Archive

───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ Kz Smarje HRM             │ kz-smarje-hrm                  │ 260270846570   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ Limbo documents module    │ limbo-documents-module         │ 198384766242   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ limbo-haccp               │ limbo-haccp                    │ 311937966378   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ Limbo HRM PRODUCTION      │ limbo-hrm-prod                 │ 283822716235   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ Limbo HRM STAGING         │ limbo-hrm-stg                  │ 22611514900    │ europe-west          │

/**
 * Definition for singly-linked list.
 * struct ListNode {
 *     int val;
 *     ListNode *next;
 *     ListNode() : val(0), next(nullptr) {}
 *     ListNode(int x) : val(x), next(nullptr) {}
 *     ListNode(int x, ListNode *next) : val(x), next(next) {}
 * };
 */

┌───────────────────────────┬────────────────────────────────┬────────────────┬──────────────────────┐
│ Project Display Name      │ Project ID                     │ Project Number │ Resource Location ID │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ adam                      │ adam-7e838                     │ 24145074895    │ [Not specified]      │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ airbagauto-epolypus       │ airbagauto-epolypus            │ 136372231850   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ airbagauto-epolypus-stg   │ airbagauto-epolypus-stg        │ 229684269511   │ europe-west          │
├───────────────────────────┼────────────────────────────────┼────────────────┼──────────────────────┤
│ Aram                      │ aram-epopylus                  │ 438088348753   │ europe-west          │

# Initialize a dictionary
my_dict = {
        "name": "Ram",
            "age": 25,
                "city": "Bellary",
                    "profession": "Engineer"
}

# 1. Accessing values using [] (key)
def access_by_key(my_dict, key):

from collections import deque

def bfs_path(grid, start, goal):
 rows, cols = len(grid), len(grid[0])
 queue = deque([start])
 parent = {start: None}
 moves = [(-1, 0), (1, 0), (0, -1), (0, 1)] # up, down, left, right
    
 while queue:
     r, c = queue.popleft()

11:19:38 ERROR]: Thread infinity-metrics failed main thread check: Chunk getEntities call
java.lang.Throwable: null
        at org.spigotmc.AsyncCatcher.catchOp(AsyncCatcher.java:14) ~[energy-1.20.4.jar:git-Energy-"236b63c"]
        at net.minecraft.server.level.ServerLevel.getEntities(ServerLevel.java:2856) ~[?:?]
        at org.bukkit.craftbukkit.v1_20_R3.CraftWorld.getEntityCount(CraftWorld.java:172) ~[energy-1.20.4.jar:git-Energy-"236b63c"]
        at jdk.internal.reflect.DirectMethodHandleAccessor.invoke(DirectMethodHandleAccessor.java:103) ~[?:?]
        at java.lang.reflect.Method.invoke(Method.java:580) ~[?:?]
        at com.infinity.xp.XpMetrics.call(XpMetrics.java:329) ~[app:?]
        at com.infinity.xp.XpMetrics.intCall(XpMetrics.java:333) ~[app:?]
        at com.infinity.xp.XpMetrics.bukkit(XpMetrics.java:205) ~[app:?]

class Car:
    def __init__(self, make, model, year, km):
        self.make = make
        self.model = model
        self.year = year
        self.year = year
        self.km = km
        self.status = True

    def set_km(self, new_km):

include <stdio.h>

int isEven(int n) {
        if (n % 2 == 0)
                return 1;
                    else
                            return 0;
}

int main() {

from tensorflow.keras.applications import VGG16
from tensorflow.keras import layers, models
from tensorflow.keras.datasets import cifar10
import tensorflow as tf
(X_train, y_train), (X_test, y_test) = cifar10.load_data()
X_train = tf.image.resize(X_train, (96,96)) / 255.0
X_test = tf.image.resize(X_test, (96,96)) / 255.0
base_model = VGG16(weights='imagenet', include_top=False, input_shape=(96,96,3))
base_model.trainable = False # Freeze pre-trained layers
model = models.Sequential([

import pandas as pd
import numpy as np


df = pd.read_csv("iris.csv")

df = df[df["variety"].isin(["Setosa", "Versicolor"])]


X = df[

        document.addEventListener('DOMContentLoaded', function () {
            var editModal = document.getElementById("edit-modal");
            var closeEditBtn = document.querySelector(".close-edit");

            // Open Bewerken Modal
            document.querySelectorAll('.edit-url-btn').forEach(button => {
                button.addEventListener('click', function () {
                    const listItem = this.closest('li');
                    document.getElementById('edit-url-id').value = listItem.dataset.id;
                    document.getElementById('edit-url').value = listItem.querySelector('.url-address').textContent;

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report

# Load dataset
df = pd.read_csv("iris.csv")

# Select only two classes
df = df[df["variety"].isin(["Setosa", "Versicolor"])]