atlassian-python-api

What it is and what it does

atlassian-python-api is a wrapper around the REST APIs of Atlassian's product suite, letting you automate and integrate with Jira, Confluence, Bitbucket, Bamboo, ServiceDesk, Insight, and Xray from Python code. It abstracts away HTTP details and authentication, exposing product-specific classes (Jira, Confluence, Bitbucket, etc.) with methods for common operations like querying issues, creating pages, or listing projects. The library supports both Atlassian Server and Cloud deployments and can work with optional requests.Session objects for connection pooling.

The package depends on requests for HTTP, oauthlib and requests_oauthlib for OAuth flows, beautifulsoup4 for HTML parsing, jmespath for JSON queries, and typing-extensions for type hints. It is in Beta status, actively maintained, and has been in development since 2015. The description notes that some methods like the traditional jql() are deprecated for Jira Cloud in favor of enhanced_jql() to align with Atlassian's pagination changes.

Use it for:

• Automate Jira issue creation, updates, and queries using JQL without writing raw HTTP requests.
• Create and manage Confluence pages and spaces programmatically for documentation workflows.
• Retrieve Bitbucket project and repository data for CI/CD pipeline integration.
• Query Jira Service Desk customer requests and manage tickets in support workflows.
• Access Insight (CMDB) and Xray (test management) data for enterprise asset and test tracking.
• Build custom applications that synchronize data between Atlassian products and external systems.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides Python bindings to REST APIs for Atlassian products (Jira, Confluence, Bitbucket, Bamboo, ServiceDesk, Insight, Xray) and supports both Server and Cloud instances.

Yes. The package has low install friction, active maintenance, no known vulnerabilities, and permissive licensing. It is well-suited for teams already using Atlassian products who need programmatic access. The main gotcha is ensuring you use the correct authentication method (token for Cloud, password for Server) and staying aware of deprecated methods like traditional jql() for Cloud instances.

Install

atlassian-python-api on PyPI

pip install atlassian-python-api

uv add atlassian-python-api

poetry add atlassian-python-api

Installing atlassian-python-api

Before you install

Low friction installation with a pure-Python wheel and seven runtime dependencies. Actively maintained with recent commits and no known vulnerabilities.

License in practice

Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions.

Quickstart

pip install atlassian-python-api

from atlassian import Jira
import requests

session = requests.Session()
jira = Jira(
    url='http://localhost:8080',
    username='admin',
    password='admin',
    session=session)
data = jira.jql('project = DEMO')
print(data)

Requires network access to an Atlassian instance and valid credentials (username/password or API token for Cloud).

Verify before relying

• Whether all seven runtime dependencies are required for every use case or if some are optional per module.
• Performance characteristics when handling large result sets or batch operations.
• Current test coverage and CI/CD pipeline status beyond the GitHub repository activity.

Package facts

Evidence: atlassian_python_api-4.0.7-py3-none-any.whl

Keywords: atlassian, jira, core, software, confluence, bitbucket, bamboo, crowd, portfolio, tempo, servicedesk, assets, api

Tags

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