diff --git a/.cruft.json b/.cruft.json
new file mode 100644
index 0000000..f53d42a
--- /dev/null
+++ b/.cruft.json
@@ -0,0 +1,18 @@
+{
+  "template": "https://github.com/woltapp/wolt-python-package-cookiecutter",
+  "commit": "b25684a2c63387153b83a1cc03ea332be8c8279a",
+  "checkout": null,
+  "context": {
+    "cookiecutter": {
+      "author_name": "Markus Shepherd",
+      "author_email": "markus@recommend.games",
+      "github_username": "recommend-games",
+      "project_name": "Board Game Recommender",
+      "project_slug": "board-game-recommender",
+      "package_name": "board_game_recommender",
+      "project_short_description": "Board game recommendation engine.",
+      "_template": "https://github.com/woltapp/wolt-python-package-cookiecutter"
+    }
+  },
+  "directory": null
+}
diff --git a/.github/actions/python-poetry-env/action.yml b/.github/actions/python-poetry-env/action.yml
new file mode 100644
index 0000000..455d73e
--- /dev/null
+++ b/.github/actions/python-poetry-env/action.yml
@@ -0,0 +1,21 @@
+name: 'Setup Python + Poetry environment'
+description: 'Setup Python + Poetry environment'
+
+inputs:
+  python-version:
+    required: false
+    description: 'Python version'
+    default: '3.12'
+outputs: {}
+runs:
+  using: 'composite'
+  steps:
+    - uses: actions/setup-python@v5
+      with:
+        python-version: ${{inputs.python-version}}
+    - name: Install poetry
+      run: python -m pip install poetry
+      shell: bash
+    - name: Create virtual environment
+      run: poetry install
+      shell: bash
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
new file mode 100644
index 0000000..5e7937b
--- /dev/null
+++ b/.github/pull_request_template.md
@@ -0,0 +1,10 @@
+## Description
+
+A short description about the changes in this pull request. If the pull request is related to some issue, mention it
+ here.
+
+## Checklist
+
+- [ ] Tests covering the new functionality have been added
+- [ ] Documentation has been updated OR the change is too minor to be documented
+- [ ] Changes are listed in the `CHANGELOG.md` OR changes are insignificant
diff --git a/.github/workflows/cookiecutter.yml b/.github/workflows/cookiecutter.yml
new file mode 100644
index 0000000..c9886db
--- /dev/null
+++ b/.github/workflows/cookiecutter.yml
@@ -0,0 +1,79 @@
+name: Autoupdate project structure
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "0 0 * * *"  # at the end of every day
+
+jobs:
+  auto-update-project:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install dependencies
+        run: python -m pip install cruft poetry jello tabulate
+
+      - name: Update project structure
+        run: |
+          cruft update -y
+
+      - name: Check if there are changes
+        id: changes
+        run: echo "::set-output name=changed::$(git status --porcelain | wc -l)"
+
+      - name: apply additional changes and fixes
+        if: steps.changes.outputs.changed > 0
+        run: |
+          poetry lock --no-update  # add new dependencies
+          poetry install
+          poetry run pre-commit run -a || true  # we have to fix other issues manually
+
+      - name: Get template versions
+        id: get_versions
+        if: steps.changes.outputs.changed > 0
+        shell: bash
+        run: |
+          CURRENT_VERSION=$(git show HEAD:.cruft.json | jello -r "_['commit'][:8]")
+          NEXT_VERSION=$(jello -r "_['commit'][:8]" < .cruft.json)
+          echo ::set-output name="current_version::$CURRENT_VERSION"
+          echo ::set-output name="next_version::$NEXT_VERSION"
+
+      - name: Get changelog
+        id: get_changelog
+        if: steps.changes.outputs.changed > 0
+        shell: bash
+        run: |
+          TEMPLATE=$(jello -r "_['template']" < .cruft.json)
+          git clone "$TEMPLATE" /tmp/template
+          cd /tmp/template
+          body=$( (echo "Date;Change;Hash"; git log --pretty=format:"%as;%s;%h" ${{ steps.get_versions.outputs.current_version }}..${{ steps.get_versions.outputs.next_version }}) | tabulate --header --format github -s ';' -)
+          body=$(cat <<EOF
+          Changes from $TEMPLATE
+
+          $body
+          EOF
+          )
+          body="${body//'%'/'%25'}"
+          body="${body//$'\n'/'%0A'}"
+          body="${body//$'\r'/'%0D'}"
+          echo ::set-output name="changelog::$body"
+
+      # behaviour if PR already exists: https://github.com/marketplace/actions/create-pull-request#action-behaviour
+      - name: Create Pull Request
+        env:
+          # a PAT is required to be able to update workflows
+          GITHUB_TOKEN: ${{ secrets.AUTO_UPDATE_GITHUB_TOKEN }}
+        if: ${{ steps.changes.outputs.changed > 0 && env.GITHUB_TOKEN != 0 }}
+        uses: peter-evans/create-pull-request@v3
+        with:
+          token: ${{ env.GITHUB_TOKEN }}
+          commit-message: >-
+            chore: update project structure to ${{ steps.get_versions.outputs.next_version }}
+          title: "[Actions] Auto-Update cookiecutter template"
+          body: ${{ steps.get_changelog.outputs.changelog }}
+          branch: chore/auto-update-project-from-template
+          delete-branch: true
diff --git a/.github/workflows/dependencies.yml b/.github/workflows/dependencies.yml
new file mode 100644
index 0000000..a657d27
--- /dev/null
+++ b/.github/workflows/dependencies.yml
@@ -0,0 +1,57 @@
+name: Autoupdate dependencies
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "0 0 1 * *"
+
+jobs:
+  auto-update-dependencies:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+
