klaw-dbase 0.1.2

Fast Polars-based reading/writing of dBase/DBF files with async I/O and compression support

klaw-dbase

A Polars plugin for reading and writing dBase III files (.DBF), with built-in support for DATASUS compressed files (.DBC).

Features

• Polars IO plugin with lazy scanning, projection pushdown, and predicate pushdown
• DATASUS .DBC support for compressed Brazilian health system files
• Parallel reading across multiple files
• Flexible encodings (cp1252, utf-8, iso-8859-1, etc.)
• Globbing and directory scanning

Installation

pip install klaw-dbase

Requirements: Python 3.13+

Quickstart

Read a .DBF file

from klaw_dbase import read_dbase

df = read_dbase('data.dbf')

Lazy scan for large files

import polars as pl
from klaw_dbase import scan_dbase

lf = scan_dbase('data.dbf')
result = lf.filter(pl.col('age') > 30).select('name', 'age').collect()

Write a DataFrame

import polars as pl
from klaw_dbase import write_dbase

df = pl.DataFrame({'name': ['Alice', 'Bob'], 'age': [25, 30]})
write_dbase(df, 'output.dbf', overwrite=True)

DATASUS .DBC Files

The primary use case for this library is handling DATASUS files from Brazil's public health system—both compressed (.DBC) and uncompressed (.DBF).

Read a compressed .DBC file

from klaw_dbase import read_dbase

# Auto-detected by .dbc extension
df = read_dbase('RDPA2402.dbc')

# Or explicitly
df = read_dbase('RDPA2402.dbc', compressed=True)

Read multiple DATASUS files

from klaw_dbase import read_dbase

files = [
    'RDPA2401.dbc',
    'RDPA2402.dbc',
    'RDPA2403.dbc',
]
df = read_dbase(files)

Lazy scan with glob patterns

import polars as pl
from klaw_dbase import scan_dbase

lf = scan_dbase('data/RDPA24*.dbc')
summary = lf.filter(pl.col('IDADE') >= 65).group_by('UF_RESID').agg(pl.len().alias('count')).collect()

Get record count without loading data

from klaw_dbase import get_dbase_record_count

n = get_dbase_record_count('RDPA2402.dbc')

API Reference

read_dbase

read_dbase(
    sources,                    # path, list of paths, directory, or glob pattern
    *,
    columns=None,               # columns to select (names or indices)
    n_rows=None,                # limit number of rows
    row_index_name=None,        # add row index column
    row_index_offset=0,
    rechunk=False,
    batch_size=8192,
    n_workers=None,             # parallel readers (default: all CPUs)
    glob=True,
    encoding="cp1252",
    character_trim="begin_end",
    skip_deleted=True,
    validate_schema=True,
    compressed=False,           # auto-detected for .dbc files
) -> pl.DataFrame

scan_dbase

scan_dbase(
    sources,
    *,
    batch_size=8192,
    n_workers=None,
    single_col_name=None,
    encoding="cp1252",
    character_trim="begin_end",
    skip_deleted=True,
    validate_schema=True,
    compressed=False,
    glob=True,
    progress=False,
) -> pl.LazyFrame

write_dbase

write_dbase(
    df,                         # polars DataFrame
    dest,                       # path or file-like object
    *,
    batch_size=None,
    encoding="cp1252",
    overwrite=False,
) -> None

get_dbase_record_count

get_dbase_record_count(path) -> int

Encodings

Common encodings for dBase files:

Encoding	Use case
cp1252	Windows Latin-1 (default, common for DATASUS)
utf-8	Unicode
iso-8859-1	Latin-1
iso-8859-15	Latin-9 (Euro sign)

Error Handling

Exception	When raised
DbaseError	Corrupted or invalid dBase file
DbcError	Compression-specific problems
EmptySources	No input files or empty DataFrame on write
SchemaMismatch	Multiple files with incompatible schemas
EncodingError	Invalid or unsupported encoding

from klaw_dbase import DbaseError, DbcError, EmptySources

try:
    df = read_dbase('corrupted.dbf')
except DbaseError as e:
    print(f'Failed to read: {e}')

License

MIT