PROJECT1-SEC-1-Password Generator Application

Click Here to view live version of our project

Group member

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• Chanakarn Kruehong | 65130500013
  • Task: Password Generator Implementation, Copy to clipboard feature, Password Generator Strength UI, Password Checker UI
  • Responsibility: 25%
• Nathaphat Lertsiriphongphan | 65130500020
  • Task: Password History Implementation, Generate Password Logic, Reactivity on Password Checker Component, Password Checker Strength UI
  • Responsibility: 25%
• Pornchai Kaewkrabil | 65130500047
  • Task: Password Checker UI, Switch Tab, Wireframe, Reactivity on Password Checker Component, Drawer Component
  • Responsibility: 25%
• Pattaradanai Srichon | 65130500057
  • Task: Password Checker Logic, Theme Controller, Animation, Password Checker Strength Reactivity
  • Responsibility: 25%

Project Document

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This project is the part of INT203 Client-side subject. It's feature two main functionality: a Password Generator and a Password Checker. The Password Generator allows users to create secure, customized passwords based on selected criteria, while the Password Checker evaluates the strength of entered passwords against common security standards.

Click here to watch a video introducing the functions password-Generator App

Features

• Password Generator: Generates password base on selected options. (length, symbols, numbers, lowercase, uppercase).
• Password Checker: Evaluates password strength and provides feedback on improvements.
• Dark Mode: Using local storages to store user's preferences themes.
• Password Generated History: User can view the generated password in the drawer tab.

Tools

• Vue.js
• Tailwind CSS
• Daisy UI

Video Showcase

PLACE HOLDER

External Tool

• Natural Language Toolkit (ntlk lib)

Usage

The code here used to generate a JSON dictionary with first 10000 most frequently used words.

import nltk
import json

nltk.download('words')
nltk.download('brown')

from nltk.corpus import brown

from nltk.probability import FreqDist

def get_frequent_words(corpus, num_words=100):
    # Extract words from the corpus
    words = [word.lower() for word in corpus.words()]
    # Calculate word frequencies
    fdist = FreqDist(words)
    # Get the most common words
    common_words = [word for word, _ in fdist.most_common(num_words)]
    filtered_words = [word for word in common_words if word.isalpha()]

    return filtered_words

# Export
common_words = get_frequent_words(brown, 10000)
json_words = json.dumps(common_words)

with open('words.json', 'w') as f:
    f.write(json_words)