nbase-converter

nbase-converter is a native Rust/Arrow Python package for reading, writing, and converting SAS7BDAT, SAS XPORT v5/v8, and Parquet datasets.

Version 0.0.5 is the next alpha release, not yet published. The production SAS7BDAT writer's Windows SAS 9.4 validation is recorded in the repository release notes; stable 1.0.0 compatibility is not yet declared.

Install

PyPI currently provides 0.0.4; the command below applies after 0.0.5 is published. Before publication, install the wheel built from this checkout for local validation.

python -m pip install nbase-converter==0.0.5

Python 3.11 through 3.14 is supported on 64-bit Linux, macOS, and Windows.

Example

from nbase_converter import convert_dataset, filter_field, read_dataset, write_dataset

result = read_dataset(
    "input.xpt",
    columns=["USUBJID", "AGE"],
    filter=filter_field("AGE") >= 18,
    output="pandas",
)

write_dataset(
    result.data,
    "output.parquet",
    target_format="parquet",
    overwrite=True,
)

convert_dataset(
    "source.parquet",
    "submission.xpt",
    target_format="xpt8",
    metadata={
        "dataset_label": "Adverse Events",
        "columns": {
            "ASTDT": {
                "label": "Analysis Start Date",
                "sas": {"format": "IS8601DA", "length": 8},
            }
        },
    },
)

The public dataset operations are:

• read_dataset: materialized, streaming, or metadata-only reads with projection, row bounds, encoding selection, and structured filters.
• write_dataset: Arrow-compatible writes to Parquet, XPT v5/v8, or SAS7BDAT.
• convert_dataset: bounded-memory full-file conversion with optional supplemental metadata.

For writes and conversions, explicit metadata overrides recognized input metadata while omitted attributes remain preserved. Supported supplemental attributes are the dataset label and each column's label, SAS format, informat, and storage length. For string attributes, "" explicitly clears an inherited value; whitespace-only labels remain literal labels.

Structured filters are created with filter_field, combined with filter_all, filter_any, or filter_not, and evaluated by these leaf helpers:

• comparisons: filter_equal, filter_not_equal, filter_less_than, filter_less_than_or_equal, filter_greater_than, and filter_greater_than_or_equal;
• collections and text: filter_in, filter_between, filter_contains, filter_starts_with, and filter_ends_with;
• missing values: filter_is_missing, filter_is_not_missing, filter_is_null, and filter_is_not_null.

Python comparison operators are also available on filter_field(...). Public result and metadata contracts ship as TypedDict definitions, and the wheel is marked as a typed package.

The default cross-format type policy accepts Float64 and UTF-8 text. Non-null IEEE NaNs are written as standard SAS numeric missing values and reported as coercions. Local filesystem paths are the only supported storage interface in this release.

Source, issues, release notes, and the full contract are available from the Bitbucket repository.