Skip to content

Latest commit

 

History

History
107 lines (76 loc) · 4.99 KB

README.md

File metadata and controls

107 lines (76 loc) · 4.99 KB
Raw

Build Status Coverage Status

django-osgeo-importer

osgeo-importer is a Django application that helps you create custom pipelines for uploading geospatial data. It's goal is to provide a highly extensible, easily testable and reusable framework for importing data into geospatial applications.

Installation

pip install git+https://github.com/GeoNode/django-osgeo-importer.git

Supported geodata formats

  • Shapefile
  • KML
  • GeoJSON
  • GeoTIFF
  • GeoPackage
  • CSV
  • NITF

These formats are officially supported, meaning that we make a public commitment to maintain support for them, including testing and maintenance to ensure they keep working. In particular, we will not make any changes to dependencies (like supported GDAL versions) which endangers support for these officially supported formats.

Settings

  • OSGEO_IMPORTER: The default Importer to use for uploads.
  • OSGEO_INSPECTOR: The default Inspector to use for uploads.
  • OSGEO_IMPORTER_GEONODE_ENABLED: If True, the osgeo_importer will expose the GeoNode-flavored APIs vs a vanilla API.
  • IMPORT_HANDLERS: A list of handlers that each layer is passed through during the import process. Changing this setting allows complete customization – even replacement – of the osgeo-importer import process.

Running test cases.

docker-compose up --build
docker exec -it djangoosgeoimporter_django_1 python manage.py test osgeo_importer

Frontend

The Django app comes with an Angular-based wizard. If you are just using the Django app, you do not need to do anything special for the frontend and you can ignore this section.

However, if you are interested in making changes to the frontend, the frontend dependencies can be managed using npm via a package.json file, and the most common tasks are automated via make (using a Makefile).

For example, if you want to regenerate the static files for the frontend, then you can change to the directory osgeo_importer/static/osgeo_importer and then just run make.

If you want to upgrade versions of anything, you can edit package.json to specify the desired updates, then run make clean; make. If any files are changed, it is up to you to commit them into the git repo if you want them to be used "out of the box."

To watch files for changes and run the tests, you can run ./node_modules/karma/bin/karma start.

Concepts

The import process starts with an extensible Angular-based wizard that allows the user to upload a file and provide configuration options. Once the user starts the import, the configuration options are passed to an Importer which will read the incoming geospatial data and load it into a target data store (ie: PostGIS). Once the data has been successfully loaded, the Importer will execute a series of "handlers" that process the data for use in your application.

Inspectors

Inspectors are Python classes that are responsible for reading incoming geospatial datasets. Custom inspectors should implement the methods exposed in the InspectorMixin.

GDALInspector

Uses the GDAL library to read geospatial data.

GDALInspector settings:

IMPORT_CSV_X_FIELDS : List of fields passed in as the X_POSSIBLE_NAMES open options to the CSV Driver. IMPORT_CSV_Y_FIELDS : List of fields passed in as the Y_POSSIBLE_NAMES open options to the CSV Driver. IMPORT_CSV_GEOM_FIELDS : List of fields passed in as the GEOM_POSSIBLE_NAMES open options to the CSV Driver.

OGRInspector

Uses the OGR library to read geospatial data.

Handlers

Handlers are Python classes which are executed in order by the Importer after the import process has succeeded. The response from the Importer's import method is sent to each handler which includes the configuration options provided at upload.

Importers

Importers are Python classes that are responsible for opening incoming geospatial datasets (using one or many inspectors) and copying features to a target location - typically a PostGIS database.

Adding Support for Additional EPSG Codes

If you have data sets with projections that are not currently supported by the EPSG codes in the Pyproj data directory, you can add additional EPSG codes. Inside the scripts folder there is a file called epsg_extra with some examples of additional EPSG codes that we've added. You can add any additional EPSG code with it's corresponding projection in that file using the same format as our examples.

You'll need to copy that file to your Pyproj data directory, which by default is /usr/local/lib/python2.7/dist-packages/pyproj/data. If your Pyproj data directory is in a different location, you may need to add the PROJECTION_SETTINGS settings variable in your own Django settings with the directory that you're using.