lingodotdev 1.2.0

Lingo.dev Python SDK

Lingo.dev Python SDK

A powerful async-first localization engine that supports various content types including plain text, objects, chat sequences, and HTML documents.

✨ Key Features

• 🚀 Async-first design for high-performance concurrent translations
• 🔀 Concurrent processing for dramatically faster bulk translations
• 🎯 Multiple content types: text, objects, chat messages, and more
• 🌐 Auto-detection of source languages
• ⚡ Fast mode for quick translations
• 🔧 Flexible configuration with progress callbacks
• 📦 Context manager support for proper resource management

🚀 Performance Benefits

The async implementation provides significant performance improvements:

• Concurrent chunk processing for large payloads
• Batch operations for multiple translations
• Parallel API requests instead of sequential ones
• Better resource management with httpx

📦 Installation

pip install lingodotdev

🎯 Quick Start

Simple Translation

import asyncio
from lingodotdev import LingoDotDevEngine

async def main():
    # Quick one-off translation (handles context management automatically)
    result = await LingoDotDevEngine.quick_translate(
        "Hello, world!",
        api_key="your-api-key",
        target_locale="es"
    )
    print(result)  # "¡Hola, mundo!"

asyncio.run(main())

Context Manager (Recommended for Multiple Operations)

import asyncio
from lingodotdev import LingoDotDevEngine

async def main():
    config = {
        "api_key": "your-api-key",
        "api_url": "https://engine.lingo.dev"  # Optional, defaults to this
    }
    
    async with LingoDotDevEngine(config) as engine:
        # Translate text
        text_result = await engine.localize_text(
            "Hello, world!",
            {"target_locale": "es"}
        )
        
        # Translate object with concurrent processing
        obj_result = await engine.localize_object(
            {
                "greeting": "Hello",
                "farewell": "Goodbye",
                "question": "How are you?"
            },
            {"target_locale": "es"},
            concurrent=True  # Process chunks concurrently for speed
        )

asyncio.run(main())

🔥 Advanced Usage

Batch Processing (Multiple Target Languages)

async def batch_example():
    # Translate to multiple languages at once
    results = await LingoDotDevEngine.quick_batch_translate(
        "Welcome to our application",
        api_key="your-api-key",
        target_locales=["es", "fr", "de", "it"]
    )
    # Results: ["Bienvenido...", "Bienvenue...", "Willkommen...", "Benvenuto..."]

Large Object Processing with Progress

async def progress_example():
    def progress_callback(progress, source_chunk, processed_chunk):
        print(f"Progress: {progress}% - Processed {len(processed_chunk)} items")

    large_content = {f"item_{i}": f"Content {i}" for i in range(1000)}
    
    async with LingoDotDevEngine({"api_key": "your-api-key"}) as engine:
        result = await engine.localize_object(
            large_content,
            {"target_locale": "es"},
            progress_callback=progress_callback,
            concurrent=True  # Much faster for large objects
        )

Chat Translation

async def chat_example():
    chat_messages = [
        {"name": "Alice", "text": "Hello everyone!"},
        {"name": "Bob", "text": "How is everyone doing?"},
        {"name": "Charlie", "text": "Great to see you all!"}
    ]
    
    async with LingoDotDevEngine({"api_key": "your-api-key"}) as engine:
        translated_chat = await engine.localize_chat(
            chat_messages,
            {"source_locale": "en", "target_locale": "es"}
        )
        # Names preserved, text translated

Multiple Objects Concurrently

async def concurrent_objects_example():
    objects = [
        {"title": "Welcome", "description": "Please sign in"},
        {"error": "Invalid input", "help": "Check your email"},
        {"success": "Account created", "next": "Continue to dashboard"}
    ]
    
    async with LingoDotDevEngine({"api_key": "your-api-key"}) as engine:
        results = await engine.batch_localize_objects(
            objects,
            {"target_locale": "fr"}
        )
        # All objects translated concurrently

Language Detection

async def detection_example():
    async with LingoDotDevEngine({"api_key": "your-api-key"}) as engine:
        detected = await engine.recognize_locale("Bonjour le monde")
        print(detected)  # "fr"

⚙️ Configuration Options

config = {
    "api_key": "your-api-key",              # Required: Your API key
    "api_url": "https://engine.lingo.dev",  # Optional: API endpoint
    "batch_size": 25,                       # Optional: Items per batch (1-250)
    "ideal_batch_item_size": 250            # Optional: Target words per batch (1-2500)
}

🎛️ Method Parameters

Translation Parameters

• source_locale: Source language code (auto-detected if None)
• target_locale: Target language code (required)
• fast: Enable fast mode for quicker translations
• reference: Reference translations for context
• concurrent: Process chunks concurrently (faster, but no progress callbacks)

Performance Options

• concurrent=True: Enables parallel processing of chunks
• progress_callback: Function to track progress (disabled with concurrent=True)

🔧 Error Handling

async def error_handling_example():
    try:
        async with LingoDotDevEngine({"api_key": "invalid-key"}) as engine:
            result = await engine.localize_text("Hello", {"target_locale": "es"})
    except ValueError as e:
        print(f"Invalid request: {e}")
    except RuntimeError as e:
        print(f"API error: {e}")

🚀 Performance Tips

1. Use concurrent=True for large objects or multiple chunks
2. Use batch_localize_objects() for multiple objects
3. Use context managers for multiple operations
4. Use quick_translate() for one-off translations
5. Adjust batch_size based on your content structure

🤝 Migration from Sync Version

The async version is a drop-in replacement with these changes:

• Add async/await to all method calls
• Use async with for context managers
• All methods now return awaitable coroutines

📚 API Reference

Core Methods

• localize_text(text, params) - Translate text strings
• localize_object(obj, params) - Translate dictionary objects
• localize_chat(chat, params) - Translate chat messages
• batch_localize_text(text, params) - Translate to multiple languages
• batch_localize_objects(objects, params) - Translate multiple objects
• recognize_locale(text) - Detect language
• whoami() - Get API account info

Convenience Methods

• quick_translate(content, api_key, target_locale, ...) - One-off translation
• quick_batch_translate(content, api_key, target_locales, ...) - Batch translation

📄 License

Apache-2.0 License

🤖 Support

• 📚 Documentation
• 🐛 Issues
• 💬 Community