CI/CD using Jira & GitHub-Actions, Python, REST API.

Author: aashutosh

Updated: 17 Feb 2023 8:49 p.m.

Tags: #Python #Scripting #REST #API #Automation #Jira

Summary : Integrate Jira and GitHub-Actions using Python script & REST API.

This is quick hack to automate advanced functionalities in Jira using custom Python script and utilizing GitHub-Actions or any other tools like AWS Lambda, GCP & Azure Functions, Jenkins, or any custom webserver.

Jira Service Management has very good Automation feature, but to automate highly advanced features, we can use a custom python script which does the business logic processing and update Jira via REST API.

We can write a workflow, whenever any event happens in Jira, we will trigger our script to execute, hosted on GitHub in this case.

Use Case Example:

Global Finance Application

A request form, which takes input from user for Payment requests.
Based on inputs like Country, City etc., automatically assign Approvers.
Convert user input amount and currency to desired currency.
Automatically decide levels of approvals, based on threshold value.
Once approvals done, send web request to Payment API.

Step 1 : Create automation rule in Jira.

Project -> Project Settings -> Automation -> Create Rule
New Trigger -> Select Event when you want to trigger rule.
Example: When Issue Created.

Then Send Web Request
Send Web Request to GitHub Repository dispatch with custom data (issue key & jira api token)

Step 2: Set up GitHub

Create a GitHub Repo and below workflow.yml file in .github/workflows/ directory

name: my build name

# trigger when this repository is dispatch (called from Jira Web request) on: repository_dispatch jobs: build: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: '3.10' - name: Install Dependencies run: | python -m pip install --upgrade pip pip install -r requirements.txt - name: Name of run task run: | python automation_script.py ${{ github.event.client_payload.key }} ${{ github.event.client_payload.jira-token }}

Upload Python Script & dependent files to GitHub Reposiory

Approvers Matrix

Python Script

import re import sys import json import requests import datetime import pandas as pd from requests.auth import HTTPBasicAuth

# get jira issue key and api token passed via Jira web request as arguments to script as defined in GitHub-Actions Workflow issueKey=sys.argv[1] jiraAPIToken=sys.argv[2]

jiraAPIToken = '***********8' email = 'aashutosh' auth = HTTPBasicAuth(email,jiraAPIToken) headers = { "Accept": "application/json", "Content-Type": "application/json" }

# generate REST API URL with issue-key url='https://mysite.atlassian.net/rest/api/3/issue/'+issueKey

# fetch data using requests from Jira REST API response = requests.request( "GET", url, headers=headers, auth=auth )

# print json data in pretty format # print(json.dumps(json.loads(response.text), sort_keys=True, indent=4, separators=(",", ": "))) data=json.loads(response.text)

''' Perform Business Logic Jira Custom Fields ID customfield_10001 = Country & City Custom Field id in Jira customfield_10002 = Amount customfield_10003 = Currency customfield_10004 = Level 1 Approver customfield_10005 = Level 2 Approver customfield_10006 = Level 3 Approver customfield_10007 = Amount in Euro '''

country = data['fields']['customfield_10001']['value'] city = data['fields']['customfield_10001']['value'] amount = float(data['fields']['customfield_10002']) currency = data['fields']['customfield_10003']

#Store Approver & Approvers Matrix in an excel sheet mapped to each Country & City #Read approvers excel sheet using pandas dataframe df = pd.read_excel('approver.xlsx')

# Read Approvers Excel file df = pd.read_excel('approvers.xlsx')

# Read Approvers Name & Jira Account IDs. convert pairs into dictionary accountIDs_df = pd.read_excel('approvers.xlsx', sheet_name=1)

# Make Dictionary of Approvers Account Names & AccountIDs approvers_accountIDs = dict(zip(accountIDs_df.Name, accountIDs_df.AccountID))

#Filter Approvers Row for each Country & City approver_row = df[ (country == df['Country']) & (city == df['City']) ]

def get_approversID(column_name, approver_row): ''' Get Approvers Account ID from Excel sheet, join account ids for multiple users in single cell, split, strip & join. ''' # split multiple users in once cell approvers = approver_row[column_name].values[0].split(',') # strip whitespaces in users name approvers = [ user.strip() for user in approvers ] # join users with comma, return their Account ID approvers = ','.join([approvers_accountIDs[user] for user in approvers]) return approvers

level1Approvers = get_approversID('Level_1_Approver',approver_row) level2Approvers = get_approversID('Level_2_Approver',approver_row) level3Approvers = get_approversID('Level_3_Approver',approver_row)

def currRate(curr): # Function to convert currency into EURO, ruturn currency exchange rate w.r.t EURO return { 'AED - UAE Dirham' : 4.55, 'ARS - Argentine Peso' : 90.4693, 'AUD - Australian Dollar' : 1.62, 'BRL - Brazilian Real' : 6.6308, 'CAD - Canadian Dollar' : 1.52, 'CNY - Yuan Reminbi' : 7.972, 'EUR - Euro' : 1, 'GBP - Pound Sterling' : 0.89, 'HKD - Hong Kong Dollar' : 8.915, 'INR - Indian Rupee' : 84, 'JPY - Yen' : 121, 'MXN - Mexican Peso' : 24, 'RUB - Ruble' : 91.7763, 'SEK - Swedish Kronor' : 10.5713, 'SGD - Singapore Dollar' : 1.58, 'THB - Baht' : 37.079, 'USD - US Dollar' : 1.15, }.get(curr)

# get amount in Eurom by multiplying amount with currency rate amount_Euro = float(amount * currRate(currency)

payload = json.dumps( { "fields": { "customfield_10004": [{"accountId": level1Approvers}], "customfield_10004": [{"accountId": level1Approvers}], "customfield_10005": [{"accountId": level2Approvers}], "customfield_10006": [{"accountId": level3Approvers}], "customfield_10007": amount_Euro, } })