This package provides convenient encoding and decoding to/from binary data for all Swift Codable
types. It also provides limited cross-compatibility to Google Protocol Buffers.
There are only few encoders and decoders available for Swift's Codable format, and Apple provides a JSONEncoder and a PropertyListEncoder for basic encoding. While these can cover some use cases (especially when interacting with Web Content through JSON), they lack encoding efficiency when designing APIs within an ecosystem. JSON, for example, is notoriously inefficient when it comes to binary data.
One very popular alternative for binary data are Google's Protocol Buffers, which offer broad support across different platforms and programming languages. But they don't support Swift's Codable
protocol, and thus require manual message definitions, the Protobuf compiler, and a lot of copying between data structures during encoding and decoding.
So if you're looking for a decently efficient binary encoder in a pure Swift project, then BinaryCodable
may be right for you. Simply make your struct
s (or classes!) conform to Codable
, and BinaryCodable
does the rest!
The message format is similar to that of Protocol Buffers
(with some additions to support more types). It is possible to create limited compatibility between the two formats to exchange data with systems that don't support Swift.
Simply include in your Package.swift
:
dependencies: [
.package(
name: "BinaryCodable",
url: "https://github.com/christophhagen/BinaryCodable",
from: "1.0.0")
],
targets: [
.target(name: "MyTarget", dependencies: [
.product(name: "BinaryCodable", package: "BinaryCodable")
])
]
Select your Project
, navigate to the Package Dependencies
tab, and add https://github.com/christophhagen/BinaryCodable
using the +
button.
Let's assume a message definition:
struct Message: Codable {
var sender: String
var isRead: Bool
var unreadCount: Int
}
Simply import the module where you need to encode or decode a message:
import BinaryCodable
Construct an encoder when converting instances to binary data, and feed the message(s) into it:
let message: Message = ...
let encoder = BinaryEncoder()
let data = try encoder.encode(message)
It's also possible to encode single values, arrays, optionals, sets, enums, dictionaries, and more, so long as they conform to Codable
.
Decoding instances from binary data works much the same way:
let decoder = BinaryDecoder()
let message = try decoder.decode(Message.self, from: data)
Alternatively, the type can be inferred:
let message: Message = try decoder.decode(from: data)
It is possible for both encoding and decoding to fail.
All possible errors occuring during encoding produce BinaryEncodingError
errors, while unsuccessful decoding produces BinaryDecodingError
s.
Both are enums with several cases describing the nature of the error.
See the documentation of the types to learn more about the different error conditions.
The Codable
protocol uses CodingKey
definitions to identify properties of instances. By default, coding keys are generated using the string values of the property names.
Similar to JSON encoding, BinaryCodable
can embed the property names in the encoded data.
Unlike JSON (which is human-readable), the binary representation produced by BinaryCodable
is intended for cases when efficient encoding is important. Codable
allows the use of integer keys for each property, which significantly increases encoding efficiency. You can specify integer keys by adding an Int
enum conforming to the CodingKey
protocol to the Codable
type:
struct Message: Codable {
var sender: String
var isRead: Bool
var unreadCount: Int
// Assign an integer to each property
enum CodingKeys: Int, CodingKey {
case sender = 1
case isRead = 2
case unreadCount = 3
}
}
The enum must have a raw value of either Int
or String
, and the cases must match the property names within the type (it is possible to omit keys for properties which should not be encoded).
Using integer keys can significantly decrease the binary size, especially for long property names. Additionally, integer keys can be useful when intending to store the binary data persistently. Changes to property names can be performed in the code without breaking the decoding of older data (although this can also be achieved with custom String
keys).
Notes:
0
integer key shouldn't be used, since it is also used internally when encoding super
.Varint
, they are very inefficient for negative numbers.-576460752303423488
(-2^59
, inclusive) to 576460752303423487
(2^59-1
, inclusive). Values outside of these bounds will cause a fatalError
crash.While varints are efficient for small numbers, their encoding introduces a storage and computation penalty when the integers are often large, e.g. for random numbers. BinaryCodable
provides the FixedSize
wrapper, which forces integers to be encoded using their little-endian binary representations. This means that e.g. an Int32
is always encoded as 4 byte (instead of 1-5 bytes using Varint encoding). This makes 32-bit FixedSize
types more efficient than Varint
if values are often larger than 2^28
(2^56
for 64-bit types).
Use the property wrapper within a Codable
definition to enforce fixed-width encoding for a property:
struct MyStruct: Codable {
/// Always encoded as 4 bytes
@FixedSize
var largeInteger: Int32
}
The FixedSize
wrapper is available to all Varint
types: Int
, UInt
, Int32
, UInt32
, Int64
, and UInt64
.
There is an additional SignedValue
wrapper, which is only useful when encoding in protobuf-compatible format.
The BinaryEncoder
provides the sortKeysDuringEncoding
option, which forces fields in "keyed" containers, such as struct
properties (and some dictionaries), to be sorted in the binary data. This sorting is done by using either the integer keys (if defined), or the property names. Dictionaries with Int
or String
keys are also sorted.
Sorting the binary data does not influence decoding, but introduces a computation penalty during encoding. It should therefore only be used if the binary data must be consistent across multiple invocations.
Note: The sortKeysDuringEncoding
option does not guarantee deterministic binary data, and should be used with care.
Achieving Protocol Buffer compatibility is described in ProtobufSupport.md.
To learn more about the encoding format, see BinaryFormat.md.
The library comes with an extensive test suite, which checks that encoding works correctly for many cases. These tests can be executed using swift test
from the package root, or when opening the package using Xcode.
MIT. See License.md
It should be possible to generate a string containing a working Protobuf definition for any type that is determined to be Protobuf compatible.
Increasing the speed of the encoding and decoding process is not a huge priority at the moment. If you have any pointers on how to improve the performance further, feel free to contribute.
Users of the library are encouraged to contribute to this repository.
Please file an issue with a description of the feature you're missing. Check other open and closed issues for similar suggestions and comment on them before creating a new issue.
File an issue with a clear description of the problem. Please include message definitions and other data where possible so that the error can be reproduced.
If you would like to extend the documentation of this library, or translate the documentation into other languages, please also open an issue, and I'll contact you for further discussions.
link |
Stars: 9 |
Last commit: 1 week ago |
This release fixes compilation on 32-bit systems.
The upper and lower bounds for valid integer coding keys where given as string literals, and required 64-bit wide integers. The bounds now adapt to the system the library compiles on.
Swiftpack is being maintained by Petr Pavlik | @ptrpavlik | @swiftpackco | API | Analytics