Postman with Newman – Run API Tests from the Command Line Like a Pro

Postman with Newman – A Complete Guide for API Test Automation

Postman is a popular tool for testing RESTful APIs. While it's great for manual testing, running tests as part of automation or CI/CD pipelines requires a command-line interface. That’s where Newman comes in!

🚀 What is Newman?

Newman is Postman’s command-line tool that lets you run Postman collections directly from your terminal. It allows automated API testing and is perfect for continuous integration workflows.

🛠️ How to Set Up Postman with Newman

Step 1: Install Node.js

Download and install Node.js from https://nodejs.org/.

Step 2: Install Newman

Open your terminal and run:

npm install -g newman

Step 3: Export Postman Collection

• Open Postman app
• Select your collection → click "..." → Export
• Choose "Collection v2.1 (recommended)" format

Step 4: Run Collection Using Newman

newman run your_collection.json

🧪 Run with Environment File

newman run your_collection.json -e your_environment.json

📊 Generate HTML Report

npm install -g newman-reporter-html
newman run your_collection.json -r html

🔁 Run with Data File (CSV or JSON)

newman run your_collection.json -d data.csv

⚙️ CI/CD Integration Ideas

• Jenkins: Add as a shell step
• GitHub Actions: Add in your YAML workflow
• GitLab CI: Include in your .gitlab-ci.yml

✅ Summary

Newman helps you automate Postman collections via CLI, making your API tests easily repeatable, CI/CD-friendly, and reportable. This approach saves time, improves accuracy, and helps detect issues earlier in the development cycle.

📎 Helpful Links

• Postman Official Site
• Newman on NPM
• Postman Learning Center

Written by Anup Khobragade | Published on SoftwareTesting-Guideline

Browser Automation with Google Gemini Model to run UI Tests

Browser Automation Using Google Gemini to run UI Test

🔧 Prerequisites

• Python 3.8 or above
• Visual Studio Code or any Python IDE
• Internet connection to download models and dependencies

📦 Installation Steps

1. Install browser-use

pip install browser-use

GitHub: https://github.com/browser-use/browser-use

2. Install Chromium browser with Playwright

playwright install chromium --with-deps --no-shell

3. Add your API keys to a .env file

OPENAI_API_KEY=your_openai_key_here

(Gemini/Gemma public model doesn't require a token.)

🤖 Example: AI Agent Running a Selenium Script

This example uses Gemini model to generate a Selenium script that runs a test in headful mode and interacts with your blog.

from smolagents import CodeAgent, DuckDuckGoSearchTool, InferenceClientModel
agent = CodeAgent(
    tools=[DuckDuckGoSearchTool()],
    model=InferenceClientModel(model_id="google/gemma-2b-it"),
    additional_authorized_imports=[
        "selenium",
        "selenium.webdriver",
        "selenium.webdriver.common.by",
        "selenium.webdriver.common.keys",
        "selenium.webdriver.support.ui",
        "selenium.webdriver.support.expected_conditions",
        "webdriver_manager.chrome"
    ]
)
agent.run("write selenium code to test to run in headful mode for 

https://softwaretesting-guideline.blogspot.com/ and click on different posts")

The resulting execution demonstrates how the AI agent parses the site's DOM, 

detects all hyperlink elements, and programmatically simulates user interactions 

by clicking on various blog post links.

✅ Benefits

• No manual code writing — just describe your intent
• Perfect for test engineers and QA automation
• Supports flexible tools and models

⚠️ Tips

• Make sure Playwright is installed correctly and compatible with your OS
• If using OpenAI or HuggingFace models, store API keys securely

🎯 Conclusion

By combining SmolAgents, Gemini model, and Selenium, you can create powerful browser-based test automation flows with minimal effort. AI-powered agents are the future of QA automation!

Happy Testing 🚀

Build an AI Agent with SmolAgents to Control Selenium Browser Automation

AI Agent Controlling Browser Using Selenium with SmolAgents

Artificial Intelligence is rapidly transforming how we automate web tasks. In this tutorial, we will explore how to control a browser using Selenium through a Python AI agent created using SmolAgents. We'll also discuss how to handle import restrictions by allowing additional modules explicitly.

🚀 What Is SmolAgents?

As I describe in my previous post, SmolAgents is a lightweight, open-source Python framework created by Hugging Face. It enables you to build smart autonomous agents that can interact with external tools, models, and libraries like selenium, duckduckgo, and more.

🧰 Prerequisites

1. Python Installed (Recommended: 3.11 or 3.12) 
2. VS Code or any Python IDE
3. Install SmolAgents:

   python -m pip install "smolagents[openai]"

4. Install Selenium & ChromeDriver Manager:

   pip install selenium webdriver-manager

⚠️ Issue with Unauthorized Imports

By default, SmolAgents restricts importing some external libraries such as selenium. This is for safety reasons. But in our use case, we can safely allow it using the additional_authorised_import parameter when initializing the agent.

