Py.Cafe

import streamlit as st
import pandas as pd
import requests

# === USER CONFIGURABLE SETTINGS ===
API_KEY = st.text_input("Torn API Key", value="gZWmfZJgegZFL2vN")
TRAVEL_TYPE = st.selectbox("Travel Type", ["Standard", "Airstrip", "WLT", "Business"], index=1)
ITEM_SLOTS = st.number_input("Item Slots", min_value=1, max_value=100, value=29)
HOURS_PER_DAY = st.number_input("Hours Per Day", min_value=1, max_value=24, value=12)
TORNEX_USER_IDS = st.text_area(
    "TornExchange User IDs (name:id, one per line)",
    value="Malvoiy:2290370"
)
# Parse user IDs
TORNEX_USER_IDS = {
    line.split(":")[0].strip(): int(line.split(":")[1].strip())
    for line in TORNEX_USER_IDS.strip().splitlines() if ":" in line
}

# Travel time data in minutes (one-way)
travel_data = {
    "Mexico": {"Standard": 26, "Airstrip": 18, "WLT": 13, "Business": 8, "Cost": 6500},
    "Cayman Islands": {"Standard": 35, "Airstrip": 25, "WLT": 18, "Business": 11, "Cost": 10000},
    "Canada": {"Standard": 41, "Airstrip": 29, "WLT": 20, "Business": 12, "Cost": 9000},
    "Hawaii": {"Standard": 134, "Airstrip": 94, "WLT": 67, "Business": 40, "Cost": 11000},
    "United Kingdom": {"Standard": 159, "Airstrip": 111, "WLT": 80, "Business": 48, "Cost": 18000},
    "Argentina": {"Standard": 167, "Airstrip": 117, "WLT": 83, "Business": 50, "Cost": 21000},
    "Switzerland": {"Standard": 175, "Airstrip": 123, "WLT": 88, "Business": 53, "Cost": 27000},
    "Japan": {"Standard": 225, "Airstrip": 158, "WLT": 113, "Business": 68, "Cost": 32000},
    "China": {"Standard": 242, "Airstrip": 169, "WLT": 121, "Business": 72, "Cost": 35000},
    "United Arab Emirates": {"Standard": 271, "Airstrip": 190, "WLT": 135, "Business": 81, "Cost": 32000},
    "South Africa": {"Standard": 297, "Airstrip": 208, "WLT": 149, "Business": 89, "Cost": 40000}
}

foreign_prices = {
    "South Africa": {"Xanax": 752508, "LSD": 33445, "Lion Plushie": 400, "African Violet": 2000, "Opium": 66890, "PCP": 100334, "Shrooms": 16720},
    "United Arab Emirates": {"Camel Plushie": 14000, "Tribulus Omanense": 6000},
    "China": {"Panda Plushie": 400, "Peony": 5000, "Ecstasy": 45840, "LSD": 35597, "Speed": 152801, "Opium": 72632, "PCP": 103619},
    "Argentina": {"Monkey Plushie": 400, "Ceibo Flower": 500, "Cannabis": 5000, "LSD": 41210, "Speed": 168292, "Ketamine": 100005, "Shrooms": 19801},
    "Japan": {"Cherry Blossom": 500, "Xanax": 819084, "Ecstasy": 46424, "Speed": 154716, "Opium": 73543, "Ketamine": 91929, "Shrooms": 18386, "Vicodin": 119507},
    "United Kingdom": {"Heather": 5000, "Red Fox Plushie": 1000, "Nessie Plushie": 200, "Cannabis": 5057, "Ecstasy": 50063, "PCP": 121365, "Ketamine": 100127, "Shrooms": 20228, "Vicodin": 132794, "Xanax": 910149},
    "Mexico": {"Jaguar Plushie": 10000, "Dahlia": 300},
    "Cayman Islands": {"Stingray Plushie": 400, "Banana Orchid": 4000},
    "Canada": {"Wolverine Plushie": 30, "Crocus": 600, "Ecstasy": 61002, "Cannabis": 6099, "PCP": 146389, "Vicodin": 165029, "Xanax": 1109126},
    "Hawaii": {"Orchid": 700},
    "Switzerland": {"Chamois Plushie": 400, "Edelweiss": 900, "Cannabis": 4936, "LSD": 39487, "Speed": 167818, "PCP": 118460, "Ketamine": 100701, "Shrooms": 19743}
}

