Skip to main content

How can I get bookmarked hash links to work with a jQuery change function?

What's the simplest way with this jQuery change function to enable bookmarked hash links to work, i.e to be able to use example.com/#theme1 or example.com/#theme2 links?

The jQuery #theme-selector changes the hash and shows/hides the relevant divs with the class, i.e. .theme1 or .theme2, but when going to example.com/#theme1 from a bookmarked link, all divs are shown.

In addition, if I refresh example.com/#theme1, the hash remains #theme1, but all divs are shown.

Some other questions on SO deal with bookmarkable hashes, but they're many years old. And some libraries that appear useful are ten years old, too, like https://github.com/asual/jquery-address

Unfortunately, running the snippet here won't show browser hash changes, nor will JSFiddle.

Any ideas?

  jQuery(document).ready(function(jQuery){
    
        jQuery("#theme-selector").change(function () {
    
        var urlhash = document.getElementById('theme-selector').value;
    
        window.location.hash = urlhash;
    
    });
    
    
    jQuery("#theme-selector").change(function () {
    
    themeclass = window.location.hash.substr(1);
    
    jQuery('.blockcontent').hide();
    jQuery('.' +themeclass).show();
    jQuery('.theme-header').hide();
    jQuery('.' +themeclass).show();
    
        });
    
    });
 .blockcontent {
    display:inline-block;
    width:150px;
    border:1px solid #acacac;
    }
    
    .theme-header {
    display:none;
    }
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>

 <label for="theme-selector">Filter by Theme:</label>
    
    <select name="theme-selector" id="theme-selector" value="">
    
    <option value="all-themes">All Themes</option>
    <option value="theme1">Theme 1</option>
    <option value="theme2">Theme 2</option>
    <option value="theme3">Theme 3</option>
    
    </select>
    
    <br>
    
    <div id="theme-description-container">
    <div class="theme1 theme-header">Theme 1 Description</div>
    <div class="theme2 theme-header">Theme 2 Description</div>
    <div class="theme3 theme-header">Theme 3 Description</div>
    </div>
   
    <br>
    
    <div class="blockcontent all-themes theme1">
    theme1<br><br>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do 
    </div>
    
    <div class="blockcontent all-themes theme2">
    theme2<br><br>sed do eiusmod tempor incididunt sed do eiusmod eiusmod
    </div>
    
    <div class="blockcontent all-themes theme3 theme2">
    theme2 and theme3<br><br>consectetur adipiscing elit,consect adipiscing elit, 
    </div>
    
    <div class="blockcontent all-themes theme3">
    theme3<br><br>consectetur adipiscing elit,consect etur adipiscing elit, 
    </div>
Via Active questions tagged javascript - Stack Overflow https://ift.tt/kdCn58I

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...