KO
|
EN
gitlite — search
Search
#javascript
#python
#hacktoberfest
#react
#ai
#typescript
#llm
#go
#golang
#android
#machine-learning
#rust
#deep-learning
#linux
dash-rs
★ 11
Open GitHub ↗
Efficient processing of Geometry Dash data
Download README (.md)
Explore Similar Repositories
MultiServerCounter
:
A PocketMine-MP plugin that combines online players counts of multiple servers
ncov-statistics
:
武汉新型冠状病毒肺炎疫情热力统计图
ThermalCameraMod
:
AMG8833 thermal camera with ESP8266
docs
:
Repository for Unlock Protocol docs.
ByteToHeader
:
Simple C tool to generate a C header file with an array of bytes of given file.
// repository documentation
Was this content helpful?
★ 0
(0 ratings)
Select Rating:
★
★
★
★
★
Submit Feedback
Recent Feedback
×
Download README
Do you want to download the
README.md
file for
dash-rs
?
Download (.md)
# `dash-rs` - Efficient processing of Geometry Dash data  [](https://codecov.io/gh/stadust/dash-rs) `dash-rs` (spoken 'dashers') is an experimental library related to modelling, and more imporant _processing_ all data formats related to RobTop's 2013 game "Geometry Dash". The long-term goal is to have this crate replace `gdcf_model`, `gdcf_parse` and some parts of `gdrs` in GDCF. The project is a collaboration with [mgostIH](https://github.com/mgostIH), on whose idea the initial library design is based on and who continues to provide incredibly helpful insights into optimization, Geometry Dash and Rust. ## Using With a Custom GDPS If you are planning to use this library to interact with a GDPS, you can use: ```rust use dash_rs::request::GD_SERVER_ENDPOINT_BASE_URL; GD_SERVER_ENDPOINT_BASE_URL.get_or_init(|| "https://your-custom-gdps-url.com".to_string()); ``` Insert this anywhere before the first call to any `dash-rs` function. ## Goals The goals for dash-rs are, in order: + Zero allocation deserialization for RobTop's HTTP response and local savefile formats, using [serde](https://serde.rs) + Accurate modelling of all game related data + Efficient serialization routines for RobTop's HTTP response and local save file formats, using serde. The benchmark we're trying to beat is parsing and calculating the length in seconds of the level 'Spacial Rend' in `56ms`, achieved on my Laptop's Intel:tm: Core i7-8850H using `gdcf_parse`. ## Disclaimer I, in no way, claim to know what I'm doing. ## License This project is licensed under the terms of the MIT license.