wetflix-device_data-simulator/main.py

124 lines
4.6 KiB
Python

import requests
import json
import time
from datetime import datetime, timedelta
import random
from concurrent.futures import ThreadPoolExecutor, as_completed
# API endpoint
URL = "https://api.dev.wetflix.net/api/v2/device/createDeviceData"
# Initial conditions
waterlevel = 4500 # Start at max
batterystatus = 100.0 # Start at full charge
# Track timestamps to avoid duplicates
timestamp_set = set()
# Add a counter to track how many times the waterlevel has been at 1
waterlevel_reset_counter = 0
def generate_payload(timestamp):
global waterlevel, batterystatus, waterlevel_reset_counter
# Ensure unique timestamps
if timestamp.timestamp() in timestamp_set:
return None # Skip duplicates
timestamp_set.add(timestamp.timestamp())
# Gradual water level decrease (integer)
waterlevel = max(1, waterlevel - random.randint(1, 5)) # Smaller decrement range
# Reset waterlevel to max if it reaches 1 and has been at 1 for 3 iterations
if waterlevel == 1:
waterlevel_reset_counter += 1
if waterlevel_reset_counter >= 3: # Reset after 3 iterations at 1
waterlevel = 4500
waterlevel_reset_counter = 0 # Reset the counter
else:
waterlevel_reset_counter = 0 # Reset the counter if waterlevel is not 1
# Battery drain logic (decimal percentage)
if 6 <= timestamp.hour < 18: # 6 AM - 6 PM (higher usage)
batterystatus = max(1, batterystatus - random.uniform(0.3, 1.0))
else: # 6 PM - 6 AM (lower usage)
batterystatus = max(1, batterystatus - random.uniform(0.1, 0.5))
# Round the battery status to an integer
rounded_battery = int(round(batterystatus))
# If battery status rounds to 1, replace it with a random integer between 10 and 100
if rounded_battery == 1:
rounded_battery = random.randint(10, 100)
# Generate a random WiFi signal strength between -25 and -95 dBm.
wifi_signal = random.randint(-95, -25)
return {
"deviceid": "A1:B2:C3:D20",
"waterlevel": waterlevel, # Now an integer
"errorcondition": "nil",
"batterystatus": f"{rounded_battery}%",
"wifistatus": str(wifi_signal),
"version": "v001",
"createdtime": int(timestamp.timestamp()) # Unix timestamp
}
# Function to send data to the API
def send_data(payload, session):
headers = {'Content-Type': 'application/json'}
try:
response = session.post(URL, headers=headers, data=json.dumps(payload), timeout=10)
print(f"Sent: {datetime.fromtimestamp(payload['createdtime'])} → Status: {response.status_code}, Response: {response.text}")
except requests.exceptions.RequestException as e:
print(f"Error sending data for {datetime.fromtimestamp(payload['createdtime'])}: {e}")
# Simulation function
def simulate_data(start_date, end_date):
current_date = start_date
payloads = []
while current_date <= end_date:
timestamp = datetime(current_date.year, current_date.month, current_date.day, 6, 0) # Start at 6 AM
# Simulate from 6 AM to 12 AM (Midnight)
while timestamp.hour < 24 and timestamp.date() <= end_date.date():
payload = generate_payload(timestamp)
if payload:
payloads.append(payload)
interval = timedelta(minutes=30) if 6 <= timestamp.hour < 18 else timedelta(hours=1)
timestamp += interval
# Simulate from 12 AM to 6 AM (every 1 hour)
timestamp = datetime(current_date.year, current_date.month, current_date.day, 0, 0) # Start at Midnight
while timestamp.hour < 6 and timestamp.date() <= end_date.date():
payload = generate_payload(timestamp)
if payload:
payloads.append(payload)
timestamp += timedelta(hours=1)
# Move to the next day
current_date += timedelta(days=1)
print(f"Total records to send: {len(payloads)}") # Debugging info
# Send all data using multi-threading
with ThreadPoolExecutor(max_workers=25) as executor: # 25 threads for ultra-fast sending
with requests.Session() as session: # Persistent session for speed
future_to_payload = {executor.submit(send_data, payload, session): payload for payload in payloads}
for future in as_completed(future_to_payload):
future.result() # Ensures errors are caught
# Define your start and end date
start_date = datetime(2024, 12, 1) # Change to your required start date
end_date = datetime(2025, 2, 24) # Change to your required end date
# Run the simulation
simulate_data(start_date, end_date)