gr.Column: corresponds to open_close_btn_col
|
| 460 |
+
gr.Button: corresponds to open_close_btn
|
| 461 |
+
'''
|
| 462 |
+
def make_visible(schedule_name:str, password: str):
|
| 463 |
+
skip_output = gr.Button(), gr.Column(), gr.Column(), gr.Row(), gr.Column(), gr.Button()
|
| 464 |
+
|
| 465 |
+
if len(schedule_name) == 0:
|
| 466 |
+
gr.Warning('Please enter the form name.', ALERT_TIME)
|
| 467 |
+
return skip_output
|
| 468 |
+
if len(password) == 0:
|
| 469 |
+
gr.Warning('Please enter the password.', ALERT_TIME)
|
| 470 |
+
return skip_output
|
| 471 |
+
|
| 472 |
+
|
| 473 |
+
response = client.table('Forms').select('password', 'status').eq('form_name', standardize(schedule_name)).execute()
|
| 474 |
+
data = response.data
|
| 475 |
+
|
| 476 |
+
if len(data) > 0:
|
| 477 |
+
my_dict = data[0]
|
| 478 |
+
if password != my_dict['password']:
|
| 479 |
+
gr.Warning(INCORRECT_PASSWORD, ALERT_TIME)
|
| 480 |
+
return skip_output
|
| 481 |
+
else:
|
| 482 |
+
if my_dict['status'] == 'open':
|
| 483 |
+
gr.Info('', ALERT_TIME, title='Btw, the form is currently OPEN.')
|
| 484 |
+
return gr.Button(variant='secondary'), gr.Column(visible=True), gr.Column(visible=True), gr.Row(visible=True), gr.Column(visible=True), gr.Button("Close Form", visible=True)
|
| 485 |
+
|
| 486 |
+
elif my_dict['status'] == 'closed':
|
| 487 |
+
gr.Info('', ALERT_TIME, title='Btw, the form is currently CLOSED.')
|
| 488 |
+
return gr.Button(variant='secondary'), gr.Column(visible=True), gr.Column(visible=True), gr.Row(visible=True),gr.Column(visible=True), gr.Button("Open Form", visible=True)
|
| 489 |
+
|
| 490 |
+
else:
|
| 491 |
+
gr.Warning(f"There is no form called \"{schedule_name}\". Please check the spelling and try again.", ALERT_TIME)
|
| 492 |
+
return skip_output
|
| 493 |
+
|
| 494 |
+
|
| 495 |
+
|
| 496 |
+
|
| 497 |
+
'''
|
| 498 |
+
Makes a blank schedule that we can return to prevent things from breaking.
|
| 499 |
+
Returns: tuple with 3 elements:
|
| 500 |
+
0: str indicating that the form wasn't found
|
| 501 |
+
1: the DataFrame
|
| 502 |
+
2: the path to the DataFrame
|
| 503 |
+
'''
|
| 504 |
+
def make_blank_schedule():
|
| 505 |
+
df = pd.DataFrame({
|
| 506 |
+
'Schedule': [],
|
| 507 |
+
'Instructors': []
|
| 508 |
+
})
|
| 509 |
+
|
| 510 |
+
directory = os.path.abspath(os.getcwd())
|
| 511 |
+
path = directory + "/schedule.csv"
|
| 512 |
+
df.to_csv(path, index=False)
|
| 513 |
+
return FORM_NOT_FOUND, df, path
|
| 514 |
+
|
| 515 |
+
|
| 516 |
+
'''
|
| 517 |
+
Gets a the form responses from Supabase and converts them to a DataFrame
|
| 518 |
+
Returns:
|
| 519 |
+
if found: a dictionary with three keys: capacity (int), df (DataFrame), and slots (list)
|
| 520 |
+
if not found: a string indicating the form was not found
|
| 521 |
+
'''
|
| 522 |
+
def get_df_from_db(schedule_name: str, password: str):
|
| 523 |
+
response = client.table('Forms').select('password', 'capacity', 'responses', 'slots').eq('form_name', standardize(schedule_name)).execute()
|
| 524 |
+
data = response.data
|
| 525 |
+
|
| 526 |
+
if len(data) > 0:
|
| 527 |
+
my_dict = data[0]
|
| 528 |
+
if password != my_dict['password']:
|
| 529 |
+
gr.Warning(INCORRECT_PASSWORD, ALERT_TIME)
|
| 530 |
+
return FORM_NOT_FOUND
|
| 531 |
+
|
| 532 |
+
# Convert to df
|
| 533 |
+
df = pd.DataFrame(json.loads(my_dict['responses']))
|
| 534 |
+
return {'capacity': my_dict['capacity'], 'df': df, 'slots': my_dict['slots']}
|
| 535 |
+
|
| 536 |
+
else:
|
| 537 |
+
gr.Warning(f"There is no form called \"{schedule_name}\". Please check the spelling and try again.", ALERT_TIME)
|
| 538 |
+
return FORM_NOT_FOUND
|
| 539 |
+
|
| 540 |
+
|
| 541 |
+
'''
|
| 542 |
+
Puts all of the form responses into a DataFrame.
