Laundry Lookup

A small Dash app for browsing and comparing laundry detergents, pretreaters, and boosters in one grid.

Data sourced by /u/KismaiAesthetics on Reddit.

AI Disclosure

This project was created with the assistance of GPT-5.4-Codex.

Run it

Docker (Registry)

docker pull strayingfromthepath/laundry:latest
docker run -p 8050:8050 strayingfromthepath/laundry:latest

Docker (Building Locally)

docker build -t laundry-app .
docker run -p 8050:8050 laundry-app

Git Clone and run:

git clone https://github.com/strayingfromthepath/laundry.git
cd laundry
uv sync
uv run python app.py

Then open http://127.0.0.1:8050.

Data

The app reads laundry_sheet.xlsx if it's present locally, or falls back to the linked Google Sheet export.

Scraping Enrichment

The repo now includes a first-pass enrichment pipeline for official disclosure and product pages.

Run the full scrape:

uv run python -m laundry_app.scraping

Run a subset of source families:

uv run python -m laundry_app.scraping --family wholefoods --family sprouts --family clorox

List available source families:

uv run python -m laundry_app.scraping --list-families

By default the pipeline writes CSV sidecar tables to data/enrichment/:

• product_sources.csv
• ingredients_long.csv
• unmatched_products.csv
• scrape_errors.csv
• summary.json

Current source-family coverage includes:

• Church & Dwight / OxiClean disclosure pages
• Whole Foods Market disclosure pages
• Sprouts California disclosure pages
• ECOS product pages with embedded ingredient tables
• Dirty Labs product pages
• Dropps disclosure landing pages
• Tide official product pages with SmartLabel source links
• Clorox official product pages with Label Insight / SmartLabel ingredient pages

This is intentionally a sidecar pipeline, not an app dependency. It is meant to generate enrichment tables you can join back to the workbook dataset over time.

When those CSVs are present, the product detail modal will surface official source links and ingredient snippets directly in the app.

Playwright for JS-only Pages

Use Playwright selectively, not as the default scrape path. It is most useful for:

• Tide SmartLabel pages on smartlabel.pg.com
• Dropps disclosure pages whose ingredient tables are client-rendered

Install the optional browser tooling:

uv sync --extra scraping-browser
uv run playwright install chromium

Then run the scraper with rendered-page support:

uv run python -m laundry_app.scraping --use-playwright

Everything else in the pipeline still works over plain HTTP, so this stays an opt-in path instead of slowing down the whole scrape.

Backend

The main logic is in components.py, which defines the layout and callbacks for the app.

Frontend

The frontend is built using Dash Bootstrap Components, Dash Mantine Components, and Dash AG Grid.