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Python vs JavaScript: Understanding the Key Differences and Use Cases

Arthur Kaminsky
CodePubCast
Published in
9 min readJan 26, 2023

Comparing the Pros and Cons for your individual use cases

Python and JavaScript are both popular programming languages, but they have some key differences.

Python is a general-purpose, high-level programming language that is often used for scientific computing, data analysis, artificial intelligence, machine learning, computer vision, image processing, biology, medicine and astronomy. Web development is something we can start to compare against JavaScript since JavaScript lacks a wide range of data science packages unlike Python. Python has a large standard library and a simple, easy-to-learn syntax. In addition, Python is often used for scripting for general purpose and fast solutions to problems which we’ll provide examples later.

JavaScript, on the other hand, is a programming language primarily used for creating interactive front-end web applications. It can also be used on the back-end through technologies like Node.js. JavaScript is commonly used for creating dynamic user interfaces, interactive form validation, and creating single-page web applications using Vue.js, Angular, and React.

We’ll go through 5 differences between the languages and provide with code examples:

Syntax

Python is known for its simple and easy-to-read syntax. It uses indentation to indicate code blocks, which makes the code more organized and visually appealing. On the other hand, JavaScript has a more complex syntax with the use of curly braces, which can take some time to get used to.

Let’s provide some basic code examples for both languages:

If-else statements:

# Python code for a simple if-else statement
if x > 0:
    print("x is positive")
else:
    print("x is non-positive")
// JavaScript code for a simple if-else statement
if (x > 0) {
    console.log("x is positive");
} else {
    console.log("x is non-positive");
}

Loops:

# Python code for a for loop
for i in range(5):
    print(i) # Output: 0 1 2 3 4
// JavaScript code for a for loop
for (let i = 0; i < 5; i++) {
    console.log(i); // Output: 0 1 2 3 4
}

Functions:

# Python code for a simple function
def add(a, b):
    return a + b

print(add(1, 2)) # Output: 3
// JavaScript code for a simple function
function add(a, b) {
    return a + b;
}

console.log(add(1, 2)); // Output: 3

Objects:

# Python code for creating an object with properties and methods
class Circle:
    def __init__(self, radius):
        self.radius = radius

    def area(self):
        return 3.14 * (self.radius ** 2)

c = Circle(5)
print(c.radius) # Output: 5
print(c.area()) # Output: 78.5
// JavaScript code for creating an object with properties and methods
const Circle = function (radius) {
    this.radius = radius;
    this.area = function () {
        return 3.14 * (this.radius ** 2);
    };
};
const c = new Circle(5);
console.log(c.radius); // Output: 5
console.log(c.area()); // Output: 78.5

HTTP Server:

import http.server

class MyHandler(http.server.BaseHTTPRequestHandler):
    def do_GET(self):
        self.send_response(200)
        self.send_header('Content-type','text/html')
        self.end_headers()
        self.wfile.write(b'Hello World!')

server = http.server.HTTPServer(('', 8080), MyHandler)
server.serve_forever()
const http = require('http');

const server = http.createServer((req, res) => {
    res.statusCode = 200;
    res.setHeader('Content-Type', 'text/plain');
    res.end('Hello World\n');
});

server.listen(8080, () => {
    console.log('Server running at http://localhost:8080/');
});

Generally, both provide easy-readable syntax and of course there’s a lot more to cover in terms of scale when the projects you develop become more complex as more code being added, but that’s not the purpose of this blog.

Execution:

Before going through the execution process of both languages, we ought to first understand the difference between interpreted and compiled languages and the pros and cons of each one.

The main difference between interpreted and compiled languages is that with interpreted languages the source code is translated at runtime, while with compiled languages, the source code is translated before runtime.

Meaning for compiled languages the developer will be able to catch errors before running their application providing much more security and reliability of their application, unlike in interpreted languages bugs are usually found during runtime when the application is already deployed.

Compiled languages generally run faster than interpreted languages because the machine code is optimized for the specific hardware it will be run on and can be executed directly by the computer’s hardware without the need for an interpreter. However, interpreted languages have the advantage of being more portable, since the same source code can be run on multiple platforms with a compatible interpreter.

In general, JavaScript runs faster than Python because it is a compiled language, and it runs directly on the web browser. JavaScript is designed to be executed quickly by a JavaScript engine, such as V8 (used by Chrome and Node.js) and SpiderMonkey (used by Firefox). These engines use advanced techniques such as just-in-time (JIT) compilation to improve performance.

Python, on the other hand, is an interpreted language, which means that it is executed by an interpreter rather than being compiled to machine code. This can make Python code run slower than JavaScript. However, Python has the advantage of being highly portable, and it can run on a wide variety of platforms and devices.

