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Gist 349fc7fda8932252cbcb4ee8a0b605c8

This example tracks the availability and licensing of the French IGN’s BD TOPO® departmental datasets by organizing URLs for both December 2021 and March 2021 releases. It shows a structured index of geographic data files, with each entry linking to a specific departmental Shapefile resource. The visualization uses a data-driven list format, likely rendered with JavaScript’s `fetch` to parse the provided CSV or JSON and display the sorted URLs. It highlights the variation in resource IDs across departments and time periods, emphasizing the dataset’s scope without mapping or spatial rendering.

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Generation GeoJSON des mairies avec code INSEE

This example generates a GeoJSON file of French town halls (mairies) with their INSEE commune codes, distinguishing principal towns from associated communes. It uses `ogr2ogr` with an SQLite dialect to join commune boundaries with their chief-town points from the IGN ADMIN-EXPRESS dataset, applying `PointOnSurface` as a fallback when no official point exists. The resulting output is written with RFC 7946 compliance for modern web mapping. The script downloads a 7z archive and extracts the necessary shapefiles before performing the spatial join.

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Code pour passer des id de parcelles Etalab en commune, prefixe, section, numero et inversement

This example demonstrates how to convert between French land parcel identifiers from the Etalab system and their constituent components: municipality code, prefix, section, and number. It shows the parsing of a composite key, such as `323190000A0133`, into its semantic parts, and the reverse operation to reconstruct the identifier. Implemented in both JavaScript and Python, the code uses basic string manipulation methods including `substring`, `replace` with a regular expression, `padStart`, and `zfill` for handling leading zeros. The JavaScript version runs directly in the console, while the Python version uses f-string formatting for output.

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Export DVF geolocalisées en Geoparquet

This example converts French land-registry transaction data (DVF) from compressed CSV files into a single spatially-indexed GeoParquet file. It downloads yearly datasets from data.gouv.fr, loads them into a DuckDB database, and creates a point geometry for each transaction before exporting with a Hilbert-curve spatial ordering. The script leverages DuckDB’s spatial extension, the `ST_Point` and `ST_Hilbert` functions, and parquet compression via zstd.

Gist 1f575522ca61946b31d92bbd146a9dce

This visualization compares French legislative electoral districts between 2012 and 2017, showing how commune boundaries and canton assignments shifted across the two years. It displays two side-by-side maps, likely using Three.js with WebGL rendering to animate or morph between the two configurations. The data comes from CSV files containing commune-to-canton and commune-to-district correspondences for both years. The visualization relies on the Vue framework to manage the interface and handle state transitions, with the geographic comparisons rendered through WebGL for smooth interactive exploration.

Lien Adresse et parcelles

This example shows the relationship between French addresses and land parcels, producing flat CSV files per department and for the whole country from the IGN BAN PLUS dataset. The workflow uses a bash pipeline combining Python with `xml.etree.ElementTree` to fix VRT files, GDAL’s `ogr2ogr` and `ogrinfo` for data conversion and indexing, `jq` to parse layer names, and `xsv` to concatenate departmental rows into a nationwide file. Results are gzip-compressed and organized into `france` and `departements` directories.

Gist 32329a8557135f11cb5656e3bfd4d35c

A WebGL map visualizes the locations of French tobacco shops, using points to show their distribution. The code geocodes addresses from an official customs dataset via the data.gouv.fr API, then processes the CSV with the `requests` library. It uses a Vue.js front-end to render the points in a 3D space, allowing users to explore the spatial patterns of the shops.

Copie données WFS depuis le géoportail de l'urbanisme

This example automates the bulk download of France’s urban planning WFS data from the Géoportail de l’Urbanisme, specifically extracting the GPKG files. It shows how to list available remote directories via `lftp` over SFTP, identify the latest dated export, and mirror the chosen folder with parallel transfers. The workflow uses shell commands with `timeout`, `ssh`, and `lftp` to handle authentication and file retrieval. It relies on public credentials and a documented PDF manual, making the process reproducible for users needing recent, structured land-use datasets.