| import gradio as gr |
| import requests |
| import pandas as pd |
| import numpy as np |
| from datetime import datetime |
| import time |
|
|
| |
| |
| |
| COINS = { |
| "bitcoin": "BTC", |
| "ethereum": "ETH", |
| "binancecoin": "BNB", |
| "ripple": "XRP", |
| "solana": "SOL", |
| "cardano": "ADA", |
| "dogecoin": "DOGE", |
| "avalanche-2": "AVAX", |
| "chainlink": "LINK", |
| "polkadot": "DOT", |
| "matic-network": "MATIC", |
| "tron": "TRX", |
| "litecoin": "LTC", |
| "uniswap": "UNI", |
| "cosmos": "ATOM", |
| "near": "NEAR", |
| "algorand": "ALGO", |
| "stellar": "XLM", |
| "filecoin": "FIL", |
| "internet-computer": "ICP", |
| "aptos": "APT", |
| "arbitrum": "ARB", |
| "optimism": "OP", |
| "sui": "SUI", |
| "pepe": "PEPE", |
| "shiba-inu": "SHIB", |
| "the-sandbox": "SAND", |
| "decentraland": "MANA", |
| "aave": "AAVE", |
| "maker": "MKR", |
| } |
|
|
| BASE_URL = "https://api.coingecko.com/api/v3" |
| HEADERS = {"accept": "application/json"} |
|
|
| |
| |
| |
|
|
| def fetch_ohlc(coin_id: str, days: int = 30) -> pd.Series | None: |
| """CoinGecko OHLC endpoint – günlük kapanış fiyatları.""" |
| url = f"{BASE_URL}/coins/{coin_id}/ohlc?vs_currency=usd&days={days}" |
| try: |
| r = requests.get(url, headers=HEADERS, timeout=20) |
| r.raise_for_status() |
| data = r.json() |
| if not data: |
| return None |
| df = pd.DataFrame(data, columns=["ts", "open", "high", "low", "close"]) |
| df["ts"] = pd.to_datetime(df["ts"], unit="ms") |
| df = df.set_index("ts").resample("D").last().dropna() |
| return df["close"] |
| except Exception: |
| return None |
|
|
|
|
| def fetch_market_chart(coin_id: str, days: int = 30) -> pd.Series | None: |
| """Fallback: /market_chart ile günlük fiyat.""" |
| url = f"{BASE_URL}/coins/{coin_id}/market_chart?vs_currency=usd&days={days}&interval=daily" |
| try: |
| r = requests.get(url, headers=HEADERS, timeout=20) |
| r.raise_for_status() |
| data = r.json().get("prices", []) |
| if not data: |
| return None |
| df = pd.DataFrame(data, columns=["ts", "price"]) |
| df["ts"] = pd.to_datetime(df["ts"], unit="ms") |
| df = df.set_index("ts").resample("D").last().dropna() |
| return df["price"] |
| except Exception: |
| return None |
|
|
|
|
| def get_price_series(coin_id: str, days: int) -> pd.Series | None: |
| s = fetch_ohlc(coin_id, days) |
| if s is None or len(s) < 5: |
| s = fetch_market_chart(coin_id, days) |
| return s if s is not None and len(s) >= 5 else None |
|
|
|
|
| |
| |
| |
|
|
| def returns(series: pd.Series) -> pd.Series: |
| return series.pct_change().dropna() |
|
|
|
|
| def rolling_corr(s1: pd.Series, s2: pd.Series, window: int = 14) -> float: |
| """Son N günlük rolling correlation.""" |
| r1 = returns(s1) |
| r2 = returns(s2) |
| combined = pd.concat([r1, r2], axis=1).dropna() |
| if len(combined) < window: |
| return float(combined.iloc[:, 0].corr(combined.iloc[:, 1])) |
| tail = combined.tail(window) |
| return float(tail.iloc[:, 0].corr(tail.iloc[:, 1])) |
|
|
|
|
| def zscore_spread(s1: pd.Series, s2: pd.Series, window: int = 20) -> dict | None: |