item_name_to_id = {
    "Cannabis": 196, "Ecstasy": 197, "Ketamine": 198, "LSD": 199, "Opium": 200,
    "PCP": 201, "Shrooms": 203, "Speed": 204, "Vicodin": 205, "Xanax": 206,
    "Jaguar Plushie": 258, "Dahlia": 260, "Wolverine Plushie": 261, "Crocus": 263, "Orchid": 264,
    "Nessie Plushie": 266, "Heather": 267, "Red Fox Plushie": 268, "Monkey Plushie": 269,
    "Ceibo Flower": 271, "Edelweiss": 272, "Chamois Plushie": 273, "Panda Plushie": 274,
    "Peony": 276, "Cherry Blossom": 277, "Lion Plushie": 281, "African Violet": 282,
    "Camel Plushie": 384, "Tribulus Omanense": 385, "Banana Orchid": 617, "Stingray Plushie": 618
}

def fetch_market_price(item_id):
    url = f"https://api.torn.com/v2/market/{item_id}/itemmarket?offset=0&key={API_KEY}"
    try:
        response = requests.get(url)
        data = response.json()
        return data.get("itemmarket", {}).get("item", {}).get("average_price")
    except Exception as e:
        st.warning(f"❌ Failed to fetch price for item ID {item_id}: {e}")
        return None

def fetch_tornexchange_user_price(user_id, item_id):
    url = f"https://tornexchange.com/api/price?user_id={user_id}&item_id={item_id}"
    try:
        response = requests.get(url)
        data = response.json()
        if data.get("status") == "error" and data.get("rate_limited"):
            retry_after = data.get("retry_after", 0)
            mins, secs = divmod(retry_after, 60)
            st.error(f"TornEx API Request limit reached. Try again in {mins} minutes {secs} seconds.")
            st.stop()
        if data.get("status") == "success":
            return data["data"]["price"]
    except Exception as e:
        st.warning(f"❌ Failed to fetch TornExchange price for user {user_id}, item {item_id}: {e}")
    return None

def fetch_tornexchange_best_listing(item_id):
    url = f"https://tornexchange.com/api/listings?item_id={item_id}&sort_by=price&page=1"
    try:
        response = requests.get(url)
        data = response.json()
        if data.get("status") == "error" and data.get("rate_limited"):
            retry_after = data.get("retry_after", 0)
            mins, secs = divmod(retry_after, 60)
            st.error(f"TornEx API Request limit reached. Try again in {mins} minutes {secs} seconds.")
            st.stop()
        if data.get("status") == "success":
            listings = data.get("data", {}).get("listings", [])
            if listings:
                return listings[0]["price"], listings[0]["trader"]
    except Exception as e:
        st.warning(f"❌ Failed to fetch TornExchange best listing for item {item_id}: {e}")
    return None, None

if st.button("Run Profit Analysis"):
    results = []

    for country, items in foreign_prices.items():
        travel_time = travel_data[country][TRAVEL_TYPE]
        round_trip = travel_time * 2
        trips_per_day = (HOURS_PER_DAY * 60) // round_trip

        for item_name, abroad_price in items.items():
            item_id = item_name_to_id.get(item_name)
            if not item_id:
                st.warning(f"⚠️ Missing item ID for {item_name}")
                continue

            market_price = fetch_market_price(item_id)
            if not market_price:
                st.warning(f"⚠️ Could not fetch price for {item_name} (ID {item_id})")
                continue

            # Apply 5% tax to market price
            taxed_market_price = market_price * 0.95

            # TornExchange best listing (now using /listings and highest price)
            best_listing_price, best_listing_trader = fetch_tornexchange_best_listing(item_id)

            # TornExchange user prices
            user_prices = {}
            for user, user_id in TORNEX_USER_IDS.items():
                user_price = fetch_tornexchange_user_price(user_id, item_id)
                if user_price:
                    user_prices[user] = user_price

            # Profit calculations
            profit_per_item_market = taxed_market_price - abroad_price
            profit_per_trip_market = profit_per_item_market * ITEM_SLOTS
            profit_per_minute_market = profit_per_trip_market / round_trip
            profit_per_day_market = profit_per_trip_market * trips_per_day

            # TornExchange best listing profit
            if best_listing_price:
                profit_per_item_best_listing = best_listing_price - abroad_price
                profit_per_trip_best_listing = profit_per_item_best_listing * ITEM_SLOTS
                profit_per_minute_best_listing = profit_per_trip_best_listing / round_trip
            else:
                profit_per_item_best_listing = profit_per_trip_best_listing = profit_per_minute_best_listing = None

            # TornExchange user profits
            user_profits = {}
            for user, price in user_prices.items():
                profit_per_item_user = price - abroad_price
                profit_per_trip_user = profit_per_item_user * ITEM_SLOTS
                profit_per_minute_user = profit_per_trip_user / round_trip
                user_profits[user] = {
                    "price": price,
                    "profit_per_item": profit_per_item_user,
                    "profit_per_trip": profit_per_trip_user,
                    "profit_per_minute": profit_per_minute_user
                }

