elasticsearch · Python Simple Repository Browser

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Author: Honza Král

Classifiers

Development Status

5 - Production/Stable

License

OSI Approved :: Apache Software License

Intended Audience

Developers

Operating System

OS Independent

Programming Language

Python
Python :: 2
Python :: 2.6
Python :: 2.7
Python :: 3
Python :: 3.2
Python :: 3.3
Python :: 3.4
Python :: Implementation :: CPython
Python :: Implementation :: PyPy

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.

Compatibility

The library is compatible with all Elasticsearch versions since 0.90.x but you have to use a matching major version:

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 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 1.x branches, respectively.

Installation

Install the elasticsearch package with pip:

pip install elasticsearch

Example use

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'}

Full documentation.

Features

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

License

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.