A command-line interface (CLI) for working with Vecorel files.
In order to make working with Vecorel easier we have developed command-line interface (CLI) tools such as inspection, validation and file format conversions.
This project uses Pixi for dependency management. Install Pixi first, then:
# Clone the repository and navigate to it
git clone https://github.com/vecorel/cli.git
cd cli
# Install all dependencies
pixi install
# Run the CLI
pixi run vecAlternatively, you can install from PyPI with Python 3.10 or any later version:
pip install vecorel-cliAfter the installation you should be able to run the following command: vec (or pixi run vec if using Pixi)
You should see usage instructions and available commands for the CLI.
Vecorel CLI supports various commands to work with the files:
- Vecorel CLI
- Getting Started
- Commands
- Validation
- Create Vecorel GeoParquet from GeoJSON
- Create Vecorel GeoJSON from GeoParquet
- Inspect Vecorel GeoParquet file
- Merge Vecorel GeoParquet files
- Create JSON Schema from Vecorel Schema
- Validate a Vecorel Schema
- Improve a Vecorel Parquet file
- Update an extension template with new names
- Converter for existing datasets
- Development
To validate a Vecorel GeoParquet or GeoJSON file, you can for example run:
- GeoJSON:
vec validate example.json --collection collection.json - GeoParquet:
vec validate example.parquet --data
Check vec validate --help for more details.
The validator also supports remote files.
http://orhttps://: no further configuration is needed.s3://: With Pixi, runpixi install -e s3or with pip, runpip install vecorel-cli[s3]and you may need to set environment variables. Refer to the s3fs credentials documentation for how to define credentials.gs://: With Pixi, runpixi install -e gcsor with pip, runpip install vecorel-cli[gcs]. By default,gcsfswill attempt to use your default gcloud credentials or, attempt to get credentials from the google metadata service, or fall back to anonymous access.
To create a Vecorel-compliant GeoParquet for a Vecorel-compliant set of GeoJSON files containing Features or FeatureCollections, you can for example run:
vec create-geoparquet geojson/example.json -o example.parquet -c geojson/collection.json
Check vec create-geoparquet --help for more details.
To create one or multiple Vecorel-compliant GeoJSON file(s) for a Vecorel-compliant GeoParquet file, you can for example run:
-
GeoJSON FeatureCollection:
vec create-geojson example.parquet -o dest-folder -
GeoJSON Features (with indentation and max. 100 features):
vec create-geojson example.parquet -o dest-folder -n 100 -i 2 -fvec create-geojson example.parquet -o dest-folder -n 100 -i 2 -f
Check vec create-geojson --help for more details.
To look into a Vecorel GeoParquet file to get a rough understanding of the content, the following can be executed:
vec describe example.parquet
Check vec describe --help for more details.
Merges multiple Vecorel datasets to a combined Vecorel dataset:
vec merge ec_ee.parquet ec_lv.parquet -o merged.parquet -e https://vecorel.org/hcat-extension/v0.1.0/schema.yaml -i ec:hcat_name -i ec:hcat_code -i ec:translated_name
Check vec merge --help for more details.
To create a JSON Schema for a Vecorel Schema YAML file, you can for example run:
vec jsonschema example.json --id=https://vecorel.org/specification/v0.1.0/geojson/schema.json -o schema.json
Check vec jsonschema --help for more details.
To validate a Vecorel Schema YAML file, you can for example run:
vec validate-schema schema/schema.yaml
Check vec validate-schema --help for more details.
Various "improvements" can be applied to a Vecorel GeoParquet file. The commands allows to
- change the CRS (
--crs) - change the GeoParquet version (
-gp1) and compression (-pc) - add/fill missing perimeter/area values (
-sz) - fix invalid geometries (
-g) - rename columns (
-r)
Example:
vec improve file.parquet -o file2.parquet -g -sz -r old=new -pc zstd
Check vec improve --help for more details.
Once you've created and git cloned a new extension, you can use the CLI to update all template placeholders with proper names.
For example, if your extension is meant to have
- the title "Administrative Division Extension",
- the prefix
admin(e.g. fieldadmin:country_codeoradmin:subdivision_code), - is hosted at
https://github.io/vecorel/administrative-division-extension(organization:vecorel, repository/administrative-division-extension), - and you run Vecorel in the folder of the extension.
Then the following command could be used:
vec rename-extension . -t "Administrative Division" -p admin -s administrative-division-extension -o vecorel
Check vec rename-extension --help for more details.
The CLI ships various converters for existing datasets.
To get a list of available converters/datasets with title, license, etc. run:
vec converters
Use any of the IDs from the list to convert an existing dataset to Vecorel:
vec convert de_nrw
See Implement a converter for details about how to
This project uses Pixi for dependency management and development workflows.
# Install all dependencies including development tools
pixi install -e dev
# Install the package in editable mode
pixi run install-dev
# Run tests
pixi run test
# Format and lint code
pixi run format
pixi run lint
# Run all checks (lint, format, test)
pixi run check
# Install and run pre-commit
pixi run pre-commit-install
pixi run pre-commit-runThe following high-level description gives an idea how to implement a converter in Vecorel CLI:
- Create a new file in
vecorel_cli/datasetsbased on thetemplate.py - Fill in the required variables / test it / run it
- Add missing dependencies into the appropriate feature group in
pixi.toml(orsetup.pyfor pip users) - Add the converter to the list above
- Create a PR to submit your converter for review