# %% [markdown]

# ## Installation

# Installation is done via ``pip``:

#

# ```bash

# pip install openml

# ```

# %% [markdown]

# ## Authentication

#

# For certain functionality, such as uploading tasks or datasets, users have to

# sign up. Only accessing the data on OpenML does not require an account!

#

# If you don't have an account yet, sign up now.

# You will receive an API key, which will authenticate you to the server

# and allow you to download and upload datasets, tasks, runs and flows.

#

# * Create an OpenML account (free) on https://www.openml.org.

# * After logging in, open your account page (avatar on the top right)

# * Open 'Account Settings', then 'API authentication' to find your API key.

#

# There are two ways to permanently authenticate:

#

# * Use the ``openml`` CLI tool with ``openml configure apikey MYKEY``,

# replacing **MYKEY** with your API key.

# * Create a plain text file **~/.openml/config** with the line

# **'apikey=MYKEY'**, replacing **MYKEY** with your API key. The config

# file must be in the directory ~/.openml/config and exist prior to

# importing the openml module.

#

# Alternatively, by running the code below and replacing 'YOURKEY' with your API key,

# you authenticate for the duration of the Python process.

# %%

import openml

openml.config.apikey = "YOURKEY"

# %% [markdown]

# ## Caching

# When downloading datasets, tasks, runs and flows, they will be cached to

# retrieve them without calling the server later. As with the API key,

# the cache directory can be either specified through the config file or

# through the API:

#

# * Add the line **cachedir = 'MYDIR'** to the config file, replacing

# 'MYDIR' with the path to the cache directory. By default, OpenML

# will use **~/.openml/cache** as the cache directory.

# * Run the code below, replacing 'YOURDIR' with the path to the cache directory.

# %%

import openml

openml.config.set_root_cache_directory("YOURDIR")