Datasets:
Tasks:
Text Classification
Formats:
parquet
Languages:
Ancient Greek (to 1453)
Size:
100K - 1M
License:
File size: 3,683 Bytes
85f00da 4a0d2b0 85f00da 1bcc6c0 85f00da 1bcc6c0 85f00da ecfe7f5 1bcc6c0 ecfe7f5 1bcc6c0 ecfe7f5 24c3b46 1bcc6c0 24c3b46 ecfe7f5 4a0d2b0 ecfe7f5 1bcc6c0 ecfe7f5 1bcc6c0 85f00da ecfe7f5 85f00da | 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 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 | #!/usr/bin/env python3
"""Regenerate all Sphragis task variants from the current atomic datasets."""
from __future__ import annotations
import argparse
import json
import os
from pathlib import Path
import tempfile
import pyarrow as pa
import pyarrow.parquet as pq
try:
from scripts.dataset_variants import (
BASE_CONFIGS,
SPLITS,
make_dataset_variants,
variant_schema,
)
from scripts.metrical_lines import sanitize_metrical_lines
except ModuleNotFoundError: # Direct execution from the scripts directory.
from dataset_variants import ( # type: ignore[no-redef]
BASE_CONFIGS,
SPLITS,
make_dataset_variants,
variant_schema,
)
from metrical_lines import sanitize_metrical_lines
def read_full_configs(data_root: Path) -> tuple[dict[str, list[dict]], dict[str, pa.Schema]]:
rows_by_config = {}
schemas = {}
for base_config in BASE_CONFIGS:
rows = []
for split in SPLITS:
path = data_root / f"{base_config}_1" / f"{split}-00000-of-00001.parquet"
parquet = pq.ParquetFile(path)
table = parquet.read(use_threads=False)
if base_config == "verse_metre" and "scansion" in table.column_names:
table = table.drop(["scansion"])
schemas.setdefault(base_config, table.schema)
assert table.schema == schemas[base_config]
split_rows = table.to_pylist()
if base_config == "verse_sentence":
for row in split_rows:
row["metrical_lines"] = sanitize_metrical_lines(
row["metrical_lines"]
)
rows.extend(split_rows)
rows_by_config[base_config] = rows
return rows_by_config, schemas
def write_variants(
data_root: Path,
variants: dict[str, list[dict]],
schemas: dict[str, pa.Schema],
) -> None:
for config, rows in variants.items():
base_config = config.rsplit("_", 1)[0]
schema = (
schemas[base_config]
if config.endswith("_1")
else variant_schema(schemas[base_config])
)
config_root = data_root / config
config_root.mkdir(parents=True, exist_ok=True)
for split in SPLITS:
split_rows = [row for row in rows if row["split"] == split]
table = pa.Table.from_pylist(split_rows, schema=schema)
destination = config_root / f"{split}-00000-of-00001.parquet"
descriptor, temporary_name = tempfile.mkstemp(
dir=config_root,
prefix=f".{destination.name}.",
suffix=".tmp",
)
os.close(descriptor)
temporary = Path(temporary_name)
try:
pq.write_table(
table,
temporary,
compression="zstd",
compression_level=9,
)
temporary.replace(destination)
finally:
temporary.unlink(missing_ok=True)
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--data", type=Path, default=Path("data"))
parser.add_argument("--report", type=Path)
args = parser.parse_args()
rows_by_config, schemas = read_full_configs(args.data)
variants, report = make_dataset_variants(rows_by_config)
write_variants(args.data, variants, schemas)
rendered = json.dumps(report, indent=2, ensure_ascii=False, sort_keys=True) + "\n"
if args.report:
args.report.write_text(rendered)
print(rendered, end="")
if __name__ == "__main__":
main()
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