add mccs scripts
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>CSV Filterer</title>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/PapaParse/5.3.0/papaparse.min.js"></script>
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<script src="./CSVFilterer.js"></script>
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</head>
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<body>
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<h1>CSV Filterer</h1>
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<label for="ueFileInput">UserEnrollments.csv:</label>
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<input type="file" id="ueFileInput" accept=".csv">
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<button onclick="filterEnrollments(document)">Filter Enrollments</button>
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<br />
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<label for="usersFileInput">Users.csv:</label>
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<input type="file" id="usersFileInput" accept=".csv">
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<button onclick="parseUsers(document.getElementById('usersFileInput'), document)">Parse Users</button>
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<br />
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<button onclick="refreshStatus(document)">Refresh Status</button>
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<p>Status: <span id="status">Unknown</span></p>
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<a id="downloadLink" style="display:none;">Download Filtered CSV</a>
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</body>
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</html>
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class UserData {
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constructor(dataRow) {
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this.userId = dataRow[0];
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this.uName = dataRow[1];
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this.fName = dataRow[3];
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this.sName = dataRow[5];
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}
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}
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class EnrollmentData {
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constructor(dataRow) {
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this.orgUnitId = dataRow[0];
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this.userId = dataRow[1];
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this.roleName = dataRow[2];
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this.timestamp = dataRow[3];
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this.roleId = dataRow[5];
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this.fName = "N/A";
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this.sName = "N/A";
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this.uName = "N/A";
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}
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}
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// Create empty Maps to store the filtered enrollment data and user info in
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// These will be cross checked later to generate the list of all instructors
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const users = new Map();
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const enrollments = new Map();
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let states = {
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enrollments: "Unfiltered",
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users: "Unparsed"
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}
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function filterEnrollments(document) {
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let fileInput = document.getElementById('ueFileInput');
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let filterValue = "KV Instructor";
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document.getElementById('downloadLink')
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if (!fileInput.files.length) {
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alert('Please select a CSV file.');
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return;
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}
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const file = fileInput.files[0];
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Papa.parse(file, {
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complete: function(results) {
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// Iterate over the entire data set
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results.data.forEach(row => {
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// Create an EnrollmentData object with it:
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const enrollmentData = new EnrollmentData(row);
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// If the row contains the filter string and is not in the 'seen' Set
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if (row.some(cell => cell.includes(filterValue)) && !enrollments.has(enrollmentData.userId)) {
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// Add it to the data array
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enrollments.set(enrollmentData.userId, enrollmentData);
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}
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});
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states.enrollments = "Filtered";
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refreshStatus(document);
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},
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error: function(error) {
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console.error(error);
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alert('An error occurred while processing the file.');
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}
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});
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}
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const parseUsers = (usersFileInputs, document) => {
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if (!usersFileInputs.files.length) {
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alert('Please select a CSV file.');
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return;
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}
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const usersFile = usersFileInputs.files[0];
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Papa.parse(usersFile, {
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complete: function(results) {
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// Iterate over the entire data set
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results.data.forEach(row => {
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// Create an object with it:
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const userData = new UserData(row);
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// Add it to the data array
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users.set(userData.userId, userData);
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});
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states.users = "Parsed";
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refreshStatus(document);
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generateList(document);
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},
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error: function(error) {
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console.error(error);
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alert('An error occurred while processing the Users.csv file.');
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}
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});
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}
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const generateList = (document) => {
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const preCSV = [
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"UserId,Timestamp,FirstName,LastName,Username"
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];
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enrollments.forEach(e => {
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// Get the associated user
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const user = users.get(e.userId);
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preCSV.push(`${user.userId},${e.timestamp}.${user.fName},${user.sName},${user.uName}`);
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});
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generateCSV(preCSV, document);
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}
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const generateCSV = (input, document) => {
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const downloadLink = document.getElementById("downloadLink");
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const csv = Papa.unparse(input);
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const blob = new Blob([csv], { type: 'text/csv' });
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const url = URL.createObjectURL(blob);
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downloadLink.href = url;
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downloadLink.download = 'filtered.csv';
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downloadLink.style.display = 'block';
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downloadLink.textContent = 'Download Filtered CSV';
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}
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function refreshStatus(document) {
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let statusSpan = document.getElementById('status')
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let statusString = `Enrollments: ${states.enrollments} | Users: ${states.users}`;
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statusSpan.innerHTML = statusString;
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}
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# coding=utf-8
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from selenium import webdriver
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from selenium.webdriver.common.keys import Keys
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from selenium.webdriver.common.by import By
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from selenium.webdriver.common.alert import Alert
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import time
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import getpass
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# Put
