elastic/elasticsearch-py

Official Python client for Elasticsearch

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Summary Information

Updated 54 minutes ago
Added to GitGenius on September 15th, 2026
Created on May 1st, 2013
Open Issues & Pull Requests: 68 (+0)
GitHub issues: Enabled
Number of forks: 1,221
Total Stargazers: 4,386 (+0)
Total Subscribers: 393 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 19.1 hours
Mean response time: 30.9 days
90th percentile: 38.3 days
Tracked items: 125

Most active contributors

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How this project is maintained

Roughly one issue in four opened in the past year never receives a reply. 91% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "Area: Client" is answered fastest, typically in about 7 hours, while "tracking" waits about 10 days. 64% of issues opened in the past year have been closed, leaving a working backlog. Three people close 67% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 55
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,122 days
Stale 30+ days: 54
Stale 90+ days: 51

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • tracking (60)
  • Area: Client (15)
  • Category: Question (14)
  • Category: Enhancement (13)
  • Category: Bug (11)
  • Stale (10)
  • Area: Documentation (9)
  • Area: Helpers (3)

Most active issues this week

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Detailed Description

elasticsearch-py is the official Python client library for Elasticsearch.

The tool solves the problem of communicating with Elasticsearch clusters from Python applications. It provides a programmatic interface to send requests to Elasticsearch nodes and handle responses, abstracting away the details of HTTP communication and serialization. The client translates Python method calls into Elasticsearch API requests and parses the results back into Python objects.

Developers building Python applications that need to index, search, or manage data in Elasticsearch should use this client. It suits projects ranging from simple search implementations to complex data pipelines that rely on Elasticsearch as a backend. Because this is the official client maintained by Elastic, it receives updates in lockstep with Elasticsearch server releases and provides the most direct path to using new server features from Python code.

The project maintains active development with regular updates to track Elasticsearch API changes. The codebase receives consistent attention to keep the client aligned with server capabilities. Development activity shows ongoing refinement of the client's core functionality and its integration patterns with the broader Elasticsearch ecosystem.