[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f30me9q9ye63kh":3},{"code":4,"message":5,"data":6,"timestamp":31},10000,"success",{"full_name":7,"position":8,"description":9,"language":10,"stars":11,"forks":12,"stars_gained":13,"age_days":14,"hn_threads":15,"one_liner":16,"summary_md":17,"topic":18,"github_topics":21,"license":27,"homepage":28,"updated_at":29,"history":30},"opengeos\u002FRustGIS",7,"A fast, free and open-source GIS in pure Rust.","Rust",1914,273,137,14,[],"A desktop and browser GIS for mapping, analyzing and exporting geospatial data, with scriptable CLI and Python access.","RustGIS is worth a look if you work with vector geospatial files and want a QGIS-like desktop experience without a heavy install, or you want the same map operations available from a script. Treat it as a young project: the dated history here covers a single day, so staying power is unknown.\n\n## The problem\n\nSomeone with a folder of Shapefiles, GeoJSON, GeoPackages or CSV coordinates wants to open them on a map, style and join them, run a buffer or point-in-polygon count, and export a finished image or dataset. Normally that means either installing a large desktop GIS, or writing a chain of command-line and Python tools that each handle one format. RustGIS replaces that with one application where opening, styling and geoprocessing share a canvas and the same operations are exposed as named commands. The output is a styled map, an exported PNG or converted data, plus a project file you can reopen.\n\n## What's different\n\nThe distinguishing mechanism is that every ribbon action is a command with an id, so the GUI, `rustgis-cli` and the `rustgis` Python package drive the same engine. You can render a map, run geoprocessing, apply graduated symbology and export at high DPI from one CLI call, or run the same steps in a notebook and hand the layer to GeoPandas. The CLI can also run as an MCP server, letting an AI agent invoke those commands. The desktop app bundles its own formats, while GDAL and DuckDB are used through their programs only when installed, which widens coverage without making them hard dependencies.\n\nThe trade-off is that scripting buys reproducibility only if you keep the command ids and parameters stable in your own workflows; the GUI and script paths share a command vocabulary you will need to learn from the [CLI guide](https:\u002F\u002Fgithub.com\u002Fopengeos\u002FRustGIS\u002Fblob\u002Fmain\u002Fdocs\u002Fcli.md). The README also states the project is primarily built with an AI model under human direction and review, and asks users to check results and report problems, so analysis outputs deserve spot checks against a second tool for now.\n\n## Who should try it\n\nA good fit is a desktop GIS user who wants to open zipped Shapefiles, LiDAR point clouds, PostGIS tables or QGIS projects, do light geoprocessing, and script the same steps later. It also suits a Python analyst who wants a map image from a buffer operation without assembling several libraries. A poor fit is someone who needs the full plugin ecosystem and long-established cartographic tooling of a mature desktop GIS, or whose workflow depends on formats only reachable through GDAL being guaranteed rather than optional. Browser users get a no-install path at [web.rustgis.app](https:\u002F\u002Fweb.rustgis.app), but the README notes that live database tables and Esri File Geodatabases are desktop-only.\n\n## Requirements and limitations\n\nFor desktop use you download the app for Windows, macOS or Linux or install it from the Microsoft Store; see the [installation notes](https:\u002F\u002Fgithub.com\u002Fopengeos\u002FRustGIS\u002Fblob\u002Fmain\u002Fdocs\u002Finstallation.md). Across every path, full format coverage depends on optional external programs: GDAL-backed vector formats and DuckDB SQL need those installed, and live PostGIS, MySQL, MariaDB and SQL Server tables are desktop-only. In the browser, files go through the browser picker and saves become downloads, so large local datasets are less convenient. The Python package and the MCP server need their own setup.\n\n## HotRepo's take\n\nHotRepo first records RustGIS on 2026-10-24, when it appeared at #7 on the NEW-REPOSITORY board (新项目榜) for Rust with 1,914 total stars; that is a dated snapshot, not a daily gain, and no comparable daily history exists. Persistence therefore cannot be judged. Before committing a workflow, verify that the command ids your scripts depend on are documented and stable in the CLI guide.",{"slug":19,"name":20},"data","Data",[22,23,24,25,26],"geospatial","gis","remote-sensing","rust","rust-lang","Apache-2.0","https:\u002F\u002Frustgis.app","2026-10-25T03:22:34Z",[],1792917483]