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studentIds = [
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"5121951",
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"5010522",
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"5137363",
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"5145175",
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"5144503",
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"5146582",
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"5142212",
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"5146605",
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"5109465",
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"5146602",
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"5146608",
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"5146598",
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"5127204",
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"5142694",
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"5123415",
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"5146588",
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"5146589",
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"5146600",
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"5146581",
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"5146506",
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"5146609",
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"5146607",
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"5146601",
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"5131148",
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"5107200",
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"5133891",
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"5005257",
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"5146590",
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"5135862",
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"5146599",
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"5146586",
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"5146552",
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"5146308",
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"5136688",
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"5126696",
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]
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class StudentInfo:
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def __init__(self, name, id, auth_method, ad_ou):
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self.name = name
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self.id = id
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self.auth_method = auth_method
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self.ad_ou = ad_ou
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driver = webdriver.Firefox()
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def login():
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username = input("MyKV Username: ")
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password = getpass.getpass(prompt="MyKV Password: ", stream=None)
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driver.get("https://my.kvcc.me.edu/ics/")
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time.sleep(1)
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driver.find_element(By.ID, "userName").send_keys(username)
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driver.find_element(By.ID, "password").send_keys(password)
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driver.find_element(By.ID, "siteNavBar_welcomeBackBarLoggedOut_ButtonLogin").click()
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time.sleep(1)
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def navToLookup():
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driver.get("https://my.kvcc.me.edu/ICS/IT_Admin/Help_Desk_Apps/")
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time.sleep(1)
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driver.find_element(By.ID, "pg0_V_lnkToMainView").click()
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time.sleep(1)
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def navToStudentInfo(id):
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driver.get("https://my.kvcc.me.edu/jicspages/It_Utilities/Helpdesk/HelpDesk_Main.aspx?1=" + id + "&2=@@UserName&3=" + id)
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def getStudentInfo():
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stu_name = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[4]/td[1]").text
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stu_id = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[4]/td[2]").text
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# auth_text = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[5]/td[3]").text
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auth_method = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[6]/td[1]").text
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# ad_text = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[7]/td[2]").text
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ad_ou = driver.find_element(By.XPATH, "//html/body/form/div/table/tbody/tr/td/span/table/tbody/tr[8]/td[3]").text
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info = StudentInfo(stu_name, stu_id, auth_method, ad_ou)
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combined = stu_name + " (" + stu_id + ")\nAD OU: "+ ad_ou + "\nAuthentication: " + auth_method
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print(combined)
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return info
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def resetPassword(info):
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# TODO
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driver.get("https://my.kvcc.me.edu/jicspages/It_Utilities/Helpdesk/HelpDesk_Main.aspx?1=" + info.id + "&2=@@UserName&3=" + info.id + "&4=3")
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alert = Alert(driver)
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print(alert.text)
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alert.accept()
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time.sleep(1)
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driver.get("https://my.kvcc.me.edu/jicspages/It_Utilities/Helpdesk/HelpDesk_Main.aspx?1=" + info.id + "&2=@@UserName&3=" + info.id)
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print("Password reset.")
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def createADAcct(info):
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driver.get("https://my.kvcc.me.edu/jicspages/It_Utilities/Helpdesk/HelpDesk_Main.aspx?1=" + info.id + "&2=@@UserName&3=" + info.id + "&4=2")
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alert = Alert(driver)
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print(alert.text)
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alert.accept()
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time.sleep(1)
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driver.get("https://my.kvcc.me.edu/jicspages/It_Utilities/Helpdesk/HelpDesk_Main.aspx?1=" + info.id + "&2=@@UserName&3=" + info.id)
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def checkStudentInfo(info):
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if info.auth_method == "Portal Only":
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print("No AD authentication, only resetting password.")
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resetPassword(info)
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elif info.auth_method == "Active Directory":
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if info.ad_ou != "":
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print("AD authentication set up, with an already existing account, only resetting password.")
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resetPassword(info)
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else:
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print("AD authentication set up, without an AD account. Creating account then resetting password.")
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resetPassword(info)
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else:
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print("Unable to determine authentication method. Please complete this manually.")
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login()
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for id in studentIds:
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navToStudentInfo(id)
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studentInfo = getStudentInfo()
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checkStudentInfo(studentInfo)
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# Filters Brightspace's DataHub's UserEnrollments.csv file for a single college
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# Install Python on Windows from Powershell by running `python` with no arguments
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# pip install pandas
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import pandas as pd
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# Variables
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college = 'KV'
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ue_input_file = '.\\data\\UserEnrollments.csv'
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ue_output_file = '.\\data\\UEFiltered' + college + '.csv'
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ue_field_name = 'RoleName'
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ue_filter_value = college + ' Instructor'
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users_input_file = '.\\data\\Users.csv'
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users_output_file = '.\\data\\UsersFiltered' + college + '.csv'
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users_field_name = 'UserName'
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users_filter_value = "KV_"
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def filter_csv(input_file, output_file, field_name, filter_value):
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# Read the CSV file
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df = pd.read_csv(input_file)
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# Filter the DataFrame based on the field value
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filtered_df = df[df[field_name].str.contains(filter_value, na=False)]
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# Export the filtered DataFrame to a new CSV file
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filtered_df.to_csv(output_file, index=False)
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filter_csv(ue_input_file, ue_output_file, ue_field_name, ue_filter_value)
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filter_csv(users_input_file, users_output_file, users_field_name, users_filter_value)
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