Async Batch Processing Integration

1import asyncio
2from cognitora import CognitoraAsync
3
4async def process_data_batch():
5    async with CognitoraAsync(api_key="your_api_key") as client:
6        # Define multiple processing tasks
7        tasks = [
8            "import pandas as pd; df = pd.read_csv('data1.csv'); print(df.mean())",
9            "import numpy as np; arr = np.random.rand(1000); print(np.std(arr))",
10            "import matplotlib.pyplot as plt; plt.plot([1,2,3]); plt.savefig('plot.png')",
11            "import requests; resp = requests.get('https://api.github.com'); print(resp.status_code)"
12        ]
13        
14        # Execute all tasks concurrently
15        coroutines = [
16            client.code_interpreter.execute(
17                code=task,
18                language="python",
19                timeout_seconds=30
20            )
21            for task in tasks
22        ]
23        
24        results = await asyncio.gather(*coroutines, return_exceptions=True)
25        
26        # Process results
27        for i, result in enumerate(results):
28            if isinstance(result, Exception):
29                print(f"Task {i+1} failed: {result}")
30            else:
31                print(f"Task {i+1} completed: {result.data.status}")
32                for output in result.data.outputs:
33                    if output.type == "stdout":
34                        print(f"  Output: {output.data}")
35
36# Run the batch processing
37asyncio.run(process_data_batch())