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Mapshader

Test Suite Status PyPI version Downloads License

Simple Python GIS Web Services

  • Create mapshader.MapSource objects and render them as geojson, tiles, or images
  • This project should still be considered experimental
pip install mapshader

Setup Mapshader Conda Environment

conda create -n mapshader python=3.8
conda activate mapshader
git clone git@github.com:makepath/mapshader.git
cd mapshader
pip install -e .

Run Tests

conda activate mapshader
pytest mapshader/tests -sv

Run Flask Server

conda activate mapshader
mapshader serve

>>> * Serving Flask app "flask_app" (lazy loading)
>>> * Environment: production
>>>   WARNING: This is a development server. Do not use it in a production deployment.
>>>   Use a production WSGI server instead.
>>> * Debug mode: on
>>> * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
>>> * Restarting with stat

Mapshader Config (YAML)

While mapshader comes with default services to help with testing, users can create their own services via YAML.

my_services.yaml

---

metadata:
  version: 1

sources:
  - name: Global Elevation Example
    key: elevation-example
    text: Elevation
    description: Global elevation example
    geometry_type: raster
    shade_how: linear
    cmap:
      - white
      - black
    span:
      - 58
      - 248
    raster_padding: 0
    raster_interpolate: linear
    xfield: geometry
    yfield: geometry
    filepath: mapshader/tests/fixtures/elevation.tif
    transforms:
      - name: squeeze
        args:
          dim: band
      - name: cast
        args:
          dtype: float64
      - name: orient_array
      - name: flip_coords
        args:
          dim: y
      - name: reproject_raster
        args:
          epsg: 3857
    service_types:
      - tile

This configuration file can then be passed to the flask server upon startup:

conda activate mapshader
mapshader serve my_services.yaml

>>> * Serving Flask app "flask_app" (lazy loading)
>>> * Environment: production
>>>   WARNING: This is a development server. Do not use it in a production deployment.
>>>   Use a production WSGI server instead.
>>> * Debug mode: on
>>> * Running on http://0.0.0.0:5000/ (Press CTRL+C to quit)
>>> * Restarting with stat