08, Jul 2023

MONITOR USAGE LIMIT EXCEEDED WITH PYTHON LANGUAGE

Palzin Track Python Use Cases

Monitor when a user exceeds the usage limit for your Python service

In today's landscape, many services are adopting a pay-as-you-go approach, which can be based on either monthly usage limits or metered usage. This trend is particularly prevalent in cloud computing, software, and various online services. If you are developing a Python-based service, you will likely need to establish your usage model and associated limits.

Irrespective of your specific implementation, it becomes essential to create an internal system for tracking usage and setting up notifications to alert you and your team when a user reaches their designated limit. This is a common challenge, as it provides valuable insights into how your users utilize your service, enabling you to enhance your product based on user behavior.

Enter Palzin Track, a service designed to offer real-time event tracking. It serves as an ideal solution for this task and seamlessly integrates with Python. Palzin Track simplifies the process of transmitting events to your dashboard and facilitates push notifications whenever critical events occur.

For instance, consider a scenario where you are developing a Python-based service that allows users to upload files, but you wish to impose a limit of ten uploads per user. Palzin Track comes to the rescue by enabling you to send events to your dashboard whenever a user uploads a file. Additionally, you can configure a rule to notify you when a user hits the ten-file upload limit. This functionality ensures you are promptly informed when a user reaches their designated threshold, empowering you to take further action as needed.

Connect Palzin Track to Python


Setting up Palzin Track

  1. Sign up for a free Palzin Track account.
  2. Create your first project from the dashboard.
  3. Head to settings and copy your API token.

Python code snippets

Copy the following code snippet to your Python project. Please note that you will need to replace the API token with your own.

Using Python with http.client


import http.client  


import json  


conn = http.client.HTTPSConnection("palzin.live")  


payload = json.dumps({  


 "project": "my-project",  


 "channel": "limits",  


 "event": "Usage Limit Exceeded",  


 "description": "The user has exceeded the usage limit for the service.",  


 "icon": "🚨",  


 "notify": True  


})  


headers = {  


 'Content-Type': 'application/json',  


 'Authorization': 'Bearer YOUR_API_TOKEN'  


}  


conn.request("POST", "/api/v1/log", payload, headers)  


res = conn.getresponse()  


data = res.read()  


print(data.decode("utf-8"))

Using Python with Requests


import requests  


import json  


url = "https://api.palzin.live/v1/log"  


payload = json.dumps({  


 "project": "my-project",  


 "channel": "limits",  


 "event": "Usage Limit Exceeded",  


 "description": "The user has exceeded the usage limit for the service.",  


 "icon": "🚨",  


 "notify": True  


})  


headers = {  


 'Content-Type': 'application/json',  


 'Authorization': 'Bearer YOUR_API_TOKEN'  


}  


response = requests.request("POST", url, headers=headers, data=payload)  


print(response.text)

Python integration details

Palzin Track is a flexible and easy-to-use event tracking service that works excellently with Python. In addition to real-time event tracking and cross-platform push notifications, Palzin Track provides powerful user journey tracking, simple event filtering, search, and analytic tools such as charts.

In addition to tracking usage events, you can also use Palzin Track to track other important events such as errors, user sign-ups, user logins, payments, or anything else you can think of.

Setting up Palzin Track with your Python application takes a few minutes, and you can start tracking events in no time.

Other use-cases for Palzin Track

  1. Monitor your CI/CD build status for your Python application
  2. Monitor your CPU usage in your Python application
  3. Monitor when database goes down in your Python application
  4. Monitor high disk usage in your Python application
  5. Monitor when a user changes their email address in your Python application
  6. Monitor failed logins in your Python application
  7. Monitor failed payments for your Python application
  8. Monitor memory usage in your Python application
  9. Monitor MySQL downtime in your Python application
  10. Monitor when a new feature is used in your Python application
  11. Monitor your Postgres downtime in your Python application
  12. Monitor Redis downtime in your Python application
  13. Monitor suspicious activity in your Python application
  14. Monitor when a user is being rate limited in your Python application
  15. Get a notification when your Python code is done executing
  16. Send push notifications to your phone or desktop using Python
  17. Track canceled subscriptions in your Python application
  18. Track your Python cron jobs
  19. Track when a file is uploaded to your Python application
  20. Track when a form is submitted to your Python application
  21. Track payment events via Python
  22. Track user sign in events in Python
  23. Monitor user signup events via Python
  24. Track waitlist signup events via Python

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