point form

erDiagram
    InvoiceLineItem {
        int InvoiceLineNumber
        varchar Supplier_root_id
        varchar Part_root_Id
        varchar UNSPSC_root_Id
        decimal POAmount_Amount
        varchar SourceSystem
    }
    
    Part {
        varchar RootId
        int product_id
    }

    Supplier {
        varchar RootId
        int SupplierId
        varchar SupplierName
    }

    UNSPSC {
        varchar RootId
        varchar CategoryL3
    }

    EmissionBySupplier {
        int SFM_ID
        int Product_id
        int Supplier_id
    }

    InvoiceLineItem ||--|| Part: "Part_root_Id = RootId"
    InvoiceLineItem ||--|| Supplier: "Supplier_root_id = RootId"
    InvoiceLineItem ||--|| UNSPSC: "UNSPSC_root_Id = RootId"
    Part ||--|| EmissionBySupplier: "product_id = Product_id"
    Supplier ||--|| EmissionBySupplier: "SupplierId = Supplier_id"

extends CharacterBody3D

@export var speed : float = 6.0
@export var jump_velocity : float = 8.0
@export var look_sensitivity : float = 0.001

@onready var camera : Camera3D = $Camera3D
@onready var head : Node3D = $Head
@onready var pivot : Node3D = $Head/Pivot
@onready var collision_shape = $CollisionShape3D


var gravity : float = ProjectSettings.get_setting("physics/3d/default_gravity")*2
var velocity_y : float = 0
var update : bool = false
var gt_prev : Transform3D
var gt_current : Transform3D
var mesh_gt_prev : Transform3D
var mesh_gt_current : Transform3D

var obstacles : Array
var is_climbing : bool = false

func _ready():
	# Camera set up to prevent jitter.
	camera_setup()
	
	Input.mouse_mode = Input.MOUSE_MODE_CAPTURED 
	
func _input(event):
	# Mouse movement.
	if event is InputEventMouseMotion:
		rotate_y(-event.relative.x * look_sensitivity)
		
		head.rotate_x(-event.relative.y * look_sensitivity)
		
		head.rotation.x = clamp(head.rotation.x, -PI/2, PI/2)
		
# In-process func set up for preventing jitter.
func _process(delta):
	if update:
		update_transform()
		
		update = false
		
	var f = clamp(Engine.get_physics_interpolation_fraction(), 0 ,1)
	
	camera.global_transform = gt_prev.interpolate_with(gt_current, f)
	
func _physics_process(delta):
	update = true
	# Basic movement.
	var horizontal_velocity = Input.get_vector("left", "right", "forward", "backward").normalized() * speed
	
	velocity = horizontal_velocity.x * global_transform.basis.x + horizontal_velocity.y * global_transform.basis.z
	
	# Checking if the player is on the floor or climbing.
	if not is_on_floor() and not is_climbing:    
		velocity_y -= gravity * delta
		
	else:
		velocity_y = 0
		
	# Jump.
	if Input.is_action_just_pressed("jump") and is_on_floor():
		velocity_y = jump_velocity 
		
	# Vaulting with place_to_land detection and animation.
	vaulting(delta)
	
	velocity.y = velocity_y
	move_and_slide()
	
# Camera set up to prevent jitter.
func camera_setup():
	camera.set_as_top_level(true)
	
	camera.global_transform = pivot.global_transform
	
	gt_prev = pivot.global_transform
	
	gt_current = pivot.global_transform
	
# Updating transform to interpolate the camera's movement for smoothness. 
func update_transform():
	gt_prev = gt_current
	
	gt_current = pivot.global_transform
	
# Creating RayCast via code.
func raycast(from: Vector3, to: Vector3):
	var space = get_world_3d().direct_space_state
	
	var query = PhysicsRayQueryParameters3D.create(from, to, 2)
	
	query.collide_with_areas = true
	
	return space.intersect_ray(query)

# Calculating the place_to_land position and initiating the vault animation.
func vaulting(delta):
	if Input.is_action_just_pressed("jump"):
		# Player's RayCast to detect climbable areas.
		var start_hit = raycast(camera.transform.origin, camera.to_global(Vector3(0, 0, -1)))
		
		if start_hit and obstacles.is_empty():
			# RayCast to detect the perfect place to land. (Not that special, I just exaggerate :D)
			var place_to_land = raycast(start_hit.position + self.to_global(Vector3.FORWARD) * collision_shape.shape.radius + 
			(Vector3.UP * collision_shape.shape.height), Vector3.DOWN * (collision_shape.shape.height))
			
			if place_to_land:
				# Playing the animation
				vault_animation(place_to_land)

