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Documentation and Release Inconsistencies

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#1,530 8 comentarios 0 reacciones 0 asignados Ver en GitHub

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
45/100
Tipo de issue
Documentación
Claridad
Bastante claro
Estado de actividad
Tranquilo
Stack tecnológico
python
Área
documentation, release

Línea de trabajo

Start with the linked OpenML Python documentation example and compare its behavior with the package built from GitHub and installed from PyPI, focusing on run_model_on_task and the avoid_duplicate_runs parameter. Then review how the develop and main branches are used for development and releases. Done means the API-key or parameter requirement and the intended stable and development branches are clearly documented.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

Documentation question

While trying to reproduce the example from the documentation, we noticed that it does not work when using the openml-python package built from the GitHub source in a local development environment. The same example does work when installing the package from PyPI, but only if avoid_duplicate_runs=False is explicitly passed to run_model_on_task; otherwise, an API key–related error is raised. If this behavior is expected, it might be helpful to document that an API key is required (or that this parameter needs to be set) in order to run the example successfully.

Additionally, it appears that the develop branch is currently being used for both active development and releases, while main is somewhat out of date. This can make it unclear which branch should be considered the stable reference point for users and contributors. Would it make sense to either update main and use it as the release branch, or to more explicitly document the intended branching and release strategy?

Lenguaje dominante
Python
Estrellas
361
Forks
296
Sin PR fusionados en 30 d

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Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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