### Serve Documentation Preview

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Start a local web server to preview the documentation. This command is used after installing dependencies and setting up the documentation build environment.

```bash
mkdocs serve
```

--------------------------------

### Install Documentation Dependencies

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Install the necessary dependencies to preview the documentation locally. This command installs the package in editable mode with example and documentation extras.

```bash
uv pip install -e .[examples,docs]
```

--------------------------------

### Install openml with test dependencies and pre-commit

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Install the openml package with its test dependencies and configure pre-commit hooks from the repository folder. This command should be run after activating the virtual environment.

```bash
uv pip install -e .[test]
pre-commit install
```

--------------------------------

### Install uv package manager

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Install the `uv` package manager using pip. This is recommended for a smooth development experience.

```bash
pip install uv
```

--------------------------------

### Install and Run Pre-commit Hooks

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Set up pre-commit hooks to enforce coding standards and run them on all files in the repository.

```bash
pre-commit install
pre-commit run --all-files
```

--------------------------------

### Launch API v1 Docker Services

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Initialize and start the Docker container stack for the API v1 backend.

```bash
docker compose --profile all up -d
```

--------------------------------

### Install openml-python Dependencies

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Install the openml-python package in editable mode, including development and documentation dependencies.

```bash
python -m pip install -e ".[dev,docs]"
```

--------------------------------

### Create and activate virtual environment with uv

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Create a virtual environment named 'openml-python' using `uv` with Python 3.8, activate it, and then install `uv` within the virtual environment.

```bash
uv venv --seed --python 3.8 ~/.venvs/openml-python
source ~/.venvs/openml-python/bin/activate
pip install uv # Install uv within the virtual environment
```

--------------------------------

### Install OpenML-Python

Source: https://github.com/openml/openml-python/blob/main/README.md

Installs the OpenML-Python library using pip. This command is suitable for Linux, MacOS, and Windows environments with Python 3.10 or higher.

```bash
pip install openml
```

--------------------------------

### Launch API v2 Docker Services

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Build and start the Docker container stack for the API v2 (FastAPI) backend.

```bash
docker compose --profile all up
```

--------------------------------

### Run All Tests

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Execute all tests in the repository to verify your installation and changes. For Windows, ensure pytest is in your PATH.

```bash
pytest tests
```

--------------------------------

### Configure openml-python Client for Local API v1

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Set the OpenML client to point to the local Docker instance of API v1 and use the default API key. This example also demonstrates testing flow publication.

```python
import openml
from openml_sklearn.extension import SklearnExtension
from sklearn.neighbors import KNeighborsClassifier

# Configure client to use local Docker instance
openml.config.server = "http://localhost:8080/api/v1/xml"
openml.config.apikey = "AD000000000000000000000000000000"

# Test flow publication
clf = KNeighborsClassifier(n_neighbors=3)
extension = SklearnExtension()
knn_flow = extension.model_to_flow(clf)

knn_flow.publish()
```

--------------------------------

### Run OpenML-Python Docker Container

Source: https://github.com/openml/openml-python/blob/main/docs/details.md

Execute the latest development version of openml-python within a Docker container. Ensure Docker is installed and configured.

```bash
docker run -it openml/openml-python
```

--------------------------------

### Download Task and Dataset

Source: https://github.com/openml/openml-python/blob/main/README.md

Fetches a specific machine learning task by its ID and then retrieves the associated dataset. It also demonstrates how to get data splits for cross-validation.

```python
import openml

task = openml.tasks.get_task(31)
dataset = task.get_dataset()
X, y, categorical_indicator, attribute_names = dataset.get_data(target=task.target_name)
# get splits for the first fold of 10-fold cross-validation
train_indices, test_indices = task.get_train_test_split_indices(fold=0)
```

--------------------------------

### Build Documentation (Windows)

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Builds documentation for the 'develop' branch, mounting an output directory on Windows.

```bash
docker run --mount type=bind,source="E:\files/output",destination="/output" openml/openml-python doc develop
```

--------------------------------

### Build Documentation (Linux)

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Builds documentation for the 'develop' branch, mounting an output directory on Linux.

```bash
docker run --mount type=bind,source="./output",destination="/output" openml/openml-python doc develop
```

