oddball 1.4.0

Anomaly Detection Dataset Collection

oddball

Lightweight access to the 47 ADBench classical anomaly detection datasets. Downloads the published .npz assets from the GitHub release on demand and returns raw (X, y) NumPy arrays.

• Default assets: https://github.com/OliverHennhoefer/oddball/releases/tag/v1.0-datasets
• Cache: ~/.cache/oddball/<version> (override with env vars below)

Installation

pip install oddball

Usage

from oddball import Dataset, load, split_by_label, list_available

print("Available:", list_available())

X, y = load(Dataset.COVER)           # raw arrays
normal, anomaly = split_by_label("cover")  # feature slices

# Generators for batch/online experimentation
from oddball import BatchGenerator, OnlineGenerator

batch_gen = BatchGenerator(
    load_data_func=lambda: load(Dataset.COVER, as_dataframe=True),
    batch_size=32,
    anomaly_proportion=0.1,
    seed=42,
)
for x_batch, y_batch in batch_gen.generate():
    print(f"Batch: {x_batch.shape}, anomalies: {y_batch.sum()}")
    break

Configuration

• ODDBALL_DATASET_VERSION (default: v1.0-datasets)
• ODDBALL_DATASET_URL (default: https://github.com/OliverHennhoefer/oddball/releases/download/<version>/)
• ODDBALL_CACHE_DIR (default: ~/.cache/oddball/<version>)
• .env support: place the above keys in .env (or set ODDBALL_DOTENV=/path/to/.env).

Supported datasets

All 47 ADBench classical datasets are available. Call oddball.list_available() to see slugs (e.g., cover, fraud, satimage2).