Best GIS Software for Python

Compare the Top GIS Software that integrates with Python as of February 2026

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This a list of GIS software that integrates with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.

What is GIS Software for Python?

GIS (Geographic Information System) software is used to capture, store, analyze, and present spatial and geographic data. These tools allow users to map, visualize, and interpret complex data related to geography, helping to make decisions based on location-based insights. GIS software supports a wide range of industries, from urban planning and environmental management to transportation and utilities, by enabling the analysis of geographical patterns and relationships. Features often include data layering, spatial analysis, cartographic tools, and the ability to integrate with other systems for more comprehensive data analysis. GIS software is invaluable for planning, resource management, logistics, and location-based decision-making. Compare and read user reviews of the best GIS software for Python currently available using the table below. This list is updated regularly.

1

OpenCage Geocoding API

OpenCage

Hundreds of satisfied customers worldwide, tens of millions of requests per day. Here today, here tomorrow. Funded by customers, not VCs - since 2013. Redundant EU data centers, fully GDPR compliant. Independently monitored uptime All API requests via 256-bit SSL encryption (HTTPS). Responsive customer support. Ask us anything. Proud corporate member of the OpenStreetMap Foundation. Great product. Many open gecoders behind a single API. Most permissive licensing in the industry. Cache results as long as you like. No vendor lock-in, display results on ANY map. Worldwide coverage. Continual updates - OpenStreetMap has over four million edits/day. Avoid the stress and on-going costs of maintaining your own system Easy setup: Tutorials and SDKs for over 30 different programming languages. We add useful info like timezones, calling codes, FIPS codes, speed limits, currency, what3words, sunrise/sunset, etc to save you engineering time.

Starting Price: $50 per month

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2

Wherobots

Wherobots

Wherobots, the Spatial Intelligence Cloud, enables any data team to analyze data about the physical world faster, at greater scale, and at lower cost compared to traditional solutions. Built by the creators of Apache Sedona, it's a compute lakehouse engine that unifies spatial and non-spatial data, automates data workflows, and runs AI on planetary scale imagery. Spatial data refers to information about places, objects, or activities. Examples include GPS points and tracks, routes, land, road, parcel, crop, and building data, as well as imagery from drones and satellites. This data is fundamental to various industries including aerospace, mobility, ag-tech, insurance, energy, telecommunications, retail, and logistics. In one solution, Wherobots handles these diverse spatial data types and formats, with customers seeing production workloads run up to 20x faster and at lower cost than popular lakehouse engines.

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3

GRASS GIS

GRASS

GRASS GIS (Geographic Resources Analysis Support System) is a free and open-source Geographic Information System (GIS) software suite utilized for geospatial data management and analysis, image processing, graphics and map production, spatial modeling, and visualization. It supports raster, vector, and geospatial processing, enabling advanced modeling, data management, imagery processing, and time series analysis with a Python API, optimized for large-scale analysis. GRASS GIS is compatible with multiple operating systems, including OS X, Windows, and Linux, and can be accessed through a graphical user interface or integrated with other software such as QGIS. The software includes over 350 modules for rendering maps and images, manipulating raster and vector data, processing multispectral image data, and creating, managing, and storing spatial data. GRASS GIS is widely used in academic and commercial settings, as well as by governmental agencies.

Starting Price: Free

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4

Google Earth Engine

Google

Google Earth Engine is a cloud-based platform for scientific analysis and visualization of geospatial datasets, providing access to a vast public data archive that includes over 90 petabytes of analysis-ready satellite imagery and more than 1,000 curated geospatial datasets. This extensive catalog encompasses over 50 years of historical imagery, updated daily, with resolutions as fine as one meter per pixel, featuring datasets such as Landsat, MODIS, Sentinel, and the National Agriculture Imagery Program (NAIP). Earth Engine enables users to analyze Earth observation data and apply machine learning techniques through its web-based JavaScript Code Editor and Python API, facilitating the development of complex geospatial workflows. The platform's integration with Google Cloud allows for large-scale parallel processing, empowering users to conduct comprehensive analyses and visualize Earth data efficiently. Additionally, Earth Engine offers interoperability with BigQuery.

Starting Price: $500 per month

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5

Carmenta

Carmenta

Carmenta provides a powerful geospatial software development kit (SDK) and related tools that enable creation of advanced applications for real-time visualization and analysis of geospatial information across air, sea, and land environments. The core SDK, Carmenta Engine, supports high-performance rendering of 2D and 3D maps with live dynamic data like video streams and radar plots, and offers advanced analytics such as line-of-sight, terrain analysis, and tactical overlays, while running on Windows, Linux, and Android with APIs for C++, .NET, Java, and Python. Carmenta Server is a scalable web map server backend that reads and serves more than 100 geospatial data formats through open standards, supports spatial analysis, and can deploy on-premises, in the cloud, or in container environments for interactive web services. The technology emphasizes flexibility, interoperability, and integration into mission-critical systems with open standards support and cross-platform capabilities.

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