# Animation for vaulting/climbing.
func vault_animation(place_to_land):
	# Player is climbing. This variable prevents hiccups along the process of climbing.
	is_climbing = true
	
	# First Tween animation will make player move up.
	var vertical_climb = Vector3(global_transform.origin.x, place_to_land.position.y, global_transform.origin.z)
	# If your player controller's pivot is located in the middle use this: 
	# var vertical_climb = Vector3(global_transform.origin.x, (place_to_land.position.y + collision_shape.shape.height / 2), global_transform.origin.z)
	var vertical_tween = get_tree().create_tween().set_trans(Tween.TRANS_LINEAR).set_ease(Tween.EASE_IN)
	vertical_tween.tween_property(self, "global_transform:origin", vertical_climb, 0.4)
	
	# We wait for the animation to finish.
	await vertical_tween.finished
	
	# Second Tween animation will make the player move forward where the player is facing.
	var forward = global_transform.origin + (-self.basis.z * 1.2)
	var forward_tween = get_tree().create_tween().set_trans(Tween.TRANS_LINEAR).set_ease(Tween.EASE_IN_OUT)
	forward_tween.tween_property(self, "global_transform:origin", forward, 0.3)
	
	# We wait for the animation to finish.
	await forward_tween.finished
	
	# Player isn't climbing anymore.
	is_climbing = false

# Obstacle detection above the head.
func _on_obstacle_detector_body_entered(body):
	if body != self:
		obstacles.append(body)

func _on_obstacle_detector_body_exited(body):
	if body != self :
		obstacles.remove_at(obstacles.find(body))

0020-052F,2000-9FFF,AC00-D7AF,D7B0-D7FF,F900-FAFF,FF00-FFEF

 <form>
    <label>
      <input type="radio" name="question">
      Yes
    </label>
    <br>
    <label>
      <input type="radio" name="question">
      No
    </label>
  </form>

from pymongo import MongoClient, errors
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import statistics
import nltk
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
import string

mongo_uri = "mongodb://localhost:27017/"
database_name = "twitter_database"
collection_name = "tweet_cleaned"

client = MongoClient(mongo_uri, serverSelectionTimeoutMS=5000)
db = client[database_name]
collection = db[collection_name]
 
def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    compound_score = sentiment['compound']
    return compound_score

compound_scores = []
cursor = collection.find()
positive_count = 0
neutral_count = 0
negative_count = 0


for doc in cursor:
    lang = doc.get("json_data.lang")
    user_id = doc.get("json_data.user.id")
    user_mention = doc.get("json_data.entities.user_mentions.id")
    tweet_text = doc.get('json_data.text')
    full_text = doc.get('json_data.extended_tweet.full_text')
    
    if lang == 'en' :
        if full_text:
            if (user_id == 56377143) or (user_mention == 56377143) or ('KLM' in full_text) or ('klm' in full_text):
                sentiment = analyze_sentiment(full_text)
                compound_scores.append(sentiment)
                if sentiment >= 0.05:
                    positive_count += 1
                elif sentiment <= -0.05:
                    negative_count += 1
                else:
                    neutral_count += 1
        elif tweet_text:
            if (user_id == 56377143) or (user_mention == 56377143) or ('KLM' in tweet_text) or ('klm' in tweet_text):
                sentiment = analyze_sentiment(tweet_text)
                compound_scores.append(sentiment)
                if sentiment >= 0.05:
                    positive_count += 1
                elif sentiment <= -0.05:
                    negative_count += 1
                else:
                    neutral_count += 1
mean_score = statistics.mean(compound_scores)
print("Positive:", positive_count)
print("Neutral:", neutral_count)
print("Negative:", negative_count)
print("Mean compound score:", mean_score)


client.close()

#include <Adafruit_Sensor.h>
#include <DHT.h>
#include <Adafruit_GFX.h>
#include <Adafruit_SSD1306.h>

// Define the pin for the DHT11 sensor
#define DHTPIN 2
#define DHTTYPE DHT11

// Initialize DHT sensor
DHT dht(DHTPIN, DHTTYPE);

// Define the I2C address for the display
#define SCREEN_WIDTH 128
#define SCREEN_HEIGHT 64
#define OLED_RESET -1
#define SCREEN_ADDRESS 0x3C // Common I2C address for SSD1306