| """ |
| Pairs trading Z-score. |
| ratio = log(s1) - log(s2) |
| z = (ratio - mean) / std (rolling window) |
| """ |
| log1 = np.log(s1) |
| log2 = np.log(s2) |
| ratio = (log1 - log2).dropna() |
| if len(ratio) < window: |
| window = max(5, len(ratio) // 2) |
| roll_mean = ratio.rolling(window).mean() |
| roll_std = ratio.rolling(window).std() |
| zscore = ((ratio - roll_mean) / roll_std).dropna() |
| if len(zscore) == 0: |
| return None |
| current_z = float(zscore.iloc[-1]) |
| current_ratio = float(ratio.iloc[-1]) |
| ratio_mean = float(ratio.mean()) |
| ratio_std = float(ratio.std()) |
| half_life = _half_life(ratio) |
| return { |
| "current_z": current_z, |
| "current_ratio": current_ratio, |
| "ratio_mean": ratio_mean, |
| "ratio_std": ratio_std, |
| "half_life": half_life, |
| } |
|
|
|
|
| def _half_life(spread: pd.Series) -> float: |
| """Ornstein-Uhlenbeck half-life (OLS).""" |
| try: |
| lag = spread.shift(1).dropna() |
| delta = spread.diff().dropna() |
| combined = pd.concat([lag, delta], axis=1).dropna() |
| if len(combined) < 5: |
| return float("nan") |
| x = combined.iloc[:, 0].values |
| y = combined.iloc[:, 1].values |
| A = np.vstack([np.ones(len(x)), x]).T |
| result = np.linalg.lstsq(A, y, rcond=None) |
| b = result[0][1] |
| if b >= 0: |
| return float("nan") |
| return round(-np.log(2) / b, 1) |
| except Exception: |
| return float("nan") |
|
|
|
|
| def trade_signal(z: float, corr: float, half_life: float) -> tuple[str, str]: |
| """Sinyal üret.""" |
| if abs(z) < 0.5: |
| return "NÖTR", "#555577" |
| if corr < 0.5: |
| return "DÜŞÜK KOR.", "#443344" |
| hl_ok = not np.isnan(half_life) and 2 <= half_life <= 60 |
| if abs(z) >= 2.5 and hl_ok: |
| strength = "GÜÇLÜ" |
| elif abs(z) >= 1.5: |
| strength = "ORTA" |
| else: |
| strength = "İZLE" |
| if z > 2.0: |
| return f"{strength} · 1.SAT / 2.AL", "red" |
| elif z < -2.0: |
| return f"{strength} · 1.AL / 2.SAT", "green" |
| elif z > 1.0: |
| return f"{strength} · 1.SAT / 2.AL", "orange" |
| else: |
| return f"{strength} · 1.AL / 2.SAT", "yellow" |
|
|
|
|
| |
| |
| |
|
|
| def scan_correlations( |
| selected_coins: list, |
| days: int, |
| min_corr: float, |
| min_abs_z: float, |
| progress=gr.Progress(), |
| ): |
| if not selected_coins or len(selected_coins) < 2: |
| return _err_html("En az 2 coin seçin!"), None, "Tarama yapılmadı." |
|
|
| coin_ids = [k for k, v in COINS.items() if v in selected_coins] |
| n = len(coin_ids) |
|
|
| |
| price_data = {} |
| for i, cid in enumerate(coin_ids): |
| sym = COINS[cid] |
| progress((i + 1) / (n + 1), desc=f"{sym} fiyatları çekiliyor...") |
| s = get_price_series(cid, days) |
| if s is not None: |
| price_data[sym] = s |
| time.sleep(0.35) |
|
|
| available = list(price_data.keys()) |
| if len(available) < 2: |
| return _err_html("Yeterli fiyat verisi alınamadı. Tekrar deneyin."), None, "Hata." |
|
|
| |
| pairs = [] |
| total_pairs = len(available) * (len(available) - 1) // 2 |
| idx = 0 |
| for i in range(len(available)): |
