Merge remote-tracking branch 'flask_repo/main' into flask

- COMMLD570A did not penalize/track absences at all so i cut this completely

.gitignore

@@ -1,2 +1,3 @@
 *~
 __pycache__
+*.pyc

README

@@ -1,7 +1,7 @@
 Setting up the Discord Bot
 ======================================
 
-I run the Discord boy from my laptop. It requires the discord Python
+I run the Discord bot from my laptop. It requires the discord Python
 module available in PyPi and installable like:
 
     $ pip3 install discord
@@ -44,7 +44,7 @@ Daily Process
 
 You need to start the bot from the laptop each day. I do that by:
 
-  $ ./coldcallboy.py
+  $ ./coldcallbot.py
 
 The bot will run in the terminal, print out data as it works including
 detailed weights as it goes, and it will record data into files in the

assessment_and_tracking/compute_final_case_grades.R

@@ -1,36 +1,23 @@
 ## load in the data
 #################################
 
-case.sessions  <- 15
-myuw <- read.csv("myuw-COM_482_A_autumn_2020_students.csv", stringsAsFactors=FALSE)
+myuw <- read.csv("myuw-COMMLD_570_A_spring_2021_students.csv", stringsAsFactors=FALSE)
 
 ## class-level variables
-question.grades <- c("GOOD"=100, "FAIR"=100-(50/3.3), "BAD"=100-(50/(3.3)*2))
-missed.question.penalty <- (50/3.3) * 0.2 ## 1/5 of a full point on the GPA scale
+question.grades <- c("GOOD"=100, "FAIR"=100-(50/3.3), "WEAK"=100-(50/(3.3)*2))
 
 source("../assessment_and_tracking/track_participation.R")
 setwd("case_grades")
 
-rownames(d) <- d$discord.name
+rownames(d) <- d$unique.name
 
 ## show the distribution of assessments
-table(call.list.full$assessment)
-prop.table(table(call.list.full$assessment))
-table(call.list.full$answered)
-prop.table(table(call.list.full$answered))
+table(call.list$assessment)
+prop.table(table(call.list$assessment))
+table(call.list$answered)
+prop.table(table(call.list$answered))
 
-total.questions.asked <- nrow(call.list.full)
-
-## create new column with number of questions present
-d$prop.asked <- d$num.calls / d$num.present
-
-## generate statistics using these new variables
-prop.asks.quantiles <- quantile(d$prop.asked, probs=seq(0,1, 0.01))
-prop.asks.quantiles <- prop.asks.quantiles[!duplicated(prop.asks.quantiles)]
-
-## this is generating broken stuff but it's not used for anything
-d$prop.asked.quant <- cut(d$prop.asked, breaks=prop.asks.quantiles,
-    labels=names(prop.asks.quantiles)[1:(length(prop.asks.quantiles)-1)])
+total.questions.asked <- nrow(call.list)
 
 ## generate grades
 ##########################################################
@@ -39,81 +26,47 @@ d$part.grade <- NA
 
 ## print the median number of questions for (a) everybody and (b)
 ## people that have been present 75% of the time
-median(d$num.calls[d$days.absent < 0.25*case.sessions])
 median(d$num.calls)
 
 questions.cutoff <- median(d$num.calls)
 
 ## helper function to generate average grade minus number of missing
-gen.part.grade <- function (x.discord.name) {
-    q.scores <- question.grades[call.list$assessment[call.list$discord.name == x.discord.name]]
+gen.part.grade <- function (x.unique.name) {
+    q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]]
     base.score <- mean(q.scores, na.rm=TRUE)
 
     ## number of missing days
-    missing.days <- nrow(missing.in.class[missing.in.class$discord.name == x.discord.name,])
+    # missing.days <- nrow(missing.in.class[missing.in.class$unique.name == x.unique.name,])
 
     ## return the final score
-    data.frame(discord.name=x.discord.name,
-               part.grade=(base.score - missing.days * missed.question.penalty))
+    data.frame(unique.name=x.unique.name,
+               part.grade=(base.score))
 }
 
-tmp <- do.call("rbind", lapply(d$discord.name[d$num.calls >= questions.cutoff], gen.part.grade))
 
-d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade
+tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade))
 
