CAUTION this project is current in development and should be used at your own risk. Until there is a stable tagged release, be careful.
This is a library adding several generally useful tools that are either not included in the standard library or have slightly different behavior. As the zig programming language matures, we should get more and more awesome std library features but until then...
All data structures, algorithms and utilities included in this library are written from scratch. This minimizes the threat of malicious or unintentional supply chain attacks. It also ensures that all code is controlled in a single place and HOPEFULLY minimizes the chance that zig turns into the hellish monstrocity that is npm and the nodejs ecosystem.
Using stdx is just as simple as using any other zig dependency.
// import the library into your file
const stdx = @import("stdx");
fn main() !void {
// your code
// ....
const memory_pool = try stdx.MemoryPool(i32).init(allocator, 200);
defer memory_pool.deinit();
// your code
// ...
}
You can install stdx just like any other zig dependency by editing your build.zig.zon file.
.dependencies = .{
.stdx = .{
.url = "https://github.com/kobolds-io/stdx/archive/refs/tags/v0.0.10.tar.gz",
.hash = "",
},
},run zig build --fetch to fetch the dependencies. This will return an error as the has will not match. Copy the new hash and try again.Sometimes zig is helpful and it caches stuff for you in the zig-cache dir. Try deleting that directory if you see some issues.
This library follows the organization of the zig std library. You will see familiar hierarchies like stdx.mem for memory stuff and std.<DATA_STRUCTURE> for other data structures. As I build this library out, I'll add more notes and documentation.
There are examples included in this library that go over a brief overview of how each feature can be used. You can build and run examples by performing the following steps. Examples are in the examples directory. Examples are always welcome.
zig build examples
./zig-out/bin/<example_name>Examples are best used if you modify the code and add print statements to figure out what is going on. Look at the source code files for additional tips on how features work by taking a look at the tests included in the source code.
There are benchmarks included in this library that you can run your local hardware or target hardware. You can run benchmarksby performing the following steps. Benchmarks are in the benchmarks directory. More benchmarks are always welcome. Benchmarks in this library are written using zbench by hendriknielander. Please check out that repo and star it and support other zig developers.
Note Benchmarks are always a point of contention between everyone. One of my goals is to provision some hardware in the cloud that is consistently used as the hardware for all comparisons. Until then, you can run the code locally to test out your performance. These benchmarks are run inside of a virtual machine and the CPU is fully emulated. This means you will see better performance on your native machines.
# with standard optimizations (debug build)
zig build bench
# or with more optimizations
zig build bench -Doptimize=ReleaseFastExample output
--------------------------------------------------------
Operating System: linux x86
CPU: 12th Gen Intel(R) Core(TM) i7-12700H
CPU Cores: 14
Total Memory: 31.021GiB
--------------------------------------------------------
|----------------------------|
| BufferedChannel Benchmarks |
|----------------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
send 10000 items 65535 6.902s 105.324us ± 3.344us (102.754us ... 260.784us) 104.624us 115.121us 119.248us
receive 10000 items 65535 7.739s 118.09us ± 3.686us (100.845us ... 285.061us) 117.304us 128.697us 133.555us
|-------------------------|
| EventEmitter Benchmarks |
|-------------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
emit 1 listeners 10000 65535 4.115s 62.798us ± 2.378us (57.294us ... 277.264us) 63.252us 68.788us 69.487us
emit 10 listeners 1000 65535 15.335s 234.008us ± 13.06us (210.043us ... 638.419us) 236.551us 280.198us 315.506us
emit 100 listeners 100 65535 2m8.851s 1.966ms ± 86.803us (1.639ms ... 3.713ms) 1.982ms 2.203ms 2.302ms
|-----------------------|
| MemoryPool Benchmarks |
|-----------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
create 10000 items 65535 15.994s 244.054us ± 9.911us (216.952us ... 758.137us) 248.183us 271.691us 282.87us
unsafeCreate 10000 ite 65535 13.124s 200.27us ± 11.563us (176.582us ... 790.382us) 203.808us 230.245us 261.234us
|-----------------------|
| RingBuffer Benchmarks |
|-----------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
prepend 10000 items 65535 2.576s 39.32us ± 2.408us (38.388us ... 200.972us) 38.481us 46.605us 49.154us
enqueue 10000 items 65535 2.419s 36.919us ± 1.979us (36.246us ... 191.532us) 36.312us 44.499us 46.592us
