Free AI Code Generator
Write code in any programming language using plain English. Powered by advanced AI to generate clean, efficient, and production-ready code instantly.
Why Use Our AI Code Generator?
Natural Language Input
Describe what you want to build in plain English
100+ Languages
Generate code in any programming language
Instant Results
Get working code in seconds
Hint: Paste original code on left, modified code on right, then click Compare to see differences highlighted.
Paste code in both editors to see differences
Hint: Paste your code, customize font size and line numbers, then click Export PDF to download formatted code.
Hint: Describe what you want to build or paste requirements, select target language, and click Generate.
Issue Description
Generate Code in 100+ Languages
Generate code in any programming language. Describe what you want in plain English and get production-ready code instantly.
What Makes Swapcode Generator Different
Swapcode vs ChatGPT
While ChatGPT is a general-purpose AI that handles conversations, questions, and code, Swapcode is laser-focused on code generation. Our specialized AI model is trained exclusively on programming tasks, making it faster and more accurate for code creation. ChatGPT requires careful prompt engineering and often mixes explanations with code. Swapcode delivers pure, ready-to-use code optimized for your exact needs, with no fluff. Plus, Swapcode offers a dedicated interface designed specifically for developers—no chat history to manage, just instant code generation.
Swapcode vs GitHub Copilot
GitHub Copilot excels at autocomplete and in-editor suggestions as you type. It's fantastic for incremental coding. However, Swapcode shines when you need complete functions, classes, or modules generated from scratch. You don't need an IDE integration—just describe what you need, and get complete, working code instantly. Swapcode is perfect for planning architecture, generating boilerplate, or quickly prototyping ideas before you even open your code editor. It's also completely free with no subscription required, whereas Copilot requires a paid plan.
Your Key Advantages
- Dedicated Code Focus: 100% specialized for code generation, not general AI tasks
- Complete Code Blocks: Generate entire functions, classes, and modules, not just snippets
- Framework-Aware: Understands React, Django, Spring Boot, Flask patterns automatically
- No Context Switching: Standalone tool—no need to interrupt your IDE workflow
- Free Trial Plan: Start with limited attempts per day, no credit card required
- Instant Results: Optimized for speed—typically under 2 seconds
Real-World Example:
Prompt: "Generate a Python Flask API endpoint that accepts user registration data, validates email format, hashes password with bcrypt, saves to PostgreSQL, and returns a JWT token"
Result: Swapcode generates complete, production-ready code with all imports, error handling, and best practices in 2 seconds. ChatGPT would require multiple prompts and clarifications. Copilot would help you write it line by line over several minutes.
Code Generation by Category
Web Development
JavaScript - React Component with State
Prompt: "Generate React component with useState for counter with increment and decrement buttons"
import React, { useState } from 'react';
function Counter() {
const [count, setCount] = useState(0);
return (
<div className="counter">
<h2>Count: {count}</h2>
<button onClick={() => setCount(count + 1)}>Increment</button>
<button onClick={() => setCount(count - 1)}>Decrement</button>
<button onClick={() => setCount(0)}>Reset</button>
</div>
);
}
export default Counter;Python - Flask API Endpoint
Prompt: "Create Flask API endpoint to fetch user data with error handling"
from flask import Flask, jsonify, request
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
@app.route('/api/users/<int:user_id>', methods=['GET'])
def get_user(user_id):
try:
user = User.query.get(user_id)
if not user:
return jsonify({'error': 'User not found'}), 404
return jsonify({
'id': user.id,
'name': user.name,
'email': user.email
}), 200
except Exception as e:
return jsonify({'error': str(e)}), 500PHP - Laravel Controller CRUD
Prompt: "Generate Laravel controller for CRUD operations on Product model"
namespace App\Http\Controllers;
use App\Models\Product;
use Illuminate\Http\Request;
class ProductController extends Controller {
public function index() {
return Product::all();
}
public function store(Request $request) {
$validated = $request->validate([
'name' => 'required|max:255',
'price' => 'required|numeric'
]);
return Product::create($validated);
}
public function update(Request $request, Product $product) {
$product->update($request->all());
return $product;
}
public function destroy(Product $product) {
$product->delete();
return response()->json(null, 204);
}
}Data Processing
Python - CSV Processing
Prompt: "Generate function to parse CSV and calculate averages by category"
import pandas as pd
def calculate_category_averages(csv_file):
"""Read CSV and calculate average values by category"""
df = pd.read_csv(csv_file)
# Group by category and calculate mean
averages = df.groupby('category')['value'].mean()
return averages.to_dict()SQL - Analytics Query
Prompt: "Generate query to get top 10 products by revenue with category names"
SELECT
p.product_name,
c.category_name,
SUM(oi.quantity * oi.unit_price) as total_revenue
FROM products p
JOIN categories c ON p.category_id = c.id
JOIN order_items oi ON p.id = oi.product_id
GROUP BY p.id, p.product_name, c.category_name
ORDER BY total_revenue DESC
LIMIT 10;Mobile Development
Swift - iOS View Controller
Prompt: "Generate iOS view controller with table view for displaying user list"
import UIKit
class UserListViewController: UIViewController, UITableViewDelegate, UITableViewDataSource {
let tableView = UITableView()
var users: [User] = []
override func viewDidLoad() {
super.viewDidLoad()
setupTableView()
loadUsers()
}
func setupTableView() {
tableView.delegate = self
tableView.dataSource = self
tableView.register(UITableViewCell.self, forCellReuseIdentifier: "cell")
view.addSubview(tableView)
}
func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
return users.count
}
func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
let cell = tableView.dequeueReusableCell(withIdentifier: "cell", for: indexPath)
cell.textLabel?.text = users[indexPath.row].name
return cell
}
}Kotlin - Android Fragment
Prompt: "Create Android fragment with RecyclerView for product list"
class ProductListFragment : Fragment() {
private lateinit var recyclerView: RecyclerView
private lateinit var adapter: ProductAdapter
override fun onCreateView(
inflater: LayoutInflater,
container: ViewGroup?,
savedInstanceState: Bundle?
