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The HDX Scraper Geonode Library enables easy building of scrapers for extracting data from geonode servers.

Usage

The library has detailed API documentation which can be found here: http://ocha-dap.github.io/hdx-scraper-geonode/. The code for the library is here: https://github.com/ocha-dap/hdx-scraper-geonode.

Breaking Changes

1.4.0 supports only Python 3.6 and later

GeoNodeToHDX Class

You should create an object of the GeoNodeToHDX class:

geonodetohdx = GeoNodeToHDX('https://geonode.wfp.org', downloader)
geonodetohdx = GeoNodeToHDX('https://geonode.themimu.info', downloader)

It has high level methods generate_datasets_and_showcases and delete_other_datasets:

# generate datasets and showcases reading country and layer information from the GeoNode
datasets = generate_datasets_and_showcases('maintainerid', 'orgid', 'orgname', updatefreq='Adhoc', 
                                           subnational=True)
# generate datasets and showcases reading layer information ignoring region (country) in layers call
countrydata = {'iso3': 'MMR', 'name': 'Myanmar', 'layers': None}
datasets = generate_datasets_and_showcases('maintainerid', 'orgid', 'orgname', updatefreq='Adhoc', 
                                           subnational=True, countrydata=countrydata)
# delete any datasets and associated showcases from HDX that are not in the list datasets
# (assuming matching organisation id, maintainer id and geonode url in the resource url)
delete_other_datasets(datasets)

If you need more fine grained control, it has low level methods get_locationsdata, get_layersdata, generate_dataset_and_showcase:

# get countries where count > 0
countries = geonodetohdx.get_countries(use_count=True)
# get layers for country with ISO 3 code SDN
layers = geonodetohdx.get_layers(countryiso='SDN')
# get layers for all countries
layers = get_layers(countryiso=None)

There are default terms to be ignored and mapped. These can be overridden by creating a YAML configuration with the new configuration in this format:

ignore_data:
  - deprecated

category_mapping:
  Elevation: 'elevation - topography - altitude'
  'Inland Waters': river

titleabstract_mapping:
  bridges:
    - bridges
    - transportation
    - 'facilities and infrastructure'
  idp:
    camp:
      - 'displaced persons locations - camps - shelters'
      - 'internally displaced persons - idp'
    else:
      - 'internally displaced persons - idp'

ignore_data are any terms in the abstract that mean that the dataset should not be added to HDX.

category_mapping are mappings from the category field category__gn_description to HDX metadata tags.

titleabstract_mapping are mappings from terms in the title or abstract to HDX metadata tags.

For more fine grained tuning of these, you retrieve the dictionaries and manipulate them directly:

geonodetohdx = GeoNodeToHDX('https://geonode.wfp.org', downloader)
ignore_data = geonodetohdx.get_ignore_data() 
category_mapping = geonodetohdx.get_category_mapping() 
titleabstract_mapping = geonodetohdx.get_titleabstract_mapping()

Project links

Key dates

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  • Released:
Newer release available (1.5.9)

1 maintainer

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Avatar for mcarans from gravatar.com mcarans

Credits

Author: Michael Rans

License

MIT License (MIT)

Tags

HDX scraper geonode

Classifiers

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