geoarrow-c

library0.3.1pypypi✓ verified 91d ago

geoarrow-c provides Python bindings to the GeoArrow C and C++ implementation, enabling a geospatial type system and generic coordinate-shuffling. It supports Well-Known Binary (WKB), Well-Known Text (ISO), and GeoArrow encodings as Arrow extension types. The library is currently at version 0.3.1 and primarily serves as a low-level dependency for higher-level Python libraries like `geoarrow-python`. Its release cadence follows updates to the GeoArrow specification and its underlying C/C++ implementation.

data serialization

pip install geoarrow-c

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · GEOARROW-C

geoarrow-c

datapythonv0.3.1

Install

1.6s avg

Import

12ms

Disk

24MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.3.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.013s · 26.7MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 1.6s · import 0.011s · 25MB

24MB installed

● package 24MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

lib

✓ from geoarrow.c import lib

✗ import geoarrow.c as gc

The core C functions are exposed under the 'lib' submodule within 'geoarrow.c'.

geoarrow.c

✓ import geoarrow.c

While `import geoarrow.c` is correct, direct usage of its low-level interface is generally not recommended for most high-level geospatial tasks. Users should typically prefer `geoarrow.pyarrow`.

This quickstart demonstrates the recommended way to interact with GeoArrow data in Python using `geoarrow-pyarrow`, which leverages `geoarrow-c` internally. It includes a basic example of reading GeoArrow-encoded data. It also shows a minimal direct import of `geoarrow.c.lib` for low-level access, which is generally not needed by most users.

import geoarrow.pyarrow as ga import pyarrow as pa import urllib.request import os # Most users should interact with GeoArrow via geoarrow-pyarrow for higher-level operations. # geoarrow-c works under the hood of geoarrow-pyarrow. # Example: Reading a GeoArrow-enabled IPC file using geoarrow.pyarrow # This requires geoarrow-pyarrow and pyarrow, which internally use geoarrow-c. # Replace with a real URL or local path if needed. url = os.environ.get('GEOARROW_SAMPLE_DATA_URL', 'https://raw.githubusercontent.com/geoarrow/geoarrow-data/v0.2.0/natural-earth/files/natural-earth_cities_wkb.arrows') try: with urllib.request.urlopen(url) as f, pa.ipc.open_stream(f) as reader: table = reader.read_all() print("Successfully read GeoArrow data via geoarrow.pyarrow.") print(table.schema.field("geometry").type) except Exception as e: print(f"Could not fetch or read sample data: {e}") print("Ensure geoarrow-pyarrow and pyarrow are installed and the URL is accessible.") # For direct, low-level interaction with geoarrow.c (less common for end-users): from geoarrow.c import lib print(f"geoarrow.c library loaded: {lib.__name__}") # Further usage of `lib` involves Arrow C Data interface specifics, often via ctypes.

Debug

Known issues

gotchaDirect usage of `geoarrow-c` for high-level geospatial operations is generally discouraged. Its primary role is as a low-level binding for the C/C++ GeoArrow implementation. For most Python users, `geoarrow-pyarrow` (from the `geoarrow-python` package) offers a much more ergonomic and feature-rich interface for working with GeoArrow data, including integrations with `pyarrow`, `pandas`, and `geopandas`.

fix

Prefer `pip install geoarrow-pyarrow` and `import geoarrow.pyarrow as ga` for most use cases.

affects: >=0.1.0

breakingThe GeoArrow specification itself has undergone revisions (e.g., from v0.1 to v0.2). These updates introduced new array types (Box, Geometry, Geometry Collection), updated Coordinate Reference System (CRS) definitions, and support for binary view/string view storage types for WKT/WKB. While `geoarrow-c` aims to support these, changes in the specification might implicitly affect how data is interpreted or structured across different versions, especially when exchanging data with tools built on older spec versions.

fix

Ensure all GeoArrow-related libraries in your ecosystem (e.g., `geoarrow-python`, `geoarrow-c`) are updated to versions that support the same GeoArrow specification (preferably 0.2 or newer) to ensure compatibility and correct interpretation of data structures and metadata. Refer to the GeoArrow specification changelog.

affects: <0.3.0

gotchaWhen building `geoarrow-c` from source, particularly in development environments, ensure that `nanoarrow` and other C dependencies are correctly handled. The library utilizes amalgamated C/C++ files for distribution, but direct compilation might require specific CMake configurations.

fix

For standard installation, use `pip install geoarrow-c` to leverage pre-built wheels. For development builds, consult the `geoarrow-c` GitHub repository's build instructions and ensure all submodules and dependencies are correctly fetched and configured with CMake. The internal vendored copies of geoarrow-c and nanoarrow are updated in `geoarrow 0.4.0`.

affects: >=0.1.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'geoarrow.c'

The `geoarrow-c` package is not installed in the current Python environment.

fix

Run `pip install geoarrow-c`.

AttributeError: module 'geoarrow.c' has no attribute 'some_high_level_function'

Attempting to use `geoarrow.c` for high-level geospatial operations, which are typically found in `geoarrow-pyarrow`.

fix

Install `geoarrow-pyarrow` (`pip install geoarrow-pyarrow`) and use `import geoarrow.pyarrow as ga` for operations like reading GeoParquet, converting to GeoPandas, or performing computations.

Segmentation fault (core dumped) or other memory errors when manipulating ArrowArrays directly with `geoarrow.c.lib`.

Incorrect handling of Arrow C Data interface structures (e.g., `ArrowArray`, `ArrowSchema`) when interacting with `geoarrow.c.lib`, often due to misuse of pointers, incorrect buffer sizes, or memory lifetimes.

fix

Direct interaction with `geoarrow.c.lib` requires a deep understanding of the Arrow C Data interface. It is highly recommended to use higher-level Python libraries like `pyarrow` and `geoarrow-pyarrow` that safely manage these low-level details. If direct interaction is unavoidable, meticulously follow the Arrow C Data interface specification and `geoarrow-c`'s C/C++ examples for correct memory management.

Upgrade

Version history

0.3.1latest on PyPI · released Oct 10, 2025

Audit

Dependencies

geoarrow-pythonrequiredgeoarrow-c is primarily intended as a dependency for higher-level GeoArrow Python bindings like `geoarrow-pyarrow` which offer a more user-friendly interface for common geospatial operations.

pyarrowrequiredDirect usage of geoarrow-c often involves interacting with the Arrow C Data interface, making `pyarrow` a practical dependency for creating and consuming Arrow arrays in Python.

Agent activity

6 hits · last 30 days

node

Resources

githubhttps://github.com/geoarrow/geoarrow-c ↗

packagehttps://pypi.org/project/geoarrow-c/ ↗

homepagehttps://geoarrow.org ↗