import pandas as pd
from trend_detector_macd import TrendDetectorMACD
from trend_detector_simple import TrendDetectorSimple
from cycle_detector import CycleDetector

# Load data from CSV file instead of database
data = pd.read_csv('data/btcusd_1-day_data.csv')


# Convert datetime column to datetime type
start_date = pd.to_datetime('2024-04-06')
stop_date = pd.to_datetime('2025-05-06')

daily_data = data[(pd.to_datetime(data['datetime']) >= start_date) & 
                  (pd.to_datetime(data['datetime']) < stop_date)]
print(f"Number of data points: {len(daily_data)}")

trend_detector = TrendDetectorSimple(daily_data, verbose=True)
trends, analysis_results = trend_detector.detect_trends()
trend_detector.plot_trends(trends, analysis_results, "supertrend")