Skip to main content

Wp All Import Function Editor

I'm trying to import a csv file with wp all import set specific functions to set the sale price and the offer price. Now I would need to call the function that forms the regular price, inside the function of the offer price, to work on the result and maybe apply a percentage discount.

<?php

$GLOBALS['$commissione_paypal_lm'] = 4;
$GLOBALS['$spese_spedizione_moto_lm'] = 10;
$GLOBALS['$spese_spedizione_autocarro_lm'] = 10;
$GLOBALS['$spese_spedizione_varie_lm'] = 7;
$GLOBALS['$pfu_moto_lm'] = 1.50;
$GLOBALS['$pfu_autocarro_lm'] = 4.90;
$GLOBALS['$pfu_varie_lm'] = 2.90;
// First function for regular price,i take variables from csv and global variables
function prezzo_finale( $price = null, $pfu = null, $diametro = null ) {
    if ( !empty( $price ) ) {
        // strip any extra characters from price
        $price = preg_replace("/[^0-9,.]/", "", $price);
        $pfu = preg_replace("/[^0-9,.]/", "", $pfu);
        
        //price ommas and dots fix
        $price = str_replace(",",".",str_replace(".","",$price));
        $pfu = str_replace(",",".",str_replace(".","",$pfu));
        
        // calculate percentage
        $percent = 0;
        if ($diametro != '') {
            $term = term_exists( $diametro, 'pa_diametro', 0 ); 
            if ( $term !== 0 && $term !== null ) { 
                $percent = get_field('percentage', 'pa_diametro_' . $term["term_id"]);
            }
        }
        
        // final price
        $prezzo_finale = $price;
        if (empty( $percent ) ) {
            // Se il campo percentuale ĆØ vuoto metto 20% automatico
            $prezzo_appoggio_finale = round((($prezzo_finale + round($prezzo_finale * (20 / 100), 2) + $pfu ) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale = ($prezzo_finale + round($prezzo_finale * (20 / 100), 2) + $pfu + $prezzo_appoggio_finale);
        }else if ($percent > 0){
            $prezzo_appoggio_finale = round((($prezzo_finale + round($prezzo_finale * ($percent / 100), 2) + $pfu ) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale = ($prezzo_finale + round($prezzo_finale * ($percent / 100), 2) + $pfu + $prezzo_appoggio_finale);
        }else{
            // Se il campo percentuale ĆØ inferiore uguale a zero metto 20% automatico
            $prezzo_appoggio_finale = round((($prezzo_finale + round($prezzo_finale * (20 / 100), 2) + $pfu ) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale = ($prezzo_finale + round($prezzo_finale * (20 / 100), 2) + $pfu + $prezzo_appoggio_finale);
        }

        // perform calculations
        return $prezzo_finale; 
    }
}
function prezzo_finale_lm( $fifo_ponderato = null, $diametro = null, $settori_codice= null ) {
    if ( !empty( $fifo_ponderato ) ) {
        // strip any extra characters from price
        $fifo_ponderato = preg_replace("/[^0-9,.]/", "", $fifo_ponderato);
        
        //price ommas and dots fix
        $fifo_ponderato = str_replace(",",".",str_replace(".","",$fifo_ponderato));
        
        // calculate percentage
        $percent = 0;
        if ($diametro != '') {
            $term = term_exists( $diametro, 'pa_diametro', 0 ); 
            if ( $term !== 0 && $term !== null ) { 
                $percent = get_field('percentage', 'pa_diametro_' . $term["term_id"]);
            }
        }
        
        // final price
        // moto = 10; vettura 8; isole extra valutare; paypal 3%;
        $prezzo_finale_lm = ($fifo_ponderato);
        if ($settori_codice === 'MOTO' || $settori_codice === 'SCOOTER' || $settori_codice === 'CICLOMOTORI'){
        $spese_spedizione = $GLOBALS['$spese_spedizione_moto_lm'];
        $pfu = $GLOBALS['$pfu_moto_lm'];
        }else if ($settori_codice === 'AUTOCARRO'){
        $spese_spedizione = $GLOBALS['$spese_spedizione_autocarro_lm'];
        $pfu = $GLOBALS['$pfu_autocarro_lm'];
        }else{
        $spese_spedizione = $GLOBALS['$spese_spedizione_varie_lm'];
        $pfu = $GLOBALS['$pfu_varie_lm'];
        }       
        if (empty( $percent ) ) {
            // Se il campo percentuale ĆØ vuoto metto 20% automatico
            $prezzo_appoggio_lm = round((($prezzo_finale_lm + round($prezzo_finale_lm * (20 / 100), 2) + $pfu + $spese_spedizione) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale_lm_paypal = ($prezzo_finale_lm + round($prezzo_finale_lm * (20 / 100), 2) + $pfu + $spese_spedizione + $prezzo_appoggio_lm);
        }else if ($percent > 0){            
            $prezzo_appoggio_lm = round((($prezzo_finale_lm + round($prezzo_finale_lm * ($percent / 100), 2) + $pfu + $spese_spedizione) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale_lm_paypal = ($prezzo_finale_lm + round($prezzo_finale_lm * ($percent / 100), 2) + $pfu + $spese_spedizione + $prezzo_appoggio_lm);
        }else{
            // Se il campo percentuale ĆØ inferiore uguale a zero metto 20% automatico
            $prezzo_appoggio_lm = round((($prezzo_finale_lm + round($prezzo_finale_lm * (20 / 100), 2) + $pfu + $spese_spedizione) * $GLOBALS['$commissione_paypal_lm'])/100,2) ;
            $prezzo_finale_lm_paypal = ($prezzo_finale_lm + round($prezzo_finale_lm * (20 / 100), 2) + $pfu + $spese_spedizione + $prezzo_appoggio_lm);
        }

        // perform calculations
        return $prezzo_finale_lm_paypal; 
                
    }
}
    // Second function for offer price,i would take regular price and work with
function prezzo_offerta_lm() {

        if (prezzo_finale_lm()){
        return prezzo_finale_lm();
        // and for example apply discount as global variable
        }else{
        
        }

        // perform calculations
        
}
?>

This is shortcode i use for regular price:

[prezzo_finale_lm({fifo_ponderato[1]},{diametro[1]},{settori_codice[1]})]

Thank you all for any advice.



source https://stackoverflow.com/questions/69003644/wp-all-import-function-editor

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...