Hacktoberfest 2026: as issues que os mantenedores marcaram para outubro, abertas e boas para iniciantes. Ver issues do Hacktoberfest

[BUG] Creating a task requires an estimation procedure ID, but procedure is not correctly created

Fechada
  • Algo errado?
#1,751 6 comentários 0 reações 1 responsável Ver no GitHub

Mantenedores costumam responder em até 1 dia

@RugvedBane já está trabalhando nisso.

Desde 29/9/2026.

  • #1756 de @RugvedBane — aberto

Avaliação

Dificuldade
3/5
Tempo estimado
1-2 dias
Facilidade para iniciantes
55/100
Tipo de issue
Bug
Clareza
Razoavelmente clara
Status de atividade
Ativa
Stack de tecnologia
python
Domínio
backend-api-design

Direção de pesquisa

The issue is in openml/tasks/task.py, specifically the create_task() function and the OpenMLTask class handling of estimation_procedure_id. Start by examining the default value flow and where the procedure becomes None. Test with the provided script on a local docker instance to reproduce the error. Check the split dimensions and estimation procedure attributes after task creation to confirm the bug.

Escrita pelo modelo de indexação a partir do texto da issue.

Descrição

module:Task

It is important to first note that the tasks/task.py appears to be slightly different from the version obtainable through pip install "openml==0.15.1", which would've elevated the priority while reducing the effort had the GitHub version not experienced the same bug.

The create_task() function requires an estimation_procedure_id parameter despite it having a default value in all cases, which all funnel towards the same OpenMLTask class where the handling of estimation procedure appears to break*.
It was tested without publication on the main server, as well as with publication on a local docker instance (test server does not have any procedures), where in both cases the create_task() function creates a task with Estimation Procedure equal to None and no data split (errors follow).

import openml
from openml.tasks import TaskType

openml.config.server = "..."
openml.config.apikey = "..."

did = 128  # iris

try:
    my_task = openml.tasks.create_task(
        task_type=TaskType.SUPERVISED_CLASSIFICATION,
        dataset_id=did,
        target_name="class",
        evaluation_measure="predictive_accuracy",
        estimation_procedure_id=1,
    )
    my_task.publish()
except openml.exceptions.OpenMLServerException as e:
    # Error code for 'task already exists'
    if e.code == 614:
        # Lookup task
        tasks = openml.tasks.list_tasks(data_id=did, output_format='dataframe')
        tasks = tasks.query(
            'task_type == "Supervised Classification" '
            'and estimation_procedure == "10-fold Crossvalidation" '
            'and evaluation_measures == "predictive_accuracy"'
        )
        display(tasks)
        task_id = tasks.loc[:, "tid"].values[0]
        print("Task already exists. Task ID is", task_id)
    
print(my_task)
print(my_task.estimation_procedure)
print(my_task.get_split_dimensions())

* Unconfirmed, however it is a good starting point.

Linguagem predominante
Python
Estrelas
366
Forks
308
Merge médio
1d 16h
PRs com merge (30d)
7

Preparar o ambiente

Primeiros passos

  1. Leia a issue inteira e depois o guia de contribuição do projeto.
  2. Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
  3. Faça um fork do repositório e trabalhe em uma branch.
  4. Abra um pull request que referencie o número da issue.

Mais de openml/openml-python

Todas as issues de openml/openml-python

Issues semelhantes

Mais issues de Python

Receba novas issues na sua caixa de entrada

Um resumo curto de issues do GitHub para quem está começando.