WagsTAILS

Technology-Assisted Information Loading and Structure (TAILS) for Wagnerds.

This tool provides data acquisition and access utilities for several projects developed by the Wagner Lab.

Installation

Install from PyPI:

python3 -m pip install wags_tails

Usage

Data source classes provide a get_latest() method that acquires the most recent available data file and returns a pathlib.Path object with its location:

>>> from wags_tails.mondo import MondoData
>>> m = MondoData()
>>> m.get_latest(force_refresh=True)
Downloading mondo.owl: 100%|█████████████████| 171M/171M [00:28<00:00, 6.23MB/s]
PosixPath('/Users/genomicmedlab/.local/share/wags_tails/mondo/mondo_v2023-09-12.owl'), 'v2023-09-12'

Initialize the source class with the silent parameter set to True to suppress console output:

>>> from wags_tails.mondo import MondoData
>>> m = MondoData(silent=True)
>>> latest_file, version = m.get_latest(force_refresh=True)

Configuration

All data is stored within source-specific subdirectories of a designated WagsTails data directory. By default, this location is ~/.local/share/wags_tails/, but it can be configured by passing a Path directly to a data class on initialization, via the $WAGS_TAILS_DIR environment variable, or via XDG data environment variables.

Development

Check out the repository:

git clone https://github.com/GenomicMedLab/wags-tails
cd wags-tails

Create a developer environment, e.g. with virtualenv:

python3 -m virtualenv venv
source venv/bin/activate

Install dev and test dependencies, including pre-commit:

python3 -m pip install -e '.[dev,test]'
pre-commit install

Check style:

black . && ruff check --fix .

Run tests:

pytest