): View? {
val view = inflater.inflate(R.layout.fragment_product_list, container, false)
recyclerView = view.findViewById(R.id.recyclerView)
recyclerView.layoutManager = LinearLayoutManager(context)
adapter = ProductAdapter(getProducts())
recyclerView.adapter = adapter
return view
}
}How to Write Better Prompts
Bad Prompt:
"make a function"
Too vague—AI doesn't know what language, what the function should do, or what inputs/outputs are needed.
Good Prompt:
"Generate a Python function that takes a list of integers, removes duplicates, sorts in ascending order, and returns the result"
Specific about language, inputs, processing steps, and output format.
Bad Prompt:
"login code"
Good Prompt:
"Generate JavaScript code for a login form that validates email format, checks password length (min 8 chars), and makes POST request to /api/login endpoint with error handling"
Prompt Template:
"Generate [LANGUAGE] code that [ACTION] which [REQUIREMENTS] and [HANDLES] [EDGE CASES]"
Pro Tips for Better Results:
Be Specific About Inputs and Outputs
Specify data types, formats, and expected return values
Mention Error Handling Needs
Tell the AI what errors to catch and how to handle them
Specify Libraries/Frameworks
If relevant, mention specific libraries (pandas, React, etc.)
Include Edge Cases to Handle
Empty inputs, null values, invalid data, etc.
When to Use vs When to Write Manually
Perfect for AI Generation
- ✓ Boilerplate Code
CRUD operations, form handlers, API clients
- ✓ Standard Patterns
Database connections, authentication flows, file handling
- ✓ Repetitive Tasks
Data validation, formatting, parsing utilities
- ✓ Learning Syntax
See examples in new languages you're learning
- ✓ Quick Prototypes
Test ideas fast before full implementation
Review Carefully
- ⚠ Business Logic
AI may not understand your specific requirements fully
- ⚠ Security-Critical Code
Authentication, encryption—always audit carefully
- ⚠ Performance-Optimized
May need manual tuning for speed-critical paths
Write Manually
- ✗ Core Business Logic
Domain-specific rules with nuanced requirements
- ✗ Novel Algorithms
AI is trained on existing patterns, not inventions
- ✗ Deep Architectural Decisions
System design requires human judgment and context
Frequently Asked Questions (FAQs)
What types of code can I generate?
You can generate a wide variety of code, including functions, classes, scripts, boilerplate for web pages or applications, configuration files, and specific algorithms. The more precise your plain English description, the better the AI can tailor the code to your needs across many different programming languages.
Is the generated code production-ready?
While AI Code Generators aim to produce high-quality and efficient code, it should be considered a starting point or a powerful assistant. Always thoroughly review, test, and understand any AI-generated code, especially for security and project-specific requirements, before deploying it in a production environment. Human oversight is crucial.
How does natural language input work for code generation?
You describe the functionality you need in plain English, as if you were explaining it to another developer. The AI model, trained on vast amounts of code and text, interprets your description, identifies the programming logic required, and then translates that into source code in your chosen language. Clarity and specificity in your description usually yield the best results.
Can I use this tool to learn programming?
Absolutely! A Free AI Code Generator can be an excellent learning tool. You can describe a problem and see how it's solved in code, try generating code in different languages to compare syntax, or ask for explanations of generated snippets. It helps bridge the gap between concept and implementation.
Can it generate entire applications?
Swapcode is optimized for generating functions, classes, modules, and code snippets. For entire applications, we recommend breaking down your requirements into smaller components and generating them individually, which also makes the code easier to review and integrate.
What if the generated code has bugs?
If generated code has issues, you can refine your prompt with more specific requirements or use our AI Code Debugger to identify and fix bugs. The more detailed your initial description, the fewer issues you'll encounter.
How do I describe complex requirements?
Break complex requirements into specific details: specify the language, inputs, outputs, error handling, and edge cases. Use our prompt template: "Generate [LANGUAGE] code that [ACTION] which [REQUIREMENTS] and handles [EDGE CASES]".
Does it understand framework-specific patterns (React hooks, Django ORM)?
Yes! Swapcode understands popular frameworks like React, Django, Spring Boot, Flask, and more. Mention the framework in your prompt for framework-specific code generation that follows best practices.
Can it generate code using specific libraries?
Yes, specify the library in your prompt (e.g., 'Generate Python code using pandas to read CSV'). Our AI is trained on popular libraries and frameworks across all major languages.
Is generated code optimized for performance?
Swapcode generates efficient, idiomatic code following best practices for each language. For performance-critical applications, review and profile the generated code, and specify performance requirements in your prompt.
Can it generate tests along with code?
Yes! Request test generation in your prompt (e.g., 'Generate a Python function with unit tests'). Swapcode can create unit tests, integration tests, and test fixtures for most languages.
How does it compare to GitHub Copilot?
Swapcode focuses on complete code generation from descriptions, while Copilot excels at in-editor completion. Swapcode is standalone and free, making it ideal for planning code structure before writing, while Copilot assists during active coding.
Can I use generated code commercially?
Yes, code generated by Swapcode can be used in commercial projects. You own the output. However, always review code for quality, security, and compliance with your project requirements before deployment.
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