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Installation

Requirements

  • Python 3.9+ (3.10 or 3.11 or newer recommended)
  • pip 21 or newer

Install from PyPI

pip install skyulf-core

Optional extras

Install only what you need:

Extra What it adds Command
viz Matplotlib, Rich (visualisation helpers) pip install skyulf-core[viz]
eda VADER sentiment, causal-learn pip install skyulf-core[eda]
tuning Optuna + Optuna-integration pip install skyulf-core[tuning]
modeling-xgboost XGBoost estimators pip install skyulf-core[modeling-xgboost]
preprocessing-imbalanced imbalanced-learn (SMOTE, etc.) pip install skyulf-core[preprocessing-imbalanced]
dev pytest, twine, build pip install skyulf-core[dev]

Install everything at once:

pip install skyulf-core[viz,eda,tuning,modeling-xgboost,preprocessing-imbalanced]

Editable install (contributor workflow)

If you cloned the repository and want live changes reflected:

git clone https://github.com/flyingriverhorse/Skyulf.git
cd Skyulf
pip install -e ./skyulf-core

Runtime dependencies (auto-installed)

These are pulled in automatically by pip install skyulf-core:

  • pandas >= 2.0
  • numpy >= 1.24
  • scikit-learn >= 1.4
  • polars >= 1.36
  • pyarrow >= 21.0
  • pydantic >= 2.0
  • scipy >= 1.10
  • statsmodels >= 0.14

Full platform (Docker)

To run the complete Skyulf platform (backend + frontend + Celery workers):

1. Configure environment

cp .env.example .env

Key variables to review:

Variable Default Description
DB_TYPE sqlite Database backend (sqlite or postgres)
USE_CELERY true Set false to skip Redis and run tasks in-process
CELERY_BROKER_URL redis://localhost:6379/1 Redis URL for Celery
SECRET_KEY (placeholder) Change this in production

Quick start: For local development with no Redis, just set USE_CELERY=false in .env.

2. Launch with Docker Compose

docker compose up --build

This starts three containers:

Service Port Purpose
api 8000 FastAPI backend + static frontend
redis 6379 Message broker for Celery
worker — Celery worker for background training

3. Verify

For the full manual setup (without Docker), see the Platform Setup guide.

Import check

Verify the installation:

from skyulf.pipeline import SkyulfPipeline
from skyulf.data.dataset import SplitDataset

print("skyulf-core installed successfully")