catboost-cgo

README

CatBoost-Cgo

Evaluation library is the fastest way for inference a model CatBoost. The library provides a C API.
The C API interface can be accessed from any programming language (example Golang + Cgo).

Prebuilt shared library (*.so | *.dylib) artifacts are available of the releases page on GitHub CatBoost project.
The shared library:

1. Should be in /usr/local/lib
2. Or set path in environment CATBOOST_LIBRARY_PATH
3. Or set path manual in source code SetSharedLibraryPath (see example below)

For more information, see https://catboost.ai/en/docs/concepts/c-plus-plus-api_dynamic-c-pluplus-wrapper.

Compatibility

Previous versions	v1.2.2	v1.2.3	v1.2.4	v1.2.5	v1.2.6	v1.2.7	v1.2.8
🚫 (not testing)	✅	✅	✅	✅	✅	✅	✅

Features

Supported functionality (https://catboost.ai/en/docs/concepts/python-quickstart):

• CatBoostRegressor ✅
• CatBoostClassifier ✅
• CatBoostRanker ✅

Supported prediction types (https://github.com/catboost/catboost/blob/master/catboost/libs/model/enums.h):

• RawFormulaVal ✅
• Probability ✅
• Class ✅
• RMSEWithUncertainty ✅
• Exponent ✅

Limitation

Supported operating system and architectures:

Operating system	CPU architectures	GPU support using CUDA
MacOS	✅ (x86_64)	🚫
Linux	✅ (x86_64)	✅ (x86_64)
Windows 10 and 11	🚫	🚫

If you use GPU - only device 0 is supported for now. More details: https://github.com/catboost/catboost/issues/2774.

Supported Type:

• Numeric ✅
• Categorical ✅ (https://catboost.ai/en/docs/features/categorical-features)
• Text 🚫 (https://catboost.ai/en/docs/features/text-features)
• Embeddings 🚫 (https://catboost.ai/en/docs/features/embeddings-features)

Installation

1. Install catboost-cgo:

go get github.com/mirecl/catboost-cgo

1. Download CatBoost shared library from release page: https://github.com/catboost/catboost/releases

2. Save CatBoost shared library in /usr/local/lib or manual set path:

import (
 cb "github.com/mirecl/catboost-cgo/catboost"
)

func main(){
  cb.SetSharedLibraryPath(...)
}

1. See examples of use

Usage

• Regression
• Binary classification
• Multiclassification
• Ranker
• Titanic
• Metadata
• Uncertainty
• Survival

Thanks

• @lukangping for https://github.com/lukangping/catboost-go
• @bourbaki for https://github.com/bourbaki/catboost-go
• @yalue for https://github.com/yalue/onnxruntime_go