| for j in range(i + 1, len(available)): |
| idx += 1 |
| progress(idx / max(total_pairs, 1), desc=f"{available[i]}-{available[j]} analiz...") |
| s1 = price_data[available[i]] |
| s2 = price_data[available[j]] |
|
|
| common = s1.index.intersection(s2.index) |
| if len(common) < 10: |
| continue |
| s1c = s1.loc[common] |
| s2c = s2.loc[common] |
|
|
| corr = rolling_corr(s1c, s2c, window=min(14, len(common) - 1)) |
| if abs(corr) < min_corr: |
| continue |
|
|
| spread_info = zscore_spread(s1c, s2c, window=min(20, len(common) - 2)) |
| if spread_info is None: |
| continue |
|
|
| z = spread_info["current_z"] |
| if abs(z) < min_abs_z: |
| continue |
|
|
| hl = spread_info["half_life"] |
| signal, _ = trade_signal(z, corr, hl) |
|
|
| pairs.append({ |
| "Coin 1": available[i], |
| "Coin 2": available[j], |
| "Korelasyon": round(corr, 4), |
| "Z-Score": round(z, 3), |
| "Half-Life (gün)": round(hl, 1) if not np.isnan(hl) else "-", |
| "Ratio (log)": round(spread_info["current_ratio"], 5), |
| "Ratio Ort.": round(spread_info["ratio_mean"], 5), |
| "Sinyal": signal, |
| }) |
|
|
| if not pairs: |
| return _empty_html(min_corr, min_abs_z), None, f"Uygun çift bulunamadı (corr≥{min_corr}, |z|≥{min_abs_z})." |
|
|
| df = ( |
| pd.DataFrame(pairs) |
| .sort_values("Z-Score", key=abs, ascending=False) |
| .reset_index(drop=True) |
| ) |
|
|
| html = _render_html(df) |
| log = _make_log(df, days, available) |
| return html, df, log |
|
|
|
|
| |
| |
| |
|
|
| def _signal_style(sig: str) -> str: |
| if "GÜÇLÜ" in sig and "SAT" in sig: |
| return "background:#ff6b6b22;color:#ff6b6b;border:1px solid #ff6b6b55" |
| if "GÜÇLÜ" in sig and "AL" in sig: |
| return "background:#00ff8822;color:#00ff88;border:1px solid #00ff8855" |
| if "ORTA" in sig and "SAT" in sig: |
| return "background:#ff9f4322;color:#ff9f43;border:1px solid #ff9f4355" |
| if "ORTA" in sig and "AL" in sig: |
| return "background:#ffd70022;color:#ffd700;border:1px solid #ffd70055" |
| if "İZLE" in sig: |
| return "background:#7b7bff22;color:#7b7bff;border:1px solid #7b7bff55" |
| return "color:#555;border:1px solid #333" |
|
|
|
|
| def _corr_bar(c: float) -> str: |
| pct = int(abs(c) * 100) |
| color = "#00d2ff" if c > 0 else "#ff6b9d" |
| return ( |
| f"<div style='display:flex;align-items:center;gap:8px'>" |
| f"<div style='width:64px;height:5px;background:#1a1a3a;border-radius:3px'>" |
| f"<div style='width:{pct}%;height:100%;background:{color};border-radius:3px'></div></div>" |
| f"<span style='color:{color};font-size:13px;font-weight:700'>{c:+.3f}</span></div>" |
| ) |
|
|
|
|
| def _z_badge(z: float) -> str: |
| az = abs(z) |
| if az >= 2.5: |
| c, sz = ("#ff4444" if z > 0 else "#00ff88"), "17px" |
| elif az >= 1.5: |
| c, sz = ("#ff9f43" if z > 0 else "#ffd700"), "15px" |
| else: |
| c, sz = "#7b7bff", "13px" |
| arrow = "▲" if z > 0 else "▼" |
| return f"<span style='color:{c};font-size:{sz};font-weight:800'>{arrow} {z:+.3f}</span>" |
|
|
|
|
| def _hl_badge(hl) -> str: |
| if hl == "-" or (isinstance(hl, float) and np.isnan(hl)): |
