Python

vibssingh

How to Use Pytest for REST API Testing

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Pytest is a versatile testing framework in Python. It can be used for various types of testing, like REST API testing. In this tutorial, we will test Rest API in PyTest Framework.

Table of Contents

  1. Prerequisite
  2. Implementation Steps
    1. Setup and Required Libraries
    2. Setup PyTest Project
    3. Writing Test Cases
    4. Running the Tests
    5. Generating HTML report

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

Implementation Steps

Step 1 – Setup and Required Libraries

1.1 Install pytest

pip install -U pytest

1.2 Install requests

pip install pytest requests

Step 2 – Setup PyTest Project

2.1 Create a new project folder and open it in PyCharm.

2.2 – Go to the project folder and create a new python file – test_restapi.py.

2.3 – Add requests package to the PyCharms

Go to File->Settings ->Project: PyTest_Framework->Python Interpreter.

Click on the “+” sign and enter allure-r in the search bar. It will show a list of packages. Select the “requests” package and click on the “Install Package”.

Once the package is installed, we will see the message that the package is installed successfully.

Step 3- Writing Test Cases

import pytest
import requests

BASE_URL = "https://reqres.in/api"

def test_get_endpoint():
       response = requests.get(f"{BASE_URL}/users/2")
       assert response.status_code == 200
       assert response.json()["data"]["email"]   == "janet.weaver@reqres.in"
       assert response.json()["data"]["id"] == 2
       assert response.json()["data"]["first_name"] == "Janet"
       assert response.json()["data"]["last_name"] == "Weaver"

def test_post_endpoint():
       payload = {"name": "Vibha", "job": "CTO"}
       headers = {"x-api-key": "reqres-free-v1"}

       response = requests.post(f"{BASE_URL}/users", headers=headers, json=payload)

       print(response.status_code)
       print(response.text) 
       assert response.status_code == 201
       assert response.json()["name"] == "Vibha"

Explanation

This is the base URL pointing to the API server on which the endpoints will be tested.

BASE_URL = "https://reqres.in/api"

1.Function: test_get_endpoint()

Sends a GET request to fetch user details with ID 2.

response = requests.get(f"{BASE_URL}/users/2")

Verifies that the response status is 200, indicating success.

assert response.status_code == 200

Checks that the email, id, first_name and last_name in the response matches the expected value.

assert response.json()["data"]["email"]   == "janet.weaver@reqres.in"
assert response.json()["data"]["id"] == 2
assert response.json()["data"]["first_name"] == "Janet"
assert response.json()["data"]["last_name"] == "Weaver"

2. Function: test_post_endpoint()

Defines the payload (data) to be sent in the POST request, specifying the name and job.

payload = {"name": "Vibha", "job": "CTO"}

Sets a custom header.

headers = {"x-api-key": "reqres-free-v1"}

Sends a POST request with the payload and headers.

response = requests.post(f"{BASE_URL}/users", headers=headers, json=payload)

Print the status code and response text for debugging purposes.

print(response.status_code)
print(response.text)

Checks whether the server returned a status code of 201, indicating resource creation.

assert response.status_code == 201

Validates that the name returned in the response matches the submitted name “Vibha”.

assert response.json()["name"] == "Vibha"

Step 4- Running the Tests

pytest test_api.py

The output of the above execution is

If you have pytest-html plugin already installed, then we can generate a HTML Report also. To learn more, please refer to this – How to generate HTML Report in PyTest Framework

pytest test_api.py --html=report.html

The report.html report will be generated in the root directory.

Step 5 – Generating HTML report

Right-click and open with Web Browser.

Enhancements and Best Practices:

  1. Use fixtures for setting up test data or configuration if needed.
  2. Use parameterized testing to run a test function with multiple sets of inputs.
  3. Consider organizing tests in different files based on different functionalities or endpoints in your API.

That’s it! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

Appending Data to Excel with Python using openpyxl

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We are given an Excel file and our task is to append the data into this excel file using Python. In this article, we’ll explore openpyxl library to append data to an Excel file using Python.