|
| 543 |
+
Returns this DF along with the filepath.
|
| 544 |
+
'''
|
| 545 |
+
def get_all_responses(schedule_name:str, password:str):
|
| 546 |
+
res = get_df_from_db(schedule_name, password)
|
| 547 |
+
|
| 548 |
+
if res == FORM_NOT_FOUND:
|
| 549 |
+
df = pd.DataFrame({
|
| 550 |
+
NAME_COL: [],
|
| 551 |
+
EMAIL_COL: [],
|
| 552 |
+
NUM_WORKSHOPS_COL: [],
|
| 553 |
+
AVAIL_COL: [],
|
| 554 |
+
DESCRIP_COL: []
|
| 555 |
+
})
|
| 556 |
+
|
| 557 |
+
else:
|
| 558 |
+
df = res['df']
|
| 559 |
+
df[AVAIL_COL] = [elem.replace(DELIMITER, f"{DELIMITER} ") for elem in df[AVAIL_COL].to_list()]
|
| 560 |
+
|
| 561 |
+
directory = os.path.abspath(os.getcwd())
|
| 562 |
+
path = directory + "/all responses.csv"
|
| 563 |
+
df.to_csv(path, index=False)
|
| 564 |
+
|
| 565 |
+
if len(df) == 0:
|
| 566 |
+
gr.Warning('', ALERT_TIME, title='No one has filled out the form yet.')
|
| 567 |
+
return gr.DataFrame(df, visible=True), gr.File(path, visible=True)
|
| 568 |
+
|
| 569 |
+
|
| 570 |
+
'''
|
| 571 |
+
Calls the algorithm to generate the best possible schedules,
|
| 572 |
+
and returns a random subset of the results.
|
| 573 |
+
(The same as generate_schedules_wrapper_all_results, except that this function only returns a subset of them.
|
| 574 |
+
I had to make it into two separate functions in order to work with Gradio).
|
| 575 |
+
Returns:
|
| 576 |
+
DataFrame
|
| 577 |
+
Filepath to DF (str)
|
| 578 |
+
'''
|
| 579 |
+
def generate_schedules_wrapper_subset_results(schedule_name: str, password: str):
|
| 580 |
+
res = get_df_from_db(schedule_name, password)
|
| 581 |
+
# Return blank schedule (should be impossible to get to this condition btw)
|
| 582 |
+
if res == FORM_NOT_FOUND:
|
| 583 |
+
to_return = make_blank_schedule()
|
| 584 |
+
gr.Warning(FORM_NOT_FOUND, ALERT_TIME)
|
| 585 |
+
|
| 586 |
+
else:
|
| 587 |
+
df = res['df']
|
| 588 |
+
if len(df) == 0:
|
| 589 |
+
gr.Warning('', ALERT_TIME, title='No one has filled out the form yet.')
|
| 590 |
+
to_return = make_blank_schedule()
|
| 591 |
+
else:
|
| 592 |
+
gr.Info('', ALERT_TIME, title='Working on generating schedules! Please DO NOT click anything on this page.')
|
| 593 |
+
to_return = main(df, res['capacity'], NUM_RESULTS, res['slots'])
|
| 594 |
+
gr.Info('', ALERT_TIME, title=to_return[0])
|
| 595 |
+
|
| 596 |
+
|
| 597 |
+
return gr.Textbox(to_return[0]), gr.DataFrame(to_return[1], visible=True), gr.File(to_return[2], visible=True)
|
| 598 |
+
|
| 599 |
+
|
| 600 |
+
'''
|
| 601 |
+
Calls the algorithm to generate the best possible schedules,
|
| 602 |
+
and returns ALL of the results.