Adafruit_SSD1306 display(SCREEN_WIDTH, SCREEN_HEIGHT, &Wire, OLED_RESET);

void setup() {
  // Start serial communication
  Serial.begin(9600);
  
  // Start the DHT sensor
  dht.begin();
  
  // Start the display
  if(!display.begin(SSD1306_SWITCHCAPVCC, SCREEN_ADDRESS)) {
    Serial.println(F("SSD1306 allocation failed"));
    for(;;);
  }
  display.display();
  delay(2000);
  display.clearDisplay();
  display.setTextSize(1);
  display.setTextColor(WHITE);
}

void sendSensor() {
  // Read humidity and temperature
  float h = dht.readHumidity();
  float t = dht.readTemperature();
  
  // Check if any reads failed and exit early
  if (isnan(h) || isnan(t)) {
    Serial.println(F("Failed to read from DHT sensor!"));
    return;
  }
  
  // Print values to Serial
  Serial.print(F("Humidity: "));
  Serial.print(h);
  Serial.print(F("%  Temperature: "));
  Serial.print(t);
  Serial.println(F("°C "));
  
  // Display values on OLED
  display.clearDisplay();
  display.setCursor(0,0);
  display.print(F("Humidity: "));
  display.print(h);
  display.print(F("%"));
  display.setCursor(0, 10);
  display.print(F("Temp: "));
  display.print(t);
  display.print(F(" C"));
  display.display();
}

import qrcode  
# generating a QR code using the make() function  
qr_img = qrcode.make("https://stupendous-cheesecake-5c5aa3.netlify.app")  
# saving the image file  
qr_img.save("qr-img.jpg") 

public class SpriteManager : MonoBehaviour
{
    public SpriteAtlas spriteAtlas; 

    public Image img;

    void Start()
    {
      	// public으로 선언 시, 생략하고 드래그앤드롭으로 가능
        spriteAtlas = Resources.Load<SpriteAtlas>("SpriteAtlas"); 
    }

    void Update()
    {
        if (Input.GetMouseButtonDown(0)) 
        	img.sprite = SpriteReturn("sprite0"); // 좌클릭
        if (Input.GetMouseButtonDown(1)) 
        	img.sprite = SpriteReturn("sprite1"); // 우클릭
        if (Input.GetMouseButtonDown(2)) 
        	img.sprite = SpriteReturn("sprite2"); // 휠클릭
    }

    public Sprite SpriteReturn(string spriteName)
    {
        return spriteAtlas.GetSprite(spriteName);
    }
}

What's the weather like?

You are an alien that lives on Europa, one of Jupiter's moons.

 docker pull tensorflow/tensorflow:latest  # Download latest stable image
 docker run -it -p 8888:8888 tensorflow/tensorflow:latest-jupyter  # Start Jupyter server 

# Requires the latest pip
pip install --upgrade pip

# Current stable release for CPU and GPU
pip install tensorflow

# Or try the preview build (unstable)
pip install tf-nightly

NAME          RSRC
metadata.name metadata.resourceVersion

NAME           RSRC
submit-queue   610995

kubectl get pods <pod-name> --server-print=false

NAME       AGE
pod-name   1m

kubectl [command] [TYPE] [NAME] --sort-by=<jsonpath_exp>

kubectl get pods --sort-by=.metadata.name

# Create a service using the definition in example-service.yaml.

kubectl apply -f example-service.yaml



# Create a replication controller using the definition in example-controller.yaml.

kubectl apply -f example-controller.yaml



# Create the objects that are defined in any .yaml, .yml, or .json file within the <directory> directory.

kubectl apply -f <directory>

# List all pods in plain-text output format.

kubectl get pods



# List all pods in plain-text output format and include additional information (such as node name).

kubectl get pods -o wide



# List the replication controller with the specified name in plain-text output format. Tip: You can shorten and replace the 'replicationcontroller' resource type with the alias 'rc'.

kubectl get replicationcontroller <rc-name>



# List all replication controllers and services together in plain-text output format.

kubectl get rc,services



# List all daemon sets in plain-text output format.

kubectl get ds



# List all pods running on node server01

kubectl get pods --field-selector=spec.nodeName=server01

# Display the details of the node with name <node-name>.

kubectl describe nodes <node-name>



# Display the details of the pod with name <pod-name>.

kubectl describe pods/<pod-name>



# Display the details of all the pods that are managed by the replication controller named <rc-name>.

# Remember: Any pods that are created by the replication controller get prefixed with the name of the replication controller.