Prerequisite:

Python is installed
PIP is installed
PyCharms is installed

Sample Excel

Step 1 – Install openpyxl

Openpyxl can be installed using pip

pip install openpyxl

Step 2 – Load the workbook

workbook = load_workbook("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

Step 3 – Select the active worksheet

sheet = workbook.active

Step 4 – Create new data to be appended to the Excel in the list of lists.

new_data =[
    ["Scrum Master", "5-10 Years", "35K"],
    ["Consultatnt", "8-12 Years", "37K"]
]

Step 5 – Find the next available row in the sheet.

last_row = sheet.max_row + 1

Step 6 – Append the data to the excel by using the nested loops.

for i, row in enumerate(new_data, start=last_row):
    for j, value in enumerate(row, start=1):
        sheet.cell(row=i, column=j, value=value)

Step 7 – Save the changes made to the workbook

workbook.save("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

The complete program is

from openpyxl.reader.excel import load_workbook
from openpyxl.styles import Font


#Load the workbook
workbook = load_workbook("C:\\Users\\ykv12\\Documents\\Vibha\\Automation\\SearchInBing.xlsx")

sheet = workbook.active

#Sample data
new_data =[
    ["Scrum Master", "5-10 Years", "35K"],
    ["Consultatnt", "8-12 Years", "37K"]
]

#Append the new data to the sheet
last_row = sheet.max_row + 1
for i, row in enumerate(new_data, start=last_row):
    for j, value in enumerate(row, start=1):
        sheet.cell(row=i, column=j, value=value)

#Save the workbook
workbook.save("C:\\Users\\ykv12\\Documents\\Vibha\\Automation\\SearchInBing.xlsx")

print("Data is appended in the Excel file successfully")

The output of the above program is

Updated Excel

That’s it! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

Create and Format Excel Files with Python Openpyxl – Tutorial

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Reading data from Excel files is a common practice in software development and testing. Excel provides a tabular format which is easy to understand and navigate. Data can be written to Excel for manipulation, analysis and visualization using Java, Python, R and soon. There are several ways to read the data from Excel in Python, but we will discuss openpyxl.

Prerequisite:

Python is installed
PIP is installed
PyCharms is installed

Implementation Steps

Step 1 – Install openpyxl

Openpyxl can be installed using pip

pip install openpyxl

Step 2 – Create a new workbook

workbook = Workbook()
sheet = workbook.active

Step 3 – Select or rename the Sheet

sheet.title ="Sample Sheet"

Step 4 – Prepare the data

data =[
    ["Name", "Designation", "EmployeeId"],
    ["Tom", "BA", 11001],
    ["Trina", "PO", 11002],
    ["Will", "Dev", 11003]
]

Step 5 – Write the data

Loop through each sub-list and use sheet.append(row) to add the row to the sheet

for row in data:
    sheet.append(row)

Step 6 – Save the workbook

workbook.save("C:\\Users\\Vibha\\Automation\\WriteExcel.xlsx")

The complete program is

from openpyxl.workbook import Workbook

#Create a new workbook
workbook = Workbook()
sheet = workbook.active

#Rename the sheet
sheet.title ="Sample Sheet"

#Sample data
data =[
    ["Name", "Designation", "EmployeeId"],
    ["Tom", "BA", 11001],
    ["Trina", "PO", 11002],
    ["Will", "Dev", 11003]
]

#Write data to the sheet
for row in data:
    sheet.append(row)

#Save the workbook
workbook.save("C:\\Users\\Documents\\Vibha\\Automation\\WriteExcel.xlsx")
print("Data is written the Excel file successfully")

The output of the above program is

The Excel is created and saved at the specified location.