It’s worth noting that some Python implementations such as PyPy, Cython, and Jython, have a JIT compiler that can speed up the execution of some Python code. Also, there are JavaScript engines such as V8, SpiderMonkey, and JavaScriptCore that interpret JavaScript code.

So, in general, JavaScript runs faster than Python, but the difference in performance will depend on the specific task and implementation. You should also consider other factors such as development time, maintainability, and portability when deciding which language to use for a particular project.

Object-oriented programming

Both Python and JavaScript support object-oriented programming, but they have different approaches. Python is a fully object-oriented language, meaning that everything in Python is an object. JavaScript uses a prototype-based approach, which is less strict than the class-based approach used by Python.

For example:

# Python code for a simple class
class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def say_hello(self):
        print("Hello, my name is " + self.name)

p = Person("John", 30)
p.say_hello()As you can see, both languages allow you to create objects, however, Python uses a class-based approach, whereas JavaScript uses a prototype-based approach.

In this example, we define a Person class with a constructor method (__init__) that takes in a name and an age as arguments. We also define a say_hello method that prints out a message introducing the person. We then create an instance of the Person class and call the say_hello method on it.

Here’s an example of a prototype-based implementation of a simple “Person” object in JavaScript:

function Person(name, age) {
    this.name = name;
    this.age = age;
}

Person.prototype.sayHello = function() {
    console.log("Hello, my name is " + this.name);
}

var p = new Person("John", 30);
p.sayHello();

In this example, we define a Person function that creates an object with properties name and age. We then add a sayHello method to the Person.prototype object, which allows all instances of the Person object to inherit the method. Finally, we create an instance of the Person object and call the sayHello method on it.

It’s worth noting that javascript also supports classes from ES6, and the above example can be written as:

class Person {
    constructor(name, age) {
        this.name = name;
        this.age = age;
    }

    sayHello() {
        console.log(`Hello, my name is ${this.name}`);
    }
}

const p = new Person("John", 30);
p.sayHello();

As you can see, both languages support OOP, but their syntax and approach are different. Python uses a class-based approach, which is more traditional and consistent, while JavaScript uses a prototype-based approach, which allows for more flexibility and dynamic behavior.

Standard Library

Python has a larger standard library than JavaScript, which includes modules for a wide range of tasks such as data science, web scraping, and machine learning. JavaScript has a relatively small standard library but has a large ecosystem of third-party libraries and frameworks that can be used to extend its functionality

Python:

# using the json module to parse a json string
import json

json_string = '{"name": "John", "age": 30}'
data = json.loads(json_string)
print(data["name"])

# using the re module to match a regular expression
import re

text = "The number is 42"
match = re.search(r"\d+", text)
print(match.group())

In the first example, we use the json module to parse a JSON string and extract the value of the "name" key. In the second example, we use the re module to search for a pattern of one or more digits in a string, and print the first match.

JavaScript:

// using the JSON object to parse a json string
let jsonString = '{"name": "John", "age": 30}';
let data = JSON.parse(jsonString);
console.log(data.name);

// using the String.prototype.match method to match a regular expression
let text = "The number is 42";
let match = text.match(/\d+/);
console.log(match[0]);

In the first example, we use the JSON.parse method to parse a JSON string and extract the value of the "name" key. In the second example, we use the String.prototype.match method to match a pattern of one or more digits in a string, and print the first match.

Python has a lot of libraries that are not only used for web development, but also for machine learning, data analysis, and scientific computing. It’s standard library is considered to be more comprehensive than JavaScript’s. JavaScript on the other hand, is primarily focused on web development and browser-specific functionality, with a lot of libraries for front-end and back-end development. It’s standard library is more focused on web development and browser-specific functionality.

Use-cases

As mentioned in the beginning of the blog, Python is often used for scientific computing, data analysis, artificial intelligence, and back-end web development. JavaScript is primarily used for creating interactive front-end web applications and for building full stack web applications using NodeJS.

Python:

# use case 1: data analysis and visualization
import pandas as pd
import matplotlib.pyplot as plt

data = pd.read_csv('data.csv')
data.plot(kind='scatter', x='x', y='y')
plt.show()

In this example, we use the pandas library to read a CSV file and the matplotlib library to create a scatter plot of the data. This is a common use case for Python in data science and scientific computing, as it has a wide range of libraries and tools for these tasks.