--------------------------------

### Build Docs with Local Repo and Output Mount

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Builds documentation using a local repository and mounts an output directory.

```bash
docker run --mount type=bind,source="./output",destination="/output" --mount type=bind,source="/Users/pietergijsbers/repositories/openml-python",destination="/code" openml/openml-python doc
```

--------------------------------

### Clone and Navigate Repository

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Clone your fork of the openml-python repository and navigate into the project directory.

```bash
git clone git@github.com:YourLogin/openml-python.git
cd openml-python
```

--------------------------------

### Checkout Main Branch

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Switch to the main branch of the repository.

```bash
git checkout main
```

--------------------------------

### Use Local Repository for Tests (Linux)

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Runs tests using a local repository mounted into the container on Linux.

```bash
docker run --mount type=bind,source="/Users/pietergijsbers/repositories/openml-python",destination="/code" openml/openml-python test
```

--------------------------------

### Use Local Repository for Tests (Windows)

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Runs tests using a local repository mounted into the container on Windows.

```bash
docker run --mount type=bind,source="E:\repositories/openml-python",destination="/code" openml/openml-python test
```

--------------------------------

### Run Local Script

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Executes a local Python script by mounting it into the container's /openml directory.

```bash
docker run -v PATH/TO/FILE:/openml/MY_SCRIPT.py openml/openml-python MY_SCRIPT.py
```

--------------------------------

### Resolve Container Conflicts and Launch API v1

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Stop and remove any existing API v2 containers to prevent name conflicts, then launch the API v1 services.

```bash
docker compose --profile all down
docker compose --profile all up -d
```

--------------------------------

### Run Unit Tests

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Executes unit tests for the 'develop' branch within the container.

```bash
docker run openml/openml-python test develop
```

--------------------------------

### Initialize Conda Environment for openml-python

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Create and activate a new Conda virtual environment specifically for developing the openml-python library.

```bash
conda create -n openml-python-dev python=3.12
conda activate openml-python-dev
```

--------------------------------

### Clone OpenML Server API (API v2) Repository

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Retrieve the source code for the new Python-based API v2 backend.

```bash
git clone https://github.com/openml/server-api
cd server-api
```

--------------------------------

### Run Pre-commit Checks

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Execute pre-commit checks locally to ensure code style and formatting compliance. This is equivalent to running `pre-commit run --all-files` on systems without `make`.

```bash
$ make check
```

```bash
$ pre-commit run --all-files
```

--------------------------------

### Clone OpenML Services Repository

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Retrieve the source code for the OpenML services (API v1). Navigate into the cloned directory.

```bash
git clone https://github.com/openml/services
cd services
```

--------------------------------

### Clone openml-python SDK Repository

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Retrieve the source code for the OpenML Python client library.

```bash
git clone https://github.com/openml/openml-python
cd openml-python
```

--------------------------------

### Run Specific Unit Tests

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Execute specific tests by providing the file path, test class, or individual test method. This helps in isolating and debugging issues.

```bash
pytest tests/test_datasets/test_dataset.py
```

```bash
pytest tests/test_datasets/test_dataset.py::OpenMLDatasetTest
```

```bash
pytest tests/test_datasets/test_dataset.py::OpenMLDatasetTest::test_get_data
```

--------------------------------

### Run All Pytest Tests

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Execute the entire test suite for the openml-python SDK.

```bash
pytest
```

--------------------------------

### Configure API v1 File Permissions

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Set correct ownership for the data directory to allow the PHP container to write files. If www-data user is not present, use 777 permissions as a fallback.

```bash
chown -R www-data:www-data data/php
```

```bash
chmod -R 777 data/php
```

--------------------------------

### Iterate Through Benchmarking Suite Tasks

Source: https://github.com/openml/openml-python/blob/main/README.md

Retrieves a predefined OpenML benchmarking suite and iterates through the task IDs within that suite to fetch individual tasks.

```python
import openml

suite = openml.study.get_suite("amlb-classification-all")  # Get a curated list of tasks for classification
for task_id in suite.tasks:
    task = openml.tasks.get_task(task_id)
```

--------------------------------

### Read Docker Image Readme

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

View the readme file within a specific Docker image tag.

```bash
docker run --entrypoint=/bin/cat openml/openml-python:TAG readme.md
```

--------------------------------

### Add and Commit Changes

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Stage modified files using git add and commit them with a descriptive message.

```bash
git add modified_files
git commit
```