Header with bold font

Below is the complete program:

from openpyxl.styles import Font
from openpyxl.workbook import Workbook

#Create a new workbook
workbook = Workbook()
sheet = workbook.active

#Rename the sheet
sheet.title ="Sample Sheet"

#Sample data
headers =  ["Name", "Designation", "EmployeeId"]
rows =[
    ["Tom", "BA", 11001],
    ["Trina", "PO", 11002],
    ["Will", "Dev", 11003]
]

#Write headers with bold font
for col_num, header in enumerate(headers, start=1):
    cell = sheet.cell(row=1, column=col_num, value=header)
    cell.font = Font(bold=True)


#Write rows
for row_num, row_data in enumerate(rows, start=2):
    for col_num, cell_value in enumerate(row_data, start=1):
       sheet.cell(row=row_num, column=col_num, value=cell_value)

#Save the workbook
workbook.save("C:\\Users\\Documents\\Vibha\\Automation\\FormattedExcel.xlsx")
print("Data is written the Excel file successfully")

Define the list “headers” containing the name of the headers. Iterate over the headers using enumerate(headers, start=1), which provides an index starting from 1. For each header, create a cell in the first row and corresponding column and set its value.

Use Font(bold=True) to make the font of the header bold and assign it to “cell.font”.

The output of the above program is

Formatted Excel

We are done! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

Reading Excel Data in Python using openpyxl

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Reading data from Excel files is a common practice in software development and testing. Excel provides a tabular format which is easy to understand and navigate. Data can be read from Excel for manipulation, analysis and visualization using Java, Python, R and soon. There are several ways to read the data from Excel in Python, but we will discuss openpyxl.

Prerequisite:

Python is installed
PIP is installed
PyCharms is installed

Sample Excel

Implementation Steps

Step 1 – Install openpyxl

Openpyxl can be installed using pip

pip install openpyxl

Step 2 – Load the workbook

workbook = load_workbook("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

Step 3 – Select the active worksheet

sheet = workbook.active

Step 4 – Read the Excel (.xlsx) file

for row in sheet.iter_rows(min_row=1, max_row=sheet.max_row, min_col=1, max_col=sheet.max_column):
    for cell in row:
        print(cell.value)

The complete program is

from openpyxl import load_workbook
from tabulate import tabulate

#Load the workbook
workbook = load_workbook("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

#Select the active worksheet
sheet = workbook.active

#Iterate over rows and columns
for row in sheet.iter_rows(min_row=1, max_row=sheet.max_row, min_col=1, max_col=sheet.max_column):
    for cell in row:
        print(cell.value)

The output of the above program is

sheet.iter_rows() is used to iterate over the specified rows and columns

cell.value extracts the data from the each cell.

As we can see that the output is not displayed in structured format.

To display the output in the structure format, use the below program:

from openpyxl import load_workbook
from tabulate import tabulate

#Load the workbook
workbook = load_workbook("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

#Select the active worksheet
sheet = workbook.active

#Display data in a structured format
for row in sheet.iter_rows(min_row=1, max_row=sheet.max_row, min_col=1, max_col=sheet.max_column):
    row_data =[]
    for cell in row:
        row_data.append((cell.value))
    print(row_data)

The output of the above program is

Display the Excel data in Tabular Format

Install the tabulate library

pip install tabulate

Below is the complete program:

from openpyxl import load_workbook
from tabulate import tabulate

#Load the workbook
workbook = load_workbook("C:\\Users\\Vibha\\Automation\\SearchInBing.xlsx")

#Select the active worksheet
sheet = workbook.active

#Display data in a tabular format
data =[]
for row in sheet.iter_rows(values_only = True):
    data.append(list(row))

print(tabulate(data, headers='firstrow', tablefmt='grid'))

sheet.iter_rows(values_only = True) reads the rowss in the sheet and values_only=True ensures that we get the cell values only. Collect the data onto a list of lists.

tabulate(data, headers=’firstrow’, tablefmt=’grid’) is used to print the data nicely in grid format. headers=firstrow uses the first row as headers and tablefmt=grid sets the format to a grid style.

The output of the above program is

We are done! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

Status Code, Line, Body, and Header Verification in Python Requests

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Python requests are generally used to fetch the content from a particular resource URI. Whenever we make a request to a specified URI through Python, it returns a response object. Now, this response object would be used to access certain features such as status code, status line, body, content, headers, etc. 

