When utilizing Jira, managing projects and monitoring issues can be made easier. However, at times, it may be necessary to transfer this information to Excel for tasks such as reporting or data analysis. In this post, we will guide you through the process of automatically exporting data from Jira to Excel.
Prerequisites
Before we get started, make sure you have the following:
- Access to Jira Software Cloud or Server
- Excel installed on your computer
- Basic understanding of Jira and Excel
- Python installed on your computer (for automation)
- Jira’s REST API access
Methodology
The idea is to use Python and Jira’s REST API to fetch the data and then save it as an Excel file. Python has libraries such as jira and pandas that make this task relatively straightforward.
Steps to Follow
Here are the steps you need to follow:
1. Install Required Python Libraries
The below command installs the jira and pandas libraries:
<br> pip install jira pandas<br>
2. Connect to Jira
First, we need to establish a connection to JIRA. Make sure to replace the ‘YOUR_USERNAME’, ‘YOUR_PASSWORD’, and ‘YOUR_JIRA_URL’ with your credentials and Jira URL.
<br>
from jira import JIRA<br>
jira = JIRA('YOUR_JIRA_URL', basic_auth=('YOUR_USERNAME', 'YOUR_PASSWORD'))<br>
3. Fetch Data from Jira
Now, fetch the required data using Jira’s REST API. The JQL (Jira Query Language) is used here to filter the data.
<br>
data = jira.search_issues('project = "Your Project Name"')<br>
4. Convert Data to Excel
Use pandas to create a DataFrame from the fetched data:
<br>
import pandas as pd<br>
df = pd.DataFrame(data)<br>
Then, save this DataFrame to an Excel file:
<br>
df.to_excel('jira_data.xlsx', index=False)<br>
Conclusion
By following these steps, you should be able to automate the process of getting data from Jira to Excel. This can save you a significant amount of time, allowing you to concentrate more on analyzing the data rather than on the tedious task of data extraction.
