Skip to main content

Javascript / React - Question about .focus() behaviour

I've just created a small search bar component that appears/disappear when clicking on an icon. It hides and shows (changes opacity and width) with a nice animation based on if the input is focused or not.

Here is the code that works perfectly:

const SearchBar = () => {
  const inputRef = useRef();
  const [isSearchBarOpen, setIsSearchBarOpen] = useState(false);

  const handleClick = () => {
    if (!isSearchBarOpen) {
      setIsSearchBarOpen(true);
      inputRef.current.focus();
    } else {
      inputRef.current.blur();
      setIsSearchBarOpen(false);
    }
  };

  return (
    <div className="search-container">
      <input
        type="text"
        placeholder="Search content"
        className="searchbar-input"
        ref={inputRef}
      />
      <BiSearch
        className="search-icon"
        size="2.5rem"
        color="#fff"
        onClick={handleClick}
      />
    </div>
  );
};

However when building it, I noticed a few things. The following code doesn't work (the search bar only shrinks when pressing the icon but as soon as it's not pressed anymore the input is focused again):

if (inputRef.current.focus()) {
  inputRef.current.blur();
} else {
  inputRef.current.focus();
}

Other weird reaction, I noticed that the exact same thing happen when I just insert .focus() in a if statement.

if (!inputRef.current.focus()) console.log('I dont know whats happening');

The line of code above also triggers an input focus when clicking on the icon.

Could someone just explain me what happens under the hood? Why is .focus called no matter what? And is there a better way/practice to toggle focus while clicking on the same button than my code that works?

Via Active questions tagged javascript - Stack Overflow https://ift.tt/PVhpB7t06

Comments

Popular posts from this blog

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...

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...