Implementation:Scikit learn Scikit learn ApiReference

Knowledge Sources	Scikit_learn Scikit-learn Docs
Domains	Documentation, API Design
Last Updated	2026-02-08 15:00 GMT

Overview

Concrete tool for configuring the API reference documentation structure provided by scikit-learn.

Description

This module defines the complete API reference configuration for scikit-learn's documentation. It maps each sklearn module to a structured dictionary containing short summaries, descriptions, and organized sections with autosummary blocks. The configuration drives the generation of API reference pages for all public classes and functions across every sklearn submodule, from calibration to utils.

Usage

Use this configuration module when modifying the structure of scikit-learn's API reference documentation, adding new modules, or reorganizing how classes and functions are presented in the documentation.

Code Reference

Source Location

• Repository: scikit-learn
• File: doc/api_reference.py

Signature

def _get_guide(*refs, is_developer=False)
def _get_submodule(module_name, submodule_name)

# Main data structure:
API_REFERENCE = {
    "sklearn.calibration": {...},
    "sklearn.cluster": {...},
    # ... all sklearn modules
}

Import

# Used internally by the Sphinx documentation build
from api_reference import API_REFERENCE

I/O Contract

Inputs

Name	Type	Required	Description
refs	str (variadic)	Yes	RST reference labels for user/developer guide links
is_developer	bool	No	Whether to link to developer guide instead of user guide (default: False)
module_name	str	Yes	Full module path (e.g., 'sklearn.feature_extraction')
submodule_name	str	Yes	Submodule name (e.g., 'image')

Outputs

Name	Type	Description
API_REFERENCE	dict	Complete mapping of module names to documentation structure
guide text	str	Formatted RST text for user/developer guide references
submodule text	str	RST automodule directives for submodule documentation

Usage Examples

Basic Usage

# Helper function usage within the documentation build
from api_reference import _get_guide, _get_submodule

# Generate a user guide reference
guide_text = _get_guide("clustering", "kmeans")
# Returns: "**User guide.** See the :ref:`clustering` and :ref:`kmeans` sections ..."

# Generate submodule documentation hook
submodule_text = _get_submodule("sklearn.feature_extraction", "image")

Related Pages

• Principle:Scikit_learn_Scikit_learn_Dataset_Loading