This is an ever-growing package of core tools for use on client projects by Oreum Industries.

• Provides an essential workflow for data curation, EDA, basic ML using the core scientific Python stack incl. numpy, scipy, matplotlib, seaborn, pandas, scikit-learn, umap-learn
• Optionally provides an advanced Bayesian modelling workflow in R&D and Production using a leading probabilistic programming stack incl. pymc, pytensor, arviz (do pip install oreum_core[pymc])
• Optionally enables a generalist black-box ML workflow in R&D using a leading Gradient Boosted Trees stack incl. catboost, xgboost, optuna, shap (do pip install oreum_core[tree])
• Also includes several utilities for text cleaning, sql scripting, file handling

This package is:

• A work in progress (v0.y.z) and liable to breaking changes and inconvenience to the user
• Solely designed for ease of use and rapid development by employees of Oreum Industries, and selected clients with guidance

This package is not:

• Intended for public usage and will not be supported for public usage
• Intended for contributions by anyone not an employee of Oreum Industries, and unsolicitied contributions will not be accepted.

• Project began on 2021-01-01
• The README.md is MacOS and POSIX oriented
• See LICENCE.md for licensing and copyright details
• See pyproject.toml for various pacakge details
• This uses a logger named 'oreum_core', feel free to incorporate or ignore
• Hosting:
  • Source code repo on GitHub
  • Source code release on GitHub
  • Package release on PyPi

For local development on MacOS

1. Install Homebrew, see instuctions at https://brew.sh
2. Install direnv, git, git-lfs, graphviz, zsh

$> brew update && upgrade
$> brew install direnv git git-lfs graphviz zsh

Assumes direnv, git, git-lfs and zsh installed as above

$> git clone https://github.com/oreum-industries/oreum_core
$> cd oreum_core

Then allow direnv on MacOS to autorun file .envrc upon directory open

Notes:

• We use conda virtual envs controlled by mamba (quicker than conda)
• We install packages using miniforge (sourced from the conda-forge repo) wherever possible and only use pip for packages that are handled better by pip and/or more up-to-date on pypi
• Packages might not be the very latest because we want stability for pymc which is usually in a state of development flux
• See cheat sheet of conda commands
• The Makefile creates a dev env and will also download and preinstall miniforge if not yet installed on your system

From the dir above oreum_core/ project dir:

$> make -C oreum_core/ dev

This will also create some files to help confirm / diagnose successful installation:

• dev/install_log/blas_info.txt for the BLAS MKL installation for numpy
• dev/install_log/pipdeptree[_rev].txt lists installed package deps (and reversed)
• LICENSES_THIRD_PARTY.md details the license for each package used

From the dir above oreum_core/ project dir:

$> make -C oreum_core/ test-dev-env

This will also add files dev/install_log/[numpy|scipy].txt which detail successful installation (or not) for numpy, scipy

From the dir above oreum_core/ project dir:

$> make -C oreum_core/ uninstall-env

We use pre-commit to run a suite of automated tests for code linting & quality control and repo control prior to commit on local development machines.

• Precommit is already installed by the make dev command (which itself calls pip install -e .[dev])
• The pre-commit script will then run on your system upon git commit
• See this project's .pre-commit-config.yaml for details

We use Github Actions aka Github Workflows to run:

1. A suite of automated tests for commits received at the origin (i.e. GitHub)
2. Publishing to PyPi upon creating a GH Release

• See Makefile for the CLI commands that are issued
• See .github/workflows/* for workflow details

Copyright 2024 Oreum OÜ t/a Oreum Industries. All rights reserved. See LICENSE.md.

Oreum OÜ t/a Oreum Industries, Sepapaja 6, Tallinn, 15551, Estonia, reg.16122291, oreum.io

Oreum OÜ © 2024