-## next handle the folks *under* the median
-
-## first we handle the zeros
-## step 1: first double check the people who have zeros and ensure that they didn't "just" get unlucky"
-d[d$num.calls == 0,]
-
-## set those people to 0 :(
-d$part.grade[d$num.calls == 0] <- 0
-
-## step 2 is to handle folks who got unlucky in the normal way
-tmp <- do.call("rbind", lapply(d$discord.name[is.na(d$part.grade) & d$prop.asked <= median(d$prop.asked)], gen.part.grade))
-d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade
-
-## the people who are left are lucky and still undercounted so we'll penalize them
-d[is.na(d$part.grade),]
-penalized.discord.names <- d$discord.name[is.na(d$part.grade)]
+d[as.character(tmp$unique.name), "part.grade"] <- tmp$part.grade
 
 ## generate the baseline participation grades as per the process above
-tmp <- do.call("rbind", lapply(penalized.discord.names, gen.part.grade))
-d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade
-
-## now add "zeros" for every questions that is below the normal
-d[as.character(penalized.discord.names),"part.grade"] <- ((
-    (questions.cutoff - d[as.character(penalized.discord.names),"num.calls"] * 0) +
-    (d[as.character(penalized.discord.names),"num.calls"] * d[as.character(penalized.discord.names),"part.grade"]) )
-    / questions.cutoff)
-
-d[as.character(penalized.discord.names),]
 
 ## map part grades back to 4.0 letter scale and points
 d$part.4point <-round((d$part.grade / (50/3.3)) - 2.6, 2)
 
-d[sort.list(d$prop.asked), c("discord.name", "num.calls", "num.present",
-                             "prop.asked", "prop.asked.quant", "part.grade", "part.4point",
-                             "days.absent")]
-
-d[sort.list(d$part.4point), c("discord.name", "num.calls", "num.present",
-                             "prop.asked", "prop.asked.quant", "part.grade", "part.4point",
-                             "days.absent")]
+d[sort.list(d$part.4point),]
 
 
 ## writing out data
-quantile(d$num.calls, probs=(0:100*0.01))
 d.print <- merge(d, myuw[,c("StudentNo", "FirstName", "LastName", "UWNetID")],
            by.x="student.num", by.y="StudentNo")
 write.csv(d.print, file="final_participation_grades.csv")
 
-library(rmarkdown)
+## library(rmarkdown)
 
-for (x.discord.name in d$discord.name) {
-    render(input="../../assessment_and_tracking/student_report_template.Rmd",
-           output_format="html_document",
-           output_file=paste("../data/case_grades/student_reports/",
-                             d.print$UWNetID[d.print$discord.name == x.discord.name],
-                             sep=""))
-}
+## for (x.unique.name in d$unique.name) {
+##     render(input="../../assessment_and_tracking/student_report_template.Rmd",
+##            output_format="html_document",
+##            output_file=paste("../data/case_grades/student_reports/",
+##                              d.print$UWNetID[d.print$unique.name == x.unique.name],
+##                              sep=""))
+## }

assessment_and_tracking/track_enrolled.R

@@ -1,4 +1,4 @@
-myuw <- read.csv("myuw-COM_482_A_autumn_2020_students.csv")
+myuw <- read.csv("myuw-COMMLD_570_A_spring_2021_students.csv")
 gs <- read.delim("student_information.tsv")
 
 ## these are students who dropped the class (should be empty)
@@ -10,14 +10,14 @@ myuw[!myuw$StudentNo %in% gs$Your.UW.student.number,]
 ## read all the folks who have been called and see who is missing from
 ## the google sheet
 
-call.list <- unlist(lapply(list.files(".", pattern="^attendance-.*tsv$"), function (x) {
-    d <- read.delim(x)
-    strsplit(d[[2]], ",")
-})
-)
-present <- unique(call.list)
-present[!present %in% gs[["Your.username.on.the.class.Discord.server"]]]
+## call.list <- unlist(lapply(list.files(".", pattern="^attendance-.*tsv$"), function (x) {
+##    d <- read.delim(x)
+##    strsplit(d[[2]], ",")
+## })
+## )
+## present <- unique(call.list)
+## present[!present %in% gs[["Your.username.on.the.class.Discord.server"]]]
 
