• Efficient, lightweight reimplementation of electrum-server

  • Fast synchronization of bitcoin mainnet from Genesis. Recent hardware should synchronize in well under 24 hours. The fastest time to height 448k (mid January 2017) reported is under 4h 30m. On the same hardware JElectrum would take around 4 days and electrum-server probably around 1 month.

  • Various configurable means of controlling resource consumption and handling bad clients and denial of service attacks. These include maximum connection counts, subscription limits per-connection and across all connections, maximum response size, per-session bandwidth limits, and session timeouts.

  • Minimal resource usage once caught up and serving clients; tracking the transaction mempool appears to be the most expensive part.

  • Mostly asynchronous processing of new blocks, mempool updates, and client requests. Busy clients should not noticeably impede other clients’ requests and notifications, nor the processing of incoming blocks and mempool updates.

  • Daemon failover. More than one daemon can be specified, and ElectrumX will failover round-robin style if the current one fails for any reason.

  • Peer discovery protocol removes need for IRC

  • Coin abstraction makes compatible altcoin and testnet support easy.


ElectrumX does not do any pruning or throwing away of history. I want to retain this property for as long as it is feasible, and it appears efficiently achievable for the foreseeable future with plain Python.

The following all play a part in making it efficient as a Python blockchain indexer:

  • aggressive caching and batching of DB writes

  • more compact and efficient representation of UTXOs, address index, and history. Electrum Server stores full transaction hash and height for each UTXO, and does the same in its pruned history. In contrast ElectrumX just stores the transaction number in the linear history of transactions. ElectrumX can determine block height from a simple binary search of tx counts stored on disk. ElectrumX stores historical transaction hashes in a linear array on disk.

  • placing static append-only metadata indexable by position on disk rather than in levelDB. It would be nice to do this for histories but I cannot think of a way.

  • avoiding unnecessary or redundant computations, such as converting address hashes to human-readable ASCII strings with expensive bignum arithmetic, and then back again.

  • better choice of Python data structures giving lower memory usage as well as faster traversal

  • leveraging asyncio for asynchronous prefetch of blocks to mostly eliminate CPU idling. As a Python program ElectrumX is unavoidably single-threaded in its essence; we must keep that CPU core busy.

Python’s asyncio means ElectrumX has no (direct) use for threads and associated complications.