How I Built a Hybrid Cloud-to-Local Photo Workflow Using Google Sheets and Python

Ray Basweti — Tue, 03 Feb 2026 11:31:20 +0000

Bridging the gap between mobile culling and local file management without uploading 1TB of data.

As a developer and photographer, I faced a unique bottleneck. I wanted to select my best photos while sitting on the couch using my phone, but my 50MB RAW files lived on a massive hard drive in my office. I didn't want to pay for expensive cloud culling software, and I certainly didn't want to upload terabytes of data just to select 50 images.

My solution? A Hybrid Workflow using Google Sheets as a lightweight frontend and Python as the heavy-lifting backend.

The Architecture

1. The Cloud Interface (Google Apps Script)

I utilized Google Sheets not as a spreadsheet, but as a hosting platform for a custom HTML5 Web App.

Why Sheets? It handles authentication and hosting for free.

The UI: I built a responsive, mobile-first grid using the IBM Plex Sans design system. It allows for "Start/End" range input (e.g., IMG_8100 to IMG_8500) and renders clickable tiles.

The Output: Instead of saving data to a database, it generates a "Recipe" — a PDF file containing only the IDs of the selected photos.

2. The Local Engine (Python & Flask)

Once the "Recipe PDF" is generated, the local work begins.

The Stack: I wrapped a Python script in a Flask web server to provide a modern UI, but used Tkinter for native Windows folder dialogs (because browser file pickers are too restrictive).

The Logic:

The app parses the PDF using pypdf to extract IDs (e.g., 8104).

It scans a local source directory for matches, handling multiple file extensions (.CR2, .JPG, .NEF).

It performs a safe copy (not cut) to a destination folder.

Technical Challenges & Solutions

The "WinError 32" Lock

The Problem: On Windows, reading a PDF via Flask kept the file handle open. When I tried to move or delete the file later, the app crashed with PermissionDenied.

The Fix: I implemented a strict file.seek(0) and explicit stream closure pattern in Python to release the file handle immediately after parsing the text.

Mobile UX on Sheets

The Problem: Scrolling through 2,000 grid items on a phone was sluggish, and the interface felt like... well, a spreadsheet.

The Fix: I wrote custom CSS media queries to switch from a flexible grid to a strict 2-column layout on mobile, with increased touch targets and a sticky footer, making it feel like a native app.

The Result

This tool reduced a 2-hour workflow to 15 minutes. I can cull photos on my phone, AirDrop the PDF to my PC, and have Python extract the files instantly.

Future Plans

I am looking into packaging this as an Electron app for easier distribution and adding AI-based blur detection.

Built with 💙 by Ray Basweti. Check out the code on my Github.

DEV Community: Ray Basweti