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app.py

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+import gradio as gr
+import yfinance as yf
+import pandas as pd
+import numpy as np
+
+def ema(s, n):
+    return s.ewm(span=int(n), adjust=False).mean()
+
+def rsi(s, n=9):
+    d=s.diff()
+    up=d.clip(lower=0).ewm(alpha=1/n, adjust=False).mean()
+    dn=(-d.clip(upper=0)).ewm(alpha=1/n, adjust=False).mean()
+    rs=up/dn.replace(0,np.nan)
+    return 100-100/(1+rs)
+
+def load_data(ticker, period, interval):
+    df=yf.download(ticker,period=period,interval=interval,auto_adjust=False,progress=False,threads=False)
+    if df is None or df.empty: return None
+    if isinstance(df.columns,pd.MultiIndex): df.columns=df.columns.get_level_values(0)
+    df.columns=[str(c).title() for c in df.columns]
+    needed=["Open","High","Low","Close"]
+    if not set(needed).issubset(df.columns): return None
+    return df.dropna(subset=needed).copy()
+
+def build_signals(df, fast, slow, sig, rsi_len, fee_pct, slippage_pct):
+    c=df["Close"]
+    macd=ema(c,fast)-ema(c,slow)
+    macd_sig=ema(macd,sig)
+    rs=rsi(c,rsi_len)
+    e5,e9=ema(c,5),ema(c,9)
+    buy=(macd>macd_sig)&(rs>50)&(e5>e9)
+    sell=(macd<macd_sig)&(rs<50)&(e5<e9)
+    # Avoid look-ahead: signal on close, enter at next bar open.
+    raw=np.select([buy,sell],[1,-1],default=0)
+    pos=pd.Series(raw,index=df.index).shift(1).fillna(0)
+    # Position changes close previous position and open new one at current open.
+    open_px=df["Open"].astype(float)
+    close_px=c.astype(float)
+    ret=close_px.pct_change().fillna(0)
+    # Approximate bar return while holding prior signal; fee/slippage charged on position changes.
+    strat=pos*ret
+    changes=pos.diff().abs().fillna(pos.abs())
+    costs=changes*(float(fee_pct)+float(slippage_pct))/100
+    net=strat-costs
+    equity=(1+net).cumprod()
+    return pos, net, equity, macd, macd_sig, rs, changes
+
+def backtest(ticker, interval, period, initial, fast, slow, sig, rsi_len, fee, slip):
+    try:
+        df=load_data(ticker.strip(),period,interval)
+        if df is None or len(df)<max(int(slow),int(rsi_len))+10:
+            return "Veri alınamadı veya yeterli mum yok. Sembol ve periyodu kontrol edin.",None
+        pos, net, equity, macd, ms, rs, changes=build_signals(df,int(fast),int(slow),int(sig),int(rsi_len),float(fee),float(slip))
+        # Trades are contiguous non-flat position runs. Approximate trade stats from bar returns.
+        active=pos.ne(0)
+        starts=active & ~active.shift(1,fill_value=False)
+        ends=active & ~active.shift(-1,fill_value=False)
+        trade_returns=[]
+        for start_idx in np.flatnonzero(starts.to_numpy()):
+            end_candidates=np.flatnonzero(ends.to_numpy()[start_idx:])
+            if len(end_candidates)==0: continue
+            end_idx=start_idx+end_candidates[0]
+            trade_returns.append(float((1+net.iloc[start_idx:end_idx+1]).prod()-1))
+        trades=np.array(trade_returns,dtype=float)
+        wins=int((trades>0).sum())
+        win_rate=100*wins/len(trades) if len(trades) else 0
+        total_return=float(equity.iloc[-1]-1)
+        peak=equity.cummax()
+        dd=equity/peak-1
+        max_dd=float(dd.min())
+        gross_profit=float(trades[trades>0].sum()) if len(trades) else 0
+        gross_loss=float(-trades[trades<0].sum()) if len(trades) else 0
+        pf=gross_profit/gross_loss if gross_loss>0 else (float("inf") if gross_profit>0 else 0)
+        final=float(initial)*(1+total_return)
+        report=(f"## {ticker} — Backtest sonuçları\\n"
+                f"- **İşlem sayısı:** {len(trades)}\\n"
+                f"- **Kazanma oranı:** {win_rate:.2f}%\\n"
+                f"- **Net getiri:** {total_return*100:.2f}%\\n"
+                f"- **Başlangıç bakiyesi:** {float(initial):,.2f}\\n"
+                f"- **Teorik bitiş bakiyesi:** {final:,.2f}\\n"
+                f"- **Maksimum düşüş (equity):** {max_dd*100:.2f}%\\n"
+                f"- **Profit factor (işlem getirilerinden yaklaşık):** {pf:.2f}\\n\\n"
+                f"**Not:** Bu, MACD/RSI/EMA örnek stratejisinin yaklaşık backtestidir; MT4 EA'nın birebir portu değildir. "
+                f"Yahoo Finance verileri, spread/komisyon ve kayma varsayımları sonuçları etkiler. "
+                f"Pozisyonlar kapanıştan sonraki mumda açılacak şekilde geciktirilmiştir; emir icrası ve lot artırma EA mantığı modellenmemiştir.")
+        out=df.copy()
+        out["MACD"]=macd; out["MACD_signal"]=ms; out[f"RSI_{int(rsi_len)}"]=rs
+        out["Position"]=pos.map({1:"LONG",-1:"SHORT",0:"FLAT"})
+        out["Strategy_return_%"]=net*100
+        out["Equity"]=float(initial)*equity
+        out["Drawdown_%"]=dd*100
+        out=out.reset_index().tail(500)
+        return report,out
+    except Exception as e:
+        return f"Backtest hatası: {e}",None
+
+with gr.Blocks(title="AF Global Backtest Terminal",theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# AF Global Expert — YFinance Backtest")
+    gr.Markdown("E-posta gönderimi yoktur. Veriler Yahoo Finance'tan çekilir. Strateji, örnek MACD/RSI/EMA birleşimidir; orijinal EA'nın birebir dönüşümü değildir.")
+    with gr.Row():
+        ticker=gr.Textbox(label="Yahoo sembolü",value="EURUSD=X")
+        interval=gr.Dropdown(["5m","15m","30m","60m","1h","1d","1wk"],value="1h",label="Zaman dilimi")
+        period=gr.Dropdown(["5d","1mo","3mo","6mo","1y","2y","5y"],value="1y",label="Geçmiş")
+    with gr.Row():
+        initial=gr.Number(label="Başlangıç bakiyesi",value=10000)
+        fee=gr.Number(label="Komisyon (%) / pozisyon değişimi",value=0.02)
+        slip=gr.Number(label="Kayma (%) / pozisyon değişimi",value=0.01)
+    with gr.Row():
+        fast=gr.Number(label="MACD fast",value=8,precision=0)
+        slow=gr.Number(label="MACD slow",value=17,precision=0)
+        sig=gr.Number(label="MACD signal",value=9,precision=0)
+        rsi_len=gr.Number(label="RSI period",value=9,precision=0)
+    btn=gr.Button("Veriyi çek ve backtest yap",variant="primary")
+    report=gr.Markdown()
+    table=gr.Dataframe(label="Son 500 mum — sinyal, getiri ve equity",interactive=False)
+    btn.click(backtest,[ticker,interval,period,initial,fast,slow,sig,rsi_len,fee,slip],[report,table])
+demo.launch()

requirements.txt

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+gradio>=4.44
+yfinance>=0.2.65
+pandas>=2.0
+numpy>=1.24