14 JavaScript One-Liners to Boost Your Productivity 🚀

Durvesh Danve — Sat, 10 Aug 2024 17:13:51 +0000

01 - Remove Duplicates from an Array

const uniqueArr = arr => [...new Set(arr)];
console.log(uniqueArr([1, 2, 3, 4, 5, 5, 5]));

// [1, 2, 3, 4, 5]

02 - Sum of Array Elements

const nums = [1, 2, 3, 4, 5];
const sum = nums.reduce((acc, num) => acc + num);
console.log(sum);

// 15

03 - Check if a Number is Odd or Even

const isEven = num => num % 2 === 0;
console.log(isEven(5));

// false

04 - Capitalize Every Word in a String

const capitalizeWords = str => 
  str.split(' ')
     .map(word => word.charAt(0).toUpperCase() + word.slice(1))
     .join(' ');

console.log(capitalizeWords('hello world'));
// 'Hello World'

05 - Reverse a String (By letters & words)

let str = 'Hello World!';
console.log(str.split('').reverse().join('')); 
console.log(str.split(' ').reverse().join(' '));

// '!dlroW olleH'
// 'World! Hello'

06 - Truncate a String to a Specific Length

const truncate = (str, len) => str.slice(0, len) + '...';
console.log(truncate("Lorem ipsum is simply dummy text of the printing and typesetting industry.", 15));

// 'Lorem ipsum is...'

07 - Short-Circuit Evaluation

const fullName = fname || 'John Doe';
console.log(fullName);

// 'John Doe'

08 - Remove a Specific Value from an Array

const toRemove = 5;
const newArr = nums.filter(val => val !== toRemove);
console.log(newArr);

// [1, 2, 3, 4]

09 - Swap Two Variables

[a, b] = [b, a];

10 - Toggle a Boolean Value

const toggle = bool => !bool;

11 - Generate a Random String

const randomString = () => Math.random().toString(36).slice(2);
console.log(randomString());

// 'eqsdasfefsa'  // Example output

12 - Detect Dark Mode

const isDarkMode = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').match;

13 - Scroll to the Top of the Page

const scrollTop = () => window.scrollTo(0, 0);

14 - Replace switch with Object Literals

// Traditional way 👇
const getAnimalName = (animalType) => {
    switch (animalType) {
    case 'lion':
        return '🦁';
    case 'elephant':
        return '🐘';
    case 'tiger':
        return '🐅';
    default:
        return 'Unknown';
    }
};

// Using object literals 👇
const animalNames = {
  lion: '🦁',
  elephant: '🐘',
  tiger: '🐅',
};

const getAnimalName = animalType => animalNames[animalType] || 'Unknown';
console.log(getAnimalName('lion'));

// '🦁'

These one-liners offer quick solutions to common JavaScript tasks, helping you write cleaner, more efficient code. Give them a try!

Use any LLM with Just 8 Lines of Code 🚀

Durvesh Danve — Fri, 09 Aug 2024 12:40:40 +0000

Ever wondered how easy it could be to harness the power of cutting-edge AI models in your projects?

With just 8 lines of Python code, you can start using a powerful Large Language Model (LLM) without diving into the complexities of training one from scratch.

Let’s see how!

Tools we'll be using:



1. Huggingface pretrained model (in this case, falcon)
2. Python
3. Langchain
4. Google Colab

First, open Google Colab and create a new notebook.

Let's start coding:

Step 1:
Install the necessary libraries:



!!pip install langchain huggingface_hub langchain_community

Step 2:
Set up your Hugging Face API token as an environment variable:



import os
os.environ["HUGGINGFACEHUB_API_TOKEN"] = "YOUR_TOKEN"

To get your token:

Visit Hugging Face and sign in or create an account.
Navigate to the settings page and select the Access Token tab.
Create a token and replace "YOUR_TOKEN" with your actual token.

Step 3:
Import HuggingFaceHub from langchain :



from langchain import HuggingFaceHub

Initialize your Large Language Model (LLM):



llm = HuggingFaceHub(repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature":0.6})

I’m using the tiiuae/falcon-7b-instruct model here, but there are plenty of models available. You can explore them here.

Let’s test the model:



prompt = 'Generate a Python function to print the Fibonacci series. Ensure the code is optimized for efficiency and has minimal time complexity'
response = llm(prompt)
print(response)

and this results into :



def fibonacci(n):
    if n == 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fibonacci(n - 1)+fibonacci(n - 2)

And just like that, with only 8 lines of code, we’ve set up our own version of ChatGPT! 🎉💻

Complete Code



# Install necessary libraries
!pip install langchain huggingface_hub langchain_community

import os
os.environ["HUGGINGFACEHUB_API_TOKEN"] = "YOUR_TOKEN"

from langchain import HuggingFaceHub

# Initialize the model
llm = HuggingFaceHub(repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature":0.6})

# Use the model to generate a response
prompt = 'Generate a Python function to print the Fibonacci series. Ensure the code is optimized for efficiency and has minimal time complexity'
response = llm(prompt)
print(response)

DEV Community: Durvesh Danve

14 JavaScript One-Liners to Boost Your Productivity 🚀

Use any LLM with Just 8 Lines of Code 🚀