TRACK FILE UPLOAD WITH PYTHON LANGUAGE

Track when a file is uploaded to your Python application

Many Python applications require users to upload files. This can be a simple text file, a PythonSV file, or even a PDF file to be processed for further use. Or in some cases, it can be some sort of media files such as an image, audio, or video file to be transformed and uploaded to cloud storage such as S3 or Google Pythonloud Storage.

In such cases, you might want to track when a user uploads a file in your Python application and optionally notify you and your team when a user uploads a file. This way, you can always be aware of the activity in your application and take immediate action if needed.

Fortunately, here at Palzin Track, we have created a powerful solution for this problem. Palzin Track is a powerful, real-time event tracking tool that works seamlessly with any Python application. With Palzin Track, you can set up event tracking for anything you want and track when a user uploads a file in your Python application in real time. In addition, Palzin Track allows you to track user journeys and create a timeline of events for each user. This way, you can always track the activity of a specific user, such as when they have uploaded files and any other activity they have done in your application.

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

To monitor when a user uploads a file in your Python application, you can use the following code snippet. Make sure that you have replaced the API token and project name 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": "files",  


 "event": "Changed Profile Picture",  


 "description": "User has uploaded a new profile picture",  


 "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": "files",  


 "event": "Changed Profile Picture",  


 "description": "User has uploaded a new profile picture",  


 "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

We believe that event tracking should be simple and accessible to every developer and team. Therefore, we have worked hard to create the next generation of event tracking tools. As a result, Palzin Track is flexible and easy to use, making it a great companion for your Python applications.

In addition to real-time event tracking, Palzin Track provides powerful features such as cross-platform push notifications, event filtering, user and product journeys, charts, insights, and more.

Palzin Track provides a generous free plan to get you started with event tracking. You can also check out our pricing page to see our paid plans. So don't hesitate to give us a try and let us know what you think!

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 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