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<?php

namespace App\Http\Middleware;

use Closure;

class SetLanguage
{
    /**
     * Handle an incoming request.

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function setLanguage(){
  // set the app locale
	App::setLocale( session('locale') ? session('locale') : config('app.locale'));
	
  // set PHP locale for formatting dates
  if(App::getLocale() == 'fr')
		setlocale(LC_TIME, 'fr_CH.UTF-8');
}

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function getMetaData($type){
    // set a default so it doesn't break phpunit
    if(isset($_SERVER['REQUEST_URI']))
        $page = $_SERVER['REQUEST_URI'];
    else
        $page = "/";
    
    // if we are looking at a blog article just use the default for the main blog page 
    if(strpos($page, 'blog') !== false) {
        $page = '/blog';

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return [
    'default-title' => 'Default page title',
    'default-description' => 'My whatever whatever web site default description text',

    '/termsandconditions-title' => 'Terms and Conditions',
    '/termsandconditions-description' => 'Terms and conditions for the website',

    '/privacypolicy-title' => 'Privacy Policy',
    '/privacypolicy-description' => 'Privacy policy for the website',
];

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<?php

namespace App\Console\Commands;

use Illuminate\Console\Command;
use Aws\Laravel\AwsFacade as AWS;

class BackupDB extends Command
{
    /**

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function unaccent($string)
{
    return preg_replace('~&([a-z]{1,2})(?:acute|cedil|circ|grave|lig|orn|ring|slash|th|tilde|uml|caron);~i', '$1', htmlentities($string, ENT_COMPAT, 'UTF-8'));
}

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DELETE n1 FROM names n1, names n2 WHERE n1.id > n2.id AND n1.name = n2.name

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# For two dataframes X1 and X2, sync columns in X2 to be same as X1 in same order.
missing_cols = set( X1.columns ) - set( X2.columns )
for c in missing_cols:
    X2[c] = 0
X2 = X2[X1.columns]

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# this works just like "unlist" in R
def flatten(l):
  out = []
  for item in l:
    if isinstance(item, (list, tuple)):
        out.extend(flatten(item))
    else:
        out.append(item)
  return out

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# mean encoding
means = X_tr.groupby(col).target.mean()

train_new[col+'_target_mean'] = train_new[col].map(means)
val_new[col+'_target_mean'] = val_new[col].map(means)