Skip to main content

PHP Fatal error: Uncaught Error: Class 'FPDF' not found in

I am working to implement the artkonekt/pdf-invoice project from GitHub.

I used the normal composer require konekt/pdf-invoice install method as specified in the readme.md file--and everything installed without any errors.

When I simply try to view the provided example file /vendor/konekt/pdf-invoice/examples/example1.php, the browser gives back an "HTTP ERROR 500" and the Apache2 error.log file includes the entry:

[Thu Sep 30 11:02:40.813756 2021] [php7:error] [pid 26112] [client 72.36.41.73:55343] PHP Fatal error:  Uncaught Error: Class 'FPDF' not found in /var/www/html/generate/vendor/konekt/pdf-invoice/src/Invoi
cePrinter.php:18\nStack trace:\n#0 /var/www/html/generate/vendor/konekt/pdf-invoice/examples/example1.php(5): include()\n#1 {main}\n  thrown in /var/www/html/generate/vendor/ko
nekt/pdf-invoice/src/InvoicePrinter.php on line 18

Other than the attribution credits at the top of InvoicePrinter.php, the next few lines are:

namespace Konekt\PdfInvoice;

use FPDF;

class InvoicePrinter extends FPDF
{

Line 18 is the class InvoicePrinter extends FPDF one.

The composer.json file contains:

{
    "require": {
        "konekt/pdf-invoice": "^1.10",
        "setasign/fpdf": "^1.8.4"
    }
}

and the setassign/fpdf directory is present and contains the fpdf.php file as one would expect.

Thus, how can the FPDF class be missing when it is both explicitly defined and verified as being present where composer expects?

I have tried running composer install && composer update && composer dump-autoload --optimize just to make sure...

Would someone point me in the right direction? I would have reported this as an issue in GitHub, but the repo owner has disabled issues. Thank you in advance for any assistance!



source https://stackoverflow.com/questions/69396475/php-fatal-error-uncaught-error-class-fpdf-not-found-in

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...