dr-ds 0.1.2

Small, typed data science helpers for serialization, atomic file writes, and dataframe-oriented record normalization.

dr-ds

Small, typed data science helpers for serialization, atomic file writes, and dataframe-oriented record normalization.

Install

uv add dr-ds

dr-ds currently targets Python 3.12+.

Included Helpers

dr_ds.atomic_io provides:

• dump_json_atomic
• atomic_write_jsonl
• atomic_write_parquet_records

dr_ds.serialization provides:

• serialize_timestamp
• utc_now_iso
• to_jsonable
• convert_large_ints
• parse_jsonish

dr_ds.parquet provides:

• records_to_parquet_frame
• parquet_frame_to_records

These helpers are aimed at a common pattern in data workflows:

• start with list[dict[str, Any]] records
• normalize nested JSON-like columns into strings for dataframe/parquet compatibility
• recover those structured columns on read

Atomic IO Example

from pathlib import Path

from dr_ds.atomic_io import dump_json_atomic
from dr_ds.serialization import to_jsonable

payload = to_jsonable(
    {
        "metrics": {"loss": 0.42},
        "tags": {"baseline", "v1"},
    }
)

dump_json_atomic(Path("summary.json"), payload)

Parquet Example

from dr_ds.parquet import parquet_frame_to_records, records_to_parquet_frame

records = [
    {
        "run_id": "abc123",
        "metrics": {"loss": 0.42, "token_count": 2**35},
    }
]

frame = records_to_parquet_frame(records, json_columns={"metrics"})
restored = parquet_frame_to_records(frame, json_columns={"metrics"})

records_to_parquet_frame prepares records for dataframe/parquet workflows. It does not write parquet files directly.

License

MIT

Development

Run the standard checks before committing:

uv run ruff format .
uv run ruff check .
uv run ty check
uv run pytest