Getting Started with FloppyGIS — Install, Load, VisualizeFloppyGIS is a lightweight, command-line-driven geographic information system developed to make basic spatial data processing accessible, scriptable, and efficient. Designed for users who prefer a minimal dependency stack and reproducible workflows, FloppyGIS focuses on common tasks such as reprojection, clipping, attribute filtering, and simple raster/vector manipulations. This guide walks through installation, loading common data types, and visualizing results — with practical examples and troubleshooting tips so you can get productive quickly.
What is FloppyGIS and when to use it
FloppyGIS is best thought of as a set of small, composable tools that perform focused spatial operations without the overhead of full desktop GIS applications. It’s ideal when you need:
- Fast command-line processing for automation and scripting.
- Low-dependency setups for servers or containers.
- Reproducible spatial workflows in batch jobs or CI pipelines.
- Educational purposes to learn the core operations behind GIS tools.
FloppyGIS typically handles vector formats like Shapefile, GeoJSON, and OGR-supported formats, as well as raster inputs via GDAL where applicable. It emphasizes straightforward transformation and export of spatial data.
Prerequisites
Before installing FloppyGIS, make sure your system meets these minimal requirements:
- A POSIX-compatible shell (Linux, macOS; Windows via WSL or Git Bash recommended).
- Python 3.7+ (if using Python-based installation or scripts).
- GDAL/OGR installed system-wide for broader format support (recommended).
- Basic familiarity with the terminal and command-line tools.
Installation
There are multiple ways to install FloppyGIS depending on your environment: package manager, pip (if available), or from source. Below are common methods.
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Install via pip (if package is published)
python -m pip install floppy-gis -
Install from source (GitHub)
git clone https://github.com/<username>/floppygis.git cd floppygis python -m pip install -e . -
Use a Docker container (recommended for isolation)
docker pull ghcr.io/<username>/floppygis:latest docker run --rm -it -v "$(pwd)":/work ghcr.io/<username>/floppygis:latest /bin/sh
If FloppyGIS depends on GDAL, ensure GDAL is available before installing. On Ubuntu:
sudo apt-get update sudo apt-get install -y gdal-bin libgdal-dev On macOS with Homebrew:
brew install gdal Confirming installation
After installing, verify the command-line tool is available:
floppygis --version You should see a version string or help output. If not, confirm your PATH or Python environment.
Loading vector data
FloppyGIS primarily works with vector data via simple command invocations or small Python wrappers. Example commands below assume the floppygis executable is available.
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Inspecting a vector file:
floppygis info data/countries.geojsonThis prints basic metadata: geometry types, CRS, feature count, and attribute fields.
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Converting formats:
floppygis convert data/countries.geojson data/countries.shp -
Reprojecting:
floppygis reproject data/countries.geojson data/countries_3857.geojson --to-crs EPSG:3857 -
Attribute filtering (SQL-like):
floppygis filter data/countries.geojson data/europe.geojson "continent = 'Europe'" -
Spatial clipping:
floppygis clip data/landuse.shp data/bbox.geojson data/landuse_clip.shp
For workflows embedded in Python scripts, FloppyGIS may expose a small API:
from floppygis import Vector v = Vector("data/countries.geojson") print(v.crs) europe = v.filter("continent = 'Europe'") europe.to_file("data/europe.geojson") Loading raster data
When FloppyGIS integrates with GDAL it can run basic raster operations: inspecting, resampling, reprojection, and clipping.
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Inspecting raster metadata:
floppygis raster-info data/elevation.tif -
Reprojecting a raster:
floppygis raster-reproject data/elevation.tif data/elevation_3857.tif --to-crs EPSG:3857 -
Resampling:
floppygis raster-resample data/elevation.tif data/elevation_lowres.tif --resolution 100 -
Raster clipping with a vector mask:
floppygis raster-clip data/elevation.tif data/mask.geojson data/elevation_clip.tif
Visualizing results
FloppyGIS focuses on processing rather than heavy visualization, but it includes lightweight viewers and can export data to formats compatible with full-featured visualization tools.
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Quick map (terminal-based preview or simple HTML):
floppygis quickview data/europe.geojsonThis may open a simple browser-based map or generate an HTML file in the working directory.
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Export to GeoJSON/TopoJSON for web mapping:
floppygis convert data/europe.shp data/europe.geojson floppygis toposimplify data/europe.geojson data/europe.topojson --tolerance 0.01 -
Use QGIS or other desktop GIS for richer visualization:
qgis data/europe.geojson -
Python plotting with geopandas/matplotlib:
import geopandas as gpd gdf = gpd.read_file("data/europe.geojson") gdf.plot(column="population", cmap="viridis", legend=True)
Example workflow: Clip, filter, and visualize a region
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Reproject base layers to a common CRS:
floppygis reproject data/countries.geojson data/countries_4326.geojson --to-crs EPSG:4326 floppygis reproject data/landuse.shp data/landuse_4326.shp --to-crs EPSG:4326 -
Filter for a specific country and clip landuse:
floppygis filter data/countries_4326.geojson data/country.geojson "name = 'France'" floppygis clip data/landuse_4326.shp data/country.geojson data/landuse_france.shp -
Convert to GeoJSON and quickview:
floppygis convert data/landuse_france.shp data/landuse_france.geojson floppygis quickview data/landuse_france.geojson
Tips and troubleshooting
- If format support seems limited, ensure GDAL/OGR are installed and FloppyGIS was built with GDAL support.
- CRS mismatches cause many errors; reproject datasets to the same EPSG code before spatial operations.
- For large datasets, use GDAL-native formats (GeoPackage, tiled GeoTIFF) to improve speed.
- Use verbose/debug flags to get detailed error messages (e.g., –verbose).
Alternatives and complementing tools
FloppyGIS fills a niche for lightweight, scriptable GIS. If you need richer GUI features, advanced spatial analysis, or machine learning integration, consider complementing FloppyGIS with:
- QGIS for desktop visualization and advanced analysis.
- GDAL/OGR utilities for extensive raster/vector processing.
- Python stack: geopandas, rasterio, shapely, pyproj for programmatic workflows.
FloppyGIS offers a compact, script-first approach to GIS tasks: install, confirm dependencies (GDAL), use command-line commands to load, transform, and export data, and leverage simple viewers or external tools for visualization. With these basics you can build reproducible spatial workflows suitable for automation and server-side processing.
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