secploy 0.2.7

Event tracking and monitoring SDK for Python applications

Secploy Python SDK

Event tracking, heartbeat monitoring, and real-time status updates for your apps — powered by Secploy.

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📌 Overview

Secploy is a modern security monitoring and observability platform that helps you track events, uptime, and live statuses in real time.

⚙️ Configuration

The Secploy SDK can be configured in multiple ways, providing flexibility for different environments and use cases.

Configuration Methods (in order of precedence)

1. Direct initialization parameters

    client = SecployClient()
   
    config = SecployConfig(
        api_key="your-project-key",
        environment_key="your-key"
        organization_id="your-organization-id",
        environment="production",
        log_level=LogLevel.INFO,
        batch_size=100
    )
   
    client = SecployClient(config=config)
   

2. Configuration file (.secploy or project-name.secploy)

api_key: your-project-api-key
environment_key: key
organization_id: "your-organization-id",
environment: production
debug: true

3. Environment variables

   export SECPLOY_API_KEY=your-api-key
   export SECPLOY_ORGANIZATION_ID=your-organization-id
   export SECPLOY_ENVIRONMENT=production
   export SECPLOY_DEBUG=true
   

Configuration Options

Option	Type	Default	Description
api_key	str	Required	Your Secploy project API key
environment_key	str	Required	Your Secploy environment API key
environment	str	"development"	Environment name (e.g., production, staging)
ingest_url	str	"https://api.secploy.com"	Secploy API endpoint
heartbeat_interval	int	30	Seconds between heartbeat signals
max_retry	int	3	Maximum retry attempts for failed requests
debug	bool	false	Enable debug logging
sampling_rate	float	1.0	Event sampling rate (0.0 to 1.0)
log_level	LogLevel/str	"INFO"	Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
batch_size	int	100	Maximum events per batch
max_queue_size	int	10000	Maximum events in queue before dropping
flush_interval	int	60	Maximum seconds between event batch flushes
retry_attempts	int	3	Number of retry attempts for failed events
ignore_errors	bool	false	Continue on non-critical errors
source_root	str	None	Root directory for source file paths

Configuration File Example

Create a .secploy file in your project root:

# Required settings
api_key: your-api-key
environment_key: key
environment: production

# Event batching
batch_size: 100
flush_interval: 30
max_queue_size: 5000

# Performance
sampling_rate: 0.1 # Sample 10% of events
max_retry: 3
retry_attempts: 2

# Debugging
debug: false
log_level: INFO
ignore_errors: false

# Advanced
source_root: /app
heartbeat_interval: 60
ingest_url: https://api.secploy.com

Environment Variables

All configuration options can be set via environment variables with the SECPLOY_ prefix:

# Required settings
SECPLOY_API_KEY=your-api-key
SECPLOY_ENVIRONMENT_KEY=key
SECPLOY_ENVIRONMENT=production

# Event batching
SECPLOY_BATCH_SIZE=100
SECPLOY_FLUSH_INTERVAL=30
SECPLOY_MAX_QUEUE_SIZE=5000

# Performance
SECPLOY_SAMPLING_RATE=0.1
SECPLOY_MAX_RETRY=3
SECPLOY_RETRY_ATTEMPTS=2

# Debugging
SECPLOY_DEBUG=false
SECPLOY_LOG_LEVEL=INFO
SECPLOY_IGNORE_ERRORS=false

# Advanced
SECPLOY_SOURCE_ROOT=/app
SECPLOY_HEARTBEAT_INTERVAL=60
SECPLOY_INGEST_URL=https://api.secploy.com

With the Secploy Python SDK, you can:

• ✅ Send events from your Python applications or microservices.
• 💓 Monitor uptime & availability using heartbeats.
• 📊 Attach environment and project metadata automatically.
• 📡 Receive live project statuses in your Secploy dashboard (Running, Idle, Shutdown).

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🚀 Installation

Install directly from PyPI:

pip install secploy

Or from source:

git clone https://github.com/your-org/secploy-python-sdk.git
cd secploy-python-sdk
pip install .

