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Documentation and Release Inconsistencies

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评估

难度
4/5
预计耗时
3-5 天
新手友好度
45/100
Issue 类型
文档
描述清晰度
基本清楚
活跃度
冷清
技术栈
python

调研方向

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.

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描述

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that the develop branch is currently being used for both active development and releases, while main is somewhat out of date.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?

主要语言
Python
星标
361
派生
296
PR 合并指标
30 天内没有已合并 PR

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