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[BUG] create_dataset() raises IndexError instead of ValueError on empty NumPy array

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@mayuriphad 已經在處理了。

開始於 2026年10月19日。

  • #1779 來自 @mayuriphad —— 未關閉

評估

難度
2/5
預估耗時
1-3 小時
新手友好度
82/100
Issue 類型
缺陷
描述清晰度
描述清楚
活躍度
活躍
技術堆疊
numpy, python
領域
data

研究方向

未經檢查的 data[0] 存取位於 openml/datasets/functions.py 中 create_dataset() 的格式偵測區塊裡。使用零列陣列執行 issue 中的重現程式片段，確認會出現 IndexError。當空的 data 拋出包含陣列形狀的 ValueError，且針對該情況的測試通過時，即視為完成。

由索引模型根據 Issue 內容生成。

描述

Description:

When create_dataset() is called with a zero-row NumPy array, the
function raises an IndexError instead of a descriptive ValueError.

The error originates from an unchecked data[0] access inside the
format-detection block. The message gives zero indication of what
actually went wrong — a user passing an empty DataFrame export or a
filtered-down dataset with no rows gets a raw index crash with no
context.

No warning, no descriptive message, no hint that the root cause is
simply an empty array. The function just crashes silently with a raw
IndexError pointing deep into openml internals.

Expected Behavior:

A clear ValueError that tells the user exactly what the problem is:

ValueError: 'data' must contain at least one row,
but got an array with shape (0, 2).

Environment
  • openml-python version: 0.15.1
  • Python version: 3.12
  • OS: Ubuntu 24
Error messages, stack traces, or logs
No descriptive error is raised. Just a raw IndexError with no context:

IndexError: index 0 is out of bounds for axis 0 with size 0

The traceback points inside openml internals with no hint that
the root cause is simply an empty array being passed in.

Verified with arrays of shape (0, 2), (0, 5), (0, 10) — all
produce the same IndexError with no useful message.
Steps to reproduce
import numpy as np
import openml

openml.datasets.create_dataset(
    name="empty_test",
    description="Reproduces the IndexError bug",
    creator=None,
    contributor=None,
    collection_date=None,
    language=None,
    licence=None,
    attributes=[("feature1", "NUMERIC"), ("target", "NUMERIC")],
    data=np.array([]).reshape(0, 2),   # 0 rows — triggers the bug
    default_target_attribute="target",
    ignore_attribute=None,
    citation="",
)

# Expected: ValueError: 'data' must contain at least one row,
#                        but got an array with shape (0, 2).
# Actual:   IndexError: index 0 is out of bounds for axis 0 with size 0
Additional context

Root cause is this unchecked data[0] access in datasets/functions.py:

# BEFORE (buggy)
if isinstance(data, (list, np.ndarray)):
    if isinstance(data[0], (list, np.ndarray)):  # crashes if data is empty
        data_format = "arff"
    elif isinstance(data[0], dict):
        data_format = "sparse_arff"

# AFTER (suggested fix)
if isinstance(data, (list, np.ndarray)):
    if len(data) == 0:                           # guard added
        raise ValueError(
            f"'data' must contain at least one row, "
            f"but got an array with shape {np.array(data).shape}."
        )
    if isinstance(data[0], (list, np.ndarray)):
        data_format = "arff"
    elif isinstance(data[0], dict):
        data_format = "sparse_arff"

Confirmed across 3 consecutive runs on openml==0.15.1 / Python 3.12 / Ubuntu 24.
Happy to open a PR with the fix if this is confirmed.

主要語言
Python
星號
370
分支
309
平均合併
1 天 16 小時
30 天內合併 PR
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