|
| 603 |
+
(The same as generate_schedules_wrapper_subset_results, except that this function returns all of them.
|
| 604 |
+
I had to make it into two separate functions in order to work with Gradio).
|
| 605 |
+
Returns:
|
| 606 |
+
DataFrame
|
| 607 |
+
Filepath to DF (str)
|
| 608 |
+
'''
|
| 609 |
+
def generate_schedules_wrapper_all_results(schedule_name: str, password: str):
|
| 610 |
+
res = get_df_from_db(schedule_name, password)
|
| 611 |
+
# Return blank schedule (should be impossible to get to this condition btw)
|
| 612 |
+
if res == FORM_NOT_FOUND:
|
| 613 |
+
to_return = make_blank_schedule()
|
| 614 |
+
gr.Warning(FORM_NOT_FOUND, ALERT_TIME)
|
| 615 |
+
|
| 616 |
+
else:
|
| 617 |
+
df = res['df']
|
| 618 |
+
if len(df) == 0:
|
| 619 |
+
gr.Warning('', ALERT_TIME, title='No one has filled out the form yet.')
|
| 620 |
+
to_return = make_blank_schedule()
|
| 621 |
+
else:
|
| 622 |
+
gr.Info('', ALERT_TIME, title='Working on generating schedules! Please DO NOT click anything on this page.')
|
| 623 |
+
placeholder = -1
|
| 624 |
+
to_return = main(df, res['capacity'], placeholder, res['slots'])
|
| 625 |
+
gr.Info('', ALERT_TIME, title=to_return[0])
|
| 626 |
+
|
| 627 |
+
return gr.Textbox(to_return[0]), gr.DataFrame(to_return[1], visible=True), gr.File(to_return[2], visible=True)
|
| 628 |
+
|
| 629 |
+
|
| 630 |
+
|
| 631 |
+
|
| 632 |
+
'''
|
| 633 |
+
Opens/closes a form and changes the button after opening/closing the form.
|
| 634 |
+
Returns: gr.Button
|
| 635 |
+
'''
|
| 636 |
+
def toggle_btn(schedule_name:str, password:str):
|
| 637 |
+
response = client.table('Forms').select('password', 'capacity', 'status').eq('form_name', standardize(schedule_name)).execute()
|
| 638 |
+
data = response.data
|
| 639 |
+
|
| 640 |
+
if len(data) > 0:
|
| 641 |
+
my_dict = data[0]
|
| 642 |
+
if password != my_dict['password']:
|
| 643 |
+
gr.Warning(INCORRECT_PASSWORD, ALERT_TIME)
|
| 644 |
+
return FORM_NOT_FOUND
|
| 645 |
+
|
| 646 |
+
curr_status = my_dict['status']
|
| 647 |
+
if curr_status == 'open':
|
| 648 |
+
client.table('Forms').update({'status': 'closed'}).eq('form_name', standardize(schedule_name)).execute()
|
| 649 |
+
gr.Info('', ALERT_TIME, title="The form was closed successfully!")
|
| 650 |
+
return gr.Button('Open Form')
|
| 651 |
+
|
| 652 |
+
elif curr_status == 'closed':
|
| 653 |
+
client.table('Forms').update({'status': 'open'}).eq('form_name', standardize(schedule_name)).execute()
|
| 654 |
+
gr.Info('', ALERT_TIME, title="The form was opened successfully!")
|
| 655 |
+
return gr.Button('Close Form')
|
| 656 |
+
|
| 657 |
+
else:
|
| 658 |
+
gr.Error('', ALERT_TIME, 'An unexpected error has ocurred.')
|
| 659 |
+
return gr.Button()
|
| 660 |
+
|
| 661 |
+
else:
|
| 662 |
+
gr.Warning('', ALERT_TIME, title=f"There was no form called \"{schedule_name}\". Please check the spelling and try again.")
