Utility functions for Jupyter/Colab notebooks
Project description
🧰 tsilva-notebook-utils
🔬 Handy utilities for enhancing your Jupyter and Google Colab notebooks
📖 Overview
tsilva-notebook-utils is a collection of utility functions designed to make working with Jupyter and Google Colab notebooks more efficient. It provides tools for video rendering, notification systems, and Colab-specific features like automatic disconnection after idle periods.
🛠️ Usage
Video Rendering
from tsilva_notebook_utils import render_video
# Render a simple video from frames
frames = [frame1, frame2, frame3] # List of numpy arrays
video = render_video(frames, fps=30, scale=1.5)
display(video)
# Render frames with labels
labeled_frames = [(frame1, "Start"), (frame2, "Middle"), (frame3, "End")]
video = render_video(labeled_frames, fps=24)
display(video)
# Compare multiple videos side by side
from tsilva_notebook_utils import render_videos
render_videos([(video1_frames, "Original"), (video2_frames, "Processed")])
Google Colab Utilities
from tsilva_notebook_utils import disconnect_after_timeout
# Automatically disconnect Colab after 5 minutes of inactivity
disconnect_after_timeout(timeout_seconds=300)
Notifications
Send notifications to PopDesk notification server:
from tsilva_notebook_utils import send_popdesk_notification
# Send a notification when your long-running notebook task completes
send_popdesk_notification(
url="https://your-popdesk-url",
auth_token="your-auth-token",
title="Training Complete",
message="Your model has finished training with 95% accuracy"
)
📄 License
This project is licensed under the MIT License.
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