xcstrings-translator

🚀 Project Overview

xcstrings-translator is a powerful command-line tool specifically designed for translating Localizable.xcstrings files for iOS/macOS applications. This tool supports multiple translation service providers and boasts high-performance concurrent translation capabilities.

Read this in other languages: 中文

✨ Core Functionality

🔌 Multi-Translation Service Support

• Google Translate API: Supports neural machine translation models
• DeepL API: Provides high-quality translation, supporting both free and professional versions
• Baidu Translate API: Baidu Translate service
• OpenAI API: Supports translation capabilities of GPT series models

⚡ High-Performance Concurrency

• Concurrency control based on Worker Pool mode
• Configurable number of concurrent requests
• Elegant error handling and retry mechanism
• Context timeout control

📁 xcstrings File Processing

• Complete parsing and generation of xcstrings JSON format
• Intelligent detection of strings requiring translation
• Preserve original translations, translating only missing language versions
• Maintain file structure and metadata integrity

⚙️ Flexible Configuration

• Support for YAML configuration files
• Environment variable support
• Command-line flag overrides

🛠️ Technical Implementation

🏗️ Architecture design

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│   CLI Layer     │     │  Service Layer  │     │ Provider Layer  │
│  (Cobra Commands)│────▶│ (Concurrency &  │────▶│ (Translation    │
│                 │     │   Translation)  │     │  Implementations)│
└─────────────────┘     └─────────────────┘     └─────────────────┘
        ▲                       ▲                       ▲
        │                       │                       │
        ▼                       ▼                       ▼
┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│   User Input    │     │  Model Layer    │     │  HTTP Client    │
│  (Flags/Args)   │     │ (Data Structures)│     │  (resty)        │
└─────────────────┘     └─────────────────┘     └─────────────────┘

📊 Concurrency Model

• Concurrency is achieved using Goroutines and Channels
• Concurrency is controlled using the Worker Pool pattern
• Timeout control is implemented using the Context mechanism
• WaitGroup waits for all tasks to complete

🔧 Main Technology Stack

• Go 1.21+: Main programming language
• Cobra: CLI framework
• resty: HTTP client
• JSON: xcstrings file format processing
• MD5: Baidu API signature generation

Installation

To install, run:

go install github.com/fdddf/xcstrings-translator@latest

Or download the binary from the releases page.

📋 Usage Examples

Using Configuration File

# Use default config.yaml
xcstrings-translator google

# Use specific config file
xcstrings-translator --config myconfig.yaml google

# Override specific settings from command line
xcstrings-translator --input custom.xcstrings -t "es" -t "fr" google

Google Translate

xcstrings-translator google \ 
--api-key "AIzaSy..." \ 
--input "Localizable.xcstrings" \ 
--output "Localizable_zh.xcstrings" \ 
--source-language "en" \ 
--target-languages ​​"zh-Hans" "ja" \ 
--concurrency 10 \ 
--verbose

DeepL

xcstrings-translator deepl \ 
--api-key "2a7f4..." \ 
--free \ 
--input "Localizable.xcstrings" \ 
--output "Localizable_translated.xcstrings" \ 
--target-languages ​​"zh-Hans"

Baidu Translate

xcstrings-translator baidu \ 
--app-id "2024..." \ 
--app-secret "f4K..." --input "Localizable.xcstrings" --output "Localizable_baidu.xcstrings"

OpenAI

xcstrings-translator openai
--api-key "sk-proj..."
--model "gpt-4"
--input "Localizable.xcstrings" --output "Localizable_ai.xcstrings"

Visual Web UI

# Build the Vue/Tailwind UI (once, or after editing web/)
cd web && npm install && npm run build

# Start the embedded Fiber server
xcstrings-translator serve --addr :8080

Upload a Localizable.xcstrings file, choose target languages, run batch translation with your provider keys, and export the updated file directly from the browser. Progress is streamed; translated keys appear in the grid in real time so you don’t lose work if rate limits interrupt a long run.

Native desktop app (Windows/macOS/Linux)

The CLI also ships with a native window that embeds the same UI, so you don’t need to keep a browser tab open:

# Launch the desktop window (resizes freely)
xcstrings-translator gui --width 1400 --height 900

Prerequisites:

• Windows: WebView2 runtime (installed by default on modern Windows 10/11; otherwise install from Microsoft).
• macOS: uses built-in WebKit (no extra install).
• Linux: needs WebKitGTK (e.g. sudo apt install libwebkit2gtk-4.1-dev on Debian/Ubuntu).

Build platform-specific binaries from any host:

# macOS
GOOS=darwin GOARCH=arm64 go build -o bin/xcstrings-translator-darwin ./...

# Windows
GOOS=windows GOARCH=amd64 go build -o bin/xcstrings-translator.exe ./...

# Linux
GOOS=linux GOARCH=amd64 go build -o bin/xcstrings-translator-linux ./...

These builds are CGO-enabled; make sure the target platform’s toolchain and WebView dependencies are present (Xcode Command Line Tools on macOS, WebView2 SDK/MinGW on Windows, WebKitGTK dev packages on Linux).

🔒 Security Features

• API keys are passed via command-line arguments or environment variables
• No sensitive information is stored
• HTTPS encrypted transmission
• Input validation and error handling

📈 Performance Optimizations

• Connection pool reuse
• Batch request processing
• Intelligent retry mechanism
• Efficient memory management

🎯 Applicable Scenarios

• iOS/macOS application localization
• Batch translation of string resources
• CI/CD pipeline integration
• Multilingual application development

📚 Scalability

• Easy addition of new translation service providers
• Support for custom translation rules
• Integration into automated workflows
• Support for batch translation of large projects

🔮 Future Feature Plans

• Translation caching mechanism
• Translation quality assessment
• Batch file processing
• Translation memory
• Interactive translation confirmation

🤝 Contribution Guidelines Contributions, problem reporting, and suggestions are welcome. The project uses a standard GitHub workflow:

1. Fork the project
2. Create a feature branch
3. Submit changes
4. Create a pull request

📄 License This project is licensed under the MIT license. Please see the LICENSE file for details.