GataFrame

GataFrame is a lightweight Python library built around DuckDB relations. It adds a dataframe-style wrapper plus file and database read-write helpers for tabular and geospatial workflows.

The PyPI distribution is named ga-gataframe; the import package is named gataframe.

Installation

python -m pip install ga-gataframe

Development and test tools are available as extras:

python -m pip install -e ".[test]"
python -m pip install -e ".[dev]"

Optional parallel cleanup helpers are available with:

python -m pip install -e ".[parallel]"

Quick Start

import pandas as pd

from gataframe import connect

engine = connect(extensions=None)

gf = engine.read(pd.DataFrame({"id": [1, 2], "value": [10, 20]}))
result = gf.withColumn("double_value", "value * 2").filter("double_value > 20").toPandas()

assert result["double_value"].tolist() == [40]

engine.close()

GataFrame

GataFrame wraps a duckdb.DuckDBPyRelation and keeps operations chainable. Most methods return a new GataFrame unless inplace=True is passed.

import pandas as pd

from gataframe import connect

engine = connect(extensions=None)
gf = engine.read(pd.DataFrame({"a": [1, 2], "b": [3, 4]}))

out = (
    gf.withColumn("total", "a + b")
    .renameColumn("total", "sum_ab")
    .replaceColumn("sum_ab", "sum_ab * 10")
    .select("a", "sum_ab")
)

assert out.columns == ["a", "sum_ab"]

Common methods include:

• withColumn(name, expression) and replaceColumn(name, expression)
• renameColumn(old, new) and excludeColumn(*columns)
• select(*columns), filter(expression), and limit(n)
• createTable(...), createView(...), dropTable(...), and dropView(...)
• toPandas(), toGeoPandas(...), and toPandasOrGeoPandas(...)

Engine

Engine owns the DuckDB connection and handles input/output.

from gataframe import connect

engine = connect(extensions=None, file_based=False)

gf = engine.read("data.csv", header=True)
engine.write(gf, "out.parquet", mode="overwrite")

engine.close()

Supported readers and writers are inferred from file extensions where possible: CSV, JSON, Parquet, GeoParquet, GeoJSON, GeoPackage, Shapefile, SQLite, and PostgreSQL connection URLs.

DuckDB extensions are loaded only when requested by the caller or needed by a specific geospatial/database operation.

API Summary

• connect(logger=None, extensions=None, options=None, file_based=False, file=None)
• read(engine, source, format=None, pre_limit=None, limit=None, ...)
• write(engine, df, destination, mode="overwrite", partitionBy=None, ...)
• Engine.connect(...)
• Engine.read(source, format=None, ...)
• Engine.write(df, destination, mode="overwrite", ...)
• GataFrame.withColumn(...), replaceColumn(...), renameColumn(...)
• GataFrame.select(...), filter(...), limit(...), union(...)
• GataFrame.toPandas(), toGeoPandas(...), and toPandasOrGeoPandas(...)

Development

GataFrame supports Python 3.10 and newer.

python -m pip install -e ".[dev]"
python -m compileall -q src
python -m pytest --cov=gataframe --cov-report=term-missing
ruff format --check .
ruff check .
mypy
python -m pip check
python -m build
python -m twine check dist/*

GitHub Repository Setup

This project is prepared for the future repository andreagemma/gataframe.

1. Create the empty repository on GitHub.
2. Initialize the local repository if needed and push the project to main.
3. Confirm the CI workflow passes on GitHub.
4. Configure the PyPI Trusted Publisher for project ga-gataframe, owner andreagemma, repository gataframe, workflow release.yml, and environment pypi.

Releases

src/gataframe/_version.py is the only version source. To publish a release:

1. Update __version__ in _version.py and commit the release changes.
2. Push main and wait for CI to pass.
3. Run the Create release GitHub Actions workflow. With no override it creates the v<version> tag, creates release notes, and dispatches the build and PyPI publication workflow.

PyPI versions are immutable. Increment _version.py before publishing different content.

License

GataFrame is distributed under the MIT License. See LICENSE.