Make cancun fork

setup.cfg

@@ -97,6 +97,11 @@ packages =
     ethereum/shanghai/vm
     ethereum/shanghai/vm/instructions
     ethereum/shanghai/vm/precompiled_contracts
+    ethereum/cancun
+    ethereum/cancun/utils
+    ethereum/cancun/vm
+    ethereum/cancun/vm/instructions
+    ethereum/cancun/vm/precompiled_contracts
 
 
 package_dir =

src/ethereum/cancun/__init__.py

@@ -0,0 +1,10 @@
+"""
+Ethereum Cancun Hardfork
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+The Fifteenth Ethereum hardfork.
+"""
+
+from ethereum.fork_criteria import Unscheduled
+
+FORK_CRITERIA = Unscheduled()

src/ethereum/cancun/bloom.py

@@ -0,0 +1,83 @@
+"""
+Ethereum Logs Bloom
+^^^^^^^^^^^^^^^^^^^
+
+.. contents:: Table of Contents
+    :backlinks: none
+    :local:
+
+Introduction
+------------
+
+This modules defines functions for calculating bloom filters of logs. For the
+general theory of bloom filters see e.g. `Wikipedia
+<https://en.wikipedia.org/wiki/Bloom_filter>`_. Bloom filters are used to allow
+for efficient searching of logs by address and/or topic, by rapidly
+eliminating blocks and reciepts from their search.
+"""
+
+from typing import Tuple
+
+from ethereum.base_types import Uint
+from ethereum.crypto.hash import keccak256
+
+from .fork_types import Bloom, Log
+
+
+def add_to_bloom(bloom: bytearray, bloom_entry: bytes) -> None:
+    """
+    Add a bloom entry to the bloom filter (`bloom`).
+
+    The number of hash functions used is 3. They are calculated by taking the
+    least significant 11 bits from the first 3 16-bit words of the
+    `keccak_256()` hash of `bloom_entry`.
+
+    Parameters
+    ----------
+    bloom :
+        The bloom filter.
+    bloom_entry :
+        An entry which is to be added to bloom filter.
+    """
+    hash = keccak256(bloom_entry)
+
+    for idx in (0, 2, 4):
+        # Obtain the least significant 11 bits from the pair of bytes
+        # (16 bits), and set this bit in bloom bytearray.
+        # The obtained bit is 0-indexed in the bloom filter from the least
+        # significant bit to the most significant bit.
+        bit_to_set = Uint.from_be_bytes(hash[idx : idx + 2]) & 0x07FF
+        # Below is the index of the bit in the bytearray (where 0-indexed
+        # byte is the most significant byte)
+        bit_index = 0x07FF - bit_to_set
+
+        byte_index = bit_index // 8
+        bit_value = 1 << (7 - (bit_index % 8))
+        bloom[byte_index] = bloom[byte_index] | bit_value
+
+
+def logs_bloom(logs: Tuple[Log, ...]) -> Bloom:
+    """
+    Obtain the logs bloom from a list of log entries.
+
+    The address and each topic of a log are added to the bloom filter.
+
+    Parameters
+    ----------
+    logs :
+        List of logs for which the logs bloom is to be obtained.
+
+    Returns
+    -------
+    logs_bloom : `Bloom`
+        The logs bloom obtained which is 256 bytes with some bits set as per
+        the caller address and the log topics.
+    """
+    bloom: bytearray = bytearray(b"\x00" * 256)
+
+    for log in logs:
+        add_to_bloom(bloom, log.address)
+        for topic in log.topics:
+            add_to_bloom(bloom, topic)
+
+    return Bloom(bloom)