 ## and never attended class..
-gs[["Your.username.on.the.class.Discord.server"]][!gs[["Your.username.on.the.class.Discord.server"]] %in% present]
+## gs[["Your.username.on.the.class.Discord.server"]][!gs[["Your.username.on.the.class.Discord.server"]] %in% present]
 

assessment_and_tracking/track_participation.R

@@ -1,109 +1,25 @@
+setwd("~/online_communities/coldcallbot/data/")
+
 library(ggplot2)
 library(data.table)
 
 gs <- read.delim("student_information.tsv")
-d <- gs[,c(2,5)]
-colnames(d) <- c("student.num", "discord.name")
+d <- gs[,c(2,4)]
+colnames(d) <- c("student.num", "unique.name")
+
+call.list <- do.call("rbind", lapply(list.files(".", pattern="^call_list-.*tsv$"), function (x) {read.delim(x, stringsAsFactors=FALSE)[,1:4]}))
 
-call.list <- do.call("rbind", lapply(list.files(".", pattern="^call_list-.*tsv$"), function (x) {read.delim(x)[,1:4]}))
 colnames(call.list) <- gsub("_", ".", colnames(call.list))
 
-call.list$day <- as.Date(call.list$timestamp)
+table(call.list$unique_name[call.list$answered])
 
 ## drop calls where the person wasn't present
 call.list.full <- call.list
 call.list[!call.list$answered,]
 call.list <- call.list[call.list$answered,]
 
-call.counts <- data.frame(table(call.list$discord.name))
-colnames(call.counts) <- c("discord.name", "num.calls")
+call.counts <- data.frame(table(call.list$unique.name))
+colnames(call.counts) <- c("unique.name", "num.calls")
 
-d <- merge(d, call.counts, all.x=TRUE, all.y=TRUE, by="discord.name"); d
-
-## set anything that's missing to zero
-d$num.calls[is.na(d$num.calls)] <- 0
-      
-attendance <- unlist(lapply(list.files(".", pattern="^attendance-.*tsv$"), function (x) {d <- read.delim(x); strsplit(d[[2]], ",")}))
-
-file.to.attendance.list <- function (x) {
-    tmp <- read.delim(x)
-    d.out <- data.frame(discord.name=unlist(strsplit(tmp[[2]], ",")))
-    d.out$day <- rep(as.Date(tmp[[1]][1]), nrow(d.out))
-    return(d.out)
-}
-
-attendance <- do.call("rbind",
-                      lapply(list.files(".", pattern="^attendance-.*tsv$"),
-                             file.to.attendance.list))
-
-## create list of folks who are missing in class 
-missing.in.class  <- call.list.full[is.na(call.list.full$answered) |
-                                    (!is.na(call.list.full$answered) & !call.list.full$answered),
-                                    c("discord.name", "day")]
-
-missing.in.class <- unique(missing.in.class)
-
-setDT(attendance)
-setkey(attendance, discord.name, day)
-setDT(missing.in.class)
-setkey(missing.in.class, discord.name, day)
-
-## drop presence for people on missing days
-attendance[missing.in.class,]
-attendance <- as.data.frame(attendance[!missing.in.class,])
-
-attendance.counts <- data.frame(table(attendance$discord.name))
-colnames(attendance.counts) <- c("discord.name", "num.present")
-
-d <- merge(d, attendance.counts,
-           all.x=TRUE, all.y=TRUE,
-           by="discord.name")
-
-days.list <- lapply(unique(attendance$day), function (day) {
-    day.total <- table(call.list.full$day == day)[["TRUE"]]
-    lapply(d$discord.name, function (discord.name) {
-        num.present <- nrow(attendance[attendance$day == day & attendance$discord.name == discord.name,])
-        if (num.present/day.total > 1) {print(day)}
-        data.frame(discord.name=discord.name,
-                   days.present=(num.present/day.total))
-    })
-})
-
-days.tmp <- do.call("rbind", lapply(days.list, function (x) do.call("rbind", x)))
-
-days.tbl <- tapply(days.tmp$days.present, days.tmp$discord.name, sum)
-
-attendance.days <- data.frame(discord.name=names(days.tbl),
-                              days.present=days.tbl,
-                              days.absent=length(list.files(".", pattern="^attendance-.*tsv$"))-days.tbl)
-
-d <- merge(d, attendance.days,
-           all.x=TRUE, all.y=TRUE, by="discord.name")
-
-d[sort.list(d$days.absent), c("discord.name", "num.calls", "days.absent")]
-
-## make some visualizations of whose here/not here
-#######################################################
-
-png("questions_absence_histogram_combined.png", units="px", width=800, height=600)
-
-ggplot(d) +
-    aes(x=as.factor(num.calls), fill=days.absent, group=days.absent) +
-    geom_bar(color="black") +
-    scale_x_discrete("Number of questions asked") +
-    scale_y_continuous("Number of students") +
-    scale_fill_continuous("Days absent", low="red", high="blue")+
-    theme_bw()
-
-dev.off()
-
-png("questions_absenses_boxplots.png", units="px", width=800, height=600)
-
-ggplot(data=d) +
-    aes(x=as.factor(num.calls), y=days.absent) +
-    geom_boxplot() +
-    scale_x_discrete("Number of questions asked") +
-    scale_y_continuous("Days absent")
-
-dev.off()
+d <- merge(d, call.counts, all.x=TRUE, all.y=TRUE, by="unique.name"); d
 

