# Demonstrates the use of the self-documentation resource 'taxonomies' of the expert.ai (Cloud based) Natural Language API
from expertai.nlapi.cloud.client import ExpertAiClient
client = ExpertAiClient()
output = client.taxonomies()
print("Taxonomies:\n")
for taxonomy in output.taxonomies:
print(taxonomy.name)
print("\tLanguages:")
for language in taxonomy.languages:
print("\t\t{0}".format(language.code))
def test_a_taxonomies_request_is_executed(self):
"""
...then verify that whole flow works as expected
"""
response_json = {
"success":
True,
"taxonomies": [{
"description":
"The iptc document classification resource classifies texts based on the IPTC Media Topics taxonomy",
"languages": [{
"code": "en",
"name": "English"
}, {
"code": "es",
"name": "Spanish"
}, {
"code": "fr",
"name": "French"
}, {
"code": "de",
"name": "German"
}, {
"code": "it",
"name": "Italian"
}],
"name":
"iptc"
}, {
"contract":
"https://github.com/therealexpertai/nlapi-openapi-specification/blob/master/geotax.yaml",
"description":
"The geotax document classification resource recognizes geographic places cited in the text and returns corresponding countries' names. In addition, when requested with a specific query-string parameter, it returns extra-data containing equivalent GeoJSON objects. See the specific OpenAPI document (https://github.com/therealexpertai/nlapi-openapi-specification/blob/master/geotax.yaml) for information about the way to obtain and interpret GeoJSON data.",
"languages": [{
"code": "en",
"name": "English"
}, {
"code": "es",
"name": "Spanish"
}, {
"code": "fr",
"name": "French"
}, {
"code": "de",
"name": "German"
}, {
"code": "it",
"name": "Italian"
}],
"name":
"geotax"
}]
}
response = MagicMock()
response.status_code = 200
response.ok = True
response.json.return_value = response_json
self.patched_get.return_value = response
client = ExpertAiClient()
dm = client.taxonomies()
self.assertEqual(dm.taxonomies[1].name, "geotax")
self.assertEqual(dm.taxonomies[0].languages[2].code, "fr")
