Audited every script in learning-examples/ against mainnet. Broken — found by running them, all invisible offline: - listen_geyser.py crashed with IndexError after ~11 coins: it never resolved v0 address-lookup-table accounts, which geyser reports in meta.loaded_writable_addresses / loaded_readonly_addresses. Resolving them removes the crash and brings detections level with the WebSocket listeners, 35 coins each per 150 s. - compare_listeners.py logged 13,090,862 error lines / 888 MB in 150 s and never printed its own 30-second report: the inner recv() loop caught ConnectionClosed in a broad handler that only logged, so every following recv() raised at once and the outer reconnect handler was unreachable. Now 12 KB and exit 0. Same shape fixed in compare_migration_listeners.py, listen_blocksubscribe.py and extract_blocksubscribe_transactions.py; the last two also gained the reconnect loop their siblings already had. - decode_from_gettransaction.py matched instructions on account count instead of discriminator, reporting a real 19-account create_v2 as claim_cashback with every account under the wrong name. It also walked only top-level instructions, and in 40 consecutive pump.fun transactions there was 1 top-level pump instruction against 8 inner ones. - decode_from_blocksubscribe.py crashed on every real create_v2: on chain the trailing args are variable length, 0001 in one tx and 00 in another, so is_cashback_enabled can be absent entirely. - poll_bonding_curve_progress.py polled a hardcoded dead mint and took no argv. Obsolete: - Delete listen_blocksubscribe_old_raydium.py. Seven minutes on mainnet produced 0 initialize2 events while the wrapper listener caught 3 real migrations. - Delete the duplicate geyser stubs and protos under listen-new-tokens/. The protos were byte-identical to src/geyser/proto and the stubs had drifted; both geyser examples now import src.geyser.generated. - Recapture all four fixtures. The old ones were from Aug 2024 and included a 49-byte pre-creator bonding curve. Behind the protocol: - fetch_price.py, get_bonding_curve_status.py, poll_bonding_curve_progress.py and decode_from_getaccountinfo.py never read quote_mint and scaled by a hardcoded 1e9. Against a live USDC-paired curve the price was off by 1000x. - get_pumpswap_pools.py stopped parsing at coin_creator and missed the i128 virtual_quote_reserves. Live pools carry 17.5845 SOL of them, which under-prices by 3.5-23.9% when ignored. Duplication and naming: - Merge manual_buy_cu_optimized.py into manual_buy.py --cu-optimized. The deleted file's docstring said 512 KB while its code used 16 MB; simulation confirms 512 KB and 4 MB both fail MaxLoadedAccountsDataSizeExceeded on Token-2022 mints, so 16 MB is the correct value. - Merge listen_logsubscribe_abc.py into listen_logsubscribe.py. Its ATA derivation hardcoded the legacy token program, so every Associated BC it printed for a Token2022 coin was an address that does not exist on chain. Fixed on merge and cross-checked 59/59 against on-chain accounts. - Remove 19 dead symbols. BREAKING_FEE_RECIPIENTS is still live in the PumpSwap scripts and stays there. - Normalize naming: kebab-case directories, RPC method names as one lowercase token, scripts verb-first. Rules documented in CLAUDE.md. get_graduating_tokens.py is knowingly left broken: getProgramAccounts over the whole pump program is now rejected by providers and it needs a getProgramAccountsV2 rewrite, which belongs in its own PR. Verified: both offline gates pass, all 41 examples parse, every read-only script exercised on mainnet against SOL- and USDC-paired coins, no new ruff findings (427 -> 413). No script that spends real funds was run. Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
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A Solana trading bot for pump.fun and letsbonk.fun. Its core feature is sniping new tokens: it watches for token creation, buys, and exits on a strategy you configure. learning-examples/ contains standalone scripts covering every piece of the flow — listeners, price math, manual buys and sells — useful on their own even if you never run the bot.
For the full walkthrough, see Solana: Creating a trading and sniping pump.fun bot. It explains the concepts well but lags behind the code, so treat this README as the source of truth for setup and configuration.
