Notice: This document is a work-in-progress describing typing, serialization, and Merkleization of Eth2 objects.
- SimpleSerialize (SSZ)
Name | Value | Description |
---|---|---|
BYTES_PER_CHUNK |
32 |
Number of bytes per chunk. |
BYTES_PER_LENGTH_OFFSET |
4 |
Number of bytes per serialized length offset. |
BITS_PER_BYTE |
8 |
Number of bits per byte. |
uintN
:N
-bit unsigned integer (whereN in [8, 16, 32, 64, 128, 256]
)boolean
:True
orFalse
- container: ordered heterogeneous collection of values
- python dataclass notation with key-type pairs, e.g.
class ContainerExample(Container): foo: uint64 bar: boolean
- vector: ordered fixed-length homogeneous collection, with
N
values- notation
Vector[type, N]
, e.g.Vector[uint64, N]
- notation
- list: ordered variable-length homogeneous collection, limited to
N
values- notation
List[type, N]
, e.g.List[uint64, N]
- notation
- bitvector: ordered fixed-length collection of
boolean
values, withN
bits- notation
Bitvector[N]
- notation
- bitlist: ordered variable-length collection of
boolean
values, limited toN
bits- notation
Bitlist[N]
- notation
- union: union type containing one of the given subtypes
- notation
Union[type_0, type_1, ...]
, e.g.union[null, uint64]
- notation
We recursively define "variable-size" types to be lists, unions, Bitlist
and all types that contain a variable-size type. All other types are said to be "fixed-size".
For convenience we alias:
bit
toboolean
byte
touint8
(this is a basic type)BytesN
toVector[byte, N]
(this is not a basic type)null
:{}
Assuming a helper function default(type)
which returns the default value for type
, we can recursively define the default value for all types.
Type | Default Value |
---|---|
uintN |
0 |
boolean |
False |
Container |
[default(type) for type in container] |
Vector[type, N] |
[default(type)] * N |
Bitvector[boolean, N] |
[False] * N |
List[type, N] |
[] |
Bitlist[boolean, N] |
[] |
Union[type_0, type_1, ...] |
default(type_0) |
An SSZ object is called zeroed (and thus, is_zero(object)
returns true) if it is equal to the default value for that type.
- Empty vector types (
Vector[type, 0]
,Bitvector[0]
) are illegal. - Containers with no fields are illegal.
- The
null
type is only legal as the first type in a union subtype (i.e. with type index zero).
We recursively define the serialize
function which consumes an object value
(of the type specified) and returns a bytestring of type bytes
.
Note: In the function definitions below (serialize
, hash_tree_root
, signing_root
, is_variable_size
, etc.) objects implicitly carry their type.
assert N in [8, 16, 32, 64, 128, 256]
return value.to_bytes(N // BITS_PER_BYTE, "little")
assert value in (True, False)
return b"\x01" if value is True else b"\x00"
return b""
array = [0] * ((N + 7) // 8)
for i in range(N):
array[i // 8] |= value[i] << (i % 8)
return bytes(array)
Note that from the offset coding, the length (in bytes) of the bitlist is known. An additional 1
bit is added to the end, at index e
where e
is the length of the bitlist (not the limit), so that the length in bits will also be known.
array = [0] * ((len(value) // 8) + 1)
for i in range(len(value)):
array[i // 8] |= value[i] << (i % 8)
array[len(value) // 8] |= 1 << (len(value) % 8)
return bytes(array)
# Recursively serialize
fixed_parts = [serialize(element) if not is_variable_size(element) else None for element in value]
variable_parts = [serialize(element) if is_variable_size(element) else b"" for element in value]
# Compute and check lengths
fixed_lengths = [len(part) if part != None else BYTES_PER_LENGTH_OFFSET for part in fixed_parts]
variable_lengths = [len(part) for part in variable_parts]
assert sum(fixed_lengths + variable_lengths) < 2**(BYTES_PER_LENGTH_OFFSET * BITS_PER_BYTE)
# Interleave offsets of variable-size parts with fixed-size parts
variable_offsets = [serialize(sum(fixed_lengths + variable_lengths[:i])) for i in range(len(value))]
fixed_parts = [part if part != None else variable_offsets[i] for i, part in enumerate(fixed_parts)]
# Return the concatenation of the fixed-size parts (offsets interleaved) with the variable-size parts
return b"".join(fixed_parts + variable_parts)
If value
is a union type:
Define value as an object that has properties value.value
with the contained value, and value.type_index
which indexes the type.
serialized_bytes = serialize(value.value)
serialized_type_index = value.type_index.to_bytes(BYTES_PER_LENGTH_OFFSET, "little")
return serialized_type_index + serialized_bytes
Because serialization is an injective function (i.e. two distinct objects of the same type will serialize to different values) any bytestring has at most one object it could deserialize to.
Deserialization can be implemented using a recursive algorithm. The deserialization of basic objects is easy, and from there we can find a simple recursive algorithm for all fixed-size objects. For variable-size objects we have to do one of the following depending on what kind of object it is:
- Vector/list of a variable-size object: The serialized data will start with offsets of all the serialized objects (
BYTES_PER_LENGTH_OFFSET
bytes each).- Using the first offset, we can compute the length of the list (divide by
BYTES_PER_LENGTH_OFFSET
), as it gives us the total number of bytes in the offset data. - The size of each object in the vector/list can be inferred from the difference of two offsets. To get the size of the last object, the total number of bytes has to be known (it is not generally possible to deserialize an SSZ object of unknown length)
- Using the first offset, we can compute the length of the list (divide by
- Containers follow the same principles as vectors, with the difference that there may be fixed-size objects in a container as well. This means the
fixed_parts
data will contain offsets as well as fixed-size objects. - In the case of bitlists, the length in bits cannot be uniquely inferred from the number of bytes in the object. Because of this, they have a bit at the end that is always set. This bit has to be used to infer the size of the bitlist in bits.