+      - name: Install tabulate
+        run: python -m pip install tabulate
+
+      - name: Gather outdated dependencies
+        id: check_for_outdated_dependencies
+        run: |
+          body=$(poetry show -o -n)
+          echo ::set-output name="body::$body"
+
+      - name: Format PR message
+        if: ${{ steps.check_for_outdated_dependencies.outputs.body != 0 }}
+        id: get_outdated_dependencies
+        shell: bash
+        run: |
+          body=$(poetry show -o -n | sed 's/(!)//' | awk 'BEGIN {print "Package","Used","Update"}; {print $1,$2,$3}' | tabulate --header --format github -)
+          body=$(cat <<EOF
+          The following packages are outdated
+
+          $body
+          EOF
+          )
+          body="${body//'%'/'%25'}"
+          body="${body//$'\n'/'%0A'}"
+          body="${body//$'\r'/'%0D'}"
+          echo ::set-output name="body::$body"
+
+      - name: Update outdated packages
+        if: ${{ steps.check_for_outdated_dependencies.outputs.body != 0 }}
+        run: poetry lock
+
+      # behaviour if PR already exists: https://github.com/marketplace/actions/create-pull-request#action-behaviour
+      - name: Create Pull Request
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        if: ${{ steps.check_for_outdated_dependencies.outputs.body != 0 }}
+        uses: peter-evans/create-pull-request@v3
+        with:
+          token: ${{ env.GITHUB_TOKEN }}
+          commit-message: >-
+            chore: update dependencies
+          title: "[Actions] Auto-Update dependencies"
+          body: ${{ steps.get_outdated_dependencies.outputs.body }}
+          branch: chore/update-dependencies
+          delete-branch: true
diff --git a/.github/workflows/draft_release.yml b/.github/workflows/draft_release.yml
new file mode 100644
index 0000000..16f391f
--- /dev/null
+++ b/.github/workflows/draft_release.yml
@@ -0,0 +1,52 @@
+name: Draft a release
+
+on:
+  workflow_dispatch:
+    inputs:
+      version:
+        description: 'The version number (e.g. 1.2.3) OR one of: patch|minor|major|prepatch|preminor|premajor|prerelease'
+        required: true
+        default: 'patch'
+
+jobs:
+  draft-release:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+      - name: Update version
+        id: updated_version
+        shell: bash
+        run: |
+          poetry version ${{ github.event.inputs.version }}
+          version=$(poetry version --short)
+          echo ::set-output name="version::$version"
+      - name: Update changelog
+        id: changelog
+        shell: bash
+        run: |
+          poetry run kacl-cli release ${{ steps.updated_version.outputs.version }} --modify --auto-link
+          echo "" >> CHANGELOG.md
+          body=$(poetry run kacl-cli get ${{ steps.updated_version.outputs.version }})
+          body="${body//'%'/'%25'}"
+          body="${body//$'\n'/'%0A'}"
+          body="${body//$'\r'/'%0D'}"
+          echo ::set-output name="body::$body"
+      - name: Commit changes
+        uses: EndBug/add-and-commit@v7
+        with:
+          add: 'CHANGELOG.md pyproject.toml'
+          message: 'Release ${{ steps.updated_version.outputs.version }}'
+      - name: Create tag
+        run: |
+          git tag ${{ steps.updated_version.outputs.version }}
+          git push origin ${{ steps.updated_version.outputs.version }}
+      - name: Create a draft release
+        uses: actions/create-release@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tag_name: ${{ steps.updated_version.outputs.version }}
+          release_name: Release ${{ steps.updated_version.outputs.version }}
+          body: ${{ steps.changelog.outputs.body }}
+          draft: true
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 0000000..070b134
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,18 @@
+name: Release
+
+on:
+  release:
+    types: [ published ]
+
+jobs:
+  build-and-publish:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+      - name: Publish to pypi
+        run: |
+          poetry config pypi-token.pypi ${{ secrets.PYPI_TOKEN }}
+          poetry publish --build --no-interaction
+      - name: Deploy docs
+        run: poetry run mkdocs gh-deploy --force
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
new file mode 100644
index 0000000..7760011
--- /dev/null
+++ b/.github/workflows/test.yml
@@ -0,0 +1,54 @@
+name: Test
+
+on:
+  pull_request:
+  push:
+    branches:
+      - "**"
+
+jobs:
+  actionlint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Download actionlint
+        run: bash <(curl https://raw.githubusercontent.com/rhysd/actionlint/main/scripts/download-actionlint.bash) 1.6.21
+        shell: bash
+      - name: Check workflow files
+        run: ./actionlint -color
+        shell: bash
+
+  lint-cruft:
+    name: Check if automatic project update was successful
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Fail if .rej files exist as structure update was not successful
+        run: test -z "$(find . -iname '*.rej')"
+
+  pre-commit:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+      - run: poetry run pre-commit run --all-files
+
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+        with:
+          python-version: ${{ matrix.python-version }}
+      - run: poetry run pytest
+
+  docs:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/python-poetry-env
+      - run: poetry run mkdocs build
diff --git a/.gitignore b/.gitignore
index f044718..42d1a70 100644
--- a/.gitignore
+++ b/.gitignore
@@ -8,7 +8,6 @@ __pycache__/
 