kubectl describe pods <rc-name>



# Describe all pods

kubectl describe pods

# Delete a pod using the type and name specified in the pod.yaml file.

kubectl delete -f pod.yaml



# Delete all the pods and services that have the label '<label-key>=<label-value>'.

kubectl delete pods,services -l <label-key>=<label-value>



# Delete all pods, including uninitialized ones.

kubectl delete pods --all

# Get output from running 'date' from pod <pod-name>. By default, output is from the first container.

kubectl exec <pod-name> -- date



# Get output from running 'date' in container <container-name> of pod <pod-name>.

kubectl exec <pod-name> -c <container-name> -- date



# Get an interactive TTY and run /bin/bash from pod <pod-name>. By default, output is from the first container.

kubectl exec -ti <pod-name> -- /bin/bash

# Return a snapshot of the logs from pod <pod-name>.

kubectl logs <pod-name>



# Start streaming the logs from pod <pod-name>. This is similar to the 'tail -f' Linux command.

kubectl logs -f <pod-name>

# Diff resources included in "pod.json".

kubectl diff -f pod.json



# Diff file read from stdin.

cat service.yaml | kubectl diff -f -

#!/bin/sh



# this plugin prints the words "hello world"

echo "hello world"

# create a simple plugin in any language and name the resulting executable file

# so that it begins with the prefix "kubectl-"

cat ./kubectl-hello

chmod a+x ./kubectl-hello



# and move it to a location in our PATH

sudo mv ./kubectl-hello /usr/local/bin

sudo chown root:root /usr/local/bin



# You have now created and "installed" a kubectl plugin.

# You can begin using this plugin by invoking it from kubectl as if it were a regular command

kubectl hello

# You can "uninstall" a plugin, by removing it from the folder in your

# $PATH where you placed it

sudo rm /usr/local/bin/kubectl-hello

kubectl plugin list

The following kubectl-compatible plugins are available:

/usr/local/bin/kubectl-hello
/usr/local/bin/kubectl-foo
/usr/local/bin/kubectl-bar

sudo chmod -x /usr/local/bin/kubectl-foo # remove execute permission

kubectl plugin list

The following kubectl-compatible plugins are available:

/usr/local/bin/kubectl-hello
/usr/local/bin/kubectl-foo
  - warning: /usr/local/bin/kubectl-foo identified as a plugin, but it is not executable
/usr/local/bin/kubectl-bar

error: one plugin warning was found

cat ./kubectl-whoami

#!/bin/bash



# this plugin makes use of the `kubectl config` command in order to output

# information about the current user, based on the currently selected context

kubectl config view --template='{{ range .contexts }}{{ if eq .name "'$(kubectl config current-context)'" }}Current user: {{ printf "%s\n" .context.user }}{{ end }}{{ end }}'

# make the file executable

sudo chmod +x ./kubectl-whoami



# and move it into your PATH

sudo mv ./kubectl-whoami /usr/local/bin



kubectl whoami

Current user: plugins-user

kubectl config set-context --current --namespace=<namespace-name>

kubectl get pod pod1

kubectl get pods pod1

kubectl get po pod1

kubectl [command] [TYPE] [NAME] [flags]

import tensorflow as tf
mnist = tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
  tf.keras.layers.Flatten(input_shape=(28, 28)),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
  loss='sparse_categorical_crossentropy',
  metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test)

php artisan make:controller SiteController

from pymongo import MongoClient
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
from nltk.corpus import stopwords
import statistics

def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    return sentiment['compound']

def preprocess_text(text):
    # Remove stopwords
    stop_words = set(stopwords.words('english'))
    tokens = text.split()
    tokens = [token for token in tokens if token.lower() not in stop_words]
    
