Build a Cross-Border Grocery Price Dashboard for India and the UAE

import datetime as dt, os, requests

API = "https://api.quickcommerceapi.com/v1/groupsearch"
HEADERS = {"X-API-Key": os.environ["QC_API_KEY"]}

MARKETS = {
    "IN": {"lat": 12.9021, "lon": 77.6639, "platforms": "BlinkIt,Zepto,Swiggy"},   # Bengaluru
    "AE": {"lat": 25.1972, "lon": 55.2744, "platforms": "NoonMinutes,TalabatMart"},  # Downtown Dubai
}
PRODUCTS = ["nutella 350g", "maggi noodles", "basmati rice", "kelloggs corn flakes"]

def collect():
    rows, ts = [], dt.datetime.utcnow().isoformat()
    for country, params in MARKETS.items():
        for q in PRODUCTS:
            r = requests.get(API, headers=HEADERS, params={"q": q, **params}, timeout=60)
            r.raise_for_status()
            for platform, products in r.json()["data"]["results"].items():
                for p in products[:5]:  # top matches per platform
                    if not p.get("offer_price"):
                        continue
                    rows.append({
                        "ts": ts, "country": country, "query": q, "platform": platform,
                        "name": p["name"], "brand": p.get("brand"), "quantity": p.get("quantity"),
                        "price": float(p["offer_price"]), "mrp": p.get("mrp"),
                        "currency": p["currency"], "available": p.get("available"),
                    })
    return rows

import re

# Rates to your reporting currency. Fill from your own source; these are placeholders.
TO_INR = {"INR": 1.0, "AED": None}

UNITS = {"g": 1, "kg": 1000, "ml": 1, "l": 1000}

def grams_or_ml(quantity):
    m = re.search(r"([\d.]+)\s*(kg|g|ml|l)\b", (quantity or "").lower())
    return float(m.group(1)) * UNITS[m.group(2)] if m else None

def normalise(row):
    rate = TO_INR[row["currency"]]
    size = grams_or_ml(row["quantity"])
    row["price_inr"] = row["price"] * rate if rate else None
    row["inr_per_100"] = row["price_inr"] / size * 100 if row["price_inr"] and size else None
    return row