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⚡ Quick Start

1️⃣ Initialize the Client

from secploy import SecployClient

client = SecployClient(
    api_key="your_project_api_key",
    environment="production"
)

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2️⃣ Send Events

client.track_event(
    name="user_signup",
    properties={
        "user_id": 101,
        "plan": "pro",
        "referral": "campaign_2025"
    }
)

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3️⃣ Report an Incident

incident = client.create_incident(
    title="High Error Rate",
    description="API error rate exceeded 5% in the EU region.",
    severity="critical"
)
print("Incident ID:", incident.id)

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4️⃣ Monitor Heartbeats

(Ideal for background jobs, services, or scheduled tasks)

import time

while True:
    client.heartbeat()
    time.sleep(60)  # every minute

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5️⃣ Listen for Live Status Updates

(Requires WebSocket + Django Channels backend)

for status in client.listen_status():
    print(f"[STATUS UPDATE] Project is now {status}")

Possible statuses:

• running
• idle
• shutdown

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📌 Environments

When you create a project in Secploy, multiple environments are automatically created:

Environment	Purpose
production	Live, customer-facing
staging	Pre-production testing
development	Local development

Each environment has its own API key — use the matching key for the environment you’re sending data from.

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📡 SDK Methods

Method	Description
track_event(name, properties)	Send a structured event
create_incident(title, description, severity)	Create a new incident
heartbeat()	Send a heartbeat signal
listen_status()	Stream live project status
set_environment(env_code)	Switch environment dynamically
capture_logs(loggers, level)	Start capturing logs
stop_capturing_logs(loggers)	Stop capturing specific logs

📝 Structured Logging

Secploy provides powerful structured logging capabilities that automatically format and send your logs with rich context.

Basic Log Capture

import logging
from secploy import SecployClient

# Initialize client
client = SecployClient()
client.start()

# Start capturing logs
client.capture_logs(['your_app'], level=logging.INFO)

# Your regular logging calls will now be captured
logger = logging.getLogger('your_app')
logger.info("User logged in", extra={
    'user_id': 'user123',
    'login_method': 'oauth'
})

Log Schema

All captured logs are automatically structured in a consistent format:

{
  "timestamp": "2025-09-13T16:45:00Z",
  "type": "error",
  "message": "Unhandled exception in payment processor",
  "context": {
    "user_id": "usr_12345",
    "session_id": "sess_abcd",
    "http_method": "POST",
    "http_url": "/api/payments/charge",
    "http_status": 500,
    "stacktrace": [
      "File \"payment_service.py\", line 42, in process_charge",
      "File \"stripe_gateway.py\", line 87, in create_charge",
      "Exception: Card declined"
    ],
    "tags": {
      "environment": "production",
      "service": "payments",
      "region": "us-east-1"
    }
  }
}

Example with Flask Application

import logging
from flask import Flask, request
from secploy import SecployClient

# Set up logging
logger = logging.getLogger(__name__)

# Initialize Flask and Secploy
app = Flask(__name__)
client = SecployClient()
client.start()

# Capture logs from all components
client.capture_logs([
    'flask.app',        # Flask framework logs
    __name__,          # Main application logs
    'payment_processor' # Component-specific logs
], level=logging.INFO)

@app.route('/api/payment', methods=['POST'])
def process_payment():
    try:
        data = request.json
        logger.info("Processing payment", extra={
            'user_id': data.get('user_id'),
            'http_method': request.method,
            'http_url': request.path,
            'amount': data.get('amount')
        })
        # Process payment...
        return {"status": "success"}, 200
    except Exception as e:
        logger.error(
            "Payment failed",
            exc_info=True,  # This captures the stack trace
            extra={
                'user_id': data.get('user_id'),
                'http_method': request.method,
                'http_url': request.path,
                'http_status': 500
            }
        )
        return {"error": str(e)}, 500

if __name__ == '__main__':
    try:
        app.run()
    finally:
        client.stop()

Best Practices for Logging

1. Add Context: Always include relevant context using the extra parameter
2. Use Proper Log Levels: Choose appropriate levels (DEBUG, INFO, WARNING, ERROR)
3. Include Stack Traces: Use exc_info=True when logging exceptions
4. Capture All Components: Include all relevant loggers in your capture list
5. Start Early, Stop Late: Initialize logging before your app starts and stop it in a finally block

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🛡 Requirements

• Python 3.8+
• requests
• websocket-client

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🤝 Contributing

1. Fork the repo

2. Create your feature branch:

   git checkout -b feature/my-feature
   

3. Commit your changes:

   git commit -m "Add my feature"
   

4. Push to the branch and open a Pull Request

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📄 License

MIT License — See LICENSE for details.