🪜 Bayesian Hierarchical Models at Scale
GPL-2.0 License
Accompanying source code to the blog post Finally! Bayesian Hierarchical Modelling at Scale.
NOTE: The code is GPL-2 licensed. If you require a more permissive licence, e.g. for commercial reasons, contact me to obtain a licence for your business.
In order to set up the necessary environment:
bhm-at-scale
with the help of conda,
conda env create -f environment.yaml # or `environment.lock.yaml` for exact reproduction
conda activate bhm-at-scale
bhm-at-scale
with:
python setup.py install # or `develop`
Then take a look into the notebooks
folders.
environment.yaml
and eventuallysetup.cfg
if you want to ship and install your package via pip
later on.environment.lock.yaml
for the exact reproduction of yourconda env export -n bhm-at-scale -f environment.lock.yaml
For multi-OS development, consider using --no-builds
during the export.environment.lock.yaml
using:
conda env update -f environment.lock.yaml --prune
AUTHORS.rst <- List of developers and maintainers.
CHANGELOG.rst <- Changelog to keep track of new features and fixes.
LICENSE.txt <- License as chosen on the command-line.
README.md <- The top-level README for developers.
data
external <- Data from third party sources.
interim <- Intermediate data that has been transformed.
processed <- The final, canonical data sets for modeling.
raw <- The original, immutable data dump.
docs <- Directory for Sphinx documentation in rst or md.
environment.yaml <- The conda environment file for reproducibility.
notebooks <- Jupyter notebooks. Naming convention is a number (for
ordering), the creator's initials and a description,
e.g. `1.0-fw-initial-data-exploration`.
setup.cfg <- Declarative configuration of your project.
setup.py <- Use `python setup.py develop` to install for development or
| or create a distribution with `python setup.py bdist_wheel`.
src
bhm_at_scale <- Actual Python package where the main functionality goes.
tests <- Unit tests which can be run with `py.test`.
.coveragerc <- Configuration for coverage reports of unit tests.
.isort.cfg <- Configuration for git hook that sorts imports.
.pre-commit-config.yaml <- Configuration of pre-commit git hooks.
This project has been set up using PyScaffold 3.2.3 and the dsproject extension 0.4. For details and usage information on PyScaffold see https://pyscaffold.org/.