enqueueMany 10000 item 65535 2.444s 37.296us ± 3.108us (36.291us ... 231.762us) 36.41us 48.263us 52.571us
dequeue 10000 items 65535 1.204s 18.386us ± 1.295us (18.122us ... 171.803us) 18.161us 20.959us 23.628us
dequeueMany 10000 item 65535 2.416s 36.866us ± 2.944us (36.249us ... 200.915us) 36.281us 51.079us 51.097us
concatenate 10000 item 65535 2.448s 37.364us ± 1.794us (36.294us ... 213.781us) 37.324us 40.46us 41.21us
copy 10000 items 65535 2.444s 37.304us ± 1.93us (36.562us ... 209.44us) 37.311us 40.141us 40.933us
|-------------------|
| Signal Benchmarks |
|-------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
send/receive 10000 ite 65535 11.795s 179.992us ± 4.466us (179.094us ... 357.854us) 179.147us 191.347us 193.858us
-------------------------------|
| UnbufferedChannel Benchmarks |
|------------------------------|
benchmark runs total time time/run (avg ± σ) (min ... max) p75 p99 p995
-----------------------------------------------------------------------------------------------------------------------------
send/receive 10000 ite 65535 21.773s 332.241us ± 7.918us (325.232us ... 589.507us) 331.867us 359.591us 369.972us
Please see Contributing for more information on how to get involved.
Please see the Code of Conduct file. Simple library, simple rules.
The stdx top level module. Directly contains data structures and is the parent module to modules like io and net.
added v0.0.3 as
stdx.BufferedChannel
The BufferedChannel is a structure that can be used to safely transmit data across threads. It uses a backing buffer which stores the actual values transmitted. Additionally it has a very simple api send/receive and supports concepts like cancellation and timeouts.
See example and source for more information on usage.
added v0.0.3 as
stdx.UnbufferedChannel
The UnbufferedChannel is a structure that can be used to safely transmit data across threads. It uses a Condition to notify receivers that there is new data. Additionally it has a very simple api send/receive and supports concepts like timeouts but does not currently support cancellation.
See example and source for more information on usage.
added v0.0.8 as
stdx.Signal
The Signal is a structure that can be used to safely transmit data across threads. Unlike a channel, it does not require that both threads become synchronized at the same point. Think of a Signal as a way for a sender to throw a value over the fence and a receiver to pick the value at a later time (when it is convenient for the receiver). Signals are "one shots", meaning that they should only ever be used once. These structures are ideal for things like request->reply kinds of problems.
See example and source for more information on usage.
added v0.0.6 as
stdx.EventEmitter
The EventEmitter is a tool for managing communications across callbacks. This is a very similar implementation to the nodejs event emitter class which is one of the fundemental building blocks for asynchronous events. The EventEmitter provides a simple(ish) api to register Callbacks with appropriate Contexts to be called when a specific Event is called.
See example and source for more information on usage.
added v0.0.2 as
stdx.ManagedQueue
The ManagedQueue is a generic queue implementation that uses a singly linked list. It allows for the management of a queue with operations like enqueueing, dequeueing, checking if the queue is empty, concatenating two queues, and handles the allocation/deallocation of memory used by the queue. The queue is managed by an allocator, which is used for creating and destroying nodes.
See example and source for more information on usage.
added v0.0.2 as
stdx.UnmanagedQueue
The UnmanagedQueue is a generic queue implementation that uses a singly linked list. It most closely represents the std.SinglyLinkedList in its functionality. Differing from the ManagedQueue, the UnmanagedQueue requires memory allocations to be external to the queue and provides a generic Node structure to help link everything together.
Please also see UnmanagedQueueNode which is the Node used by the UnmanagedQueue.
See example and source for more information on usage.
added v0.0.1 as
stdx.RingBuffer
A RingBuffer is a data structure that is really useful for managing memory in a fixed memory allocation. This particular implementation is particularly useful for a fixed size queue. Kobolds uses the RingBuffer data structure for inboxes and outboxes for when messages are received/sent through TCP connections.
See example and source for more information on usage.
added v0.0.1 as
stdx.MemoryPool
A MemoryPool is a structure that uses pre-allocated blocks of memory to quickly allocoate and deallocate resources quickly. It is very useful in situations where you have statically allocated memory but you will have fluctuating usage of that memory. A good example would be handling messages flowing throughout a system.