Skip to content

Latest commit

 

History

History
65 lines (43 loc) · 2.44 KB

README.md

File metadata and controls

65 lines (43 loc) · 2.44 KB

Keops

Project Status: Active – The project has reached a stable, usable state and is being actively developed. CI

Keops logo

Keops is a CLI tool that allows you to apply some logic to vector tiles in a MBTiles file, such as removing or getting the size of a given tile, obtaining the vector layers that conform the MBTiles or shrinking the vector data, in order to reduce the data size.

Read the full documentation for more details: keops.franmartin.es.

Installation

Keops needs Python 3.7 or higher. The recommended way to install it is via pip.

pip install keops-vt

If you want to run the shrink command you also need Docker.

CLI Usage

The usage is pretty simple and straigthforward. For instance, if you want to drop a given tile in a MBTiles:

keops erase input.mbtiles 6/10/23

Keops have some more functionalities. To check them, simply execute keops or keops --help in your bash.

Usage: keops [OPTIONS] COMMAND [ARGS]...

  Keops command line interface

Options:
  --help  Show this message and exit.
 
Commands:
  debug   Debug a MBTiles file: get info related with layers and their
          features in a given MBTiles
  erase   Erase a tile in a MBTiles file
  info    Extract and print the metadata info from a MBTiles file
  shrink  Reduce and simplify all features of all or any vector tiles in a
          MBTiles container. Docker required.
  size    Get the size of a given tile or zoom level in a MBTiles file

Roadmap

If you are interested on the roadmap of the project, check the ROADMAP file.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Credits

The merit of the shrink module belongs entirely to rastapasta, as the unique developer of tileshrink, and ooZberg, as the person who wrapped it in a Docker image in order to use it without worrying about the Node.js version. What I have done is creating a backup of the Docker image and wrapping it again in this package, so it can be used in a focused environment.