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import asyncio |
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import pandas as pd |
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import random |
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import os |
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import httpx |
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API_URL = "http://localhost:8000/predict" |
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SOURCE_DATA = "data/processed/current_data.csv" |
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MIN_SLEEP = 2 |
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MAX_SLEEP = 8 |
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MIN_BATCH = 1 |
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MAX_BATCH = 5 |
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STARTUP_DELAY = 7 |
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async def traffic_loop(): |
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await asyncio.sleep(STARTUP_DELAY) |
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if not os.path.exists(SOURCE_DATA): |
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print("Traffic daemon: source data not found, disabled.") |
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return |
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df = pd.read_csv(SOURCE_DATA) |
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print("Traffic daemon started.") |
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async with httpx.AsyncClient(timeout=60.0) as client: |
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while True: |
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try: |
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batch_size = random.randint(MIN_BATCH, MAX_BATCH) |
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sample = df.sample(batch_size) |
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csv_bytes = sample.to_csv(index=False).encode("utf-8") |
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resp = await client.post( |
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API_URL, |
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files={"file": ("sample.csv", csv_bytes, "text/csv")} |
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) |
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if resp.status_code != 200: |
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print("Traffic daemon warning:", resp.status_code) |
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except Exception as e: |
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print("Traffic daemon error:", e) |
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await asyncio.sleep(random.uniform(MIN_SLEEP, MAX_SLEEP)) |
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