 # Distribution / packaging
 .Python
-env/
 build/
 develop-eggs/
 dist/
@@ -24,12 +23,7 @@ wheels/
 *.egg-info/
 .installed.cfg
 *.egg
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
+MANIFEST
 
 # Installer logs
 pip-log.txt
@@ -43,24 +37,9 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
-*,cover
+*.cover
 .hypothesis/
-.mypy*
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
+.pytest_cache/
 
 # Sphinx documentation
 docs/_build/
@@ -74,38 +53,33 @@ target/
 # pyenv
 .python-version
 
-# celery beat schedule file
-celerybeat-schedule
-
-# dotenv
+# Environments
 .env
-
-# virtualenv
-.venv/
+.venv
+env/
 venv/
 ENV/
+env.bak/
+venv.bak/
 
 # Spyder project settings
 .spyderproject
+.spyproject
 
 # Rope project settings
 .ropeproject
 
-# others
-.DS_Store
-.~*
-._*
-bin/
-include/
-share/
-pip-selfcheck.json
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# IDEs
+.idea/
 
-results
-feeds/
-recommender/
-.tc*/
+# Project specific
 .bga*
 .bgg*
-*.csv
 *.ipynb
 *.npz
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 4343c0a..cadb3c2 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,24 +1,45 @@
+exclude: '^v3/.*$'
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.4.0
+  rev: v4.0.1
   hooks:
-  - id: check-yaml
-  - id: end-of-file-fixer
-  - id: trailing-whitespace
-    exclude: ^notebooks/
-- repo: https://github.com/asottile/pyupgrade
-  rev: v3.3.1
+    - id: check-ast
+    - id: check-added-large-files
+    - id: check-merge-conflict
+    - id: check-case-conflict
+    - id: check-docstring-first
+    - id: check-json
+    - id: check-yaml
+    - id: debug-statements
+    - id: end-of-file-fixer
+      exclude: 'CHANGELOG.md'
+    - id: trailing-whitespace
+    - id: mixed-line-ending
+- repo: local
   hooks:
-  - id: pyupgrade
-    exclude: ^notebooks/
-- repo: https://github.com/psf/black
-  rev: '23.3.0'
-  hooks:
-  - id: black
-    exclude: ^notebooks/
-- repo: https://github.com/pycqa/isort
-  rev: '5.12.0'
-  hooks:
-  - id: isort
-    exclude: ^notebooks/
-    args: ["--profile", "black", "--filter-files"]
+    - id: ruff-format
+      name: ruff-format
+      entry: poetry run ruff format
+      require_serial: true
+      language: system
+      types: [python]
+    - id: ruff
+      name: ruff
+      # Add --fix, in case you want it to autofix when this hook runs
+      entry: poetry run ruff check --fix --unsafe-fixes --force-exclude
+      require_serial: true
+      language: system
+      types: [python]
+    - id: mypy
+      name: mypy
+      entry: poetry run mypy --exclude v3 .
+      require_serial: true
+      language: system
+      types: [python]
+      pass_filenames: false
+    - id: kacl-verify
+      name: kacl-verify
+      entry: poetry run kacl-cli verify
+      language: system
+      files: 'CHANGELOG.md'
+      pass_filenames: false
diff --git a/CHANGELOG.md b/CHANGELOG.md
new file mode 100644
index 0000000..4f436d9
--- /dev/null
+++ b/CHANGELOG.md
@@ -0,0 +1,6 @@
+# Changelog
+All notable changes to this project will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## Unreleased
diff --git a/LICENSE b/LICENSE
index 3d14243..0032271 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,21 +1,20 @@
-MIT License
+The MIT License (MIT)
 
-Copyright (c) 2019 Markus Shepherd
+Copyright (c) 2024 Markus Shepherd <markus@recommend.games>
 
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
 
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.
 
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
diff --git a/README.md b/README.md
index b2af30b..a3e76d3 100644
--- a/README.md
+++ b/README.md
@@ -1,71 +1,91 @@
-# 🎲 Board Game Recommender 👍
+# Board Game Recommender
 
-Board game recommendation engine. View the recommendations live at
-[Recommend.Games](https://recommend.games/)! Install via
+[![PyPI](https://img.shields.io/pypi/v/board-game-recommender?style=flat-square)](https://pypi.python.org/pypi/board-game-recommender/)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/board-game-recommender?style=flat-square)](https://pypi.python.org/pypi/board-game-recommender/)
+[![PyPI - License](https://img.shields.io/pypi/l/board-game-recommender?style=flat-square)](https://pypi.python.org/pypi/board-game-recommender/)
+[![Coookiecutter - Wolt](https://img.shields.io/badge/cookiecutter-Wolt-00c2e8?style=flat-square&logo=cookiecutter&logoColor=D4AA00&link=https://github.com/woltapp/wolt-python-package-cookiecutter)](https://github.com/woltapp/wolt-python-package-cookiecutter)
 
