Skip to main content

No project description provided

Project description

dbfrs

Minimalist DBF reader and writer for Python 3 written in Rust. The state of DBF libraries in 2024 is abysmal, yet still companies rely on this format. This library aims to provide a simple, easy-to-use interface for reading and writing DBF files.

Most libraries are either outdated, have a lot of dependencies, are too complex, or a really slow. Most of them offer only reading capabilities. The main focus of dbfrs is to be minimalistic and fast.

Installation

pip install dbfrs

Usage

Reading a file

import dbfrs
import pandas as pd

filename = 'file.dbf'

records = dbfrs.load_dbf(filename)

Reading a file into a DataFrame, only loading specific fields

import dbfrs
import pandas as pd

filename = 'file.dbf'

fields = dbfrs.get_dbf_fields(filename)
records = dbfrs.load_dbf(filename, fields)
df = pd.DataFrame(records, columns=fields)

Writing a DataFrame to a file

import dbfrs
import pandas as pd

filename = 'file.dbf'
df = pd.DataFrame({'field1': [1, 2, 3], 'field2': ['a', 'b', 'c']})

fields = dbfrs.Fields()
fields.add_numeric_field('field1', 'N', 10, 0)
fields.add_character_field('field2', 'C')

records = [tuple(x) for x in df.values.tolist()]

dbfrs.write_dbf(filename, fields, records)

Development

Building the Rust library

maturin build

Publish a new version

maturin publish

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dbfrs-0.1.3.tar.gz (8.8 kB view hashes)

Uploaded Source

Built Distribution

dbfrs-0.1.3-cp310-abi3-manylinux_2_34_x86_64.whl (356.9 kB view hashes)

Uploaded CPython 3.10+ manylinux: glibc 2.34+ x86-64

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page