# use case 2: machine learning
import numpy as np
from sklearn import datasets
from sklearn.linear_model import LinearRegression

X, y = datasets.make_regression(n_samples=100, n_features=1, noise=20)
model = LinearRegression()
model.fit(X, y)
print(model.coef_)

In this example, we use the numpy and sklearn libraries to generate a dataset and fit a linear regression model. Python is a popular language for machine learning tasks, as it has a wide range of libraries and tools for these tasks.

JavaScript:

An example of a simple API written in Node.js using the Express.js framework and the MongoDB database:

const express = require('express');
const mongoose = require('mongoose');

const app = express();

// Connect to MongoDB
mongoose.connect('mongodb://localhost/mydatabase', { useNewUrlParser: true, useUnifiedTopology: true });

// Define the database schema
const productSchema = new mongoose.Schema({
  name: String,
  price: Number,
});

// Create a model based on the schema
const Product = mongoose.model('Product', productSchema);

// Define the API routes
app.get('/products', (req, res) => {
  Product.find({}, (err, products) => {
    if (err) {
      res.status(500).send(err);
    } else {
      res.json(products);
    }
  });
});

app.get('/products/:id', (req, res) => {
  Product.findById(req.params.id, (err, product) => {
    if (err) {
      res.status(500).send(err);
    } else {
      res.json(product);
    }
  });
});

app.post('/products', (req, res) => {
  const product = new Product(req.body);
  product.save((err) => {
    if (err) {
      res.status(500).send(err);
    } else {
      res.json(product);
    }
  });
});

app.put('/products/:id', (req, res) => {
  Product.findByIdAndUpdate(req.params.id, req.body, { new: true }, (err, product) => {
    if (err) {
      res.status(500).send(err);
    } else {
      res.json(product);
    }
  });
});

app.delete('/products/:id', (req, res) => {
  Product.findByIdAndRemove(req.params.id, (err) => {
    if (err) {
      res.status(500).send(err);
    } else {
      res.send('Product deleted.');
    }
  });
});

// Start the server
app.listen(3000, () => {
  console.log('Server started on port 3000');
});

This code defines a simple API with routes for getting a list of products, getting a single product by ID, creating a new product, updating an existing product, and deleting a product. The API uses the Mongoose library to interact with the MongoDB.

const axios = require('axios');

// Get all products
axios.get('http://localhost:3000/products')
  .then(response => console.log(response.data))
  .catch(error => console.log(error));

// Get product with ID of 5f5d5b5c5d5e5f5g5h5i5j
axios.get('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j')
  .then(response => console.log(response.data))
  .catch(error => console.log(error));

// Create a new product
axios.post('http://localhost:3000/products', {
    name: 'New Product',
    price: 99.99
  })
  .then(response => console.log(response.data))
  .catch(error => console.log(error));

// Update product with ID of 5f5d5b5c5d5e5f5g5h5i5j
axios.put('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j', {
    name: 'Updated Product',
    price: 79.99
  })
  .then(response => console.log(response.data))
  .catch(error => console.log(error));

// Delete product with ID of 5f5d5b5c5d5e5f5g5h5i5j
axios.delete('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j')
  .then(response => console.log(response.data))
  .catch(error => console.log(error));

This code uses the axios library to make HTTP requests to the API. You can see the different methods available (GET, POST, PUT, DELETE) are used to call the routes defined in the API, and the response data is logged to the console.

Also, you can use a library like request-promise in python to call the API.

import requests

# Get all products
response = requests.get('http://localhost:3000/products')
print(response.json())

# Get product with ID of 5f5d5b5c5d5e5f5g5h5i5j
response = requests.get('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j')
print(response.json())

# Create a new product
data = {'name': 'New Product', 'price': 99.99}
response = requests.post('http://localhost:3000/products', json=data)
print(response.json())

# Update product with ID of 5f5d5b5c5d5e5f5g5h5i5j
data = {'name': 'Updated Product', 'price': 79.99}
response = requests.put('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j', json=data)
print(response.json())

# Delete product with ID of 5f5d5b5c5d5e5f5g5h5i5j
response = requests.delete('http://localhost:3000/products/5f5d5b5c5d5e5f5g5h5i5j')
print(response.json())

In summary, Python is a versatile language that can be used for a variety of tasks, but it is particularly well-suited for back-end web development, scripting, data science, and machine learning. JavaScript is primarily used for front-end web development and creating interactive web applications. Therefore, you should use Python for tasks that require heavy data processing, data analysis, and machine learning. Use JavaScript for building interactive client-side features and creating dynamic user interfaces as well as creating back-end web development using Nodejs.

Programming
JavaScript
Python
Software Development
Development

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Arthur Kaminsky
CodePubCast

Written by Arthur Kaminsky

11 Followers
Editor for

Constantly trying to pursue understanding of thyself and others.

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