dexscreener-python

async dexscreener api client for python.

rate limiting. 429 retry. response caching. request dedup. works on any chain.

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extracted from a production trading system. handles rate limits gracefully.

🛡️ Why this library?

dexscreener's api is free and powerful, but:

• 429s kill your app if you don't handle them
• no python client exists that handles rate limits properly
• concurrent requests for the same token waste your quota

this library solves all three:

from dexscreener import DexScreenerClient

async with DexScreenerClient() as client:
    # get all trading pairs for a token
    pairs = await client.get_token_pairs("solana", "So11111111111111111111111111111111111111112")

    for pair in pairs:
        print(f"{pair.base_token_symbol}: ${pair.price_usd} | liq: ${pair.liquidity_usd}")

429s → automatic exponential backoff (3s → 6s → 12s). duplicate requests → deduplicated into one HTTP call. results → cached with configurable TTL.

📦 Install

pip install dexscreener-python

requires python 3.11+

⚡ Features

feature	description
any chain	solana, ethereum, base, bsc, arbitrum — anything dexscreener supports
adaptive rate limiting	token bucket that backs off on 429 and recovers after success
global 429 cooldown	one 429 pauses ALL requests briefly (prevents request storms)
response cache	configurable TTL per endpoint. concurrent calls share one request.
batch support	fetch up to 30 tokens in a single request
typed data	DexPairData dataclass with computed properties (buy/sell ratio, age, etc.)

🔧 Usage

💰 Token Pairs

pairs = await client.get_token_pairs("solana", token_address)

best_pair = pairs[0]  # sorted by liquidity (highest first)
print(f"Price: ${best_pair.price_usd}")
print(f"Liquidity: ${best_pair.liquidity_usd}")
print(f"24h Volume: ${best_pair.volume_24h}")
print(f"Buy/Sell 5m: {best_pair.buy_sell_ratio_5m:.2f}")
print(f"Age: {best_pair.pair_age_seconds // 3600}h")

💵 Token Price

price = await client.get_token_price("solana", token_address)
print(f"${price}")

📦 Batch Fetch (up to 30 tokens)

data = await client.get_tokens_batch("solana", [addr1, addr2, addr3])
for addr, pair in data.items():
    print(f"{pair.base_token_symbol}: ${pair.price_usd}")

🔍 Search

results = await client.search_pairs("BONK")
for pair in results:
    print(f"{pair.base_token_symbol} on {pair.dex_id}: ${pair.price_usd}")

🚀 Boosted Tokens

boosted = await client.get_boosted_tokens("solana")
# boosted tokens are paid promotions — treat with caution

🎯 Specific Pair

pair = await client.get_pair_by_address("solana", pair_address)
print(f"{pair.dex_id}: ${pair.price_usd}")

📋 DexPairData

all methods return DexPairData objects with these fields:

field	type	description
chain_id	str	chain identifier
dex_id	str	dex identifier (raydium, uniswap_v3, etc.)
pair_address	str	pair contract address
base_token_address	str	base token mint/address
base_token_symbol	str	token symbol
price_usd	Decimal	current price in USD
price_native	Decimal	price in native token (SOL, ETH, etc.)
liquidity_usd	Decimal	total liquidity in USD
volume_5m / 1h / 6h / 24h	Decimal	volume by timeframe
price_change_5m / 1h / 6h / 24h	Decimal	price change %
buys_5m / 1h / 24h	int	buy transactions
sells_5m / 1h / 24h	int	sell transactions
pair_created_at	int	unix timestamp (ms)

computed properties:

property	description
buy_sell_ratio_5m	buy/sell ratio over 5 minutes (>1 = more buying)
buy_sell_ratio_1h	buy/sell ratio over 1 hour
has_liquidity	True if liquidity > $1000
pair_age_seconds	pair age in seconds

⚙️ Configuration

client = DexScreenerClient(
    rate_limit=5.0,      # requests/second (default: 5.0, dexscreener limit is ~300/min)
    cache_ttl=8.0,       # default cache TTL in seconds
)

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🆚 Comparison

	dexscreener-python	raw httpx / requests
Rate limiting	✅ adaptive token bucket	❌ manual
429 retry	✅ exponential backoff	❌ crash
Global cooldown	✅ one 429 pauses all	❌ per-request only
Response cache	✅ TTL + dedup	❌ manual
Typed data	✅ DexPairData dataclass	❌ raw dicts
Batch support	✅ up to 30 tokens	❌ manual loop
Async	✅ native	depends

License

MIT

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📦 Also by JinUltimate1995

• jupiter-swap-python — Jupiter swap client for Python. Async. Typed.
• pumpfun-python — PumpFun bonding curve + PumpSwap AMM. Direct swaps from Python.
• solana-rpc-resilient — Fault-tolerant Solana RPC with automatic failover.

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Support

If this saved you time, a tip is appreciated — it funds maintenance.

Tip jar (SOL): Evot66rHqu6WyiBF948YipgArHSMeJ5D4GeNJXPTpV6q

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