Official low-level client for Elasticsearch. Its goal is to provide common ground for all Elasticsearch-related code in Python; because of this it tries to be opinion-free and very extendable.
For a more high level client library with more limited scope, have a look at
elasticsearch-dsl - a more pythonic library sitting on top of
elasticsearch-py.
It provides a more convenient and idiomatic way to write and manipulate queries. It stays close to the Elasticsearch JSON DSL, mirroring its terminology and structure while exposing the whole range of the DSL from Python either directly using defined classes or a queryset-like expressions.
It also provides an optional persistence layer for working with documents as Python objects in an ORM-like fashion: defining mappings, retrieving and saving documents, wrapping the document data in user-defined classes.
The library is compatible with all Elasticsearch versions since 0.90.x but you
have to use a matching major version:
For Elasticsearch 5.0 and later, use the major version 5 (5.x.y) of the
library.
For Elasticsearch 2.0 and later, use the major version 2 (2.x.y) of the
library.
For Elasticsearch 1.0 and later, use the major version 1 (1.x.y) of the
library.
For Elasticsearch 0.90.x, use a version from 0.4.x releases of the
library.
The recommended way to set your requirements in your setup.py or requirements.txt is:
# Elasticsearch 5.x elasticsearch>=5.0.0,<6.0.0 # Elasticsearch 2.x elasticsearch>=2.0.0,<3.0.0 # Elasticsearch 1.x elasticsearch>=1.0.0,<2.0.0 # Elasticsearch 0.90.x elasticsearch<1.0.0
The development is happening on master and 2.x branches respectively.
Install the elasticsearch package with pip:
pip install elasticsearch
Simple use-case:
>>> from datetime import datetime
>>> from elasticsearch import Elasticsearch
# by default we connect to localhost:9200
>>> es = Elasticsearch()
# create an index in elasticsearch, ignore status code 400 (index already exists)
>>> es.indices.create(index='my-index', ignore=400)
{u'acknowledged': True}
# datetimes will be serialized
>>> es.index(index="my-index", doc_type="test-type", id=42, body={"any": "data", "timestamp": datetime.now()})
{u'_id': u'42', u'_index': u'my-index', u'_type': u'test-type', u'_version': 1, u'ok': True}
# but not deserialized
>>> es.get(index="my-index", doc_type="test-type", id=42)['_source']
{u'any': u'data', u'timestamp': u'2013-05-12T19:45:31.804229'}
The client's features include:
- translating basic Python data types to and from json (datetimes are not decoded for performance reasons)
- configurable automatic discovery of cluster nodes
- persistent connections
- load balancing (with pluggable selection strategy) across all available nodes
- failed connection penalization (time based - failed connections won't be retried until a timeout is reached)
- support for ssl and http authentication
- thread safety
- pluggable architecture
Copyright 2017 Elasticsearch
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
