TRACK SIGN IN EVENTS WITH PYTHON LANGUAGE

Track user sign in events in Python

Most of the time, when building a Python product that requires users to authenticate and sign in to access the product, you may decide that it is essential to track the sign-in attempts.

Monitoring the sign-in events is an excellent way to track the number of users who continue to log in and use your Python application. This is a great way to gauge the effectiveness of your product and measure your user retention rate.

A good understanding of this metric is critical to the success of a product. It can give you great insight into how your business grows and how your users interact with your Python product.

An easy way to set up event tracking is to use Palzin Track, a simple event tracking tool that works seamlessly with Python.

Connect Palzin Track to Python

Start monitoring user sign-in events

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

All you have to do next is to copy the following code snippets into your Python code and replace the YOUR_API_TOKEN and project values with your API token and project name.

Using Python with http.client

import http.client  


import json  


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


payload = json.dumps({  


 "project": "my-project",  


 "channel": "auth",  


 "event": "User Signed In",  


 "description": "email: [email protected]",  


 "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": "auth",  


 "event": "User Signed In",  


 "description": "email: [email protected]",  


 "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 versatile event tracking tool that isn't limited to specific use cases. It empowers you to monitor a wide range of events, whether it's tracking prelaunch waitlist signups or beta signups for a new feature or product. It works seamlessly with Python and makes it easy to track almost anything in your Python code.

Furthermore, Palzin Track allows you to generate charts and analytics based on your data. For instance, you have the flexibility to craft a chart illustrating the daily or monthly influx of waitlist signups for your product.

Additionally, you have the capability to establish funnels for monitoring the conversion rate from waitlist signups to paying customers, features usage in your application. Furthermore, you can generate user journeys to observe how users interact with your product once they gain access to it.

Palzin Track is accessible on both desktop and mobile platforms, offering the convenience of real-time notifications upon the addition of waitlist signups. You also have the flexibility to opt for push notifications for any other events you wish to track.

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 exceeds the usage limit for your Python service
15. Monitor when a user is being rate limited in your Python application
16. Get a notification when your Python code is done executing
17. Send push notifications to your phone or desktop using Python
18. Track canceled subscriptions in your Python application
19. Track your Python cron jobs
20. Track when a file is uploaded to your Python application
21. Track when a form is submitted to your Python application
22. Track payment events via Python
23. Monitor user signup events via Python
24. Track waitlist signup events via Python