Free AI Code Converter

Convert code between any programming languages while preserving logic and maintaining code quality. Powered by AI for accurate translations.

100+ Languages

Convert between any programming languages

Preserve Logic

Maintain functionality and code structure

Instant Results

Get converted code in seconds

Code Converter
INPUT
0 chars • 1 lines
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GENERATED OUTPUT
0 chars • 1 lines
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Hint: Paste your code, select source and target languages, then click Convert to translate your code.

We never store your code

Convert Between 100+ Languages

Select any source and target language combination. Our AI supports conversions between all major programming languages.

How Swapcode's AI Conversion Works

Swapcode's AI-powered code conversion leverages advanced machine learning algorithms trained on millions of code samples across 100+ programming languages. When you submit code for conversion, our intelligent system analyzes the source code's structure, logic patterns, and syntax to create an accurate translation that preserves functionality while optimizing for the target language's best practices.

The conversion process begins with deep syntactic analysis, where our AI identifies variables, functions, classes, control flow, and data structures. It then maps these elements to their equivalents in the target language, ensuring type compatibility and maintaining the original code's intent. The AI handles edge cases intelligently, converting language-specific features like Python's list comprehensions into Java streams or JavaScript's promises into async/await patterns in other languages.

Comments and documentation are preserved and translated appropriately, converting them to match the target language's documentation standards. Variable names remain consistent unless they conflict with reserved keywords in the target language. Our AI also optimizes code structure, applying idiomatic patterns specific to each language to ensure the converted code doesn't just work-it looks natural to developers familiar with that language.

1

Input Code

Paste your source code in any supported language

2

AI Analysis

Our AI analyzes structure, patterns, and logic flow

3

Optimized Output

Get clean, functional code in your target language

Real Conversion Examples

Example 1: Python to Java - Simple Function

Python (Source)

def calculate_average(numbers):
    """Calculate the average of a list"""
    if not numbers:
        return 0
    return sum(numbers) / len(numbers)

result = calculate_average([10, 20, 30, 40])
print(f"Average: {result}")

Java (Target)

/**
 * Calculate the average of a list
 */
public static double calculateAverage(List<Integer> numbers) {
    if (numbers == null || numbers.isEmpty()) {
        return 0.0;
    }
    return numbers.stream().mapToInt(Integer::intValue).average().orElse(0.0);
}

double result = calculateAverage(Arrays.asList(10, 20, 30, 40));
System.out.println("Average: " + result);

Notice how Python's dynamic typing converts to Java's static types, and the simple sum/length calculation becomes a modern Java stream operation.

Example 2: JavaScript to TypeScript - Adding Type Safety

JavaScript (Source)

function fetchUser(userId) {
    return fetch(`/api/users/${userId}`)
        .then(response => response.json())
        .then(data => {
            return {
                name: data.name,
                email: data.email
            };
        });
}

TypeScript (Target)

interface User {
    name: string;
    email: string;
}

async function fetchUser(userId: string): Promise<User> {
    const response = await fetch(`/api/users/${userId}`);
    const data = await response.json();
    return {
        name: data.name,
        email: data.email
    };
}

The AI automatically adds TypeScript type annotations and converts promise chains to async/await for cleaner, more maintainable code.

Example 3: C++ to Rust - Memory Safety

C++ (Source)

int* createArray(int size) {
    int* arr = new int[size];
    for(int i = 0; i < size; i++) {
        arr[i] = i * 2;
    }
    return arr;
}
// Remember to delete[] arr later!

Rust (Target)

fn create_array(size: usize) -> Vec<i32> {
    let mut arr = Vec::with_capacity(size);
    for i in 0..size {
        arr.push((i * 2) as i32);
    }
    arr
}
// Memory automatically managed!

Manual memory management in C++ is converted to Rust's safe ownership system, eliminating potential memory leaks and dangling pointers.

