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feat: Add CLI Commands for Browsing and Searching OpenML Tasks

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Évaluation

Difficulté
3/5
Temps estimé
1-2 jours
Accessibilité débutants
68/100
Type d'issue
Fonctionnalité
Clarté
Clairement spécifiée
Activité
À l'abandon
Stack technique
python
Domaine
cli, machine-learning

Piste de recherche

Start in openml/cli.py, following the existing configure and models command patterns and the tasks_list(), tasks_info(), and tasks_search() entry points. Then read tests/test_openml/test_cli.py and the existing openml.tasks.list_tasks() and get_task() APIs. Done means the three tasks subcommands support the described arguments and mocked tests pass.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

Metadata

New Tests Added: Yes

Documentation Updated: No (CLI help text serves as documentation)

Change Log Entry: "Add CLI commands for browsing and searching OpenML tasks: openml tasks list, openml tasks info, and openml tasks search"

Details
What does this PR implement/fix?
This PR adds three new CLI subcommands under openml tasks to improve the user experience of the task catalogue:

openml tasks list - List tasks with optional filtering (tag, task_type, size, pagination, output format)
openml tasks info <task_id> - Display detailed information about a specific task including dataset, task type, target feature, and evaluation measure
openml tasks search - Search tasks by associated dataset name with case-insensitive matching
Why is this change necessary? What is the problem it solves?
Currently, users must write Python code to browse or search OpenML tasks, even for simple tasks like listing available tasks or finding tasks for a specific dataset. This creates a barrier to entry and makes the task catalogue less accessible. Adding CLI commands allows users to interact with the task catalogue directly from the command line without writing code.

This directly addresses the ESoC 2025 goal of "Improving user experience of the task catalogue in AIoD and OpenML".

How can I reproduce the issue this PR is solving and its solution?
Before (requires Python code):

import openml
tasks = openml.tasks.list_tasks(size=10)
for tid in tasks:
    task = openml.tasks.get_task(tid)
    print(f"{tid}: {task.task_type}")

After (CLI commands):

# List first 10 tasks
openml tasks list --size 10
# Search for tasks related to iris dataset
openml tasks search iris
# Get detailed info about a task
openml tasks info 1
# List classification tasks with a specific tag
openml tasks list --task-type "Supervised Classification" --tag study_14 --format table
# List tasks with pagination
openml tasks list --offset 20 --size 10

Implementation Details:
Added three new functions in openml/cli.py: tasks_list(), tasks_info(), and tasks_search()
Integrated into main CLI parser with proper argument handling
Added comprehensive test suite in tests/test_openml/test_cli.py
Uses existing openml.tasks.list_tasks() and openml.tasks.get_task() functions - no changes to core API
Follows existing CLI patterns (similar to configure and models commands)
All tests use mocked API calls to avoid requiring server connections
Any other comments?
All pre-commit hooks pass (ruff, mypy, formatting)
No breaking changes
Follows project code style and patterns
Ready for review

Langage dominant
Python
Étoiles
366
Forks
306
Merge moyen
2 j 9 h
PR mergées (30 j)
4

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