|
| 663 |
+
return gr.Button()
|
| 664 |
+
|
| 665 |
+
|
| 666 |
+
|
| 667 |
+
|
| 668 |
+
### GRADIO ###
|
| 669 |
+
with gr.Blocks() as demo:
|
| 670 |
+
### VIEW FORM RESULTS ###
|
| 671 |
+
with gr.Tab('View Form Results'):
|
| 672 |
+
with gr.Column() as btn_group:
|
| 673 |
+
schedule_name = gr.Textbox(label="Form Name")
|
| 674 |
+
password = gr.Textbox(label="Password")
|
| 675 |
+
find_form_btn = gr.Button('Find Form', variant='primary')
|
| 676 |
+
|
| 677 |
+
# 1. Get all responses
|
| 678 |
+
with gr.Column(visible=False) as all_responses_col:
|
| 679 |
+
gr.Markdown('# Download All Form Responses')
|
| 680 |
+
gr.Markdown("Download everyone's responses to the form.")
|
| 681 |
+
all_responses_btn = gr.Button('Download All Form Responses', variant='primary')
|
| 682 |
+
|
| 683 |
+
with gr.Row() as all_responses_output_row:
|
| 684 |
+
df_out = gr.DataFrame(row_count = (NUM_ROWS, "dynamic"),col_count = (NUM_COLS_ALL_RESPONSES, "dynamic"),headers=[NAME_COL, NUM_WORKSHOPS_COL, AVAIL_COL, DESCRIP_COL],wrap=True,scale=4,visible=False)
|
| 685 |
+
file_out = gr.File(label = "Downloadable file", scale=1, visible=False)
|
| 686 |
+
|
| 687 |
+
all_responses_btn.click(fn=get_all_responses, inputs=[schedule_name, password], outputs=[df_out, file_out])
|
| 688 |
+
|
| 689 |
+
|
| 690 |
+
# 2. Generate schedules
|
| 691 |
+
with gr.Column(visible=False) as generate_schedules_explanation_col:
|
| 692 |
+
gr.Markdown('# Create Schedules based on Everyone\'s Preferences.')
|
| 693 |
+
|
| 694 |
+
with gr.Row(visible=False) as generate_btns_row:
|
| 695 |
+
generate_ten_results_btn = gr.Button('Generate a Subset of Schedules', variant='primary', visible=True)
|
| 696 |
+
generate_all_results_btn = gr.Button('Generate All Possible Schedules', visible=True)
|
| 697 |
+
|
| 698 |
+
with gr.Row(visible=True) as generated_schedules_output:
|
| 699 |
+
text_out = gr.Textbox(label='Results')
|
| 700 |
+
generated_df_out = gr.DataFrame(row_count = (NUM_ROWS, "dynamic"),col_count = (NUM_COLS_SCHEDULES, "dynamic"),headers=["Schedule", "Instructors"],wrap=True,scale=3, visible=False)
|
| 701 |
+
generated_file_out = gr.File(label = "Downloadable schedule file", scale=1, visible=False)
|
| 702 |
+
|
| 703 |
+
generate_ten_results_btn.click(fn=generate_schedules_wrapper_subset_results, inputs=[schedule_name, password], outputs=[text_out, generated_df_out, generated_file_out], api_name='generate_random_schedules')
|
| 704 |
+
generate_all_results_btn.click(fn=generate_schedules_wrapper_all_results, inputs=[schedule_name, password], outputs=[text_out, generated_df_out, generated_file_out], api_name='generate_all_schedules')
|
| 705 |
+
|
| 706 |
+
|
| 707 |
+
# 3. Open/close button
|
| 708 |
+
with gr.Column(visible=False) as open_close_btn_col:
|
| 709 |
+
gr.Markdown('# Open or Close Form')
|
| 710 |
+
open_close_btn = gr.Button(variant='primary')
|
| 711 |
+
open_close_btn.click(fn=toggle_btn, inputs=[schedule_name, password], outputs=[open_close_btn])
|
| 712 |
+
|
| 713 |
+
|
| 714 |
+
find_form_btn.click(fn=make_visible, inputs=[schedule_name, password], outputs=[find_form_btn, all_responses_col, generate_schedules_explanation_col, generate_btns_row, open_close_btn_col, open_close_btn])
|
| 715 |
+
|
| 716 |
+
|
| 717 |
+
|
| 718 |
+
|
| 719 |
+
directory = os.path.abspath(os.getcwd())
|
| 720 |
+
allowed = directory #+ "/schedules"
|
| 721 |
+
demo.launch(allowed_paths=[allowed], show_error=True)
|