coldcall.py

@@ -8,19 +8,21 @@ from csv import DictReader
 
 import os.path
 import re
-import discord
 
 class ColdCall():
-    def __init__ (self):
+    def __init__ (self, record_attendance=True):
         self.today = str(datetime.date(datetime.now()))
         # how much less likely should it be that a student is called upon?
         self.weight = 2
+        self.record_attendance = record_attendance
 
         # filenames
         self.__fn_studentinfo = "data/student_information.tsv"
         self.__fn_daily_calllist = f"data/call_list-{self.today}.tsv"
         self.__fn_daily_attendance = f"data/attendance-{self.today}.tsv"
 
+        self.preferred_names = self.__get_preferred_names()
+        
     def __load_prev_questions(self):
         previous_questions = defaultdict(int)
 
@@ -29,21 +31,24 @@ class ColdCall():
                 with open(f"./data/{fn}", 'r') as f:
                     for row in DictReader(f, delimiter="\t"):
                         if not row["answered"] == "FALSE":
-                            previous_questions[row["discord_name"]] += 1
+                            previous_questions[row["unique_name"]] += 1
 
         return previous_questions
 
-    def __get_preferred_name(self, selected_student):
-        # translate the discord name into the preferred students name,
-        # if possible, otherwise return the discord name
+    def __get_preferred_names(self):
+        # translate the unique name into the preferred students name,
+        # if possible, otherwise return the unique name
 
         preferred_names = {}
         with open(self.__fn_studentinfo, 'r') as f:
             for row in DictReader(f, delimiter="\t"):
-                preferred_names[row["Your username on the class Discord server"]] = row["Name you'd like to go by in class"]
+                preferred_names[row["Your username on the class Teams server"]] = row["Name you'd like to go by in class"]
 
-        if selected_student in preferred_names:
-            return preferred_names[selected_student]
+        return(preferred_names)
+        
+    def __get_preferred_name(self, selected_student):
+        if selected_student in self.preferred_names:
+            return self.preferred_names[selected_student]
         else:
             return None
 
@@ -59,7 +64,7 @@ class ColdCall():
                 weights[s] = weights[s] / self.weight
 
         # choose one student from the weighted list
-        print(weights)
+        # print(weights) # DEBUG LINE
         return choices(list(weights.keys()), weights=list(weights.values()), k=1)[0]
 
     def __record_attendance(self, students_present):
@@ -78,7 +83,7 @@ class ColdCall():
         # if it's the first one of the day, write it out
         if not os.path.exists(self.__fn_daily_calllist):
             with open(self.__fn_daily_calllist, "w") as f:
-                print("\t".join(["discord_name", "timestamp", "answered", "assessment"]), file=f)
+                print("\t".join(["unique_name", "timestamp", "answered", "assessment"]), file=f)
 
         # open for appending the student
         with open(self.__fn_daily_calllist, "a") as f:
@@ -89,6 +94,7 @@ class ColdCall():
         selected_student = self.__select_student_from_list(students_present)
 
         # record the called-upon student in the right place
+        if self.record_attendance:
             self.__record_attendance(students_present)
         self.__record_coldcall(selected_student)
 

coldcallbot-manual.py

@@ -0,0 +1,15 @@
+#!/usr/bin/env python3
+
+from coldcall import ColdCall
+import re
+
+## create the coldcall object
+cc = ColdCall(record_attendance=False)
+
+student_list = cc.preferred_names
+
+# print out 100 students
+
+for i in range(100):
+    print(f"{i + 1}. {cc.coldcall(student_list)} [ ] [ ]\n")
+

data/download_data.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+
+wget 'https://docs.google.com/spreadsheets/d/FIXME/export?gid=FIXME&format=tsv' -O 'student_information.tsv'
+