    return tokens




negative_comments_klm = [
    "I had a terrible experience with KLM. Their customer service was rude and unhelpful.",
    "KLM lost my luggage and didn't offer any compensation or assistance.",
    "Avoid KLM at all costs! They canceled my flight without any notice and left me stranded.",
    "I'll never fly with KLM again. Their planes are old and uncomfortable.",
    "KLM overbooked my flight and bumped me off without any compensation or apology.",
    "KLM delayed my flight multiple times and provided no explanation or updates.",
    "I had a horrible experience with KLM. They were disorganized and incompetent.",
    "KLM's customer service is the worst I've ever encountered. They were unresponsive and dismissive.",
    "KLM's website is a nightmare to use. It's slow, confusing, and full of errors.",
    "I regret choosing KLM for my trip. Their staff was rude and disrespectful.",
    "KLM's flight attendants were unprofessional and uncaring. They ignored my requests and were rude.",
    "I'll never trust KLM again. Their flight schedules are unreliable and constantly changing.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and unreliable.",
    "KLM's seats are cramped and uncomfortable. I couldn't sleep a wink on my flight.",
    "I'll never recommend KLM to anyone after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They treated passengers with disrespect.",
    "KLM's flight was a nightmare from start to finish. I'll never fly with them again.",
    "I had a terrible experience with KLM's baggage handling. My luggage was damaged and items were missing.",
    "KLM's customer service representatives were unhelpful and unwilling to assist me with my issue.",
    "I'll be avoiding KLM in the future. Their service was atrocious and their staff were incompetent.",
    "KLM's flight was delayed for hours without any explanation or compensation. It ruined my trip.",
    "I had a horrible experience with KLM's ground staff. They were rude and unhelpful.",
    "KLM's flight was overbooked and they refused to offer any compensation or alternative arrangements.",
    "I'll never fly with KLM again after the terrible experience I had with them.",
    "KLM's flight was cancelled at the last minute and they offered no assistance or compensation.",
    "KLM's customer service was appalling. They were unresponsive and unwilling to help me with my issue.",
    "I had a terrible experience with KLM's flight attendants. They were rude and dismissive.",
    "KLM's flight was delayed multiple times and they provided no information or updates to passengers.",
    "I'll never fly with KLM again. Their service was terrible and their staff were rude.",
    "KLM's flight was overbooked and they refused to compensate me or provide alternative arrangements.",
    "I had a horrible experience with KLM's customer service. They were unhelpful and unresponsive.",
    "KLM's website is a nightmare to navigate. It's slow, confusing, and full of errors.",
    "I'll never trust KLM again after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They made me feel unwelcome and uncomfortable.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and",
    "i hate klm"]
list_of_scores = []
for text in negative_comments_klm:
    preprocessed_text = preprocess_text(text)
    processed_text = ' '.join(preprocessed_text)  # Convert preprocessed tokens back to text
    score = analyze_sentiment(processed_text)
    list_of_scores.append(score)

average_score = statistics.mean(list_of_scores)
print("Average sentiment score:", average_score)

from pymongo import MongoClient
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
from nltk.corpus import stopwords
import statistics

def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    return sentiment['compound']

def preprocess_text(text):
    # Remove stopwords
    stop_words = set(stopwords.words('english'))
    tokens = text.split()
    tokens = [token for token in tokens if token.lower() not in stop_words]
    
    return tokens




negative_comments_klm = [
    "I had a terrible experience with KLM. Their customer service was rude and unhelpful.",
    "KLM lost my luggage and didn't offer any compensation or assistance.",
    "Avoid KLM at all costs! They canceled my flight without any notice and left me stranded.",
    "I'll never fly with KLM again. Their planes are old and uncomfortable.",
    "KLM overbooked my flight and bumped me off without any compensation or apology.",
    "KLM delayed my flight multiple times and provided no explanation or updates.",
    "I had a horrible experience with KLM. They were disorganized and incompetent.",
    "KLM's customer service is the worst I've ever encountered. They were unresponsive and dismissive.",
    "KLM's website is a nightmare to use. It's slow, confusing, and full of errors.",
    "I regret choosing KLM for my trip. Their staff was rude and disrespectful.",
    "KLM's flight attendants were unprofessional and uncaring. They ignored my requests and were rude.",
    "I'll never trust KLM again. Their flight schedules are unreliable and constantly changing.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and unreliable.",
    "KLM's seats are cramped and uncomfortable. I couldn't sleep a wink on my flight.",
    "I'll never recommend KLM to anyone after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They treated passengers with disrespect.",
    "KLM's flight was a nightmare from start to finish. I'll never fly with them again.",
    "I had a terrible experience with KLM's baggage handling. My luggage was damaged and items were missing.",
    "KLM's customer service representatives were unhelpful and unwilling to assist me with my issue.",
    "I'll be avoiding KLM in the future. Their service was atrocious and their staff were incompetent.",
    "KLM's flight was delayed for hours without any explanation or compensation. It ruined my trip.",
    "I had a horrible experience with KLM's ground staff. They were rude and unhelpful.",
    "KLM's flight was overbooked and they refused to offer any compensation or alternative arrangements.",
    "I'll never fly with KLM again after the terrible experience I had with them.",
    "KLM's flight was cancelled at the last minute and they offered no assistance or compensation.",
    "KLM's customer service was appalling. They were unresponsive and unwilling to help me with my issue.",
    "I had a terrible experience with KLM's flight attendants. They were rude and dismissive.",
    "KLM's flight was delayed multiple times and they provided no information or updates to passengers.",
    "I'll never fly with KLM again. Their service was terrible and their staff were rude.",
    "KLM's flight was overbooked and they refused to compensate me or provide alternative arrangements.",
    "I had a horrible experience with KLM's customer service. They were unhelpful and unresponsive.",
    "KLM's website is a nightmare to navigate. It's slow, confusing, and full of errors.",
    "I'll never trust KLM again after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They made me feel unwelcome and uncomfortable.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and",
    "i hate klm"]
list_of_scores = []
for text in negative_comments_klm:
    preprocessed_text = preprocess_text(text)
    processed_text = ' '.join(preprocessed_text)  # Convert preprocessed tokens back to text
    score = analyze_sentiment(processed_text)
    list_of_scores.append(score)

