# SeerPy

SeerPy is the official Python client for the Seer Monitoring API by Ansr Studio. It helps you monitor jobs, capture logs, record heartbeats, and automatically report execution results to your Seer dashboard.

## 🚀 Installation

```bash
pip install seerpy
```

## 🔑 Getting Started

### 1. Import and initialize

```python
from seerpy import Seer

# Initialize with your Seer API key
seer = Seer(apiKey="YOUR_SEER_API_KEY")
```

### 2. Monitor jobs

Use the `monitor()` context manager to automatically track job execution time, status, and logs.

```python
with seer.monitor("daily_etl_job", capture_logs=True, metadata={"source": "data-lake"}):
    print("Running ETL job...")
    # Your job logic here
    raise Exception("Simulated error")  # This will be logged and marked as failed
```

When you run this, Seer automatically captures:

- Start and end timestamps
- Job status (running, success, or failed)
- Logs (if `capture_logs=True`)
- Error traceback (if any)

## 💓 Heartbeat Monitoring

Send regular heartbeats from long-running processes to confirm they’re still active.

```python
seer.heartbeat("worker_process", metadata={"pid": 1234, "status": "active"})
```

This helps detect downtime or stalled jobs in real time.

## ⚙️ Error Handling & Offline Support

If the Seer API is temporarily unavailable, payloads are safely stored locally using helpers like `payloads.save_failed_payload`. You can later replay them manually:

```python
from payloads import replay_failed_payloads

replay_failed_payloads()
```

## 🔐 Using Environment Variables (Recommended)

Store your API key in an environment variable for safer usage in production.

Create a `.env` file:

```
SEER_API_KEY=your_api_key_here
```

Load it in your code:

```python
from dotenv import load_dotenv
import os
from seerpy import Seer

load_dotenv()
api_key = os.getenv("SEER_API_KEY")
seer = Seer(apiKey=api_key)
```

## 🧩 API Reference

| Method                                                 | Description                                |
| ------------------------------------------------------ | ------------------------------------------ |
| `Seer(apiKey)`                                         | Initialize a new Seer client               |
| `monitor(job_name, capture_logs=False, metadata=None)` | Context manager to monitor a code block    |
| `heartbeat(job_name, metadata=None)`                   | Send a heartbeat signal for an ongoing job |

## 📦 Example: Full Worker Script

```python
from dotenv import load_dotenv
import os
from seerpy import Seer

load_dotenv()
seer = Seer(apiKey=os.getenv("SEER_API_KEY"))

def run_job():
    with seer.monitor("example_worker", capture_logs=True, metadata={"env": "prod"}):
        print("Starting work...")
        # simulate work
        for i in range(3):
            print(f"step {i+1}")
        # optionally send heartbeat during long tasks
        seer.heartbeat("example_worker", metadata={"progress": "50%"})
        print("Work complete.")

if __name__ == "__main__":
    run_job()
```

## 🛡️ License

Copyright (c) 2025 Ansr Studio.  
All rights reserved. Use of this software is permitted solely for connecting to and interacting with the Seer API. Redistribution, modification, or any other use of this code is prohibited without written permission from Ansr Studio. See the LICENSE file for details.

## 🧠 About

Seer is a monitoring and observability platform built by Ansr Studio. It helps data engineers and developers track, analyze, and debug their workflows effortlessly.

Learn more at: https://ansrstudio.com