flask_app/app.py

@@ -0,0 +1,155 @@
+#!/usr/bin/env python
+
+import pandas as pd
+from random import choices, shuffle
+from datetime import datetime
+import csv
+import os
+from flask import Flask, render_template, request, abort
+
+app = Flask(__name__)
+
+@app.route("/")
+def hello_world():
+    return "<p>Hello, Test!</p>"
+
+
+@app.route('/response_quality', methods=['POST'])
+def response_quality():
+    student_name = request.form['studentName']
+    button_value = request.form['buttonValue']
+    course = request.form['course']
+    print(button_value)
+
+    fn = f'../assessments/{course}/{course}.csv'
+
+    if button_value == 'absent':
+        answered = 'F'
+        button_value = ''
+    else:
+        answered = 'T'
+
+    if button_value != 'get_next':
+        write_to_file(student_name, fn,
+                answered=answered,
+                assessment=button_value)
+    student = coldcall_student(course)
+    print(f'Sending {student}')
+    return student
+
+@app.route("/coldcaller/<course>", methods=['POST','GET'])
+def coldcaller(course):
+    public = request.args.get('public')
+    print(public)
+    if request.method == "POST":
+        student = coldcall_student(course)
+        if not student:
+            abort(404)
+    else:
+        student = ''
+    return render_template('cold_caller.html', student=student, public=public)
+
+def coldcall_student(course):
+    if course not in ["com_304","com_411","com_674", "amap"]:
+        return None
+    weight = 2
+    students = pd.read_csv(f'../assessments/{course}/{course}_students.csv').Name
+    out_fn = f'../assessments/{course}/{course}.csv'
+    caller = Caller(out_fn, students, weight)
+    student = caller.get_random_student()
+    return student
+
+@app.route("/shuffler", methods=['POST','GET']) 
+def shuffler():
+    course = request.args.get('course')
+    try:
+        student_list = pd.read_csv(f'../assessments/{course}/{course}_students.csv').Name
+    except FileNotFoundError:
+        abort(404)
+    shuffle(student_list)
+    print(student_list)
+    return render_template('shuffler.html', result=student_list)
+
+@app.route("/make_groups", methods=['POST','GET'])
+def make_groups():
+    course = request.args.get('course')
+    group_size = int(request.args.get('group_size'))
+    print('running')
+    try:
+        student_list = pd.read_csv(f'../assessments/{course}/{course}_students.csv').Name
+    except FileNotFoundError:
+        abort(404)
+    shuffle(student_list)
+    print(student_list)
+    print(range(0,len(student_list)//group_size + 1, group_size))
+    result = []
+    j = 1
+    for i in range(0,len(student_list), group_size):
+        result.append((j, student_list[i:i+group_size]))
+        j += 1
+    return render_template('group_maker.html', result=result)
+
+
+
+class Caller:
+
+    def __init__(self, out_fn, students, weight = 2):
+        self.weight = weight
+        self.fn = out_fn
+        self.students = students
+        self.last_chosen = None
+        self.today = datetime.now().date()
+        self.weights_dict = self.get_weights()
+
+    def get_weights(self):
+        times_called = self.get_times_called()
+        weights_dict = {}
+        for student in self.students:
+            try:
+                curr_tc = times_called[student]
+            except KeyError:
+                curr_tc = 0
+            student_weight = (1/self.weight) ** curr_tc
+            weights_dict[student] = student_weight
+        return weights_dict
+
+
+    def get_times_called(self):
+        try:
+            df = pd.read_csv(self.fn)
+            if len(df) > 0:
+                self.last_chosen = df.name.iloc[-1]
+            df.date = pd.to_datetime(df.date).dt.date
+            times_called = df[(df.answered.isin(['T','TRUE']))|(df.date==self.today)].groupby('name').size()
+            self.absent_today = df.loc[(df.date==self.today) & (df.answered.isin(['F', 'FALSE'])), 'name']
+        except FileNotFoundError or IndexError:
+            times_called = pd.DataFrame()
+            self.absent_today = pd.DataFrame()
+        return times_called
+
+    def update_weight(self, student):
+        self.weights_dict[student] /= self.weight
+
+    def get_random_student(self, can_repeat=False):
+        if not can_repeat:
+            curr_weights = {k:v for k,v in self.weights_dict.items() if k != self.last_chosen}
+        else:
+            curr_weights = self.weights_dict
+        for student in set(self.absent_today):
+            if student != self.last_chosen:
+                del curr_weights[student]
+        rand_student = choices(list(curr_weights.keys()), weights=list(curr_weights.values()), k=1)[0]
+        print(f"Weight of {rand_student}: {curr_weights[rand_student]}")
+        self.update_weight(rand_student)
+        return(rand_student)
+
+def write_to_file(student, fn, answered, assessment):
+    if not os.path.exists(fn):
+        with open(fn, 'w') as f:
+            f.write(','.join(['name', 'date', 'answered', 'assessment']))
+            f.write('\n')
+    with open(fn, 'a') as f:
+        out_csv = csv.writer(f)
+        out_csv.writerow([student,datetime.now().date(),answered,assessment])
+
+

