Advanced Support and Resistance Zones with Buy/Sell Signals

import ccxt
import pandas as pd
import numpy as np
import ta

# اتصال به بازار (مثال: Binance)
exchange = ccxt.binance()

# تنظیمات
symbol = 'BTC/USDT' # جفت معاملاتی
timeframe = '4h' # تایم‌فریم 4 ساعته

# دریافت داده‌های قیمتی
def fetch_data(symbol, timeframe, limit=100):
try:
ohlcv = exchange.fetch_ohlcv(symbol, timeframe=timeframe, limit=limit)
df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
return df
except Exception as e:
print(f"خطا در دریافت داده‌ها: {e}")
return None

# محاسبه EMA
def calculate_ema(data, period):
return ta.trend.ema_indicator(data['close'], window=period)

# محاسبه Fibonacci Retracement
def calculate_fibonacci_levels(data):
high = data['high'].max()
low = data['low'].min()
diff = high - low
levels = {
"0%": high,
"23.6%": high - 0.236 * diff,
"38.2%": high - 0.382 * diff,
"50%": high - 0.5 * diff,
"61.8%": high - 0.618 * diff,
"100%": low
}
return levels

# محاسبه Pivot Points
def calculate_pivot_points(data):
high = data['high'].max()
low = data['low'].min()
close = data['close'].iloc[-1]
pivot = (high + low + close) / 3
r1 = (2 * pivot) - low
s1 = (2 * pivot) - high
r2 = pivot + (high - low)
s2 = pivot - (high - low)
return {"R1": r1, "S1": s1, "R2": r2, "S2": s2}

# شناسایی مناطق حمایت و مقاومت
def identify_support_resistance(data, ema_period=20):
support_zones = {}
resistance_zones = {}

# محاسبه EMA
ema = calculate_ema(data, ema_period)
ema_value = ema.iloc[-1]

# محاسبه Fibonacci Levels
fib_levels = calculate_fibonacci_levels(data)

# محاسبه Pivot Points
pivot_points = calculate_pivot_points(data)

# ترکیب ابزارها برای شناسایی مناطق
all_levels = list(fib_levels.values()) + [ema_value] + list(pivot_points.values())
for level in all_levels:
count = 0
if level in fib_levels.values():
count += 1
if abs(level - ema_value) < 100: # اگر EMA نزدیک باشد
count += 1
if level in pivot_points.values():
count += 1

if count >= 2: # حداقل دو ابزار تایید کننده
if level < data['close'].iloc[-1]: # حمایت
support_zones[level] = count
else: # مقاومت
resistance_zones[level] = count

return support_zones, resistance_zones

# اجرای ربات
if __name__ == "__main__":
df = fetch_data(symbol, timeframe)
if df is not None:
support_zones, resistance_zones = identify_support_resistance(df)

print("مناطق حمایت:")
for zone, strength in support_zones.items():
print(f"قیمت: {zone}, قوت: {strength}")

print("\nمناطق مقاومت:")
for zone, strength in resistance_zones.items():
print(f"قیمت: {zone}, قوت: {strength}")