docs-onboarding/programming-language-recommendations.md

Programming language recommendations

Azure DevOps Pipeline

The following programming languages are included in the comparison:

• C# (.NET)
• Shell Scripting Bash / Zsh
• Python
• JavaScript / TypeScript
• Ruby
• Go
• PowerShell
• Java

Comparsion of the most important points

Point	C#	Shell	Python	JS	Ruby	Go	PS	Java
Data processing (JSON)	Built-in	Built-in	Built-in	Built-in	Built-in	Built-in	Built-in	Libraries
Data presentation (PDF)	Libraries	Not natively	Libraries	Libraries	Libraries	Libraries	Libraries	Libraries
Other data processing	Libraries	Not natively	Libraries	Libraries	Libraries	Libraries	Libraries	Libraries
Availability of Extensions	Many	Few	Many	Many	Many	Few	Many	Many
Simplicity in YAML	Moderate	High	Moderate	Moderate	Moderate	High	High	Moderate
Must be Compiled	Yes	No	No	No	No	Yes	No	Yes
Cross-Platform	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Simple Installation of Dependencies	Moderate	High	High	High	Moderate	High	High	Moderate

Recommended Language: Python

Python wins in all categories. The most benefits compared to the other languages:

• Data Handling: pull data, parse it, and then format it.
• Document Generation: The libraries for data presentation are fast and simple.
• Dependencies: are easy handled with requirments.txt.
• Virtual Environments: allows different Python versions to be used in the same pipeline.
• REST APIs: can be simple used with the Pythons requests library.

Example Workflows for Python

Install Dependencies

Use a pipeline task to install Python (if not already on the agent) and the required libraries.

- task: UsePythonVersion@0
  inputs:
    versionSpec: '3.x'
- script: |
    pip install requests python-docx reportlab jinja2

Fetch Work Items

Write a Python script to call the Azure DevOps REST API to retrieve Work Items.

import requests

# Example: Get Work Items from Azure DevOps
devops_organization_url = "https://dev.azure.com/YOUR_ORG"
project = "YOUR_PROJECT"
api_version = "6.0"
query_id = "YOUR_QUERY_ID"

response = requests.get(
    f"{devops_organization_url}/{project}/_apis/wit/wiql/{query_id}?api-version={api_version}",
    auth=('PAT_USERNAME', 'PAT_TOKEN')  # or use other Auth methods
)
work_items_data = response.json()

Generate Compliance Documents

Convert the retrieved data into the document format of your choice.

from docx import Document
from docx.shared import Inches

document = Document()
document.add_heading('Compliance Report', level=1)

for item in work_items_data["workItems"]:
    document.add_heading(f'Work Item ID: {item["id"]}', level=2)
    # Additional data insertion here...

document.save('ComplianceReport.docx')