-```bash
+
+---
+
+**Documentation**: [https://recommend-games.github.io/board-game-recommender](https://recommend-games.github.io/board-game-recommender)
+
+**Source Code**: [https://github.com/recommend-games/board-game-recommender](https://github.com/recommend-games/board-game-recommender)
+
+**PyPI**: [https://pypi.org/project/board-game-recommender/](https://pypi.org/project/board-game-recommender/)
+
+---
+
+Board game recommendation engine.
+
+## Installation
+
+```sh
 pip install board-game-recommender
 ```
 
-## Training new recommender models
+## Development
 
-### Environment
+* Clone this repository
+* Requirements:
+  * [Poetry](https://python-poetry.org/)
+  * Python 3.8+
+* Create a virtual environment and install the dependencies
 
-[Requires Python 3](https://pythonclock.org/). Make sure
-[Pipenv](https://docs.pipenv.org/) is installed and create the virtual environment:
+```sh
+poetry install
+```
+
+* Activate the virtual environment
+
+```sh
+poetry shell
+```
 
-```bash
-python3 -m pip install --upgrade pipenv
-pipenv install --dev
-pipenv shell
+### Testing
+
+```sh
+pytest
 ```
 
-### Datasets
+### Documentation
+
+The documentation is automatically generated from the content of the [docs directory](https://github.com/recommend-games/board-game-recommender/tree/master/docs) and from the docstrings
+ of the public signatures of the source code. The documentation is updated and published as a [Github Pages page](https://pages.github.com/) automatically as part each release.
 
-In order to train the models you will need appropriate game and rating data.
-You can either scrape your own using the [board-game-scraper](https://gitlab.com/recommend.games/board-game-scraper)
-project or take a look at the [BoardGameGeek guild](https://boardgamegeek.com/thread/2287371/boardgamegeek-games-and-ratings-datasets)
-to obtain existing datasets.
+### Releasing
 
-At the moment there is only one [recommender implementations](board_game_recommender/recommend.py): [BoardGameGeek](https://boardgamegeek.com/).
+Trigger the [Draft release workflow](https://github.com/recommend-games/board-game-recommender/actions/workflows/draft_release.yml)
+(press _Run workflow_). This will update the changelog & version and create a GitHub release which is in _Draft_ state.
 
-### Models
+Find the draft release from the
+[GitHub releases](https://github.com/recommend-games/board-game-recommender/releases) and publish it. When
+ a release is published, it'll trigger [release](https://github.com/recommend-games/board-game-recommender/blob/master/.github/workflows/release.yml) workflow which creates PyPI
+ release and deploys updated documentation.
 
-We use the recommender implementation by [Turi Create](https://github.com/apple/turicreate).
-Two recommender models are supported out of the box:
+### Pre-commit
 
-* [`RankingFactorizationRecommender`](https://apple.github.io/turicreate/docs/api/generated/turicreate.recommender.ranking_factorization_recommender.RankingFactorizationRecommender.html)
- (default): Learns latent factors for each user and game, generally yielding
- very interesting recommendations.
-* [`ItemSimilarityRecommender`](https://apple.github.io/turicreate/docs/api/generated/turicreate.recommender.item_similarity_recommender.ItemSimilarityRecommender.html):
- Ranks a game according to its similarity to other ratings by a user, often
- resulting in less interesting recommendations. However, this model is also
- able to find games similar to a given game.
+Pre-commit hooks run all the auto-formatting (`ruff format`), linters (e.g. `ruff` and `mypy`), and other quality
+ checks to make sure the changeset is in good shape before a commit/push happens.
 
-### Run the training
+You can install the hooks with (runs for each commit):
+
+```sh
+pre-commit install
+```
 
-Run the training via the [main script](board_game_recommender/__main__.py):
+Or if you want them to run only for each push:
 
-```bash
-python -m board_game_recommender --help
+```sh
+pre-commit install -t pre-push
 ```
 
-E.g., train the default BGG mode like so:
+Or if you want e.g. want to run all checks manually for all files:
 
-```bash
-python -m board_game_recommender \
-    --train \
-    --games-file bgg_GameItem.jl \
-    --ratings-file bgg_RatingItem.jl \
-    --model model/output/dir
+```sh
+pre-commit run --all-files
 ```
 
