Deploy a System

import ccxt, pandas as pd, asyncio
from ta.trend import EMAIndicator
from ta.volatility import AverageTrueRange

MIN_VOLUME_24H = 20_000_000
LEVERAGE       = 20
SCAN_INTERVAL  = 600

async def scan_pair(exchange, symbol):
    ohlcv = await exchange.fetch_ohlcv(symbol, '15m', limit=100)
    df = pd.DataFrame(ohlcv, columns=['t','o','h','l','c','v'])
    ema21 = EMAIndicator(df['c'], window=21).ema_indicator()
    atr   = AverageTrueRange(df['h'],df['l'],df['c'],14).average_true_range()
    last  = df.iloc[-1]
    # Bull regime: price above EMA21, dip to EMA21 zone
    if last['c'] > ema21.iloc[-1] * 0.995:
        return None
    pullback = abs(last['c'] - ema21.iloc[-1]) / atr.iloc[-1]
    if 0.3 < pullback < 1.2:
        return {'symbol': symbol, 'side': 'LONG',
                'sl': last['c'] - 1.5*atr.iloc[-1],
                'tp': last['c'] + 3.0*atr.iloc[-1]}
    return None

import feedparser, asyncio, openai, aiohttp

FEEDS = ['https://cointelegraph.com/rss', 'https://cryptonews.com/news/feed/']
FNG_API = 'https://api.alternative.me/fng/?limit=1'

async def fetch_fear_greed():
    async with aiohttp.ClientSession() as s:
        async with s.get(FNG_API) as r:
            data = await r.json()
    return int(data['data'][0]['value']), data['data'][0]['value_classification']

async def analyze_headlines(headlines):
    prompt = "\n".join(f"- {h}" for h in headlines[:15])
    client = openai.AsyncOpenAI()
    resp = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content":
            f"Crypto news sentiment:\n{prompt}\nReturn: BULLISH/BEARISH/NEUTRAL + 1 sentence."}]
    )
    return resp.choices[0].message.content

async def hourly_report(bot):
    while True:
        articles = []
        for url in FEEDS:
            feed = feedparser.parse(url)
            articles += [e.title for e in feed.entries[:10]]
        fng_val, fng_lbl = await fetch_fear_greed()
        analysis = await analyze_headlines(articles)
        await bot.send_message(f"Market Pulse | F&G: {fng_val} ({fng_lbl})\n{analysis}")
        await asyncio.sleep(3600)

@app.post("/webhook")
def receive_webhook():
    update = request.get_json(silent=True)
    message = update.get("message") or update.get("edited_message")
    _handle_message(message)
    return "ok", 200

def _handle_message(message):
    text = message.get("text", "").strip()
    result = call_loumielle(text, sender_id=sender_id)
    action = result["data_extraction"]["action"]

    if action in ("ADD_EXPENSE", "ADD_INCOME"):
        insert_transaction(data, sender_id=sender_id)

    elif action == "VIEW_STATUS":
        report = build_report(query_type, sender_id=sender_id)
        reply = f"{ai_response}\n\n{report}"

    send_message(chat_id, reply)

scheduler.add_job(sync_all, "interval", hours=1)
scheduler.add_job(auto_weekly_report,  "cron", day_of_week="sun", hour=20)
scheduler.add_job(auto_monthly_report, "cron", day="last", hour=20)