--------------------------------

### Execute Python Command

Source: https://github.com/openml/openml-python/blob/main/docker/readme.md

Runs a specific Python command within the container to check the OpenML-Python version.

```bash
docker run openml/openml-python -c "import openml; print(openml.__version__)"
```

--------------------------------

### Download Dataset by Name

Source: https://github.com/openml/openml-python/blob/main/README.md

Retrieves a dataset from OpenML using its string name. It then extracts the data, target variable, and attribute names.

```python
import openml

dataset = openml.datasets.get_dataset("credit-g") # or by ID get_dataset(31)
X, y, categorical_indicator, attribute_names = dataset.get_data(target="class")
```

--------------------------------

### Push Changes to GitHub

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Push your local feature branch to your GitHub account to prepare for a pull request.

```bash
git push -u origin my-feature
```

--------------------------------

### Set Admin Key on Linux/macOS

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Sets the OPENML_TEST_SERVER_ADMIN_KEY environment variable using bash. This is required for tests needing administrative privileges on Linux or macOS.

```bash
export OPENML_TEST_SERVER_ADMIN_KEY="admin-key"
```

--------------------------------

### Set Admin API Key for Tests

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Export the admin API key as an environment variable to run tests that require admin privileges on the test server. This is typically for core contributors.

```bash
# For windows
$env:OPENML_TEST_SERVER_ADMIN_KEY = "admin-key"
```

```bash
# For linux/mac
export OPENML_TEST_SERVER_ADMIN_KEY="admin-key"
```

--------------------------------

### Create Feature Branch

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Create a new branch for your feature development. It's recommended to prepend the branch name with the type of changes (e.g., feature, fix, doc, maint).

```bash
git checkout -b feature/my-feature
```

--------------------------------

### Set Admin Key on Windows

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Sets the OPENML_TEST_SERVER_ADMIN_KEY environment variable using PowerShell. This is required for tests needing administrative privileges on Windows.

```shell
$env:OPENML_TEST_SERVER_ADMIN_KEY = "admin-key"
```

--------------------------------

### Run Pytest with Scikit-learn Marker

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Execute only the tests that require the scikit-learn library, using the `sklearn` pytest marker.

```bash
pytest -m sklearn
```

--------------------------------

### Run Pytest Excluding Production Server Tests

Source: https://github.com/openml/openml-python/blob/main/docs/developer_setup.md

Execute all tests except those that interact with the live OpenML production server, using pytest markers.

```bash
pytest -m "not production_server"
```

--------------------------------

### Diagnose Slow Tests with Pytest

Source: https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md

Use pytest options to identify and analyze slow-running tests. This includes showing test durations, setting timeouts, and profiling specific components.

```bash
# Show the 20 slowest tests (use 0 to list every test's duration)
pytest tests --durations=20
```

```bash
# Fail any test that exceeds the given timeout (requires pytest-timeout)
pytest tests --timeout=600
```

```bash
# Investigate only fixture/setup costs without actually running the tests
pytest tests --setup-only
```

```bash
# Profile a specific module, class, or test
pytest tests/test_datasets/test_dataset.py --durations=0
```

```bash
# Skip the slow live-server tests while profiling locally
pytest tests --durations=0 -m "not production_server and not test_server"
```

```bash
# Run the suite in parallel to reproduce CI behaviour (requires pytest-xdist)
pytest tests -n 4 --dist=load --durations=0
```

--------------------------------

### OpenML-Python Bibtex Citation

Source: https://github.com/openml/openml-python/blob/main/README.md

Provides the Bibtex entry for citing the OpenML-Python library in scientific publications. This format is commonly used in LaTeX documents.

```bibtex
@article{JMLR:v22:19-920,
  author  = {Matthias Feurer and Jan N. van Rijn and Arlind Kadra and Pieter Gijsbers and Neeratyoy Mallik and Sahithya Ravi and Andreas Müller and Joaquin Vanschoren and Frank Hutter},
  title   = {OpenML-Python: an extensible Python API for OpenML},
  journal = {Journal of Machine Learning Research},
  year    = {2021},
  volume  = {22},
  number  = {100},
  pages   = {1--5},
  url     = {http://jmlr.org/papers/v22/19-920.html}
}
```

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