apple-appstore-connect-client 1.0.5

A comprehensive Python client for the Apple App Store Connect API

appstore-connect-client

A comprehensive Python client for the Apple App Store Connect API, providing simple and intuitive interfaces for sales reporting, app metadata management, and advanced analytics.

Features

• 📊 Sales & Financial Reporting - Daily, weekly, monthly sales and revenue data
• 🎯 App Metadata Management - Update app listings, descriptions, and keywords
• 📈 Advanced Analytics - Period comparisons, performance ranking, trend analysis
• 💳 Subscription Analytics - Active subscriptions, events, and lifecycle metrics
• 🌍 Localization Support - Multi-language content management
• 🚀 Batch Operations - Update multiple apps simultaneously
• 🔐 Secure Authentication - JWT ES256 token-based auth
• ⚡ Smart Rate Limiting - Automatic handling of API limits (50 requests/hour)
• 🐼 Pandas Integration - DataFrames for easy data manipulation
• ✅ Type Hints - Full type support for better IDE experience

Installation

pip install appstore-connect-client

For development:

pip install appstore-connect-client[dev]

Quick Start

from appstore_connect import AppStoreConnectAPI
from datetime import date, timedelta

# Initialize the client
client = AppStoreConnectAPI(
    key_id="your_key_id",
    issuer_id="your_issuer_id",
    private_key_path="/path/to/AuthKey_XXXXXX.p8",
    vendor_number="your_vendor_number"
)

# Get yesterday's sales data
yesterday = date.today() - timedelta(days=1)
sales_df = client.get_sales_report(yesterday)
print(f"Revenue: ${sales_df['proceeds'].sum():,.2f}")

Authentication

Prerequisites

1. Apple Developer Account with App Store Connect access
2. App Store Connect API Key (generate here)
3. Private key file (.p8) downloaded from App Store Connect
4. Vendor number from your App Store Connect account

Setting up credentials

You can provide credentials in three ways:

1. Direct parameters (recommended)

client = AppStoreConnectAPI(
    key_id="your_key_id",
    issuer_id="your_issuer_id",
    private_key_path="/path/to/private_key.p8",
    vendor_number="your_vendor_number"
)

2. Environment variables

export APP_STORE_KEY_ID="your_key_id"
export APP_STORE_ISSUER_ID="your_issuer_id"
export APP_STORE_PRIVATE_KEY_PATH="/path/to/private_key.p8"
export APP_STORE_VENDOR_NUMBER="your_vendor_number"

import os
client = AppStoreConnectAPI(
    key_id=os.getenv('APP_STORE_KEY_ID'),
    issuer_id=os.getenv('APP_STORE_ISSUER_ID'),
    private_key_path=os.getenv('APP_STORE_PRIVATE_KEY_PATH'),
    vendor_number=os.getenv('APP_STORE_VENDOR_NUMBER')
)

3. Using .env file

Create a .env file based on .env.example and the client will load it automatically in development.

Usage Examples

Sales Reporting

# Get comprehensive 30-day analytics
from appstore_connect import create_report_processor

processor = create_report_processor(
    key_id=os.getenv('APP_STORE_KEY_ID'),
    issuer_id=os.getenv('APP_STORE_ISSUER_ID'),
    private_key_path=os.getenv('APP_STORE_PRIVATE_KEY_PATH'),
    vendor_number=os.getenv('APP_STORE_VENDOR_NUMBER')
)

summary = processor.get_sales_summary(days=30)
print(f"Total Revenue: ${summary['summary']['total_revenue']:,.2f}")
print(f"Total Units: {summary['summary']['total_units']:,}")

# Compare performance periods
comparison = processor.compare_periods(current_days=30, comparison_days=30)
revenue_change = comparison['changes']['total_revenue']['change_percent']
print(f"Revenue Change: {revenue_change:+.1f}%")

App Metadata Management

from appstore_connect import create_metadata_manager

manager = create_metadata_manager(
    key_id=os.getenv('APP_STORE_KEY_ID'),
    issuer_id=os.getenv('APP_STORE_ISSUER_ID'),
    private_key_path=os.getenv('APP_STORE_PRIVATE_KEY_PATH'),
    vendor_number=os.getenv('APP_STORE_VENDOR_NUMBER')
)

# Update app listing
results = manager.update_app_listing(
    app_id='123456789',
    updates={
        'name': 'My Awesome App',
        'subtitle': 'The Best App Ever',
        'description': 'This app will change your life...',
        'keywords': 'productivity,utility,business'
    }
)

# Batch update multiple apps
batch_updates = {
    '123456789': {'subtitle': 'Productivity Booster'},
    '987654321': {'subtitle': 'Entertainment Hub'}
}
results = manager.batch_update_apps(batch_updates)

DataFrame Operations

# Get sales data and calculate weekly totals
import pandas as pd

# Fetch multiple days efficiently
reports = client.fetch_multiple_days(days=90)  # Automatically optimizes API calls

# Calculate weekly revenue
reports['week'] = pd.to_datetime(reports['begin_date']).dt.isocalendar().week
weekly_revenue = reports.groupby('week')['proceeds'].sum()

# Get top performing apps
top_apps = reports.groupby('app_name')['units'].sum().nlargest(10)

API Reference

See API Documentation for complete reference.

Core Components

• AppStoreConnectAPI - Main client for direct API access
• ReportProcessor - High-level analytics with advanced reporting
• MetadataManager - Portfolio management with batch operations

Error Handling

from appstore_connect.exceptions import (
    AuthenticationError,
    RateLimitError,
    ValidationError,
    PermissionError
)

try:
    sales_df = client.get_sales_report(date.today())
except AuthenticationError:
    print("Check your API credentials")
except RateLimitError:
    print("Rate limit exceeded - wait before retrying")
except PermissionError:
    print("Insufficient API key permissions")
except ValidationError as e:
    print(f"Invalid input: {e}")

Best Practices

1. Reuse client instances - Create once and reuse for multiple requests
2. Use smart fetching - Let the client optimize API calls for date ranges
3. Handle rate limits - Built-in retry logic, but be mindful of usage
4. Leverage DataFrames - Use pandas operations for data analysis
5. Secure credentials - Never commit credentials to version control

Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=appstore_connect --cov-report=term-missing

# Run specific test file
pytest tests/test_client.py

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Install development dependencies: pip install -e .[dev]
4. Make your changes and add tests
5. Run tests: python -m pytest
6. Check formatting: python -m black --check src/appstore_connect tests
7. Format code: python -m black src/appstore_connect tests
8. Commit your changes (git commit -m 'Add amazing feature')
9. Push to the branch (git push origin feature/amazing-feature)
10. Open a Pull Request

See CLAUDE.md for detailed development commands.

Documentation

• 📚 Getting Started - Setup and basic usage
• 🔧 API Reference - Complete API documentation
• 🚑 Troubleshooting - Common issues and solutions
• 💡 Examples - Comprehensive usage examples

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• 🐛 Issues: GitHub Issues
• 📖 Documentation: Read the Docs
• 💬 Discussions: GitHub Discussions

Changelog

See CHANGELOG.md for version history and changes.

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Made with ❤️ for iOS developers and app analytics teams