# Changelog of Home Depot Product Scraper (`sian.agency/home-depot-product-scraper`) Actor

- **URL**: https://apify.com/sian.agency/home-depot-product-scraper/changelog.md
- **Full Actor documentation**: https://apify.com/sian.agency/home-depot-product-scraper.md

## Changelog

All notable changes to the Home Depot Product Scraper will be documented in this file.

### 2026-09-19

#### 🏬 In-store stock is now the store shelf, not the warehouse

- **`store_quantity` now reports what the store actually holds.** Home Depot's "ship to store"
  option is listed under *pickup* and repeats your store's own name and number, but the quantity
  attached to it is a distribution-centre figure. It was being published as in-store stock — on a
  sample page one product read **1,457 units in stock when the shelf held 3**.
- **`in_stock` and `store_name` follow the same rule** and now describe your store only.
- **Products stocked online only return `null`** for these three fields instead of a warehouse
  number dressed up as shelf stock. `availability_type` still tells you how the item is fulfilled.

#### 💎 User Benefits

- In-store quantities you can act on, instead of numbers inflated by 100× or more
- A blank cell now honestly means "not carried at this store", so store-level filters are reliable

#### 🎯 Use Cases

- Local inventory checks and store-level restock alerts
- Assortment analysis that compares what individual stores actually carry

### 2026-08-28

#### 🧾 Dataset views

- **Every row now carries its own processed-at timestamp, scraping date and processing status**,
  so you can filter, sort or audit a dataset without cross-referencing the run log.
- **Product image URLs now render as clickable links across every dataset view**, not only the
  thumbnail column.

#### 💎 User Benefits

- Filter or sort exports by when a row was scraped, without opening the run details
- Confirm at a glance which rows finished successfully

#### 🎯 Use Cases

- Analysts merging multiple runs who need a per-row scrape timestamp to dedupe correctly
- QA teams spot-checking a batch export for rows that need a re-run

### 1.0.6 — 2026-08-24

#### 📄 Run report

- **Every run now hands you a report you can read.** Open "Processing Report" on the run and you get
  your first product in full, a preview table of the rows you received, what each row cost, and a
  ready-to-paste retry input for anything that came back incomplete.
- **The charges statement is built from what you were actually billed**, so you can check the invoice
  against the `source` column in your own dataset, row by row.
- **A run stopped by the free-run limit still writes the report**, so the run that most needs
  explaining no longer finishes silently.

#### 🖼️ Dataset views

- **Product images now render as pictures in the dataset table**, not as raw links — scan a catalog
  of drills, faucets or patio sets visually instead of opening every URL.
- Clearer column labels across both the full-field view and the curated key-field view.

#### 💎 User Benefits

- See what a run delivered and what it cost without leaving the Apify Console
- Retry only the searches that came back short, straight from the report
- Faster visual QA on large product pulls thanks to inline images

#### 🎯 Use Cases

- Pricing analysts reconciling a Home Depot price monitoring run against their bill
- E-commerce teams eyeballing a fresh product catalog before exporting to CSV
- Agencies handing a client a shareable summary of a competitive analysis run

### 1.0.5 — 2026-08-13

#### 🎁 Free tier

- **Free-plan limits are now explicit.** 25 products per run in Overview mode, 5 in Detail mode, and
  6 runs per day (resetting at 00:00 UTC). Start free runs from the Apify Console — API and
  scheduled runs need a paid Apify plan. Paid plans are unchanged: unlimited results, no daily cap,
  full API access.

#### 💰 Billing

- **The run now stops delivering when it can no longer be billed.** If Apify refuses a charge — no
  credits, no valid billing, or your own "Max total charge" limit reached — the run ends with a
  clear explanation instead of continuing to produce results you cannot be charged for.

### 1.0.4 — 2026-08-02

#### 💰 Billing

- **Detail mode only charges the detail rate when the enrichment actually arrives.** If Home Depot
  fails to return specifications and a description for a product, the search result is still
  delivered — now billed at the overview rate instead of the detail rate. A single run can contain
  both, priced per row.
- Rows that were not enriched keep `source: "overview"`, so the dataset itself shows what you paid for.

#### 🔧 Reliability

- **A blocked run now says so.** When Home Depot turns the request away, the run reports a
  temporary retrieval problem you can retry, instead of "no results". A search that genuinely
  has no matches is now easy to tell apart.

### 1.0.0 — 2026-06-21

#### 🎉 Home Depot Product Scraper — Launch!

- **Keyword & Category Search** - Scrape any Home Depot search term or category page, no code required
- **Overview & Detail Modes** - Fast search results, or full enrichment with the complete specifications table and long product description
- **Per-Store Pricing & Inventory** - Pull localized prices and live in-store stock for any Home Depot store ID
- **Complete Product Data** - Price, list price, promotions, ratings, review counts, images, brand, model, and UPC for every product
- **Clean JSON & CSV Export** - Download structured, ready-to-use product data straight from the Apify dataset

#### 💎 User Benefits

- Save hours of manual checking with automated, on-demand Home Depot product data
- Monitor prices, promotions, and stock across thousands of products in a single run
- Get analysis-ready data in JSON, CSV, or Excel — no scripts, no maintenance
- Start free with 25 products per run, then scale to unlimited results on the paid tier

#### 🎯 Use Cases

- Retailers tracking Home Depot price monitoring and reacting to promotions
- Brands running competitive analysis on price, rating, and availability
- E-commerce teams building a product catalog with images and full specifications
- Manufacturers performing MAP compliance monitoring across listings
- Merchandisers doing assortment and in-store availability research