-## Links
+---
 
-* [board-game-recommender](https://gitlab.com/recommend.games/board-game-recommender):
- This repository
-* [Recommend.Games](https://recommend.games/): board game recommender website
-* [recommend-games-server](https://gitlab.com/recommend.games/recommend-games-server):
- Server code for [Recommend.Games](https://recommend.games/)
-* [board-game-scraper](https://gitlab.com/recommend.games/board-game-scraper):
- Board game data scraper
+This project was generated using the [wolt-python-package-cookiecutter](https://github.com/woltapp/wolt-python-package-cookiecutter) template.
diff --git a/docs/api_docs.md b/docs/api_docs.md
new file mode 100644
index 0000000..1231bf8
--- /dev/null
+++ b/docs/api_docs.md
@@ -0,0 +1,3 @@
+# API documentation
+
+:::board_game_recommender
diff --git a/docs/changelog.md b/docs/changelog.md
new file mode 100644
index 0000000..786b75d
--- /dev/null
+++ b/docs/changelog.md
@@ -0,0 +1 @@
+--8<-- "CHANGELOG.md"
diff --git a/docs/index.md b/docs/index.md
new file mode 100644
index 0000000..612c7a5
--- /dev/null
+++ b/docs/index.md
@@ -0,0 +1 @@
+--8<-- "README.md"
diff --git a/mkdocs.yml b/mkdocs.yml
new file mode 100644
index 0000000..b9a0ba6
--- /dev/null
+++ b/mkdocs.yml
@@ -0,0 +1,34 @@
+site_name: "Board Game Recommender"
+repo_url: https://github.com/recommend-games/board-game-recommender
+
+theme:
+  name: material
+  palette:
+    - scheme: default
+      toggle:
+        icon: material/toggle-switch-off-outline
+        name: Switch to dark mode
+    - scheme: slate
+      toggle:
+        icon: material/toggle-switch
+        name: Switch to light mode
+
+nav:
+  - Introduction: 'index.md'
+  - api_docs.md
+  - changelog.md
+
+markdown_extensions:
+  - pymdownx.snippets:
+      check_paths: true
+
+plugins:
+  - search:
+  - mkdocstrings:
+      default_handler: python
+      handlers:
+        python:
+          options:
+            show_signature_annotations: true
+            show_source: true
+            show_submodules: true
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..b08f9a0
--- /dev/null
+++ b/poetry.lock
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+optional = false
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+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9.0, <4.0"
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diff --git a/poetry.toml b/poetry.toml
new file mode 100644
index 0000000..ab1033b
--- /dev/null
+++ b/poetry.toml
@@ -0,0 +1,2 @@
+[virtualenvs]
+in-project = true
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..9a49bc1
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,131 @@
+[tool.poetry]
+name = "board-game-recommender"
+version = "4.0.0-alpha.1"
+description = "Board game recommendation engine"
+authors = [
+    "Markus Shepherd <markus@recommend.games>",
+]
+license = "MIT"
+readme = "README.md"
+
+documentation = "https://recommend-games.github.io/board-game-recommender"
+homepage = "https://recommend-games.github.io/board-game-recommender"
+repository = "https://github.com/recommend-games/board-game-recommender"
+
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+    "Typing :: Typed",
+]
+
+packages = [
+    {include = "board_game_recommender", from = "src"},
+]
+
+[tool.poetry.dependencies]
+python = ">=3.9.0, <4.0"
+
+numpy = "*"
+polars = "*"
+
+[tool.poetry.group.dev.dependencies]
+ipython = "*"
+mkdocstrings = {version = ">=0.23", extras = ["python"]}
+mkdocs-material = "*"
+mypy = "*"
+pre-commit = "*"
+pymdown-extensions = "*"
+pytest = "*"
+pytest-github-actions-annotate-failures = "*"
+pytest-cov = "*"
+python-kacl = "*"
+ruff = ">=0.2.0"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.ruff]
+target-version = "py39" # The lowest supported version
+
+[tool.ruff.lint]
+# By default, enable all the lint rules.
+# Add to the ignore list below if you don't want some rules.
+# If you need some ignores for certain modules, see tool.ruff.lint.per-file-ignores below.
+# For individual ignore cases, prefer inline `# noqa`s within the code.
+select = ["ALL"]
+ignore = [
+    "ANN",      # Type hints related, let mypy handle these.
+    "D",        # Docstrings related, way too strict to our taste
+    "ERA001",   # Found commented-out code
+    "RUF001",   # String contains ambiguous `–` (EN DASH)
+    "TD",       # TODO
+    "FIX",      # FIXME,
+    "S101",     # "Use of `assert` detected"
+    "T201",     # Removes `print`s – WTF?
+]
+
+[tool.ruff.lint.per-file-ignores]
+"tests/**" = [
+    "S101",     # "Use of `assert` detected"
+    "ARG",      # "Unused function argument". Fixtures are often unused.
+    "S105",     # "Possible hardcoded password".
+]
+
+[tool.ruff.lint.mccabe]
+max-complexity = 10
+
+[tool.ruff.lint.pep8-naming]
+classmethod-decorators = [
+    "classmethod",
+    "pydantic.validator",
+    "pydantic.root_validator",
+]
+
+[tool.pytest.ini_options]
+addopts = """\
+    --cov board_game_recommender \
+    --cov tests \
+    --cov-report term-missing \
+    --no-cov-on-fail \
+"""
+
+[tool.coverage.report]
+fail_under = 100
+exclude_lines = [
+    'if TYPE_CHECKING:',
+    'pragma: no cover'
+]
+
+[tool.mypy]
+# This is the global mypy configuration.
+# Avoid changing this!
+strict = true  # See all the enabled flags `mypy --help | grep -A 10 'Strict mode'`
+disallow_any_unimported = false
+disallow_subclassing_any = false
+
+# If you need to ignore something for some specific module,
+# add overrides for them. Avoid changing the global config!
+# For example:
+[[tool.mypy.overrides]]
+# module = [
+#  "my_unpyted_dependency1.*",
+#  "my_unpyted_dependency2.*"
+# ]
+ignore_missing_imports = true
