First Script

 Let's break down the code in detail and point out any necessary corrections:

1. Imports:

python
import json
import keyring
import requests

• json: This is used to convert Python objects into JSON strings and vice versa, which is needed when sending and receiving data in JSON format with the API.
• keyring: This module allows secure storage and retrieval of credentials (in this case, the password for the service user). This is a good practice to avoid hardcoding passwords in the script.
• requests: This library is used to send HTTP requests (e.g., POST requests) in Python.

2. Credentials:

python
user_name = 'SVC_SN_DEV_AT16933'
pwd = keyring.get_password('dev', user_name)

• user_name: This stores the service account username.
• pwd: The keyring.get_password method retrieves the stored password associated with the user_name for the given 'dev' service. This avoids hardcoding sensitive credentials.

3. API Root and Headers:

python
instance_api_root = 'https://atlas-api.ubsdev.net/api/'
headers = { 'Content-Type': 'application/json', 'Accept': 'application/json' }

• instance_api_root: This stores the root URL for the API (a placeholder URL in this example).
• headers: The headers specify that the content is JSON and the server should respond in JSON format.

4. Endpoint and Sys ID:

python
cat_item_sys_id = '4516dddd87cf06d00dc141d30cbb358b'
api_endpoint = 'sn_sc/servicecatalog/items/{0}/order_now'.format(cat_item_sys_id)

• cat_item_sys_id: A system identifier, likely for a catalog item in a service catalog.
• api_endpoint: A formatted string that dynamically injects the cat_item_sys_id into the URL endpoint. The final endpoint would look like:

  arduino
  'sn_sc/servicecatalog/items/4516dddd87cf06d00dc141d30cbb358b/order_now'
  

5. Data to Send:

python
data = {
   'sysparm_requested_for': '3792a9cf4799b1d050d346f8736d4334',
   'sysparm_quantity': 1, 
   'variables': {'hostname': 'ZU322K10'}
}

• This is the JSON payload that is sent with the POST request. It includes:
  • sysparm_requested_for: Likely the user or system requesting the service.
  • sysparm_quantity: The quantity being ordered.
  • variables: A dictionary of custom variables. In this case, it includes a hostname variable.

6. POST Request:

python
response = requests.post(
   '{0}{1}'.format(instance_api_root, api_endpoint),
   auth (user_name, pwd),
   data = json.dumps(data),
   headers = headers,
   verify = False
)

• This is where the issue arises. The auth argument is missing an equal sign (=), and it's incorrectly structured. It should be:

  python
  auth=(user_name, pwd)
  

• The correct way to write this request is:

  python
  response = requests.post(
     '{0}{1}'.format(instance_api_root, api_endpoint),
     auth=(user_name, pwd),
     data=json.dumps(data),
     headers=headers,
     verify=False
  )
  

• auth=(user_name, pwd): This argument is used for basic authentication, passing the username and password.
• data=json.dumps(data): The data dictionary is converted to a JSON string before sending.
• verify=False: This disables SSL certificate verification, which is not recommended in production environments but can be useful during development if the server uses self-signed certificates.

7. Response Handling:

python
print(response.text)

• This will print the response body (in text format) to the console, allowing you to see the result of the API request.

Corrected Code:

python
import json
import keyring
import requests

user_name = 'SVC_SN_DEV_AT16933'
pwd = keyring.get_password('dev', user_name)

instance_api_root = 'https://atlas-api.ubsdev.net/api/'
headers = { 'Content-Type': 'application/json', 'Accept': 'application/json' }

cat_item_sys_id = '4516dddd87cf06d00dc141d30cbb358b'
api_endpoint = 'sn_sc/servicecatalog/items/{0}/order_now'.format(cat_item_sys_id)

data = {
   'sysparm_requested_for': '3792a9cf4799b1d050d346f8736d4334',
   'sysparm_quantity': 1, 
   'variables': {'hostname': 'ZU322K10'}
}

response = requests.post(
   '{0}{1}'.format(instance_api_root, api_endpoint),
   auth=(user_name, pwd),
   data=json.dumps(data),
   headers=headers,
   verify=False
)

print(response.text)

Key Corrections:

• Added = in auth=(user_name, pwd) to ensure the authentication argument is correctly passed to the requests.post() function.

You said:

The above code was tried to generate REQ details from ATLAS. How to test the script? Can I test it by API endpoint? Do you have any suggestions to make it less hardcoded? I am using azure environment for all development.

