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
1 maintainer
Metadata
1 maintainer
Release files for klaw-dbase 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| klaw_dbase-0.1.2.tar.gz | 78.7 kB | With provenance | Details |
Built distributions (wheels)
Total release size: 87.5 MB
Release files / klaw_dbase-0.1.2.tar.gz
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