Mémorandum elasticsearch_dsl

environnement

Python3.8.2 elasticsearch-dsl 7.1

Comme Elasticsearch était gênant, j'ai vérifié uniquement la requête sur Python.

A, Q

test = A("terms", field="hoge")
print(test.to_dict())
print(type(test))

test2 = Q("terms", field="huge")
print(test2.to_dict())
print(type(test2))

{'terms': {'field': 'hoge'}}
<class 'elasticsearch_dsl.aggs.Terms'>
{'terms': {'field': 'huge'}}
<class 'elasticsearch_dsl.query.Terms'>

Agg Array

array_test = [A("terms", field="key_" +str(i)) for i in range(5)]

search = Search()
for i in range(5):
    search.aggs.bucket("array_" + str(i), array_test[i])

print(search.to_dict())

{'aggs': {
  'array_0': {'terms': {'field': 'key_0'}}, 
  'array_1': {'terms': {'field': 'key_1'}}, 
  'array_2': {'terms': {'field': 'key_2'}}, 
  'array_3': {'terms': {'field': 'key_3'}}, 
  'array_4': {'terms': {'field': 'key_4'}}
}}

Je souhaite ajouter une imbrication Aggs Array

array_test = [A("terms", field="key_" +str(i)) for i in range(5)]

search = Search()
X = search.aggs.bucket("array_0", array_test[0])
for i in range(1, 5):
    X = X.bucket("array_" + str(i), array_test[i])

print(search.to_dict())

{'aggs': {'array_0': {
  'terms': {'field': 'key_0'},
  'aggs': {'array_1': {
    'terms': {'field': 'key_1'},
    'aggs': {'array_2': {
      'terms': {'field': 'key_2'},
      'aggs': {'array_3': {
        'terms': {'field': 'key_3'},
        'aggs': {'array_4': {
          'terms': {'field': 'key_4'}
        }}
      }}
    }}
  }}
}}}