ChatGPT said:

Yes, you can test the script by making actual calls to the API endpoint, assuming that the API is live and accessible from your environment. However, there are some considerations for testing and improving the script to make it less hardcoded and more robust:

1. Testing the Script:

To test the script:

1. Check API Accessibility: Make sure the instance_api_root (API endpoint) is accessible from your environment (Azure). You can use a tool like Postman or curl to send a manual POST request to the endpoint to check the response.

2. Run the Script: You can run the script in your development environment or directly in Azure (for example, using Azure Cloud Shell or an Azure VM). Make sure the script has access to the required credentials.

3. Inspect the Response: Check the response by printing response.status_code and response.text. This will help you understand whether the API call is succeeding or failing, and why.

4. Use a Debugging Tool: If your API call isn't working, you can log the request and response using the logging library or inspect headers to ensure they are correct:

   python
   import logging
   logging.basicConfig(level=logging.DEBUG)
   

2. Suggestions to Make the Script Less Hardcoded:

To improve the script and make it more flexible, here are some changes you can make:

a. Use Environment Variables (Best Practice for Azure):

Instead of hardcoding credentials, system IDs, and other sensitive information in your code, store them in environment variables. Azure has built-in support for securely managing application settings, such as credentials, via Azure Key Vault and Azure App Configuration.

You can access environment variables in Python using os.environ:

python
import os

user_name = os.environ.get('USER_NAME')
pwd = keyring.get_password('dev', user_name)
instance_api_root = os.environ.get('API_ROOT')
cat_item_sys_id = os.environ.get('CAT_ITEM_SYS_ID')

You can set these environment variables in Azure either at the App Service level (if using Web Apps) or in a VM's configuration.

b. Use Azure Key Vault for Secrets:

For storing sensitive data (like passwords), you can use Azure Key Vault. The Key Vault allows you to securely store secrets, and access them programmatically using the Azure SDK.

For example:

bash
# In Azure CLI
az keyvault secret show --name <secret-name> --vault-name <vault-name>

In Python, you can access Key Vault secrets using azure-identity and azure-keyvault-secrets libraries:

python
from azure.identity import DefaultAzureCredential
from azure.keyvault.secrets import SecretClient

credential = DefaultAzureCredential()
secret_client = SecretClient(vault_url="https://<your-key-vault-name>.vault.azure.net/", credential=credential)

# Retrieve secret
user_name = secret_client.get_secret("<your-username-secret>").value

c. Dynamic Endpoints and Parameters:

To avoid hardcoding things like cat_item_sys_id and other parameters, you can dynamically pass these values via:

• Command-line arguments: Use argparse to pass parameters when running the script.
• Configuration files: Store dynamic values in a .json or .yaml configuration file and read them using Python.

Example using a .json config file:

json
{
  "instance_api_root": "https://atlas-api.ubsdev.net/api/",
  "cat_item_sys_id": "4516dddd87cf06d00dc141d30cbb358b",
  "requested_for": "3792a9cf4799b1d050d346f8736d4334",
  "hostname": "ZU322K10"
}

You can read the JSON file in your Python script:

python
import json

with open('config.json') as config_file:
    config = json.load(config_file)

instance_api_root = config['instance_api_root']
cat_item_sys_id = config['cat_item_sys_id']

d. Error Handling:

Implement error handling to catch exceptions in case the API call fails or times out:

python
try:
    response = requests.post(
        '{0}{1}'.format(instance_api_root, api_endpoint),
        auth=(user_name, pwd),
        data=json.dumps(data),
        headers=headers,
        verify=False
    )
    response.raise_for_status()  # Raise an exception for HTTP errors
except requests.exceptions.RequestException as e:
    print(f"An error occurred: {e}")

e. Use a Logging System:

Instead of printing errors, log them to a file for better debugging, especially in an Azure environment:

python
import logging

logging.basicConfig(filename='app.log', level=logging.INFO)
logging.info('API Request made to %s', instance_api_root)

3. Integration with Azure Development Environment:

If you're using Azure Pipelines for continuous integration, or Azure Functions to run this script, ensure that:

• Environment variables are managed using Azure's configuration management.
• Any Azure resources (Key Vault, Storage) are connected securely via managed identities.
• For automation, this script can be part of a scheduled Azure Function or Logic App for triggering workflows.

By applying these practices, your script will be more secure, flexible, and adaptable to changes in different environments.