Skip to main content

PHP Inheretence of methods through multiple layers of classes

I have code that when heavily boiled down, looks pretty much like this:

abstract class Car {
    public abstract static function parts();
    protected static function getParts() {
        $parts = [];
        $properties = (new ReflectionClass(static::class))->getProperties();
        foreach ($properties as $property) {
            $parts[] = $property->getName();
        }
        return $parts;
    }
}
class Ford extends car {
    public $wheels;
    public $body;
    public static function parts() {
        return self::getParts();
    }
}
class FordTruck extends Ford {
    public $truckBed;
}

function getBaseParts($cartype) {
    return $cartype::parts();
}

But when I call getBaseParts("FordTruck") I get back

array(3) {
  [0]=>
  string(8) "truckBed"
  [1]=>
  string(6) "wheels"
  [2]=>
  string(4) "body"
}

In reality, I only want back "wheels" and "body", not the 'extraneous' stuff that's added in classes past Ford. I thought that creating a parts() method in the class whose parts I care about, that then calls self::getParts(), which in turn gets the properties from static would mean that the class that 'static' is referring to would be the Ford class. But it's more like it's calling parts() from the FordTruck class.

Is there a way I can get the functionality I'm looking for with this setup? The 'easiest' way I can think of would be moving the 'getParts()' method into the Ford class and have it call a reflectionclass of self, but I have dozens of classes that extend Ford that would all just be copied code if I fixed it that way.



source https://stackoverflow.com/questions/68154072/php-inheretence-of-methods-through-multiple-layers-of-classes

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...