Example 4: Visual Basic to C# - Modernization

Visual Basic (Source)

Public Function GetFullName(firstName As String, lastName As String) As String
    Dim fullName As String
    fullName = firstName & " " & lastName
    Return fullName.Trim()
End Function

C# (Target)

public string GetFullName(string firstName, string lastName)
{
    string fullName = $"{firstName} {lastName}";
    return fullName.Trim();
}

// Or more concisely:
public string GetFullName(string firstName, string lastName) => 
    $"{firstName} {lastName}".Trim();

Legacy VB code is modernized to idiomatic C# with string interpolation and expression-bodied members for cleaner syntax.

When to Use a Code Converter

Best For:

  • Legacy Migration: Moving from outdated languages (COBOL, Visual Basic) to modern ones (Java, C#)
  • Cross-Platform Development: Converting iOS Swift apps to Android Kotlin or vice versa
  • Learning New Syntax: Understanding how familiar code patterns translate to a new language

Ideal Scenarios:

  • Converting Working Code: You have tested, functional code that needs to run in a different language
  • Batch Conversions: Multiple utility functions or helper classes to migrate
  • Prototyping: Quickly testing if an algorithm works in your target environment
  • Team Transitions: Helping developers understand codebases in unfamiliar languages

Review Needed:

  • Complex Business Logic: AI does great with syntax, but verify business rules are preserved
  • Performance-Critical Code: May need manual optimization for specific runtime characteristics
  • Security-Sensitive Code: Always audit authentication, encryption, and data handling logic

Not Recommended:

  • From-Scratch Projects: Better to design for your target language from the start
  • Highly Custom Algorithms: Novel algorithms with no clear language equivalents
  • Complex Framework Code: Deep framework integrations may need architectural redesign

Decision Checklist:

  • Is your source code tested and working?
  • Do both languages have similar paradigms (both OOP, both functional, etc.)?
  • Are you prepared to review and test the converted code?
  • Can you identify and replace any language-specific libraries?

If you answered yes to all, code conversion is an excellent choice!

Swapcode vs Other Solutions

Feature Swapcode ChatGPT GitHub Copilot Manual
Speed Instant Slow Fast Very Slow
Accuracy 98% 85% 80% 100%
Dedicated Tool Yes No No N/A
Batch Convert Yes No No No
100+ Languages Yes Yes Yes Yes
Free Trial Limited Limited No Yes
Logic Preservation Excellent Variable Variable Excellent

Speed: Swapcode is optimized specifically for code conversion, processing in under 2 seconds. ChatGPT requires prompt engineering and back-and-forth. GitHub Copilot is fast but focused on completion, not conversion. Manual conversion takes hours or days.

Accuracy: Our 98% accuracy comes from specialized training on conversion tasks. General-purpose AI tools (ChatGPT, Copilot) handle many tasks but aren't optimized for translation fidelity. Manual conversion is 100% accurate but time-intensive.

Dedicated Tool: Swapcode is purpose-built for code conversion with specialized features like batch processing, syntax mapping tables, and conversion history. Other AI tools are generalists.

Logic Preservation: Swapcode's training specifically emphasizes maintaining program behavior across languages. General AI tools may generate functionally different code that "looks right" but behaves differently.

Use Case: Choose Swapcode for efficient, reliable code translation. Use ChatGPT for explanations and learning. Use Copilot for code completion while writing. Use manual conversion when absolute precision is required and time isn't constrained.

Use Cases & Success Stories

Enterprise Migration

Financial Services Company

A major financial institution needed to migrate their legacy COBOL mainframe systems to modern Java microservices. Using Swapcode, they converted 50,000+ lines of business logic in just 3 weeks-a process that would have taken 6 months manually.

50K+
Lines Converted
80%
Time Saved
$500K
Cost Savings

Startup Performance Boost

SaaS Platform

A fast-growing startup built their MVP in Python for rapid development. As they scaled, they needed Java's performance. Swapcode converted their 15,000-line Python backend to production-ready Java in 2 weeks, achieving 3x performance improvement without missing their deadline.

15K
Lines Migrated
3x
Performance Gain
2wks
Total Time

Learning Rust

Systems Programmer

Experienced C++ developers used Swapcode to learn Rust by converting their existing projects. By seeing familiar algorithms translated into Rust's ownership system, they mastered the language in half the usual time, with 40+ projects converted as learning exercises.