flask_app/static/main.css

@@ -0,0 +1,25 @@
+body {
+  background: Linen;
+  margin-top: 50px;
+  margin-left: 100px;
+	margin-right: 100px;
+	font-family: Georgia, serif;
+  color: DarkSlateGray;
+	font-size: 1.3em;
+  }
+
+p {
+  font-family: Georgia, serif;
+  font-size: 1em;
+  color: DarkSlateGray;
+  }
+
+h1 {
+  font-family: Verdana, Geneva, sans-serif;
+  font-size: 2.5em;
+  color: FireBrick;
+  }
+
+.rand-button {
+	font-size: .8em;
+}

flask_app/static/process_button.js

@@ -0,0 +1,23 @@
+$(document).ready(function() {
+   $('#goodButton, #badButton, #neutralButton, #absentButton, #nextButton').on('click', function() {
+       var studentName = $('#studentName').text();
+       console.log(studentName);
+       var buttonValue = $(this).val();
+       var courseCode = window.location.pathname.split('/').pop();
+       $.ajax({
+           url: '/response_quality',
+           type: 'POST',
+           data: {
+              studentName: studentName,
+              buttonValue: buttonValue,
+              course: courseCode
+           },
+           success: function(response) {
+              $('#studentName').text(response);
+           },
+           error: function(error) {
+              console.log(error);
+           }
+       });
+   });
+});

flask_app/templates/cold_caller.html

@@ -0,0 +1,41 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Random Student Picker</title>
+    <link rel="stylesheet" href='/static/main.css' />
+    <script src="https://code.jquery.com/jquery-3.5.1.min.js"></script>
+  <script src="{{ url_for('static', filename='process_button.js') }}"></script>
+</head>
+<body>
+<h3>
+The next student is:
+</h3>
+
+<h2 id='studentName' name='studentName'>{{student}}</h2>
+
+
+{% if student != '' %}
+
+
+  {% if public is none %}
+<button class='assessment' id="goodButton" value="G">Good</button>
+<button class='assessment' id="badButton" value="B">Bad</button>
+<button class='assessment' id="neutralButton" value="M">Neutral</button>
+<button class='assessment' id="absentButton" value="absent">Absent</button>
+<button class='assessment' id="nextButton" value="get_next">Skip</button>
+
+
+  {% else %}
+<button class='assessment' id="neutralButton" value="?">Next Student</button>
+<button class='assessment' id="absentButton" value="absent">Absent</button>
+  {% endif %}
+
+{% else %}
+<form method="post" id="todo-form">
+        <button class='rand-button' type="submit">Get random student</button>
+
+</form>
+{% endif %}
+
+</body>
+</html>

flask_app/templates/group_maker.html

@@ -0,0 +1,25 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Random Student Picker</title>
+    <link rel="stylesheet" href='/static/main.css' />
+</head>
+<body>
+<h3>
+  Groups:
+</h3>
+
+{% for group in result %}
+<h2>Group {{group[0]}}</h2>
+
+<ul>
+  {% for member in group[1] %}
+  <li> {{member}} </li>
+  {% endfor %}
+</ul>
+
+{% endfor %}
+
+
+</body>
+</html>

flask_app/templates/shuffler.html

@@ -0,0 +1,19 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Shuffled List</title>
+    <link rel="stylesheet" href='/static/main.css' />
+</head>
+<body>
+<h3>
+  Shuffled List:
+</h3>
+
+<ul>
+  {% for member in result %}
+  <li> {{member}} </li>
+  {% endfor %}
+</ul>
+
+</body>
+</html>

flask_app/test.csv

@@ -0,0 +1,71 @@
+name,date,answered,assessment
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,
+owen,2022-01-01,,
+dad,2022-01-01,,
+dad,2022-01-01,,