| return "<span style='color:#444'>—</span>" |
| hl = float(hl) |
| if 2 <= hl <= 60: |
| c = "#00ff88" |
| elif hl < 2: |
| c = "#ff6b6b" |
| else: |
| c = "#555" |
| return f"<span style='color:{c};font-family:monospace'>{hl:.1f} gün</span>" |
|
|
|
|
| def _render_html(df: pd.DataFrame) -> str: |
| rows = "" |
| for rank, (_, row) in enumerate(df.iterrows(), 1): |
| sig = row["Sinyal"] |
| sstyle = _signal_style(sig) |
| rows += f""" |
| <tr> |
| <td style='color:#555;font-size:11px;text-align:center'>{rank}</td> |
| <td> |
| <span style='color:#c0c0ff;font-weight:700;font-size:14px'>{row['Coin 1']}</span> |
| <span style='color:#2a2a5a;margin:0 8px;font-size:18px'>⟷</span> |
| <span style='color:#c0c0ff;font-weight:700;font-size:14px'>{row['Coin 2']}</span> |
| </td> |
| <td>{_corr_bar(row['Korelasyon'])}</td> |
| <td>{_z_badge(row['Z-Score'])}</td> |
| <td>{_hl_badge(row['Half-Life (gün)'])}</td> |
| <td> |
| <span style='display:inline-block;padding:5px 12px;border-radius:6px; |
| font-size:11px;font-weight:700;letter-spacing:.5px;white-space:nowrap;{sstyle}'> |
| {sig} |
| </span> |
| </td> |
| </tr>""" |
|
|
| strong = len(df[df["Sinyal"].str.contains("GÜÇLÜ", na=False)]) |
| orta = len(df[df["Sinyal"].str.contains("ORTA", na=False)]) |
| izle = len(df[df["Sinyal"].str.contains("İZLE", na=False)]) |
|
|
| return f""" |
| <style> |
| @import url('https://fonts.googleapis.com/css2?family=Space+Mono&family=Syne:wght@400;700;800&display=swap'); |
| .ct-wrap {{ background:#06060f;border-radius:14px;overflow:hidden;font-family:'Syne',sans-serif }} |
| .ct-hdr {{ background:linear-gradient(135deg,#0d0d2a,#12122a);padding:16px 22px; |
| display:flex;justify-content:space-between;align-items:center; |
| border-bottom:1px solid #1a1a3a }} |
| .ct-title {{ font-size:11px;font-weight:800;letter-spacing:3px;color:#7b7bff }} |
| .ct-stats {{ display:flex;gap:20px }} |
| .ct-sv {{ font-size:22px;font-weight:800;text-align:center }} |
| .ct-sl {{ font-size:9px;color:#444;letter-spacing:1.5px;text-align:center }} |
| .ct-tbl {{ width:100%;border-collapse:collapse }} |
| .ct-tbl th {{ background:#0d0d22;color:#5555aa;padding:9px 14px; |
| font-size:9px;letter-spacing:2px;text-transform:uppercase; |
| text-align:left;border-bottom:1px solid #1a1a3a }} |
| .ct-tbl td {{ padding:12px 14px;border-bottom:1px solid #0e0e22;vertical-align:middle }} |
| .ct-tbl tr:hover td {{ background:#090918 }} |
| .ct-tbl tr:last-child td {{ border-bottom:none }} |
| </style> |
| <div class='ct-wrap'> |
| <div class='ct-hdr'> |
| <span class='ct-title'>⚡ KORELASYon TİCARETİ · {datetime.now().strftime('%H:%M:%S')}</span> |
| <div class='ct-stats'> |
| <div><div class='ct-sv' style='color:#ff6b6b'>{strong}</div><div class='ct-sl'>GÜÇLÜ</div></div> |
| <div><div class='ct-sv' style='color:#ffd700'>{orta}</div><div class='ct-sl'>ORTA</div></div> |
| <div><div class='ct-sv' style='color:#7b7bff'>{izle}</div><div class='ct-sl'>İZLE</div></div> |
| <div><div class='ct-sv' style='color:#aaa'>{len(df)}</div><div class='ct-sl'>TOPLAM</div></div> |
