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https://github.com/status-im/eth2.0-specs.git
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135 lines
5.4 KiB
Python
135 lines
5.4 KiB
Python
from ..merkle_minimal import merkleize_chunks, hash
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from .ssz_typing import *
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# SSZ Serialization
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# -----------------------------
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BYTES_PER_LENGTH_OFFSET = 4
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def is_basic_type(typ):
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return is_uint(typ) or typ == bool
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def serialize_basic(value, typ):
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if is_uint(typ):
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return value.to_bytes(typ.byte_len, 'little')
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if issubclass(typ, bool):
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if value:
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return b'\x01'
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else:
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return b'\x00'
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def is_fixed_size(typ):
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if is_basic_type(typ):
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return True
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elif is_list_type(typ):
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return False
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elif is_vector_type(typ):
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return is_fixed_size(read_vector_elem_typ(typ))
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elif is_container_typ(typ):
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return all([is_fixed_size(t) for t in typ.get_field_types()])
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else:
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raise Exception("Type not supported: {}".format(typ))
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def serialize(obj, typ=None):
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if typ is None:
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typ = infer_type(obj)
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if is_basic_type(typ):
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return serialize_basic(obj, typ)
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elif is_list_type(typ) or is_vector_type(typ):
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return encode_series(list(obj), [read_elem_typ(typ)]*len(obj))
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elif is_container_typ(typ):
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return encode_series(obj.get_field_values(), typ.get_field_types())
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else:
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raise Exception("Type not supported: {}".format(typ))
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def encode_series(values, types):
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# bytes and bytesN are already in the right format.
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if isinstance(values, bytes):
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return values
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# Recursively serialize
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parts = [(is_fixed_size(types[i]), serialize(values[i], types[i])) for i in range(len(values))]
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# Compute and check lengths
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fixed_lengths = [len(serialized) if constant_size else BYTES_PER_LENGTH_OFFSET
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for (constant_size, serialized) in parts]
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variable_lengths = [len(serialized) if not constant_size else 0
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for (constant_size, serialized) in parts]
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# Check if integer is not out of bounds (Python)
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assert sum(fixed_lengths + variable_lengths) < 2 ** (BYTES_PER_LENGTH_OFFSET * 8)
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# Interleave offsets of variable-size parts with fixed-size parts.
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# Avoid quadratic complexity in calculation of offsets.
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offset = sum(fixed_lengths)
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variable_parts = []
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fixed_parts = []
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for (constant_size, serialized) in parts:
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if constant_size:
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fixed_parts.append(serialized)
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else:
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fixed_parts.append(offset.to_bytes(BYTES_PER_LENGTH_OFFSET, 'little'))
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variable_parts.append(serialized)
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offset += len(serialized)
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# Return the concatenation of the fixed-size parts (offsets interleaved) with the variable-size parts
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return b''.join(fixed_parts + variable_parts)
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# SSZ Hash-tree-root
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# -----------------------------
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def pack(values, subtype):
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if isinstance(values, bytes):
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return values
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return b''.join([serialize_basic(value, subtype) for value in values])
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def chunkify(bytez):
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bytez += b'\x00' * (-len(bytez) % 32)
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return [bytez[i:i + 32] for i in range(0, len(bytez), 32)]
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def mix_in_length(root, length):
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return hash(root + length.to_bytes(32, 'little'))
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def hash_tree_root(obj, typ=None):
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if typ is None:
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typ = infer_type(obj)
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if is_basic_type(typ):
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return merkleize_chunks(chunkify(serialize_basic(obj, typ)))
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elif is_list_type(typ) or is_vector_type(typ):
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subtype = read_elem_typ(typ)
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if is_basic_type(subtype):
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leaves = chunkify(pack(obj, subtype))
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else:
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leaves = [hash_tree_root(elem, subtype) for elem in obj]
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leaf_root = merkleize_chunks(leaves)
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return mix_in_length(leaf_root, len(obj)) if is_list_type(typ) else leaf_root
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elif is_container_typ(typ):
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leaves = [hash_tree_root(elem, subtyp) for elem, subtyp in zip(obj.get_field_values(), typ.get_field_types())]
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return merkleize_chunks(chunkify(b''.join(leaves)))
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else:
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raise Exception("Type not supported: obj {} type {}".format(obj, typ))
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def signing_root(value, typ):
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if typ is None:
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typ = infer_type(obj)
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assert is_container_typ(typ)
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leaves = [hash_tree_root(elem, subtyp) for elem, subtyp in zip(obj.get_field_values(), typ.get_field_types())[:-1]]
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return merkleize_chunks(chunkify(b''.join(leaves)))
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# Implementation notes:
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# - SSZContainer,Vector/BytesN.hash_tree_root/serialize functions are for ease, implementation here
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# - uint types have a 'byte_len' attribute
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# - uint types are not classes. They use NewType(), for performance.
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# This forces us to check type equivalence by exact reference.
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# There's no class. The type data comes from an annotation/argument from the context of the value.
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# - Vector is not valid to create instances with. Give it a elem-type and length: Vector[FooBar, 123]
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# - *The class of* a Vector instance has a `elem_type` (type, may not be a class, see uint) and `length` (int)
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# - BytesN is not valid to create instances with. Give it a length: BytesN[123]
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# - *The class of* a BytesN instance has a `length` (int)
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# Where possible, it is preferable to create helpers that just act on the type, and don't unnecessarily use a value
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# E.g. is_basic_type(). This way, we can use them in type-only contexts and have no duplicate logic.
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# For every class-instance, you can get the type with my_object.__class__
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# For uints, and other NewType related, you have to rely on type information. It cannot be retrieved from the value.
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# Note: we may just want to box integers instead. And then we can do bounds checking too. But it is SLOW and MEMORY INTENSIVE.
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#
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