Table of Contents:

  1. Prerequisite:
    1. Verifying HTTP Response Status Code
    2. Handling different status code
    3. Raising an Exception for HTTP Errors
    4. Verifying HTTP Response Status Line
    5. Verifying HTTP Response Body
    6. Verifying HTTP Response Header Content Type

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

If you are using PyCharm IDE then you need to install the Request library. Execute the below command using pip.

pip install -U requests

Install pytest

pip install -U pytest

Verifying HTTP Response Status Code

A response code indicating the status of the request (e.g., 200 OK, 404 Not Found).  The status code that the server returns tells us whether the request was successful or not. If the request was successful, the server sends the status code in the range of 200-299. If the request was not successful, then the status code other than the range is returned.

response.status_code attribute allows us to access the HTTP status code returned by an HTTP request.

import requests


def test_get_statuscode():

    # Define the API endpoint
    url = "https://reqres.in/api/users/2"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve status code
    status_code = response.status_code

    # Display the results
    print("Status Code:", status_code)
    assert status_code == 200

Save above file as ResponseStatusCode_test.py and run using the below command:

pytest ResponseStatusCode_test.py -s

Note: -s is shortcut for –capture=no

The output of the above program is

Handling different status code

The requests library handles different status codes through the response.status_code attribute.

import requests


def test_get_statuscode():

    # Define the API endpoint
    url = "https://reqres.in/api/users/200000"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve status code
    status_code = response.status_code

    # Display the results
    if status_code == 200:
        print("Request is successful")
    elif status_code == 401:
        print("Unauthorized Request")
    elif status_code == 404:
        print("Resource not found")
    elif status_code == 500:
        print("Server Error")
    elif status_code == 503:
        print("Service Unavailable")
    else:
        print("Status Code:", status_code)

The output of the above program is

Raising an Exception for HTTP Errors

response.raise_for_status() method is use to raise an HTTP Error if the HTTP response returned an unsuccessful status code like 4xx, 5xx.

import requests


def test_get_statuscode():

    # Define the API endpoint
    url = "https://reqres.in/api/users/200000"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve status code
    status_code = response.status_code

    # Display the results
    try:
        response.raise_for_status()
        print("Request is successful")
    except requests.exceptions.HTTPError as http_err:
        print(f"HTTP error occurred : {http_err}")
    except Exception as err:
        print(f"Other error occurred: {err}")

The output of the above program is

Verifying HTTP Response Status Line 

import requests


def test_get_statusline():

    # Define the API endpoint
    url = "https://reqres.in/api/users/2"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve status line (in this example, requests library does not provide status line directly, so we can construct it)
    status_line = f"{response.status_code} {response.reason}"

    # Display the results
    print("Status Line:", status_line)
    assert status_line == "200 OK"

The output of the above program is

Verifying HTTP Response Body

response.content returns the content of the response, in bytes.

import requests


def test_get_responsebody():

    # Define the API endpoint
    url = "https://reqres.in/api/users/2"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve response content
    content = response.content

    # Display the results
    print("Response Content:", content)

The output of the above program is

Verifying HTTP Response Header Content Type

response.headers returns a dictionary of response headers. Headers are used for different purposes such as Authentication/ Passing and retrieving data from the server, etc.

import requests


def test_get_headers():

    # Define the API endpoint
    url = "https://reqres.in/api/users/2"

    # Make a GET request to the API endpoint
    response = requests.get(url)

    # Retrieve content type
    content_type = response.headers['Content-Type']

    # Display the results
    print("Content Type:", content_type)
    assert content_type == "application/json; charset=utf-8"

The output of the above program is

We are done! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!

vibssingh

How to handle HTTP Query Parameters in Python

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Query parameters are a way to pass information to an API flexibly and simply. They are added to the end of the API endpoint URL as a series of key-value pairs.  To append query params to the end of a URL, a ‘?’ Is added followed immediately by a query parameter.