average_score = statistics.mean(list_of_scores)
print("Average sentiment score:", average_score)

from pymongo import MongoClient
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import statistics


def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    return sentiment['compound']

negative_comments_klm = [
    "I had a terrible experience with KLM. Their customer service was rude and unhelpful.",
    "KLM lost my luggage and didn't offer any compensation or assistance.",
    "Avoid KLM at all costs! They canceled my flight without any notice and left me stranded.",
    "I'll never fly with KLM again. Their planes are old and uncomfortable.",
    "KLM overbooked my flight and bumped me off without any compensation or apology.",
    "KLM delayed my flight multiple times and provided no explanation or updates.",
    "I had a horrible experience with KLM. They were disorganized and incompetent.",
    "KLM's customer service is the worst I've ever encountered. They were unresponsive and dismissive.",
    "KLM's website is a nightmare to use. It's slow, confusing, and full of errors.",
    "I regret choosing KLM for my trip. Their staff was rude and disrespectful.",
    "KLM's flight attendants were unprofessional and uncaring. They ignored my requests and were rude.",
    "I'll never trust KLM again. Their flight schedules are unreliable and constantly changing.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and unreliable.",
    "KLM's seats are cramped and uncomfortable. I couldn't sleep a wink on my flight.",
    "I'll never recommend KLM to anyone after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They treated passengers with disrespect.",
    "KLM's flight was a nightmare from start to finish. I'll never fly with them again.",
    "I had a terrible experience with KLM's baggage handling. My luggage was damaged and items were missing.",
    "KLM's customer service representatives were unhelpful and unwilling to assist me with my issue.",
    "I'll be avoiding KLM in the future. Their service was atrocious and their staff were incompetent.",
    "KLM's flight was delayed for hours without any explanation or compensation. It ruined my trip.",
    "I had a horrible experience with KLM's ground staff. They were rude and unhelpful.",
    "KLM's flight was overbooked and they refused to offer any compensation or alternative arrangements.",
    "I'll never fly with KLM again after the terrible experience I had with them.",
    "KLM's flight was cancelled at the last minute and they offered no assistance or compensation.",
    "KLM's customer service was appalling. They were unresponsive and unwilling to help me with my issue.",
    "I had a terrible experience with KLM's flight attendants. They were rude and dismissive.",
    "KLM's flight was delayed multiple times and they provided no information or updates to passengers.",
    "I'll never fly with KLM again. Their service was terrible and their staff were rude.",
    "KLM's flight was overbooked and they refused to compensate me or provide alternative arrangements.",
    "I had a horrible experience with KLM's customer service. They were unhelpful and unresponsive.",
    "KLM's website is a nightmare to navigate. It's slow, confusing, and full of errors.",
    "I'll never trust KLM again after the terrible experience I had with them.",
    "KLM's flight attendants were rude and unprofessional. They made me feel unwelcome and uncomfortable.",
    "KLM's prices are outrageous for the terrible service they provide. Avoid them if you can.",
    "KLM's planes are dirty and poorly maintained. I felt unsafe throughout the entire flight.",
    "I had a terrible experience with KLM's customer service. They were unhelpful and unsympathetic.",
    "KLM's food and beverage options are awful. I wouldn't feed it to my worst enemy.",
    "I'll never fly KLM again after the nightmare experience I had with them.",
    "KLM's flight attendants were rude and disrespectful. They made me feel unwelcome and uncomfortable.",
    "KLM's cancellation policy is a scam. They charged me outrageous fees to cancel my flight.",
    "I'll be filing a complaint against KLM for the horrendous service I received from them.",
    "KLM's check-in process is a disaster. It took hours to get through, and their staff was unhelpful.",
    "KLM's in-flight entertainment is outdated and limited. There was nothing to do during the flight.",
    "I had a terrible experience with KLM's booking system. It was glitchy and",
    "i hate klm"]
list_of_scores = []
for text in negative_comments_klm:
    score = analyze_sentiment(text)
    list_of_scores.append(score)
aveage_score = statistics.mean(list_of_scores)
print(aveage_score)

from pymongo import MongoClient, errors
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import nltk
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
import string

