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Python SDK

The Forta bot Python SDK comes with a set of classes to provide a consistent interface for developers to write their bots. There are also some utility functions available for your convenience to do common operations like searching for an event in the transaction logs. Check out the Python bots in our examples repo to learn more.

NOTE: while you can write bots in Python, you would still use the Node.js forta-agent CLI tool to run the bot.

Handlers

The most relevant functions for bot developers are the handler functions: initialize, handle_block and handle_transaction.

Your agent.py file must declare a handle_block and/or handle_transaction function. You can implement one or both of these depending on your use case, but at least one must be provided. These functions take a BlockEvent or TransactionEvent as their input, respectively, and return an array of zero or more Finding objects.

You can also optionally declare an initialize function that will be executed on bot startup. This is useful for fetching some data from the network or parsing some file before your bot begins.

BlockEvent

When a block is mined and detected by a Forta scan node, it will generate a BlockEvent containing information such as the block hash and block number. It contains the following fields:

  • type - specifies whether this was a block reorg or a regular block
  • network - specifies which network the block was mined on (e.g. mainnet, ropsten, rinkeby, etc)
  • block_hash - alias for block.hash
  • block_number - alias for block.number
  • block - data object containing the following fields:
    • difficulty
    • extra_data
    • gas_limit
    • gas_used
    • hash
    • logs_bloom
    • miner
    • mix_hash
    • nonce
    • number
    • parent_hash
    • receipts_root
    • sha3_uncles
    • size
    • state_root
    • timestamp
    • total_difficulty
    • transactions
    • transactions_root
    • uncles

TransactionEvent

When a transaction is mined and detected by a Forta scan node, it will generate a TransactionEvent containing various information about the transaction. It contains the following fields:

  • type - specifies whether this was from a block reorg or a regular block
  • network - specifies which network the transaction was mined on (e.g. mainnet, ropsten, rinkeby, etc)
  • hash - alias for transaction.hash
  • from_ - alias for transaction.from_
  • to - alias for transaction.to
  • gas_price - alias for transaction.gas_price
  • timestamp - alias for block.timestamp
  • block_number - alias for block.number
  • block_hash - alias for block.hash
  • addresses - map of addresses involved in the transaction (generated from transaction to/from address, any event log address and trace data address if available)
  • block - data object containing following fields:
    • hash
    • number
    • timestamp
  • transaction - data object containing the following fields:
    • hash
    • from_
    • to
    • nonce
    • gas
    • gas_price
    • value
    • data
    • r
    • s
    • v
  • logs - list of log objects with following fields:
    • address
    • topics
    • data
    • log_index
    • block_number
    • block_hash
    • transaction_index
    • transaction_hash
    • removed
  • traces - only with tracing enabled; list of trace objects with following fields:
    • block_hash
    • block_number
    • subtraces
    • trace_address
    • transaction_hash
    • transaction_position
    • type
    • error
    • action - object with following fields:
      • call_type
      • to
      • from_
      • input
      • value
      • init
      • address
      • balance
      • refund_address
    • result - object with following fields:
      • gas_used
      • address
      • code
      • output

filter_log

filter_log is a convenience function on TransactionEvent to filter and decode transaction logs. For example, you can use it to get all of the Transfer logs in a transaction from a particular ERC-20 token:

erc20_token_address = '0x123abc'
transfer_event_abi = '{"name":"Transfer","type":"event","anonymous":false,"inputs":[{"indexed":true,"name":"from","type":"address"},{"indexed":true,"name":"to","type":"address"},{"indexed":false,"name":"value","type":"uint256"}]}'
transfers = transaction_event.filter_log(transfer_event_abi, erc20_token_address)
print(f'found {transfers.length} transfer events')

The underlying library used for decoding event logs is web3.py. The Python SDK uses the web3.py processLog method and returns an array of Event Log objects. To better understand usage, see the Python filtering example bot.

filter_function

filter_function is a convenience function on TransactionEvent to filter and decode function calls in the transaction or traces. For example, you can use it to get all of the transferFrom function calls on a particular ERC-20 token:

erc20_token_address = '0x123abc'
transferFrom_function_abi = '{"name":"transferFrom","type":"function","constant":false,"inputs":[{"name":"from","type":"address"},{"name":"to","type":"address"},{"name":"value","type":"uint256"}],"outputs":[],"payable":false,"stateMutability":"nonpayable"}'
transfers = transaction_event.filter_function(transferFrom_function_abi, erc20_token_address)
print(f'found {transfers.length} function calls')

The underlying library used for decoding function calls is web3.py. The Python SDK uses the web3.py decode_function_input method and returns an array of (ContractFunction, dict) tuples. To better understand usage, see the Python filtering example bot.

Finding

If a bot wants to flag a transaction/block because it meets some condition (e.g. flash loan attack), the handler function would return a Finding object. This object would detail the results of the finding and provide metadata such as the severity of the finding. A Finding object accepts the following properties:

  • name - required; human-readable name of finding e.g. "High Gas"
  • description - required; brief description e.g. "High gas used: 1,000,000"
  • alert_id - required; unique string to identify this class of finding, primarily used to group similar findings for the end user
  • protocol - required; name of protocol being reported on e.g. "aave", defaults to "ethereum" if left blank
  • type - required; indicates type of finding:
    • Exploit
    • Suspicious
    • Degraded
    • Info
  • severity - required; indicates impact level of finding:
    • Critical - exploitable vulnerabilities, massive impact on users/funds
    • High - exploitable under more specific conditions, significant impact on users/funds
    • Medium - notable unexpected behaviours, moderate to low impact on users/funds
    • Low - minor oversights, negligible impact on users/funds
    • Info - miscellaneous behaviours worth describing
  • metadata - optional; dict (both keys and values as strings) for providing extra information

get_json_rpc_url

A convenience function called get_json_rpc_url can be used to load a JSON-RPC URL for your bot. When running in production, this function will return a URL injected by the scan node that is running the bot. When running locally in development, this function will return the jsonRpcUrl property specified in your forta.config.json file (or https://cloudflare-eth.com/ by default).

get_web3_provider

get_web3_provider is a convenience function that returns a web3.py Provider which can be used to interact with the blockchain. The value from get_json_rpc_url will be used as the JSON-RPC endpoint to connect to.

get_transaction_receipt

A convenience function called get_transaction_receipt can be used to fetch the entire receipt of a transaction and returned in a format matching the SDK Receipt interface.

create_block_event

A utility function for writing tests. You can use create_block_event to easily generate a mock BlockEvent object when writing unit tests for your handle_block handler. To better understand usage, see the Python unit test example.

create_transaction_event

A utility function for writing tests. You can use create_transaction_event to easily generate a mock TransactionEvent object when writing unit tests for your handle_transaction handler. To better understand usage, see the Python unit test example.

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