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine
  4. Install pytest and requests

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

Query Param Example

https://reqres.in/api/users?page=2

Below is an example of Query Param in Postman

Below is an example of Query Param in Python

import requests

ENDPOINT = 'https://reqres.in/api/users/'


def test_verify_header():
    params = {
        'pages': 2
    }

    response = requests.get(ENDPOINT, params)
    print(response.json())

    print("Response Header", response.headers)

    #Assert status code
    assert response.status_code == 200

    # Assert Response Body
    response_body = response.json()
    assert response_body["per_page"] == 6

    assert response_body["data"][0]["id"] == 1

The output of the above program is

The tests can be run using the command line using the below command:

pytest QueryParam_test.py

The output of the above program is

Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

How to generate HTML Report in PyTest Framework

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In this tutorial, we will create a HTML Report in PyTest Framework. pytest-html is a plugin for pytest that generates a HTML report for test results.

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

Implementation Steps

Step 1 – Install pytest

pip install -U pytest

Step 2 – Install pytest-html

pip install pytest-html

Step 3 – Create a new project folder and open it in PyCharm.

Step 4 – Go to the project folder and create a new python file – sample_test.py.

Step 5 – Add pytest-html package to the PyCharms

Go to File->Settings ->Project: PyTest_Framework->Python Interpreter.

Click on the “+” sign and enter allure-r in the search bar. It will show a list of packages. Select the “pytest-html” package and click on the “Install Package”.

Once the package is installed, we will see the message that the package is installed successfully.

Step 6 – Create the test.

import pytest


def test_addition():
    a = 6
    b = 5
    c = 11

    assert a + b == 11, "Sum is not 11"
    assert a + b == c, "Sum of a and b is not equal to c"


def test_subtraction():
    x = 15
    y = 4
    z = 10

    assert x - y == z, "Subtract y from x is equal to z"


def test_multiplication():
    a = 6
    b = 5
    c = 30

    assert a * b == c, "Product of 5 and 6 is not 30"


def test_division():
    a = 16
    b = 2
    c = 8

    assert a / b == c, "Division of 2 by 6 is not 3"

Step 7 – To run this test, use the below command:

pytest --html=report.html

The output of the above execution is

The report.html report will be generated in the root directory.

Step 8 – Generating HTML report

Right-click and open with Web Browser.

That’s it! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

Configure Selenium with Python

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In this tutorial, we will configure Selenium with Python and create Selenium tests in Python.

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or another Python Editor is installed on the machine

Installation of Python Requests Module

Step 1 – Install Python

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

Step 2 – Install PyCharm

PyCharm is an Integrated Development Environment (IDE) specifically designed for the Python programming language. It is developed by JetBrains.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

Step 3 – Install the Selenium library

Execute the below command using pip.

pip install -U selenium

Step 4 – Create a new project

Create a new project and open it in PyCharm – SeleniumPython_Demo.

Step 5 – Create a new directory

Create a new directory – TestCases that will contain all the tests.

Step 6 – Create a test file

Create a new Python file, naming it “LoginTest.py”.

Step 7 – Add the Selenium package to the PyCharm

Go to File->Settings ->Project:SeleniumPython_Demo ->Python Interpreter.

Click on the “+” sign and enter selenium in the search bar. It will show a list of packages. Select the “selenium” package and click on the “Install Package”.

Once the package is installed, it can be seen under the package list as shown below:

Step 8 – Create the test

from selenium import webdriver
from selenium.webdriver.common.by import By

driver = webdriver.Chrome()
driver.maximize_window()
driver.implicitly_wait(2)
driver.get("https://opensource-demo.orangehrmlive.com/")

driver.find_element(By.NAME, "username").send_keys("Admin")
driver.find_element(By.NAME, "password").send_keys("admin123")
driver.find_element(By.XPATH, "//*[@class='oxd-form']/div[3]/button").click()

homePageTitle = driver.find_element(By.XPATH,"//*[@class='oxd-topbar-header-breadcrumb']/h6").text
print("Heading of DashBoard Page: ", homePageTitle)
driver.quit()

Importing necessary modules:

from selenium import webdriver
from selenium.webdriver.common.by import By

webdriver is used to automate the web browser. By is imported to specify the mechanism used to locate elements on a web page.