💡 AI Agent Code Using Selenium

In the below code, we explicitly authorize the necessary Selenium imports and ask the agent to write code to open our blog https://softwaretesting-guideline.blogspot.com and click on different posts in headful mode.

from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel

agent = CodeAgent(
    tools=[DuckDuckGoSearchTool()],
    model=HfApiModel(),
    additional_authorised_import=[
        "selenium",
        "selenium.webdriver",
        "selenium.webdriver.common.keys",
        "webdriver_manager.chrome"
    ]
)

agent.run("write selenium code to test to run in headful mode for 

https://softwaretesting-guideline.blogspot.com/ and click on different posts")

📝 What This Code Does

• Creates a CodeAgent with authorized imports
• Uses a search tool for reasoning
• Requests the AI to generate a Selenium script to interact with your blog

🧪 Sample Output

The agent typically returns code like the following:

from selenium import webdriver
from selenium.webdriver.common.by import By
from webdriver_manager.chrome import ChromeDriverManager
import time

driver = webdriver.Chrome(ChromeDriverManager().install())
driver.get("https://softwaretesting-guideline.blogspot.com/")
time.sleep(5)

# Click on all post links
links = driver.find_elements(By.CSS_SELECTOR, "h3.post-title a")
for link in links:
    print("Opening post:", link.text)
    link.click()
    time.sleep(3)
    driver.back()
    time.sleep(2)

driver.quit()

📌 Key Points

• Running in headful mode lets you visually see the browser actions
• You can modify the logic to open specific blog posts or interact with elements like labels, buttons, or images
• Use headless mode for automation pipelines by setting Chrome options accordingly

🔗 Resources

• SmolAgents GitHub
• Selenium Official Website

Conclusion: Using AI agents to control browsers opens up exciting new possibilities for intelligent test automation and web scraping. With SmolAgents and Selenium, you can offload even complex test tasks to an autonomous Python agent. Learn AI Agents with SmolAgents in Python for Web Automation

How to Use AI Agents with SmolAgents in Python for Web Automation and Search Tasks

Build a Python AI Agent to Control Browser Using SmolAgents

In this tutorial, we'll show how to build an AI agent in Python that uses SmolAgents to perform intelligent tasks like searching the web or controlling browsers using automation tools. We'll also walk you through a working example that uses DuckDuckGo to fetch a coupon code.

🧰 Prerequisites

1. Install Python (3.11 or 3.12):
   Download from python.org and make sure to check the box "Add Python to PATH" before clicking "Install Now".
2. Install Visual Studio Code (VS Code):
   Download and install from https://code.visualstudio.com/.
3. Install SmolAgents Library:
   Open your terminal or command prompt and run:

   python -m pip install "smolagents[openai]"

4. Optional - Install Browser Automation Tools:
   For browser interaction using Playwright:

   pip install browseruse

   And then install Playwright browsers:

   python -m playwright install

   Also install MCP server if required, based on the browser automation setup.

💡 What Are SmolAgents?

SmolAgents is a lightweight, open-source Python library created by Hugging Face that allows you to build autonomous AI agents with tools such as search engines, code execution, and browser automation.

🧪 Sample Code: Use SmolAgents to Get a Coupon Code

This example sets up a basic agent with a search tool to look for a coupon code on the website akrabtravel.com.

from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
agent = CodeAgent(
    tools=[DuckDuckGoSearchTool()],
    model=HfApiModel()
)
agent.run("Get me the coupon code for flight booking on akrabtravel.com")

🔍 Explanation:

• CodeAgent: This is the main agent type that coordinates tools and models to perform a task.
• DuckDuckGoSearchTool: A tool that uses the DuckDuckGo search engine to fetch information from the internet.
• HfApiModel: This uses Hugging Face's hosted models as the reasoning engine for the agent.
• agent.run(): Executes the instruction provided and returns the result.

📌 Output

When run, the agent will intelligently search for available coupon codes related to the instruction provided and return a summary. This process is entirely autonomous and powered by AI.

🚀 Next Steps

• Try integrating browser automation tools like browseruse or Playwright.
• Connect with APIs to fetch and interact with real-time content.
• Build more complex multi-step agents using SmolAgents tools like memory or planner agents.

🔗 Resources

• SmolAgents GitHub Repo
• Official Documentation

Conclusion: AI agents are changing the way we interact with data, browsers, and the web. SmolAgents provides a minimal, open-source approach for building smart tools with Python. Explore it further and build your own personal AI assistant today! Also read the content understanding-AI-agents