            # Decide which is best
            best_method = "Market"
            best_profit_per_minute = profit_per_minute_market
            best_sell_price = round(taxed_market_price, 2)
            best_sell_to = "Market"

            if best_listing_price and profit_per_minute_best_listing and profit_per_minute_best_listing > best_profit_per_minute:
                best_method = "TornExchange Best"
                best_profit_per_minute = profit_per_minute_best_listing
                best_sell_price = best_listing_price
                best_sell_to = f"TornExchange ({best_listing_trader})"

            for user, profit_data in user_profits.items():
                if profit_data["profit_per_minute"] and profit_data["profit_per_minute"] > best_profit_per_minute:
                    best_method = f"TornExchange User ({user})"
                    best_profit_per_minute = profit_data["profit_per_minute"]
                    best_sell_price = profit_data["price"]
                    best_sell_to = f"TornExchange ({user})"

            results.append({
                "Destination": country,
                "Item": item_name,
                "Abroad Price": abroad_price,
                "Taxed Market Price": round(taxed_market_price, 2),
                "TornEx Best Price": best_listing_price,
                "TornEx Best Trader": best_listing_trader,
                **{f"TornEx {user} Price": profit_data["price"] for user, profit_data in user_profits.items()},
                "Best Sell Method": best_method,
                "Best Sell Price": best_sell_price,
                "Best Sell To": best_sell_to,
                "Profit/min Market": round(profit_per_minute_market, 2) if profit_per_minute_market is not None else None,
                "Profit/min TornEx Best": round(profit_per_minute_best_listing, 2) if profit_per_minute_best_listing is not None else None,
                **{f"Profit/min TornEx {user}": round(profit_data['profit_per_minute'], 2) for user, profit_data in user_profits.items()},
                "Best Profit/min": round(best_profit_per_minute, 2) if best_profit_per_minute is not None else None,
            })

    df = pd.DataFrame(results)
    df["Destination"] = df["Destination"].replace("United Arab Emirates", "UAE")

    if df.empty:
        st.error("🚫 No results. Check API key or internet connection.")
    else:
        df = df.sort_values(by="Best Profit/min", ascending=False).reset_index(drop=True)

        st.subheader("Top 10 Profitable Routes (Market, TornExchange)")
        main_cols = [
            "Destination",
            "Item",
            "Taxed Market Price",
            "Profit/min Market",
            "TornEx Best Price",
            "TornEx Best Trader",
            "Profit/min TornEx Best"
        ]
        main_df = df[main_cols].head(10)
        main_df = main_df.rename(columns={
            "Taxed Market Price": "Taxed Price",
            "Profit/min Market": "Taxed PPM",
            "TornEx Best Price": "TornEx Best Price",
            "TornEx Best Trader": "TornEx Best Trader",
            "Profit/min TornEx Best": "TornEx PPM"
        })
        st.dataframe(main_df)

        for user in TORNEX_USER_IDS:
            st.markdown(f"#### TornEx {user} Prices and PPM")
            user_cols = [
                "Item",
                f"TornEx {user} Price",
                f"Profit/min TornEx {user}"
            ]
            user_df = df[user_cols].head(10)
            user_df = user_df.rename(columns={
                f"TornEx {user} Price": f"{user} Price",
                f"Profit/min TornEx {user}": f"{user} PPM"
            })
            st.dataframe(user_df)

        st.markdown("#### Profit per day (Market, TornEx Best, and Users)")
        profit_day_cols = [
            "Item",
            "Profit/min Market",
            "Profit/min TornEx Best",
            *[f"Profit/min TornEx {user}" for user in TORNEX_USER_IDS]
        ]
        profit_day_df = df[profit_day_cols].head(10).copy()
        profit_day_df["Profit/day Market"] = profit_day_df["Profit/min Market"] * 60 * HOURS_PER_DAY
        profit_day_df["Profit/day TornEx Best"] = profit_day_df["Profit/min TornEx Best"] * 60 * HOURS_PER_DAY
        for user in TORNEX_USER_IDS:
            profit_day_df[f"Profit/day {user}"] = profit_day_df[f"Profit/min TornEx {user}"] * 60 * HOURS_PER_DAY

        show_cols = ["Item", "Profit/day Market", "Profit/day TornEx Best"] + [f"Profit/day {user}" for user in TORNEX_USER_IDS]
        st.dataframe(profit_day_df[show_cols])