import httpx

# Search for a token
resp = httpx.get("https://api.dexscreener.com/latest/dex/search", params={"q": "BONK"})
pairs = resp.json()["pairs"]
for p in pairs[:3]:
    print(f"{p['baseToken']['symbol']}/{p['quoteToken']['symbol']} on {p['chainId']}: ${p['priceUsd']}")

# Or with curl
curl "https://api.dexscreener.com/latest/dex/search?q=BONK"

# Search by token name, symbol, or address (returns ~30 pairs across all chains)
GET /latest/dex/search?q=BONK
GET /latest/dex/search?q=So11111111111111111111111111111111111111112

# Single pair
GET /latest/dex/pairs/solana/PAIR_ADDRESS

# Multiple pairs (comma-separated)
GET /latest/dex/pairs/solana/PAIR1,PAIR2,PAIR3

# All pairs containing this token across all chains
GET /latest/dex/tokens/TOKEN_MINT_ADDRESS

# Chain-specific (v1)
GET /token-pairs/v1/solana/TOKEN_MINT

# Multiple tokens on one chain (v1)
GET /tokens/v1/solana/TOKEN1,TOKEN2,TOKEN3

# Latest token profiles (60 req/min)
GET /token-profiles/latest/v1

# Latest boosted tokens
GET /token-boosts/latest/v1

# Top boosted tokens (sorted by total boost amount)
GET /token-boosts/top/v1

# Token orders (ads, profile claims)
GET /orders/v1/solana/TOKEN_ADDRESS

# Community takeovers
GET /community-takeovers/latest/v1

{
  "chainId": "solana",
  "dexId": "raydium",
  "url": "https://dexscreener.com/solana/PAIR_ADDR",
  "pairAddress": "3nMFwZX...",
  "labels": ["CLMM"],
  "baseToken": { "address": "So11...", "name": "Wrapped SOL", "symbol": "SOL" },
  "quoteToken": { "address": "EPjF...", "name": "USD Coin", "symbol": "USDC" },
  "priceNative": "86.08",
  "priceUsd": "86.08",
  "txns": {
    "m5":  { "buys": 25, "sells": 18 },
    "h1":  { "buys": 916, "sells": 1282 },
    "h6":  { "buys": 11309, "sells": 12661 },
    "h24": { "buys": 27974, "sells": 31475 }
  },
  "volume": { "m5": 41680, "h1": 6773038, "h6": 71628073, "h24": 167164493 },
  "priceChange": { "m5": -0.01, "h1": -0.36, "h6": 0.82, "h24": 0.25 },
  "liquidity": { "usd": 28168478, "base": 232348, "quote": 8167805 },
  "fdv": 8171740,
  "marketCap": 8171740,
  "pairCreatedAt": 1688106058000,
  "info": {
    "imageUrl": "https://cdn.dexscreener.com/...",
    "websites": [{ "url": "https://...", "label": "Website" }],
    "socials": [{ "url": "https://x.com/...", "type": "twitter" }]
  }
}

def lookup_token(address: str) -> dict | None:
    """Get the best pair for a token by liquidity."""
    resp = httpx.get(f"https://api.dexscreener.com/latest/dex/tokens/{address}")
    pairs = resp.json().get("pairs", [])
    if not pairs:
        return None
    # Sort by liquidity (highest first)
    pairs.sort(key=lambda p: p.get("liquidity", {}).get("usd", 0), reverse=True)
    return pairs[0]

def find_best_price(symbol: str) -> list[dict]:
    """Find a token across all chains and compare prices."""
    resp = httpx.get("https://api.dexscreener.com/latest/dex/search", params={"q": symbol})
    pairs = resp.json().get("pairs", [])
    results = []
    for p in pairs:
        if p["baseToken"]["symbol"].upper() == symbol.upper():
            results.append({
                "chain": p["chainId"],
                "dex": p["dexId"],
                "price": float(p.get("priceUsd", 0)),
                "liquidity": p.get("liquidity", {}).get("usd", 0),
                "volume_24h": p.get("volume", {}).get("h24", 0),
            })
    return sorted(results, key=lambda x: x["liquidity"], reverse=True)

def get_newly_boosted() -> list[dict]:
    """Get tokens that were recently boosted (paid promotion)."""
    resp = httpx.get("https://api.dexscreener.com/token-boosts/latest/v1")
    return [
        {
            "chain": t["chainId"],
            "address": t["tokenAddress"],
            "boost_amount": t.get("amount", 0),
            "total_boost": t.get("totalAmount", 0),
            "description": t.get("description", ""),
        }
        for t in resp.json()
    ]

def analyze_pressure(pair: dict) -> dict:
    """Analyze buy/sell pressure from transaction counts."""
    txns = pair.get("txns", {})
    result = {}
    for tf in ["m5", "h1", "h6", "h24"]:
        data = txns.get(tf, {})
        buys = data.get("buys", 0)
        sells = data.get("sells", 0)
        total = buys + sells
        result[tf] = {
            "buys": buys, "sells": sells, "total": total,
            "buy_ratio": buys / total if total > 0 else 0.5,
        }
    return result