+implicit_reexport = true
+
+# [[tool.mypy.overrides]]
+# module = [
+#   "tests/my_thing/test_my_thing",
+# ]
+# disallow_untyped_defs = false
diff --git a/src/board_game_recommender/__init__.py b/src/board_game_recommender/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/board_game_recommender/abc.py b/src/board_game_recommender/abc.py
new file mode 100644
index 0000000..96e1238
--- /dev/null
+++ b/src/board_game_recommender/abc.py
@@ -0,0 +1,125 @@
+"""Abstract base recommender class."""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, Generic, TypeVar
+
+import numpy as np
+
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+    from collections.abc import Set as AbstractSet
+
+    import polars as pl
+
+GameKeyType = TypeVar("GameKeyType")
+UserKeyType = TypeVar("UserKeyType")
+
+
+class BaseGamesRecommender(ABC, Generic[GameKeyType, UserKeyType]):
+    """Abstract base games recommender class."""
+
+    @property
+    @abstractmethod
+    def known_games(self) -> AbstractSet[GameKeyType]:
+        """IDs of all known games."""
+
+    @property
+    def num_games(self) -> int:
+        """Number of known games."""
+        return len(self.known_games)
+
+    @property
+    @abstractmethod
+    def rated_games(self) -> AbstractSet[GameKeyType]:
+        """IDs of all rated games."""
+
+    @property
+    @abstractmethod
+    def known_users(self) -> AbstractSet[UserKeyType]:
+        """IDs of all known users."""
+
+    @property
+    def num_users(self) -> int:
+        """Number of known users."""
+        return len(self.known_users)
+
+    @abstractmethod
+    def recommend(
+        self,
+        users: Iterable[UserKeyType],
+        **kwargs,
+    ) -> pl.DataFrame:
+        """Recommend games for given users."""
+
+    @abstractmethod
+    def recommend_as_numpy(
+        self,
+        users: Iterable[UserKeyType],
+        games: Iterable[GameKeyType],
+    ) -> np.ndarray:
+        """Recommend games for given users and games as a numpy array."""
+
+    @abstractmethod
+    def recommend_group(
+        self,
+        users: Iterable[UserKeyType],
+        **kwargs,
+    ) -> pl.DataFrame:
+        """Recommend games for given group of users."""
+
+    @abstractmethod
+    def recommend_group_as_numpy(
+        self,
+        users: Iterable[UserKeyType],
+        games: Iterable[GameKeyType],
+    ) -> np.ndarray:
+        """Recommend games for given group of users and games as a numpy array."""
+
+    @abstractmethod
+    def recommend_similar(
+        self,
+        games: Iterable[GameKeyType],
+        **kwargs,
+    ) -> pl.DataFrame:
+        """Recommend games similar to the given ones."""
+
+    @abstractmethod
+    def similar_games(
+        self,
+        games: Iterable[GameKeyType],
+        **kwargs,
+    ) -> pl.DataFrame:
+        """Find games similar to the given ones."""
+
+    def recommend_random_games_as_numpy(
+        self,
+        users: Iterable[UserKeyType],
+        games: Iterable[GameKeyType],
+        *,
+        num_games: int = 1,
+        random_seed: int | None = None,
+    ) -> np.ndarray:
+        """
+        Select random games based on recommendations for a given group of
+        users and games as a numpy array.
+        """
+
+        users = list(users)
+        games = list(games)
+
+        if not games:
+            return np.array([])
+
+        # TODO: allow for different weighting schemes
+        weights = self.recommend_group_as_numpy(users, games).reshape(-1)
+        weights = np.exp(weights)
+
+        rng = np.random.default_rng(seed=random_seed)
+        return rng.choice(
+            a=games,  # type: ignore[arg-type]
+            size=min(num_games, len(games)),
+            replace=False,
+            p=weights / weights.sum(),
+        )
diff --git a/src/board_game_recommender/baseline.py b/src/board_game_recommender/baseline.py
new file mode 100644
index 0000000..d3481f3
--- /dev/null
+++ b/src/board_game_recommender/baseline.py
@@ -0,0 +1,329 @@
+"""Baseline recommender models."""
+
+from __future__ import annotations
+
+from collections import defaultdict
+from typing import TYPE_CHECKING, cast
+
+import numpy as np
+import polars as pl
+
+from board_game_recommender.abc import BaseGamesRecommender
+
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+    from pathlib import Path
+    from typing import Any, Self
+
+
+def dataframe_from_scores(
+    *,
+    users: Iterable[str],
+    games: Iterable[Any],
+    scores: np.ndarray,  # shape: (users, games)
+) -> pl.DataFrame:
+    """Creates a Pandas DataFrame out of raw recommendation scores."""
+
+    users = tuple(users)
+    games = tuple(games)
+
+    rank_cols = (
+        pl.col(f"{column}_score")
+        .rank(method="min", descending=True)
+        .alias(f"{column}_rank")
+        for column in users
+    )
+
+    result = (
+        pl.DataFrame(
+            data=scores.T,
+            schema=[f"{column}_score" for column in users],
+        )
+        .lazy()
+        .with_columns(
+            pl.Series("index", games),
+            *rank_cols,
+        )
+    )
+
+    if len(users) == 1:
+        result = result.sort(f"{users[0]}_rank")
+
+    return result.collect()
+
+
+class RandomGamesRecommender(BaseGamesRecommender):
+    """Random recommender."""
+
+    def __init__(self) -> None:
+        self.rng = np.random.default_rng()
+
+    @property
+    def known_games(self) -> frozenset[int]:
+        return frozenset()
+
+    @property
+    def rated_games(self) -> frozenset[int]:
+        return frozenset()
+
+    @property
+    def known_users(self) -> frozenset[str]:
+        return frozenset()
