Jira Xray Bulk Data ExtractorThis project provides a robust Python solution for extracting comprehensive issue and testing metadata from large, fragmented Jira Cloud instances.
It utilizes advanced Keyset/ID pagination to bypass standard API rate limits and indexing failures, ensuring a complete and accurate data dump for Business Intelligence (BI) and metrics analysis.FeaturesFull Project Discovery: Automatically queries the Jira API to discover all projects accessible by the authenticated user.Stable Data Extraction (Keyset Pagination): Uses the ORDER BY id DESC filtering strategy instead of the unstable startAt (offset) parameter, preventing infinite loops and data loss common in enterprise Jira environments.Granular Metrics: Extracts key fields for QA and development metrics, including Issue Type, Reporter, Assignee, Priority, Resolution, Time Estimate, and Linked
Issues.Error Handling: Includes robust error checks for API access denial (401/403) and safe handling of missing user data (using accountId as a fallback for 'Unknown' names).Clean Output: Generates a single, consolidated .xlsx file ready for use in Pandas, Excel, or Power BI.🛠️ Setup and Installation1. PrerequisitesEnsure you have Python 3.8+ installed Bash# Install required Python libraries pip install requests pandas openpyxl
- Configuration (Environment Variables)The script relies on the following environment variables for authentication. These must be set in your operating system (or in a separate .env file that you load).VariablePurposeValue ExampleJIRA_EMAILYour Atlassian email address.user@bancoicbc.com.arJIRA_API_TOKENYour Atlassian API Token (generated in your Atlassian Profile).ATATT3xFf...JIRA_BASE_URLThe base URL of your Jira instance (used internally).https://bancoicbc.atlassian.netPROXY_URL (Optional)Required if accessing Jira through a corporate firewall/proxy.http://proxy.corp:80803. ExecutionActivate your virtual environment and run the main script:Bash# Activate your virtual environment source venv/bin/activate # macOS/Linux
python jira_xray_bulk_data_extractor.py 🚀 Usage and OutputConsole OutputThe script will first query your project list, then iterate through each one, providing progress feedback:SUCCESS: Found 45 accessible projects.
[1/45] Processing UPMU... ✅ 1826 records retrieved. [2/45] Processing SDI... ✅ 14500 records retrieved. [3/45] Processing MBD... ⭕ (Empty or Access Denied) ... GLOBAL SUMMARY: 26759 total records retrieved from 45 projects. INFO: Generating Master Excel Report with 26759 records... SUCCESS: Excel saved to: /path/to/project/consolidated_report.xlsx Key Report ColumnsThe output file, consolidated_report.xlsx, includes the following essential columns for filtering and metric calculation:Column NameData PurposeExample OutputProject KeyPrimary filter for teams/modules.SDIIssue TypeDistinguishes Test vs Story vs Test Plan.Test ExecutionReporter NameUser who created the ticket.Sergio Moramarco Reporter AccountIDPermanent unique identifier (used as fallback for 'Unknown').557058:...StatusCurrent workflow state.In ProgressPriorityBusiness impact level.HighestOriginal Estimate (s)Time tracking data (in seconds).3600Linked Issues (Keys)Requirements or Bugs related to this issue.REQ-400, BUG-105CreatedDate of creation.2025-10-25