Python Automation Project: Media Collection

Python Automation Project: Media Collection & Instagram Reels Generator

Project Overview

I built a personal Python automation project as a practical learning exercise to explore web scraping, browser automation, file management, and automated video production.

The project combines several Python scripts into a workflow for collecting media, organizing files, creating short-form videos, adding background music, and preparing content for Instagram Reels.

What I Built

1. Media Collection with Python

Developed a Python script to collect photo-page URLs from Pexels using Selenium and Chrome automation, then retrieve and save image files using Requests. The script includes scrolling, duplicate-link filtering, manual CAPTCHA handling when required, and progress logging.

2. Automated File Renaming

Created a file-management script that scans an image directory, identifies supported image formats, sorts filenames, and renames files sequentially. A two-stage renaming process helps avoid filename conflicts when existing files already use numeric names.

3. Automated Video Editing

Developed a Python script using MoviePy to combine multiple source videos into a single short-form video. The workflow selects random sections from source clips, shuffles their order, adjusts clip durations to fit a target runtime, and combines the clips into a continuous video.

4. Background Music Integration

Implemented audio processing to add background music, trim longer audio tracks, and repeat shorter tracks when necessary to match the target video duration.

5. MP4 Export and Output Management

Configured the output resolution, frame rate, video codec, audio codec, and bitrate. The generated videos are saved automatically to a designated output folder.

Technologies Used

Python

Selenium

Undetected ChromeDriver

Requests

MoviePy

OS and file-system operations

Randomization and timing logic

MP4 video and audio processing

What I Learned

This project helped me practise browser automation, extracting links from web pages, downloading files, handling errors, organizing large collections of media, and building reusable automation workflows with Python.

The project was developed for personal learning and experimentation with short-form social media content. It demonstrates my interest in applying Python to practical automation tasks and developing more advanced web-scraping and data-processing solutions.

I am continuing to expand my Python skills through hands-on projects and experiments.