+
+    def _recommendation_scores(self, users: int, games: int) -> np.ndarray:
+        """Random scores."""
+        return self.rng.random((users, games))
+
+    def recommend(  # type: ignore[override]
+        self,
+        users: Iterable[str],
+        games: Iterable[int],
+        **kwargs,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        """Random recommendations for certain users."""
+
+        users = list(users)
+        games = list(games)
+        scores = self._recommendation_scores(users=len(users), games=len(games))
+
+        return dataframe_from_scores(users=users, games=games, scores=scores)
+
+    def recommend_as_numpy(
+        self,
+        users: Iterable[str],
+        games: Iterable[int],
+    ) -> np.ndarray:
+        """Random recommendations for certain users and games as a numpy array."""
+        users = list(users)
+        games = list(games)
+        return self._recommendation_scores(users=len(users), games=len(games))
+
+    def recommend_group(  # type: ignore[override]
+        self,
+        users: Iterable[str],  # noqa: ARG002
+        games: Iterable[int],
+        **kwargs,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        """Random recommendations for a group of users."""
+
+        games = list(games)
+        scores = self._recommendation_scores(users=1, games=len(games))
+
+        return dataframe_from_scores(users=["_all"], games=games, scores=scores)
+
+    def recommend_group_as_numpy(
+        self,
+        users: Iterable[str],  # noqa: ARG002
+        games: Iterable[int],
+    ) -> np.ndarray:
+        """Random recommendations for a group of users and games as a numpy array."""
+        games = list(games)
+        return self._recommendation_scores(users=1, games=len(games))
+
+    def recommend_similar(self, games: Iterable[int], **kwargs) -> pl.DataFrame:
+        raise NotImplementedError
+
+    def similar_games(self, games: Iterable[int], **kwargs) -> pl.DataFrame:
+        raise NotImplementedError
+
+
+class PopularGamesRecommender(BaseGamesRecommender):
+    """Popular games recommender."""
+
+    id_field: str = "bgg_id"
+    user_id_field: str = "bgg_user_name"
+    rating_id_field: str = "bgg_user_rating"
+
+    scores: dict[int, float]
+    raw_scores: np.ndarray
+    default_value: float
+    game_ids: tuple[int, ...]
+
+    _known_games: frozenset[int] | None = None
+
+    def __init__(
+        self,
+        game_ids: Iterable[int],
+        scores: np.ndarray,
+        default_value: float | None = None,
+    ) -> None:
+        self.default_value = (
+            default_value if default_value is not None else scores.mean()
+        )
+        self.raw_scores = scores
+        self.game_ids = tuple(game_ids)
+        self.scores = defaultdict(
+            self.default_factory,
+            zip(self.game_ids, self.raw_scores),
+        )
+
+    @classmethod
+    def train(cls, ratings: pl.DataFrame) -> Self:
+        """Train the recommender from ratings data."""
+        raise NotImplementedError
+
+    @classmethod
+    def train_from_csv(cls, ratings_file: Path | str) -> Self:
+        """Train the recommender from a ratings file in CSV format."""
+        ratings = pl.read_csv(ratings_file)
+        return cls.train(
+            ratings.select(cls.id_field, cls.user_id_field, cls.rating_id_field),
+        )
+
+    @classmethod
+    def train_from_json_lines(cls, ratings_file: Path | str) -> Self:
+        """Train the recommender from a ratings file in JSON lines format."""
+        ratings = pl.read_ndjson(ratings_file)
+        return cls.train(
+            ratings.select(cls.id_field, cls.user_id_field, cls.rating_id_field),
+        )
+
+    @property
+    def known_games(self) -> frozenset[int]:
+        if self._known_games is not None:
+            return self._known_games
+        self._known_games = frozenset(self.game_ids)
+        return self._known_games
+
+    @property
+    def rated_games(self) -> frozenset[int]:
+        return self.known_games
+
+    @property
+    def num_games(self) -> int:
+        return len(self.game_ids)
+
+    @property
+    def known_users(self) -> frozenset[str]:
+        return frozenset()
+
+    def default_factory(self) -> float:
+        """Default value for unknown games."""
+        return self.default_value
+
+    def _recommendation_scores(
+        self,
+        users: int,
+        games: list[int] | None = None,
+    ) -> np.ndarray:
+        """Popularity scores."""
+        scores = (
+            np.array([self.scores[game_id] for game_id in games])
+            if games
+            else self.raw_scores
+        )
+        return np.tile(scores, [users, 1])
+
+    def recommend(
+        self,
+        users: Iterable[str],
+        **kwargs,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        """Popular recommendations for certain users."""
+        users = list(users)
+        scores = self._recommendation_scores(users=len(users))
+        return dataframe_from_scores(users=users, games=self.game_ids, scores=scores)
+
+    def recommend_as_numpy(
+        self,
+        users: Iterable[str],
+        games: Iterable[int],
+    ) -> np.ndarray:
+        """Popular recommendations for certain users and games as a numpy array."""
+        users = list(users)
+        games = list(games)
+        return self._recommendation_scores(users=len(users), games=games)
+
+    def recommend_group(
+        self,
+        users: Iterable[str],  # noqa: ARG002
+        **kwargs,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        """Popular recommendations for a group of users."""
