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66b1c50 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | """Canonical metadata for real-world benchmark datasets."""
from __future__ import annotations
from pydantic import BaseModel, Field
class HeaderMismatch(BaseModel):
"""Pair of dirty/clean header names that align by column position."""
dirty_name: str = Field(min_length=1)
clean_name: str = Field(min_length=1)
model_config = {"frozen": True}
class DatasetMetadata(BaseModel):
"""Metadata describing a canonical benchmark dataset."""
name: str = Field(min_length=1)
domain: str = Field(min_length=1)
n_rows: int = Field(ge=0)
n_columns: int = Field(ge=1)
error_types: tuple[str, ...] = Field(default_factory=tuple)
source_urls: tuple[str, str]
citation: str = Field(min_length=1)
header_mismatches: tuple[HeaderMismatch, ...] = Field(default_factory=tuple)
model_config = {"frozen": True}
_BASE_URL = "https://raw.githubusercontent.com/BigDaMa/raha/refs/heads/master/datasets"
DATASET_REGISTRY: dict[str, DatasetMetadata] = {
"hospital": DatasetMetadata(
name="hospital",
domain="healthcare",
n_rows=1000,
n_columns=20,
error_types=("typo", "missing_value", "formatting"),
source_urls=(
f"{_BASE_URL}/hospital/dirty.csv",
f"{_BASE_URL}/hospital/clean.csv",
),
citation=(
"Mahdavi et al. Raha benchmark dataset (Hospital) via the BigDaMa/raha repository."
),
),
"flights": DatasetMetadata(
name="flights",
domain="aviation",
n_rows=2376,
n_columns=7,
error_types=("missing_value", "formatting", "datetime"),
source_urls=(
f"{_BASE_URL}/flights/dirty.csv",
f"{_BASE_URL}/flights/clean.csv",
),
citation=(
"Mahdavi et al. Raha benchmark dataset (Flights) via the BigDaMa/raha repository."
),
),
"beers": DatasetMetadata(
name="beers",
domain="consumer",
n_rows=2410,
n_columns=11,
error_types=("formatting", "missing_value", "normalization"),
source_urls=(
f"{_BASE_URL}/beers/dirty.csv",
f"{_BASE_URL}/beers/clean.csv",
),
citation=("Mahdavi et al. Raha benchmark dataset (Beers) via the BigDaMa/raha repository."),
),
}
def get_dataset_metadata(name: str) -> DatasetMetadata:
"""Return canonical metadata for a named benchmark dataset.
Args:
name: Canonical dataset name.
Returns:
The immutable metadata entry for the dataset.
Raises:
KeyError: If the dataset is not registered.
"""
return DATASET_REGISTRY[name]
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