Note that deserialization requires hardening against invalid inputs. A non-exhaustive list:
- Offsets: out of order, out of range, mismatching minimum element size.
- Scope: Extra unused bytes, not aligned with element size.
- More elements than a list limit allows. Part of enforcing consensus.
Efficient algorithms for computing this object can be found in the implementations.
We first define helper functions:
size_of(B)
, whereB
is a basic type: the length, in bytes, of the serialized form of the basic type.chunk_count(type)
: calculate the amount of leafs for merkleization of the type.- all basic types:
1
Bitlist[N]
andBitvector[N]
:(N + 255) // 256
(dividing by chunk size, rounding up)List[B, N]
andVector[B, N]
, whereB
is a basic type:(N * size_of(B) + 31) // 32
(dividing by chunk size, rounding up)List[C, N]
andVector[C, N]
, whereC
is a composite type:N
- containers:
len(fields)
- all basic types:
bitfield_bytes(bits)
: return the bits of the bitlist or bitvector, packed in bytes, aligned to the start. Length-delimiting bit for bitlists is excluded.pack
: Given ordered objects of the same basic type, serialize them, pack them intoBYTES_PER_CHUNK
-byte chunks, right-pad the last chunk with zero bytes, and return the chunks.next_pow_of_two(i)
: get the next power of 2 ofi
, if not already a power of 2, with 0 mapping to 1. Examples:0->1, 1->1, 2->2, 3->4, 4->4, 6->8, 9->16
merkleize(chunks, limit=None)
: Given orderedBYTES_PER_CHUNK
-byte chunks, merkleize the chunks, and return the root:- The merkleization depends on the effective input, which can be padded/limited:
- if no limit: pad the
chunks
with zeroed chunks tonext_pow_of_two(len(chunks))
(virtually for memory efficiency). - if
limit > len(chunks)
, pad thechunks
with zeroed chunks tonext_pow_of_two(limit)
(virtually for memory efficiency). - if
limit < len(chunks)
: do not merkleize, input exceeds limit. Raise an error instead.
- if no limit: pad the
- Then, merkleize the chunks (empty input is padded to 1 zero chunk):
- If
1
chunk: the root is the chunk itself. - If
> 1
chunks: merkleize as binary tree.
- If
- The merkleization depends on the effective input, which can be padded/limited:
mix_in_length
: Given a Merkle rootroot
and a lengthlength
("uint256"
little-endian serialization) returnhash(root + length)
.mix_in_type
: Given a Merkle rootroot
and a type_indextype_index
("uint256"
little-endian serialization) returnhash(root + type_index)
.
We now define Merkleization hash_tree_root(value)
of an object value
recursively:
merkleize(pack(value))
ifvalue
is a basic object or a vector of basic objects.merkleize(bitfield_bytes(value), limit=chunk_count(type))
ifvalue
is a bitvector.mix_in_length(merkleize(pack(value), limit=chunk_count(type)), len(value))
ifvalue
is a list of basic objects.mix_in_length(merkleize(bitfield_bytes(value), limit=chunk_count(type)), len(value))
ifvalue
is a bitlist.merkleize([hash_tree_root(element) for element in value])
ifvalue
is a vector of composite objects or a container.mix_in_length(merkleize([hash_tree_root(element) for element in value], limit=chunk_count(type)), len(value))
ifvalue
is a list of composite objects.mix_in_type(merkleize(value.value), value.type_index)
ifvalue
is of union type.
Let value
be a self-signed container object. The convention is that the signature (e.g. a "bytes96"
BLS12-381 signature) be the last field of value
. Further, the signed message for value
is signing_root(value) = hash_tree_root(truncate_last(value))
where truncate_last
truncates the last element of value
.
Let A
be an object derived from another object B
by replacing some of the (possibly nested) values of B
by their hash_tree_root
. We say A
is a "summary" of B
, and that B
is an "expansion" of A
. Notice hash_tree_root(A) == hash_tree_root(B)
.
We similarly define "summary types" and "expansion types". For example, BeaconBlock
is an expansion type of BeaconBlockHeader
. Notice that objects expand to at most one object of a given expansion type. For example, BeaconBlockHeader
objects uniquely expand to BeaconBlock
objects.
Language | Project | Maintainer | Implementation |
---|---|---|---|
Python | Ethereum 2.0 | Ethereum Foundation | https://github.com/ethereum/py-ssz |
Rust | Lighthouse | Sigma Prime | https://github.com/sigp/lighthouse/tree/master/eth2/utils/ssz |
Nim | Nimbus | Status | https://github.com/status-im/nim-beacon-chain/blob/master/beacon_chain/ssz.nim |
Rust | Shasper | ParityTech | https://github.com/paritytech/shasper/tree/master/utils/ssz |
TypeScript | Lodestar | ChainSafe Systems | https://github.com/ChainSafe/ssz-js |
Java | Cava | ConsenSys | https://www.github.com/ConsenSys/cava/tree/master/ssz |
Go | Prysm | Prysmatic Labs | https://github.com/prysmaticlabs/go-ssz |
Swift | Yeeth | Dean Eigenmann | https://github.com/yeeth/SimpleSerialize.swift |
C# | Jordan Andrews | https://github.com/codingupastorm/csharp-ssz | |
C# | Cortex | Sly Gryphon | https://www.nuget.org/packages/Cortex.SimpleSerialize |
C++ | Jiyun Kim | https://github.com/NAKsir-melody/cpp_ssz |