Setting up the web driver:

driver = webdriver.Chrome()

This line creates an instance of the Chrome WebDriver, which will be used to automate the Chrome browser.

Maximizing the browser window:

driver.maximize_window()

This line maximizes the browser window.

Implicitly waiting for elements:

driver.implicitly_wait(2)

This sets an implicit wait, meaning the WebDriver will wait up to 2 seconds for elements to be located before throwing an exception.

Navigating to a URL:

driver.get("https://opensource-demo.orangehrmlive.com/")

The script navigates the browser to the specified URL, which is the login page of an HR management system.

Enter the Credentials

driver.find_element(By.NAME, "username").send_keys("Admin")
driver.find_element(By.NAME, "password").send_keys("admin123")
driver.find_element(By.XPATH, "//*[@class='oxd-form']/div[3]/button").click()


In the method mentioned above, we can inspect and find the HTML element with which you want to interact. The script locates the username and password input fields on the page by their names and enters the credentials. The script locates the login button using an XPath expression and clicks it.

Fetching and printing the heading of the dashboard page:

homePageTitle = driver.find_element(By.XPATH,"//*[@class='oxd-topbar-header-breadcrumb']/h6").text
print("Heading of DashBoard Page: ", homePageTitle)

The script locates an element on the dashboard page (specifically an h6 element within a breadcrumb) and prints its text, which is assumed to be the heading of the dashboard page.

Quitting the browser:

driver.quit()

Finally, the script closes the browser window and ends the WebDriver session.

Step 9 – Execute the Tests

We need to move to the folder where the Python Tests are placed. In this case, we need to go to the TestCases folder.

To run the tests, use the below command:

pytest LoginTest.py -s

The output of the above program is

We are done! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

How to add environment details to Python Allure Report

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In this tutorial, we will add environment details to the Python Allure Report.

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

If you need to know the steps to generate an Allure Report, please refer to this tutorial – How to create Python Allure Report for Rest API.

For the main page of the report, you can collect various information about the environment in which the tests were executed.

For example, it is a good idea to use this to remember the OS version and Python version. This may help the future reader investigate bugs that are reproducible only in some environments.

os_platform = windows 11
os_release = 10.2
python_version = Python 3.12.1
environment = uat
release_no = 10
author = vibha singh

To provide environment information, put a file named environment.properties into the allure-results directory after running the tests. 

In our case, we have the AllureReport directory that will contain the files in JSON format needed to generate the Allure Report.

Below is an example of Allure Report with environment details.

That’s it! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!

vibssingh

How to create Python Allure Report for Rest API

HOME

In this tutorial, we will create an Allure Report for Rest API in Python.

Prerequisite:

  1. Python is installed on the machine
  2. PIP is installed on the machine
  3. PyCharm or other Python Editor is installed on the machine

If you need help in installing Python, please refer to this tutorial – How to Install Python on Windows 11.

If you need help in installing PyCharms, please refer to this tutorial – How to install PyCharms on Windows 11.

Installation of Python Requests Module

Step 1 – We are using PyCharm IDE, so we need to install the Request library. Use the below command using pip.

pip install -U requests

Step 2 – Install Pytest

pip install -U pytest

Step 3 – Install Allure Report for Python

pip install allure-pytest

Step 4 – Create a new project folder and open it in PyCharm.

Step 5 – Go to the project folder and Create a new directory – tests.

Step 6 – Add allure-pytest package to the PyCharms

Go to File->Settings ->Project: AllureReport_Python->Python Interpreter.

Click on the “+” sign and enter allure-r in the search bar. It will show a list of packages. Select the “allure-pytest” package and click on the “Install Package”.

Once the package is installed, we will see the message that the package is installed successfully.

Step 7 – Create the test.

