Created
May 28, 2025 08:14
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Events producer
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import numpy as np | |
import matplotlib.pyplot as plt | |
import random | |
import time | |
from datetime import datetime | |
import os | |
import json | |
try: | |
os.mkdir('/tmp/stockprices/') | |
except FileExistsError: | |
pass | |
class SimulatedStock: | |
def __init__(self, name, base_price, volatility, freq, slope): | |
self.name = name | |
self.base_price = base_price | |
self.volatility = volatility | |
self.freq = freq | |
self.slope = slope | |
self.t = 0 | |
def tick(self): | |
noise = random.uniform(-self.volatility, self.volatility) | |
sine_wave = np.sin(self.freq * self.t) * self.volatility | |
slope = self.t * self.slope | |
price = self.base_price + sine_wave + noise + slope | |
self.t += 1 | |
return round(price, 2) if price > 0 else 0 | |
# Define a few example stocks | |
stocks = [ | |
SimulatedStock("AAPL", 150, 20, 1.0, 0.5), | |
SimulatedStock("GOOG", 2800, 100, 0.7, 1.), | |
SimulatedStock("TSLA", 1200, 200, 1.5, -1.0), | |
SimulatedStock("AMZN", 3300, 150, 0.5, 0.1), | |
SimulatedStock("MSFT", 450, 150, 1.0, 2), | |
] | |
while True: | |
stock_prices = [json.dumps({ | |
"symbol": stock.name, | |
"time": datetime.now().isoformat(), | |
"ask": stock.tick() | |
}) | |
for stock in stocks] | |
with open(f'/tmp/stockprices/{datetime.now().isoformat()}.json', "w") as output_stream: | |
output_stream.write("\n".join(stock_prices)) | |
time.sleep(5) |
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