# MongoDB connection settings
mongo_uri = "mongodb://localhost:27017/"
database_name = "twitter_database"
source_collection_name = "tweets"

# Initialize NLTK resources
nltk.download('punkt')
nltk.download('stopwords')
nltk.download('wordnet')

def get_text_from_doc(doc):
    """
    Extracts the text from the document.
    Returns the text if available, otherwise returns None.
    """
    text = doc.get("json_data", {}).get("text")
    if text:
        return text
    extended_text = doc.get("json_data", {}).get("extended_tweet", {}).get("full_text")
    return extended_text

def preprocess_text(text):
  
    # Remove punctuation
    tokens = [token for token in tokens if token not in string.punctuation]
    
    # Remove stopwords
    stop_words = set(stopwords.words('english') + stopwords.words('spanish') + stopwords.words('dutch'))    
    tokens = [token for token in tokens if token not in stop_words]
    
    # Lemmatization
    lemmatizer = WordNetLemmatizer()
    tokens = [lemmatizer.lemmatize(token) for token in tokens]
    
    return tokens

def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    return sentiment['compound']

try:
    client = MongoClient(mongo_uri, serverSelectionTimeoutMS=5000)
    db = client[database_name]
    source_collection = db[source_collection_name]

    cursor = source_collection.find().limit(20)  # Limit to only 20 tweets

    for doc in cursor:
        text = get_text_from_doc(doc)
        if text:
            preprocessed_text = preprocess_text(text)
            processed_text = ' '.join(preprocessed_text)  # Convert preprocessed tokens back to text
            print("Original Text:", text)
            print("Processed Text:", processed_text)
            print("Sentiment Score:", analyze_sentiment(processed_text))
            print()

except errors.ServerSelectionTimeoutError as err:
    print("Failed to connect to MongoDB server:", err)
except errors.PyMongoError as err:
    print("An error occurred while working with MongoDB:", err)
finally:
    client.close()

from pymongo import MongoClient
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
import statistics
def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    return sentiment['compound']
neutral_comments_klm = [
    "I have a flight booked with KLM.",
    "I'm flying with KLM next month.",
    "I've used KLM for my travels before.",
    "I'm considering KLM for my upcoming trip.",
    "KLM operates flights to various destinations.",
    "I'll be flying with KLM for my vacation.",
    "KLM offers flights at competitive prices.",
    "I'll be traveling with KLM for work.",
    "I've heard about KLM's services.",
    "KLM is one of the airlines I'm considering.",
    "I've seen advertisements for KLM.",
    "I'll be using KLM for my international flight.",
    "KLM provides options for connecting flights.",
    "I need to check KLM's flight schedule.",
    "I'm looking into KLM's frequent flyer program.",
    "I received an email from KLM.",
    "I'm exploring flight options with KLM.",
    "KLM offers flights with various amenities.",
    "I'll be flying with KLM for my family visit.",
    "KLM has partnerships with other airlines.",
    "I'll be using KLM for my business trip.",
    "KLM has a website for booking flights.",
    "I'll be flying with KLM because of the route.",
    "KLM provides options for different classes.",
    "I've considered KLM for my travel plans.",
    "KLM offers online check-in.",
    "I've received information about KLM's services.",
    "I'll be flying with KLM due to convenience.",
    "KLM has a mobile app for flight management.",
    "I'll be using KLM for my upcoming trip abroad.",
    "KLM offers options for booking accommodations.",
    "I've heard about KLM's customer service.",
    "I'll be considering KLM for future travels.",
    "KLM provides options for flight upgrades.",
    "I'll be flying with KLM because of recommendations.",
    "KLM offers options for flight insurance.",
    "I've checked KLM's flight status online.",
    "I'll be flying with KLM for personal reasons.",
    "KLM provides options for seat selection.",
    "I've received promotions from KLM.",
    "I'll be flying with KLM for leisure travel.",
    "KLM offers options for in-flight entertainment.",
    "I've read about KLM's safety measures.",
    "I'll be flying with KLM because of scheduling.",
    "KLM provides options for booking car rentals.",
    "I've looked into KLM's baggage policies.",
    "I'll be flying with KLM for holiday travel.",
    "KLM offers options for travel insurance.",
    "I've explored KLM's route map.",
    "I'll be considering KLM for my next trip.",
    "KLM provides options for airport transfers.",
    "I've browsed KLM's website for information.",
    "I'll be flying with KLM due to flexibility.",
    "KLM offers options for flight add-ons.",
    "I've researched KLM's onboard services.",
    "I'll be considering KLM for my future travels.",
    "KLM provides options for special assistance.",
    "I've looked into KLM's loyalty program.",
    "I'll be flying with KLM for my international trip.",
    "KLM offers options for travel packages.",
    "I've compared KLM's fares with other airlines.",
    "I'll be considering KLM for my next vacation.",
    "KLM provides options for dietary preferences.",
    "I've checked KLM's reviews online.",
    "I'll be flying with KLM for my trip to Europe.",
    "KLM offers options for travel upgrades.",
    "I've explored KLM's flight routes.",
    "I'll be considering KLM for my next adventure.",
    "KLM provides options for group bookings."
]


