Track File Uploads in Your Python Application

File uploads are common functionalities in many Python applications, allowing users to share files and media. Monitoring and tracking file uploads is essential for maintaining data integrity, managing storage usage, and ensuring a smooth user experience.

Saashound, a powerful real-time event tracking tool, offers seamless tracking of file uploads in your Python application. By integrating Saashound directly into your application, you can effortlessly monitor file upload events and gain insights into user interactions.

Connecting Saashound to Your Python Application

To begin tracking file uploads in your Python application using Saashound, follow these simple steps:

  1. Sign up for a free Saashound account to start tracking your application’s events.
  2. Create your first project from the user-friendly dashboard.
  3. Access the settings and securely copy your unique API token.

Python Integration

Integrating Saashound into your Python application is straightforward. Use the following code snippet to track file uploads. Remember to replace API_TOKEN with your actual Saashound API token and update the project name to match your project.

Using requests
import json
import requests
def log_event():
api_url = 'https://api.saashound.co/log-event'
payload = {
"project": "my-project",
"channel": "user-activity",
"event": "File Upload",
"description": "User ID 12345 has uploaded a file 'example.txt'.",
"icon": "đź“‚",
"notify": True # Replace with the appropriate value
}
headers = {
'Content-Type': 'application/json',
'Authorization': 'Bearer API_TOKEN' # Replace API_TOKEN with your actual API token
}
try:
response = requests.post(api_url, data=json.dumps(payload), headers=headers)
if 200 <= response.status_code < 300:
print('Log event sent successfully!')
else:
print('Failed to send log event. Response code:', response.status_code)
except requests.exceptions.RequestException as error:
print('Error sending log event:', error)
log_event()

With Saashound tracking file uploads, you can:

  • Real-Time Monitoring: Monitor file uploads in real-time, ensuring smooth and reliable upload processes.
  • Storage Management: Track file upload sizes and frequencies to manage your application’s storage efficiently.
  • User Behavior Analysis: Gain insights into user interactions by tracking when and what type of files are being uploaded.
  • Custom Alerts: Set up custom alert rules to notify your team about specific file upload events.

Saashound Benefits

Saashound is designed to be user-friendly and accessible to developers and teams of all sizes. Here are some key benefits of using Saashound for tracking file uploads in your Python application:

  • Ease of Use: Saashound offers a no-code event tracking solution, making it simple for anyone to implement and use.
  • Flexible Integration: Saashound can seamlessly integrate with your Python application, capturing various file upload events.
  • Cross-Platform Support: Saashound’s cross-platform push notifications deliver alerts to your preferred devices, keeping you informed from anywhere.
  • Event Filtering: Customize which file upload events to track and receive notifications for, focusing on the most critical data.
  • Insights and Analytics: Utilize Saashound’s charts and analytics to visualize file upload data and gain valuable insights.

By leveraging Saashound’s tracking capabilities, you can ensure the seamless functionality of file uploads in your Python application, better understand user behavior, and optimize your application’s file management system.

Other use-cases for SaasHound

  1. Monitor API Authorization and Access Control in your Python Application
  2. Monitor API Response Times in your Python Application
  3. Monitor CPU and Memory Usage of External Services Accessed by your Python Application
  4. Monitor CPU Usage in your Python Application
  5. Monitor when a Database Goes Down in your Python Application
  6. Monitor Database Query Performance in your Python Application
  7. Monitor High Disk Usage in Your Python Application
  8. Monitor when a user changes their email address in your Python application
  9. Monitor failed logins in your Python application
  10. Monitor failed payments for your Python application
  11. Monitor memory usage in your Python application
  12. Monitor MySQL downtime in your Python application
  13. Monitor when a new feature is used in your Python application
  14. Monitor your Postgres downtime in your Python application
  15. Monitor Redis downtime in your Python application
  16. Monitor Server Health and Uptime in your Python Application
  17. Monitor suspicious activity in your Python application
  18. Monitor when a user is being rate limited in your Python application
  19. Monitor when a user exceeds the usage limit for your Python service
  20. Get a notification when your Python code is done executing
  21. Send push notifications to your phone or desktop using Python
  22. Track A/B Testing and Feature Rollouts in your Python Application
  23. Track canceled subscriptions in your Python application
  24. Track Cron Jobs in Python
  25. Track when a form is submitted to your Python application
  26. Track your Python cron jobs
  27. Track payment events via Python
  28. Track User Engagement Metrics in your Python Application
  29. Track user sign in events in Python
  30. Track user signup events via Python
  31. Track waitlist signup events via Python