Elasticsearch-py.readthedocs.io Website Review

Official low-level client for Elasticsearch. Its goal is to provide common ground for all Elasticsearch-related code in Python; because of - it is a more pythonic library sitting on top of elasticsearch-py. The library is compatible with all Elasticsearch versions since 0.90.x but you HAVE TO USE A MATCHING MAJOR VERSION: For ELASTICSEARCH 6.0 and later, use the major version 6 (6.x.y) of the library. 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, and so on. The recommended way to set your requirements in your setup.py or requirements.txt is: If you have a need to have multiple versions installed at the same time older versions are also released as elasticsearch2 and from datetime import datetime from elasticsearch import Elasticsearch     author: kimchy,     text: Elasticsearch: cool. bonsai cool., This client was designed as very thin wrapper around Elasticsearch’s REST API to allow for maximum flexibility. This means that there are no opinions in this client; it also means that some of the APIs are a little cu*bersome to use from Python. We have created some Helpers elasticsearch-py uses persistent connections inside of individual connection pools (one per each configured or sniffed node). Out of the The transport layer will create an instance of the selected connection clas* per node and keep track of the health of individual nodes - if a node becomes unresponsive (throwing exceptions while connecting to it) it’s put on a timeout by the ConnectionPool nodes are left). By default nodes are randomized before being pas*ed into the pool and round-robin strategy is used for load balancing. supported you should be able to create a subclas* of the relevant component and pas* it in as a parameter to be used instead of the If a connection fails multiple times in a row the timeout will get progressively larger to avoid hitting a node that’s, by all