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core-elasticsearch-app
Advanced tools
Elasticsearch utils for the curator core project.
.. code:: python
INSTALLED_APPS = [
...
'core_elasticsearch_app',
]
The package should be placed above core_explore_keyword_app
in the INSTALLED_APPS
to enable autocomplete powered
by elasticsearch.
.. code:: python
re_path(r'^elasticsearch/', include('core_elasticsearch_app.urls')),
Recommended version: 7.14.1 See https://github.com/usnistgov/cdcs-docker#elasticsearch for help with Elasticsearch deployment.
It is recommended to configure the mapping between the CDCS templates and the Elasticsearch indices before starting to insert data, so that data can be indexed as soon as they are published in the CDCS. For that, set the following setting:
.. code:: python
ELASTICSEARCH_AUTO_INDEX = True
Then, configure the mapping between the XSD templates and the Elasticsearch indices. Documents stored in Elasticsearch
have a common structure. They are composed of a data_id
, a title
and a description
field. A mapping can be
defined to tell where in the XML data the values for the title
and for the description
of a resource can be found.
Below is an example to set this mapping via REST, for a given template:
.. code:: python
import requests
payload = {
"template": "5f43ba192b8fd5c092e30e62",
"title_path": "Resource/identity/title",
"description_paths": ["Resource/content/description", "Resource/content/subject"],
}
requests.post(
SERVER_URI + "/elasticsearch/rest/elasticsearch_template/", data=payload, auth=(USER, PASSWORD)
)
FAQs
Elasticsearch utils for the curator core project
We found that core-elasticsearch-app demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Product
Socket now supports Scala and Kotlin, bringing AI-powered threat detection to JVM projects with easy manifest generation and fast, accurate scans.
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