Casas Bahia Scraper — Brazil Retail Prices & Specs

Scrape product listings from Casas Bahia (casasbahia.com.br), one of Brazil's largest retailers, by category or search URL. Get clean, structured product data you can pipe straight into price monitoring, market research, repricing, or a catalog feed — pay per product returned, no subscription.

What you get

One row per product, in the order it appears on the page:

Field	Description
product_id	Casas Bahia product id (from the /p/<id> URL)
title	Full product name
url	Canonical product page URL
price	Cash / à-vista price as a number (BRL)
price_string	Price as shown (e.g. R$ 776,67)
currency	Always BRL
installment	Installment terms (e.g. por R$ 776,67 ou em até 10x de R$ 77,67 sem juros)
rating	Average star rating (0–5)
reviews_count	Number of customer reviews
is_sponsored	true if the slot is a sponsored placement
image_url	Product image URL
position	Position on the page (0-based)
source_url	The listing URL this product came from
scraped_at	ISO 8601 timestamp of the run

Input

Field	Type	Description
startUrls	array	Category / search listing URLs to scrape, e.g. https://www.casasbahia.com.br/smartphone/b. Paste any listing page from the site.
categoryUrl	string	Convenience: a single listing URL added to the list.
maxItems	integer	Max products to return across all listings (default 60; 0 = unlimited).

Find a listing URL by browsing the site to any category or search-results page and copying the address — for example …/geladeira/b, …/notebook/b, …/smartphone/b. The scraper paginates automatically until maxItems is reached.

Example input

{
  "startUrls": [
    { "url": "https://www.casasbahia.com.br/smartphone/b" }
  ],
  "maxItems": 60
}

Access & reliability

Casas Bahia renders its product grid client-side behind a bot-defence edge. This actor reaches the site through a built-in managed residential exit (Brazil) and a real browser, so the grid renders exactly as a shopper sees it — no proxy account, key, or setup is required on your side. Parsing keys on structural test hooks (not styling classes), so it keeps working across the site's front-end redeploys.

Pricing

Pay per product returned (pay-per-result). You are charged only for products actually delivered to your dataset — failed or empty pages cost nothing.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.