list_of_scores = []
for text in neutral_comments_klm:
    score = analyze_sentiment(text)
    list_of_scores.append(score)
aveage_score = statistics.mean(list_of_scores)
print(aveage_score)

from pymongo import MongoClient, errors
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

# MongoDB connection settings
mongo_uri = "mongodb://localhost:27017/"
database_name = "twitter_database"
source_collection_name = "tweets"

def get_text_from_doc(doc):
    """
    Extracts the text from the document.
    Returns the text if available, otherwise returns None.
    """
    text = doc.get("json_data", {}).get("text")
    if text:
        return text
    extended_text = doc.get("json_data", {}).get("extended_tweet", {}).get("full_text")
    return extended_text

def analyze_sentiment(text):
    """
    Analyzes the sentiment of the given text using VADER.
    Returns the compound sentiment score.
    """
    analyzer = SentimentIntensityAnalyzer()
    sentiment = analyzer.polarity_scores(text)
    compound_score = sentiment['compound']
    if compound_score > 0.05:
        return 'positive'
    elif compound_score < -0.05:
        return 'negative'
    else:
        return 'neutral'

try:
    client = MongoClient(mongo_uri, serverSelectionTimeoutMS=5000)
    db = client[database_name]
    source_collection = db[source_collection_name]

    # Define query to filter tweets related to KLM (tweets made by KLM or mentioning KLM)
    query = {
        "$or": [
            {"json_data.user.id": 56377143},  # Tweets made by KLM
            {"json_data.entities.user_mentions.id": 56377143}  # Tweets mentioning KLM
        ]
    }

    # Count variables for sentiment analysis
    positive_count = 0
    neutral_count = 0
    negative_count = 0

    cursor = source_collection.find(query)

    for doc in cursor:
        text = get_text_from_doc(doc)
        if text:
            sentiment = analyze_sentiment(text)
            if sentiment == 'positive':
                positive_count += 1
            elif sentiment == 'neutral':
                neutral_count += 1
            elif sentiment == 'negative':
                negative_count += 1

    print("Number of tweets related to KLM:")
    print("Positive:", positive_count)
    print("Neutral:", neutral_count)
    print("Negative:", negative_count)

except errors.ServerSelectionTimeoutError as err:
    print("Failed to connect to MongoDB server:", err)
except errors.PyMongoError as err:
    print("An error occurred while working with MongoDB:", err)
finally:
    client.close()

import random

# Define the fruit and number words
fruits = ['pear']
number_words = ['forty-one']

# Function to generate a random fruit and number word
def get_random_fruit_and_number():
    fruit = random.choice(fruits)
    number_word = random.choice(number_words)
    return fruit, number_word

# Function to display the game
def play_game():
    print("Welcome to the Number Words Fruit Splat Game!")
    print("Match the number word to the correct number of fruits.")
    
    score = 0
    while True:
        fruit, number_word = get_random_fruit_and_number()
        print(f"How many {fruit}s are there?")
        user_input = input("Enter the number word: ")
        
        if user_input.lower() == number_word:
            print("Correct!")
            score += 1
        else:
            print(f"Incorrect. The correct answer is {number_word}.")
        
        print(f"Your current score is: {score}")
        
        play_again = input("Do you want to play again? (y/n) ")
        if play_again.lower() != 'y':
            break

if __name__ == "__main__":
    play_game()