Boosting Atlassian Integrations with the atlassian-python-api Library
As Atlassian experts, our work doesn’t stop at configuring environments or tailoring Jira, Confluence, and Bitbucket to match a customer’s processes. In many projects, we go a step further: we develop custom integrations that automate workflows, bridge systems, or provide unique capabilities that add real value to a customer’s day-to-day business.
These integrations are typically built in Python, thanks to its readability, reliability, and wide adoption, or delivered as Forge apps when the use case requires a more native experience inside the Atlassian ecosystem.
Over the years, one tool in particular has become a cornerstone for building robust Python-based integrations: the atlassian-python-api library. It’s not just a helper tool—it’s a productivity booster and an enabler for clean, maintainable, and scalable solutions.
Why atlassian-python-api Is a Game Changer
The atlassian-python-api library provides a simple, unified interface for interacting programmatically with many Atlassian products, including:
- Jira (Cloud & Server)
- Confluence
- Bitbucket
- Opsgenie
- Crowd
- Bamboo
- Service Management
Instead of manually crafting REST calls, handling authentication, or fighting with pagination, rate limits, or JSON structures, developers can focus directly on solving business problems.
Below are the top advantages that make this library a must-have.
1. Clean and Intuitive Syntax
The library abstracts away the complexities of raw REST endpoints. Instead of writing a series of requests with headers, auth handling, and error checks, developers can use straightforward methods that map directly to Atlassian concepts.
from atlassian import Jira
jira = Jira(url="https://example.atlassian.net", username="user", password="token")
issue = jira.issue("PROJ-123")
print(issue["fields"]["summary"])
This approach allows developers to work with Jira, not against it.
2. Faster Development with High-Level Methods
The library includes dozens of high-level helper methods that eliminate boilerplate code. Some examples include:
- Creating and transitioning issues
- Managing Jira components and fields
- Updating Confluence pages
- Managing repositories and pull requests in Bitbucket
These operations become one-line actions instead of verbose custom wrappers.
3. Reduced Boilerplate, Improved Maintainability
A clean API surface means fewer lines of code and fewer opportunities for bugs. When you remove repetitive request code, integrations become:
- Easier to read
- Easier to maintain
- Easier to extend
This is particularly important when multiple developers collaborate or when integrations need to be handed over to a customer team.
4. Consistent Experience Across Atlassian Products
Whether interacting with Jira, Confluence, or Bitbucket:
- Authentication is consistent
- Method patterns are similar
- Error handling works the same way
This consistency dramatically improves the learning curve for new developers and reduces context-switching.
5. Ideal for Automation and Scheduled Jobs
Many of the integrations we deliver involve recurring tasks such as:
- Synchronizing data between Jira and external systems
- Bulk updating issues
- Performing quality checks or audits
- Creating dashboards or reporting data
- Cleaning up unused resources (projects, components, labels, etc.)
The atlassian-python-api library is perfectly suited for these background tasks, ensuring stability and performance at scale.
6. Perfect Synergy with Custom Integrations
As teams build more integrations, patterns begin to emerge—how to create issues, how to search for content, how to handle pagination, how to catch errors gracefully.
This is where the library truly shines: it becomes a solid foundation upon which custom business logic can be layered, allowing developers to focus on what really matters.
Our Experience: A Positive Step in the Right Direction
We have already taken the next step by developing an internal custom library built on top of the atlassian-python-api. This wrapper gives us:
- Even cleaner and more expressive code
- Predefined conventions aligned with our customers’ environments
- Simplified authentication and configuration handling
- Higher development velocity when creating new scripts
- A consistent structure across all integrations and automation tasks
The result has been impressive: integrations are now faster to build, easier to maintain, and far more readable.
In short, adopting the atlassian-python-api as a core building block—and enriching it with our own custom layer—has proven to be a highly productive direction for our development efforts.
The atlassian-python-api library is one of the most effective tools available for Python-based Atlassian integrations. It brings clarity, stability, and speed to development workflows and drastically reduces the time spent handling low-level REST details.
Our internal experience demonstrates this clearly: by integrating the library into our own custom wrapper, we have achieved notable improvements in integration quality, readability, and development speed. It’s a solid step forward—and one that continues to pay off with every new script we build.
If you’re looking to streamline your Atlassian automation or enhance the efficiency of your integration projects, this library is absolutely worth adopting.
Valentina Da Rold
Author