+        scores = self._recommendation_scores(users=1)
+        return dataframe_from_scores(users=["_all"], games=self.game_ids, scores=scores)
+
+    def recommend_group_as_numpy(
+        self,
+        users: Iterable[str],  # noqa: ARG002
+        games: Iterable[int],
+    ) -> np.ndarray:
+        """Popular recommendations for a group of users and games as a numpy array."""
+        games = list(games)
+        return self._recommendation_scores(users=1, games=games)
+
+    def recommend_similar(
+        self,
+        games: Iterable[int],
+        **kwargs,
+    ) -> pl.DataFrame:
+        raise NotImplementedError
+
+    def similar_games(
+        self,
+        games: Iterable[int],
+        **kwargs,
+    ) -> pl.DataFrame:
+        raise NotImplementedError
+
+
+class PopularMeanGamesRecommender(PopularGamesRecommender):
+    """Recommend games by their mean rating score."""
+
+    @classmethod
+    def train(cls, ratings: pl.DataFrame) -> Self:
+        data = ratings.group_by(cls.id_field).agg(
+            mean=pl.col(cls.rating_id_field).mean(),
+        )
+        return cls(
+            game_ids=data[cls.id_field],
+            scores=data["mean"].to_numpy(),
+            default_value=cast(float, ratings[cls.rating_id_field].mean()),
+        )
+
+
+class PopularBayesianGamesRecommender(PopularGamesRecommender):
+    """Recommend games by their Bayesian average rating score."""
+
+    ratings_per_dummy: float = 10_000
+    dummy_rating: float | None = 5.5
+
+    @classmethod
+    def train(cls, ratings: pl.DataFrame) -> Self:
+        num_dummies = len(ratings) / cls.ratings_per_dummy
+        dummy_rating = cast(
+            float,
+            ratings[cls.rating_id_field].mean()
+            if cls.dummy_rating is None
+            else cls.dummy_rating,
+        )
+
+        stats = (
+            ratings.group_by(cls.id_field)
+            .agg(
+                mean=pl.col(cls.rating_id_field).mean(),
+                size=pl.len(),
+            )
+            .with_columns(
+                bayes=pl.col("mean") * pl.col("size")
+                + dummy_rating * num_dummies / (pl.col("size") + num_dummies),
+            )
+        )
+
+        return cls(
+            game_ids=stats[cls.id_field],
+            scores=stats["bayes"].to_numpy(),
+            default_value=dummy_rating,
+        )
+
+
+class PopularNumRatingsGamesRecommender(PopularGamesRecommender):
+    """Recommend games by their number of ratings."""
+
+    @classmethod
+    def train(cls, ratings: pl.DataFrame) -> Self:
+        data = ratings.group_by(cls.id_field).agg(count=pl.len())
+        return cls(
+            game_ids=data[cls.id_field],
+            scores=data["count"].to_numpy(),
+        )
diff --git a/src/board_game_recommender/py.typed b/src/board_game_recommender/py.typed
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@@ -0,0 +1,71 @@
+# 🎲 Board Game Recommender 👍
+
+Board game recommendation engine. View the recommendations live at
+[Recommend.Games](https://recommend.games/)! Install via
+
+```bash
+pip install board-game-recommender
+```
+
+## Training new recommender models
+
+### Environment
+
+[Requires Python 3](https://pythonclock.org/). Make sure
+[Pipenv](https://docs.pipenv.org/) is installed and create the virtual environment:
+
+```bash
+python3 -m pip install --upgrade pipenv
+pipenv install --dev
+pipenv shell
+```
+
+### Datasets
+
+In order to train the models you will need appropriate game and rating data.
+You can either scrape your own using the [board-game-scraper](https://gitlab.com/recommend.games/board-game-scraper)
+project or take a look at the [BoardGameGeek guild](https://boardgamegeek.com/thread/2287371/boardgamegeek-games-and-ratings-datasets)
+to obtain existing datasets.
+
+At the moment there is only one [recommender implementations](board_game_recommender/recommend.py): [BoardGameGeek](https://boardgamegeek.com/).
+
+### Models
+
+We use the recommender implementation by [Turi Create](https://github.com/apple/turicreate).
+Two recommender models are supported out of the box:
+
+* [`RankingFactorizationRecommender`](https://apple.github.io/turicreate/docs/api/generated/turicreate.recommender.ranking_factorization_recommender.RankingFactorizationRecommender.html)
+ (default): Learns latent factors for each user and game, generally yielding
+ very interesting recommendations.
+* [`ItemSimilarityRecommender`](https://apple.github.io/turicreate/docs/api/generated/turicreate.recommender.item_similarity_recommender.ItemSimilarityRecommender.html):
+ Ranks a game according to its similarity to other ratings by a user, often
+ resulting in less interesting recommendations. However, this model is also
+ able to find games similar to a given game.
+
+### Run the training
+
+Run the training via the [main script](board_game_recommender/__main__.py):
+
+```bash
+python -m board_game_recommender --help
+```
+
+E.g., train the default BGG mode like so:
+
+```bash
+python -m board_game_recommender \
+    --train \
+    --games-file bgg_GameItem.jl \
+    --ratings-file bgg_RatingItem.jl \
+    --model model/output/dir
+```
+
+## Links
+
+* [board-game-recommender](https://gitlab.com/recommend.games/board-game-recommender):
+ This repository
+* [Recommend.Games](https://recommend.games/): board game recommender website
+* [recommend-games-server](https://gitlab.com/recommend.games/recommend-games-server):
+ Server code for [Recommend.Games](https://recommend.games/)
+* [board-game-scraper](https://gitlab.com/recommend.games/board-game-scraper):
+ Board game data scraper
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