Create a file – Requests.py and create the tests in that file.

import allure
import requests

ENDPOINT = 'https://reqres.in/api/users'


@allure.description("This tests validates that the response returns status code 201")
@allure.severity(allure.severity_level.BLOCKER)
@allure.label("Owner", "Vibha Singh")
def test_create_user():
    request_body = {
        "name": "Vibha",
        "Job": "CEO"
    }

    response = requests.post(ENDPOINT, request_body)
    response_body = response.json()
    print("Request :", request_body)
    print("Response :", response_body)
    assert response.status_code == 201


@allure.description("This tests validates that the id in the response")
@allure.severity(allure.severity_level.NORMAL)
@allure.label("Owner", "Vibha Singh")
def test_response():
    request_body = {
        "name": "Vibha",
        "Job": "CEO"
    }

    response = requests.post(ENDPOINT, request_body)
    assert response.status_code == 201
    response_body = response.json()
    print("Request :", request_body)
    print("Response :", response_body)

    id = response_body["id"]
    if "id" in response_body:
        print("Value of id :", id)
    else:
        print("id not found")


@allure.description("This tests validates that the header in the response")
@allure.severity(allure.severity_level.NORMAL)
@allure.label("Owner", "Vibha Singh")
def test_header_in_request():
    request_body = {
        "name": "Vibha",
        "Job": "CEO"
    }

    headers = {'Content-Type': 'application/json; charset=utf-8'}
    response = requests.post(ENDPOINT, request_body, headers)
    print("Request :", request_body)
    print("Response :", response.json())
    print("Headers :", response.headers)
    assert response.headers["Content-Type"] == "application/json; charset=utf-8"


@allure.description("This tests validates that the name in the response - FAIL")
@allure.severity(allure.severity_level.NORMAL)
@allure.label("Owner", "Vibha Singh")
def test_verify_name():
    request_body = {
        "name": "Vibha",
        "Job": "CEO"
    }

    header = {"Content-Type":  "application/json; charset=utf-8"}
    response = requests.post(ENDPOINT, request_body, header)
    response_body = response.json()
    print("Response :", response_body)
    print("Request Header :", response.request.headers)
    assert response_body["name"] == "Test"

Step 8 – To run this test, use the below command:

pytest --alluredir=<path to report directory> test.py

In my case, I want the allure files to be generated in AllureReport folder as shown below:

Below is the command we use to run the tests. This will generate a directory to the specified path with some files in JSON format.

pytest --alluredir=C:\Users\Documents\Vibha\Automation\Python\AllureReport_Python\AllureReport Requests.py

The output of the above program is

Step 9 – Generating Allure report

Now, we have the supported data that will be required to get the report, We just need to convert it into HTML so that we can see this on the browser.

Use the below command in the terminal/cmd:

allure serve <path to report directory>

I have used the below command:

allure serve C:\User\Documents\Vibha\Automation\Python\AllureReport_Python\AllureReport

It will start a jetty server within a few seconds and the report will be visible inside your browser.

The overview page hosts several default widgets representing the basic characteristics of your project and test environment.

  1. Statistics – overall report statistics.
  2. Launches – if this report represents several test launches, statistics per launch will be shown here.
  3. Behaviours – information on results aggregated according to stories and features.
  4. Executors – information on test executors that were used to run the tests.
  5. History Trend – if tests accumulated some historical data, it’s trend will be calculated and shown on the graph.
  6. Environment – information on the test environment.

Categories in Allure Report

The categories tab gives you a way to create custom defect classifications to apply for test results. There are two categories of defects – Product Defects (failed tests) and Test Defects (broken tests).

Suites in Allure Report

On the Suites tab a standard structural representation of executed tests, grouped by suites and classes can be found.

Graphs in Allure Report

Graphs allow you to see different statistics collected from the test data: statuses breakdown or severity and duration diagrams.

Timeline in Allure Report

The timeline tab visualizes retrospective of tests execution, allure adaptors collect precise timings of tests, and here on this tab, they are arranged accordingly to their sequential or parallel timing structure.

Behaviours of Allure Report

This tab groups test results according to Epic, Feature, and Story tags.

Packages in Allure Report

The packages tab represents a tree-like layout of test results, grouped by different packages.

That’s it! Congratulations on making it through this tutorial and hope you found it useful! Happy Learning!!