Also by Chainstack — if you prefer a terminal interface or want to give an AI agent trading capabilities:
- pumpfun-cli — CLI for trading, launching, and managing tokens on pump.fun; buy, sell, wallet management, and smart routing between the bonding curve and PumpSwap AMM.
- pumpclaw — agent skill that equips AI assistants (OpenClaw, Claude Code, Cursor, Codex) with the ability to operate pumpfun-cli.
🚨 SCAM ALERT: The Issues section is regularly targeted by scam bots that try to redirect you to an external site and drain your funds. A GitHub Action tags the common patterns, which is not 100% accurate. Deleted comments in issues are scam bots after your private keys — genuine outside devs are welcome and appreciated.
⚠️ NOT FOR PRODUCTION: This code is for learning purposes only. We assume no responsibility for the code or its usage. Modify it for your needs and learn from it — the examples, issues, and PRs contain valuable insights.
Getting started
1. Prerequisites
Install uv, a fast Python package manager. The project needs Python 3.11+; uv uses an existing install if it's new enough, otherwise it fetches one for you.
2. Clone and install
git clone https://github.com/chainstacklabs/pumpfun-bonkfun-bot.git
cd pumpfun-bonkfun-bot
uv sync # create .venv and install dependencies
source .venv/bin/activate # Unix/macOS — Windows: .venv\Scripts\activate
uv pip install -e . # install the bot as an editable package
3. Set your credentials
cp .env.example .env
Fill in .env:
| Variable | Purpose |
|---|---|
SOLANA_NODE_RPC_ENDPOINT |
HTTPS RPC endpoint |
SOLANA_NODE_WSS_ENDPOINT |
WebSocket endpoint (for logs / blocks listeners) |
SOLANA_PRIVATE_KEY |
Base58 private key of the trading wallet |
GEYSER_ENDPOINT, GEYSER_API_TOKEN, GEYSER_AUTH_TYPE |
Only for the geyser listener |
Public RPC nodes will not work for this workload — see throughput below.
4. Configure a bot
Each YAML file in bots/ is one bot instance. They ship with commented defaults; start from the one matching the listener you want:
| File | Listener | Ships with |
|---|---|---|
bot-sniper-1-geyser.yaml |
geyser — fastest, needs a Geyser endpoint |
pump_fun |
bot-sniper-2-logs.yaml |
logs — logsSubscribe, supported everywhere |
pump_fun |
bot-sniper-3-blocks.yaml |
blocks — blockSubscribe, not supported by every provider |
pump_fun |
bot-sniper-4-pp.yaml |
pumpportal — third-party aggregator |
lets_bonk |
Set platform: "pump_fun" or platform: "lets_bonk". pump.fun supports all four listeners; letsbonk.fun supports blocks, geyser, and pumpportal but not logs. The bot validates the pairing at startup and refuses to run an invalid one.
Set enabled: false to keep a config around without running it. Every bot with enabled: true starts when you run the bot.
5. Run
pump_bot # as an installed package
uv run src/bot_runner.py # or directly
Logs land in logs/{bot_name}_{timestamp}.log.
Configuration reference
The YAML files are commented inline. The sections that matter most:
trade—buy_amount(in SOL), slippage,exit_strategy(time_based,tp_sl,manual), andextreme_fast_mode, which skips the bonding-curve price check and buys a fixed token amount instead. Faster, less precise.priority_fees— fixed or dynamic. Dynamic costs an extra RPC call, which slows the buy.filters—listener_type,max_token_age, name/creator matching,marry_mode(buy only, never sell),yolo_mode(trade continuously).retries— attempts and the wait windows around creation, buy, and the next token.cleanup— when to close leftover token accounts:disabled,on_fail,after_sell,post_session.node.max_rps— cap requests per second to match your provider's plan.