| </div> |
| </div> |
| <table class='ct-tbl'> |
| <thead><tr> |
| <th>#</th><th>Çift</th><th>Korelasyon</th> |
| <th>Z-Score</th><th>Half-Life</th><th>Sinyal</th> |
| </tr></thead> |
| <tbody>{rows}</tbody> |
| </table> |
| </div>""" |
|
|
|
|
| def _err_html(msg: str) -> str: |
| return ( |
| f"<div style='background:#1a0a0a;border:1px solid #ff4444;border-radius:10px;" |
| f"padding:30px;text-align:center;color:#ff6b6b;font-family:monospace'>⚠️ {msg}</div>" |
| ) |
|
|
|
|
| def _empty_html(min_corr: float, min_abs_z: float) -> str: |
| return ( |
| f"<div style='background:#06060f;border:1px solid #1a1a3a;border-radius:12px;" |
| f"padding:50px;text-align:center;font-family:monospace'>" |
| f"<div style='font-size:40px'>📭</div>" |
| f"<div style='color:#7b7bff;margin-top:14px'>corr≥{min_corr} ve |Z|≥{min_abs_z} koşullarını sağlayan çift bulunamadı.</div>" |
| f"<div style='color:#444;margin-top:8px;font-size:12px'>Eşikleri düşürün veya daha fazla coin seçin.</div></div>" |
| ) |
|
|
|
|
| def _make_log(df: pd.DataFrame, days: int, available: list) -> str: |
| lines = [ |
| f"[{datetime.now().strftime('%H:%M:%S')}] Tarama tamamlandı", |
| f" Analiz edilen coinler : {', '.join(available)}", |
| f" Tarihsel veri süresi : {days} gün", |
| f" Bulunan çift sayısı : {len(df)}", |
| "─" * 60, |
| ] |
| for _, row in df.iterrows(): |
| lines.append( |
| f" {row['Coin 1']:<6} ↔ {row['Coin 2']:<6} " |
| f"corr={row['Korelasyon']:+.3f} z={row['Z-Score']:+.3f} " |
| f"HL={row['Half-Life (gün)']} gün → {row['Sinyal']}" |
| ) |
| return "\n".join(lines) |
|
|
|
|
| |
| |
| |
|
|
| ALL_SYMBOLS = sorted(COINS.values()) |
| DEFAULT_COINS = ["BTC", "ETH", "BNB", "SOL", "AVAX", "LINK", "ADA", "MATIC", "DOT", "ATOM"] |
|
|
| CSS = """ |
| @import url('https://fonts.googleapis.com/css2?family=Syne:wght@400;700;800&display=swap'); |
| body, .gradio-container { |
| background:#06060f !important; |
| color:#e0e0ff !important; |
| font-family:'Syne',sans-serif !important; |
| } |
| .gr-button { font-family:'Syne',sans-serif !important; font-weight:700 !important; } |
| .gr-button-primary { |
| background:linear-gradient(135deg,#7b7bff,#00d2ff) !important; |
| color:#000 !important; border:none !important; letter-spacing:1px !important; |
| } |
| .gr-button-secondary { |
| background:#0d0d22 !important; |
| color:#7b7bff !important; |
| border:1px solid #2a2a4a !important; |
| } |
| label { color:#aaa !important; font-size:11px !important; letter-spacing:1px !important; } |
| .gr-panel, .gr-box { background:#0a0a1a !important; border:1px solid #1a1a3a !important; } |
| footer { display:none !important; } |
| """ |
|
|
| HEADER_HTML = """ |
| <div style='text-align:center;padding:28px 0 12px;font-family:Syne,sans-serif'> |
| <div style=' |
| font-size:26px;font-weight:800;letter-spacing:5px; |
| background:linear-gradient(90deg,#7b7bff,#00d2ff,#00ff88); |
| -webkit-background-clip:text;-webkit-text-fill-color:transparent |
| '>KORELASYON TRADİNG SKANER</div> |