40+
Projects
50%
Faster Learning
100%
Satisfaction

Cross-Platform Mobile

Mobile App Developer

A successful iOS app (25K lines of Swift) needed an Android version. Swapcode converted the business logic and UI components to Kotlin, reducing development time from 8 months to 2 months. The Android app launched with feature parity to the iOS version.

25K
Lines Converted
75%
Time Saved
2mo
Launch Time

Frequently Asked Questions (FAQs)

What's the difference between an AI code converter and an AI code generator?

An AI code converter primarily focuses on translating existing code from one programming language to another, aiming to preserve the original logic. An AI code generator, on the other hand, creates new code from scratch based on natural language prompts or partial code snippets, often assisting in tasks like boilerplate generation, function creation, or even generating entire application scaffolds.

What's your conversion accuracy rate?

Swapcode maintains a 98% accuracy rate for code conversions across all supported languages. Our AI is trained on millions of code examples and continuously improves through machine learning, ensuring high-quality, logic-preserving translations.

Can you convert entire projects or just code snippets?

Swapcode can handle both individual code snippets and entire files. For complete project migration, you can convert files one at a time or use our batch conversion feature to process multiple files efficiently while maintaining consistent syntax and structure.

How do you handle third-party libraries and dependencies?

Our AI recognizes common third-party libraries and suggests equivalent libraries in the target language. For example, when converting from Python's NumPy to Java, we recommend Java libraries like Apache Commons Math or ND4J that provide similar functionality.

Do you support framework-specific code (React, Django, Spring)?

Yes! Swapcode understands framework-specific patterns and idioms. We can convert React components to Vue or Angular, Django views to Flask or Spring Boot, and many other framework-to-framework translations while preserving the architectural patterns.

What happens to code comments during conversion?

Code comments are preserved and translated during conversion. Our AI maintains documentation quality by converting comments to the target language's documentation standards (e.g., Python docstrings to Java Javadoc format).

Can I convert SQL queries between different database dialects?

Absolutely! Swapcode handles SQL dialect conversions between MySQL, PostgreSQL, SQL Server, Oracle, and more. We automatically convert syntax differences, data types, and database-specific functions to their equivalents in the target dialect.

Is my code stored or shared with others?

No. Your code is processed in real-time and is never stored on our servers or shared with third parties. We prioritize your privacy and security, ensuring your intellectual property remains confidential.

Do you support mobile app code conversion (Swift to Kotlin)?

Yes! Swapcode excels at mobile code conversion. We can convert iOS Swift code to Android Kotlin (and vice versa), translating UI frameworks (UIKit to Android Views/Jetpack Compose), networking code, and platform-specific features.

Can you convert between different versions of the same language?

Yes, we support version-to-version migrations such as Python 2 to Python 3, Java 8 to Java 17, JavaScript ES5 to ES6+, and more. Our AI identifies deprecated features and converts them to modern equivalents.

How do you handle language-specific features that don't exist in the target?

When a feature doesn't have a direct equivalent, our AI implements functionally equivalent code using the target language's capabilities. For example, Python's list comprehensions are converted to Java streams, and C# LINQ queries are translated to appropriate Python constructs.

What file formats can I upload?

Swapcode supports standard source code files (.py, .java, .js, .cpp, .cs, .rb, .php, .go, .swift, .kt, etc.) as well as plain text files containing code. Simply paste your code or upload the file directly.

Is there a size limit for code conversion?

All plans support up to 20,000 characters per conversion with the same advanced features. The free Trial plan allows limited attempts per day. The Monthly plan provides unlimited conversions and priority processing.

Can I use this via API for automation?

Yes, Swapcode offers a REST API for automated code conversion workflows. Perfect for CI/CD pipelines, batch processing, or integrating conversion into your development tools. API access is available on our premium plans.

How long does a typical conversion take?

Most conversions complete in under 2 seconds for standard code snippets. Larger files (1,000+ lines) may take 5-10 seconds. Our AI is optimized for speed without sacrificing accuracy.

Do you offer batch conversion for multiple files?

Yes! Our batch conversion feature allows you to upload and convert multiple files simultaneously, maintaining consistent code style and structure across your entire project. This is especially useful for large-scale migration projects.