Non-SOL quote assets
pump.fun supports quote assets other than SOL, USDC first. Amounts are in that mint's own whole units, so usdc: 1.0 is one USDC and is not comparable to buy_amount:
trade:
buy_amount: 0.0001 # SOL-paired coins
quote_amounts:
usdc: 1.0 # USDC-paired coins
filters:
allowed_quote_mints: ["sol", "usdc"] # omit to allow any configured quote
Keys accept the aliases sol / wsol / usdc or a raw base58 mint. A coin whose quote mint has no configured amount is skipped with a log line rather than bought with a wrongly-scaled amount. SOL always falls back to buy_amount, so existing configs keep working untouched. Buying a USDC-paired coin needs USDC in the wallet plus a little SOL for fees and ATA rent.
Learning examples
Standalone scripts, runnable with uv run <path>. No bot config needed — they read .env directly.
| Path | What it covers |
|---|---|
listen-new-tokens/ |
One listener per method (logs, blocks, geyser, pumpportal) plus compare_listeners.py to race them |
listen-migrations/ |
Detect a token graduating from the bonding curve to PumpSwap, via the migration wrapper program or new pool accounts |
bonding-curve-progress/ |
Curve state, progress polling, and tokens close to graduating |
pumpswap/ |
Manual buy/sell against the PumpSwap AMM, and pool discovery |
letsbonk-buy-sell/ |
Manual exact-in / exact-out buys and sells on letsbonk.fun |
copy-trading/ |
Watch another wallet's transactions |
manual_buy.py, manual_sell.py, fetch_price.py |
The minimal pump.fun trade and price path. manual_buy.py --cu-optimized adds a SetLoadedAccountsDataSizeLimit instruction |
mint_and_buy_v2.py |
Create a coin and buy it in one go |
decode_from_*.py, calculate_discriminator.py |
Decoding account data, transactions, and Anchor discriminators |
cleanup_accounts.py |
Close leftover empty token accounts |
Most of these take the mint or curve address as the first argument, and print usage if
you leave it off. The decode_from_*.py scripts fall back to the saved fixtures beside
them (raw_*.json), which are recaptured from mainnet rather than hand-edited — a
stale fixture makes a working decoder look broken and a broken one look fine.
Two examples double as verification scripts to run after any pump.fun program upgrade:
uv run learning-examples/verify_v2_account_layout.py # offline: account layouts, PDAs, encoding
uv run learning-examples/simulate_v2_trades.py <MINT> # mainnet simulation, no funds moved
uv run learning-examples/verify_tx_status_checks.py # offline: every example checks meta.err
Related docs: Listening to pump.fun migrations · Sniping with only logsSubscribe
Throughput and rate limits
Every node provider has its own limits — method availability, requests per second, plan-specific caps. Consult your provider's docs before running the bot, and don't expect public RPC nodes to hold up.
For Chainstack, the numbers you need are in the throughput guidelines, kept up to date.
The bot rate-limits itself with a token bucket: node.max_rps in the YAML (25 by default) smooths the request rate while allowing short bursts, and 429s are retried with exponential backoff.
For faster execution, Chainstack offers Solana Trader nodes for transaction propagation and the Yellowstone gRPC Geyser plugin for streaming updates.
IDLs
The IDLs under idl/ are vendored from pump-fun/pump-public-docs — currently upstream commit 9c82f61. To refresh, copy pump.json, pump_amm.json, and pump_fees.json into pump_fun_idl.json, pump_swap_idl.json, and pump_fees.json, and note the upstream commit in your commit message. Don't hand-edit them.
The buy_v2 / sell_v2 account lists are complete in the IDL — that's the point of the v2 interface. The legacy buy / sell lists are not: the IDL omits PDAs the on-chain program requires. For anything outside v2, cross-check against a recent successful on-chain transaction before trusting the IDL.
CLAUDE.md documents the protocol gotchas in detail — account layouts, quote-mint handling, fee recipients, and what the IDL gets wrong.
Contributing
Maintainers are listed in MAINTAINERS.md. Open an Issue for feedback or bugs.
Lint and format the files you changed (uv sync installs ruff for you):
uv run ruff check --fix path/to/changed.py
uv run ruff format path/to/changed.py
Running ruff check over the whole repo reports a large backlog of pre-existing
errors — that's a known baseline, so scope it to your own files.
Then test your change with a learning example rather than by running a bot with real funds.