| <div style='color:#333;font-size:11px;letter-spacing:3px;margin-top:5px'> |
| PAIRS TRADING · Z-SCORE · MEAN REVERSION · COINGECKO · API ANAHTARI YOK |
| </div> |
| </div>""" |
|
|
| INFO_HTML = """ |
| <div style='background:#0a0a1e;border:1px solid #1a1a3a;border-radius:10px; |
| padding:14px 16px;font-size:12px;color:#666;line-height:2;margin-top:4px'> |
| <div style='color:#7b7bff;font-weight:700;letter-spacing:1px;margin-bottom:4px'>📐 ALGORİTMA</div> |
| <b style='color:#aaa'>Z-Score</b> = (log_ratio − ort) / std<br> |
| <b style='color:#aaa'>Half-Life</b> = OU modeli ile mean-reversion hızı<br> |
| <span style='color:#00ff88'>|Z| > 2</span> → İşlem sinyali<br> |
| <span style='color:#ffd700'>2 – 60 gün</span> → İdeal half-life aralığı<br> |
| <span style='color:#ff6b6b'>Korelasyon > 0.7</span> → Güvenilir çift |
| </div>""" |
|
|
|
|
| def export_csv(df): |
| if df is None: |
| return None |
| path = "/tmp/korelasyon_sonuclari.csv" |
| df.to_csv(path, index=False, encoding="utf-8-sig") |
| return path |
|
|
|
|
| with gr.Blocks(title="Korelasyon Trading Skaner") as demo: |
| gr.HTML(HEADER_HTML) |
|
|
| with gr.Row(): |
| |
| with gr.Column(scale=1, min_width=200): |
| coin_selector = gr.CheckboxGroup( |
| choices=ALL_SYMBOLS, |
| value=DEFAULT_COINS, |
| label="COİN SEÇİMİ", |
| ) |
| gr.HTML(INFO_HTML) |
|
|
| |
| with gr.Column(scale=3): |
| with gr.Row(): |
| days_slider = gr.Slider( |
| minimum=14, maximum=90, value=30, step=7, |
| label="VERİ SÜRESİ (GÜN)", |
| ) |
| corr_slider = gr.Slider( |
| minimum=0.3, maximum=0.99, value=0.65, step=0.05, |
| label="MİN. KORELASYON", |
| ) |
| z_slider = gr.Slider( |
| minimum=0.5, maximum=4.0, value=1.5, step=0.25, |
| label="MİN. |Z-SCORE|", |
| ) |
|
|
| with gr.Row(): |
| scan_btn = gr.Button("⚡ TARAMAYI BAŞLAT", variant="primary", size="lg") |
| clear_btn = gr.Button("🗑 TEMİZLE", variant="secondary") |
| export_btn = gr.Button("📥 CSV İNDİR", variant="secondary") |
|
|
| result_html = gr.HTML( |
| value=( |
| "<div style='color:#222;text-align:center;padding:70px;" |
| "font-family:monospace;font-size:13px'>Coin seçip taramayı başlatın →</div>" |
| ) |
| ) |
|
|
| with gr.Accordion("📋 LOG / DETAY", open=False): |
| log_box = gr.Textbox( |
| label="", |
| lines=14, |
| max_lines=22, |
| placeholder="Tarama logları burada görünür...", |
| ) |
|
|
| df_state = gr.State(None) |
| csv_file = gr.File(label="CSV Dosyası", visible=False) |
|
|
| |
| scan_btn.click( |
| fn=scan_correlations, |
| inputs=[coin_selector, days_slider, corr_slider, z_slider], |
| outputs=[result_html, df_state, log_box], |
| ) |
|
|
| clear_btn.click( |
| fn=lambda: ( |
| "<div style='color:#222;text-align:center;padding:70px;font-family:monospace'>Temizlendi.</div>", |
| None, |
| "", |
| ), |
| outputs=[result_html, df_state, log_box], |
| ) |
|
|
| export_btn.click( |
| fn=export_csv, |
| inputs=[df_state], |
| outputs=[csv_file], |
| ).then(fn=lambda: gr.update(visible=True), outputs=[csv_file]) |
|
|
|
|
| if __name__ == "__main__": |
| demo.launch(css=CSS) |
|
|
