metricsfirst 0.1.6

MetricsFirst SDK for Python - Analytics for Telegram bots

MetricsFirst Python SDK

Official Python SDK for MetricsFirst - Analytics for Telegram bots.

Note: Commands and interactions are tracked automatically when you add your bot to MetricsFirst. This SDK is for tracking custom events like services, purchases, and errors.

Installation

# Basic installation (sync only)
pip install metricsfirst

# With async support
pip install metricsfirst[async]

Features

• Fire-and-forget: All tracking calls are non-blocking and don't add latency
• Background sending: Events are sent in a separate thread (sync) or task (async)
• Error resilience: Errors are logged, never thrown to your code
• Memory safe: Queue is limited to 1000 events to prevent memory issues
• Custom Events: Track any event with dynamic properties (Mixpanel-style)

Quick Start

Custom Events (Mixpanel-style)

Track any event with dynamic properties:

from metricsfirst import MetricsFirst

mf = MetricsFirst(
    bot_id="your_bot_id",
    api_key="your_api_key",
)

# Track custom events with any properties
mf.track('STORY_RESPONSE', {
    'target': 'username123',
    'url': 'https://example.com/story',
    'response_time_ms': 150,
    'success': True,
}, user_id=123456789)

mf.track('BUTTON_CLICK', {
    'button_name': 'premium_upgrade',
    'screen': 'main_menu',
}, user_id=123456789)

mf.track('VIDEO_DOWNLOADED', {
    'duration_seconds': 45,
    'quality': '1080p',
    'source': 'instagram',
}, user_id=123456789)

mf.shutdown()

Synchronous Client

from metricsfirst import MetricsFirst, ServiceEventData

# Initialize
mf = MetricsFirst(
    bot_id="your_bot_id",
    api_key="your_api_key",
)

# Track a service (fire-and-forget, non-blocking)
mf.track_service(ServiceEventData(
    user_id=123456789,
    service_name="image_generation",
    is_free=False,
    price=10,
    currency="USD",
))

# Shutdown flushes remaining events
mf.shutdown()

Asynchronous Client

import asyncio
from metricsfirst import AsyncMetricsFirst, ServiceEventData

async def main():
    # Initialize
    mf = AsyncMetricsFirst(
        bot_id="your_bot_id",
        api_key="your_api_key",
    )
    await mf.start()

    # Track events (fire-and-forget)
    await mf.track_service(ServiceEventData(
        user_id=123456789,
        service_name="image_generation",
    ))

    # Shutdown
    await mf.shutdown()

asyncio.run(main())

Context Manager

# Sync
with MetricsFirst(bot_id="...", api_key="...") as mf:
    mf.track_service(...)

# Async
async with AsyncMetricsFirst(bot_id="...", api_key="...") as mf:
    await mf.track_service(...)

Available Methods

Method	Description
track()	Track custom events with any properties
track_service()	Track services provided
track_error()	Track errors
track_error_from_exception()	Track error from exception
track_purchase_initiated()	Track purchase start
track_purchase_completed()	Track successful purchase
track_purchase_error()	Track failed purchase
track_recurring_charge_success()	Track subscription charge
track_recurring_charge_failed()	Track failed charge
identify()	Identify user with properties

track() - Custom Events

mf.track(
    event_name: str,              # Event name (e.g., 'STORY_RESPONSE')
    properties: dict = None,      # Any key-value pairs
    user_id: int = None,          # Telegram user ID
    distinct_id: str = None,      # Alternative ID for anonymous users
    time: float = None,           # Unix timestamp (defaults to now)
)

Configuration

mf = MetricsFirst(
    bot_id="your_bot_id",
    api_key="your_api_key",
    api_url="https://api.metricsfirst.com",  # Custom API URL
    batch_events=True,      # Batch events before sending
    batch_size=10,          # Events per batch
    batch_interval=5.0,     # Seconds between flushes
    debug=False,            # Enable debug logging
    timeout=10.0,           # HTTP timeout
)

License

MIT