Salla Store Scraper — Products, Prices & Stock
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Read any Salla (سلة) store and get every public product as clean structured data — Arabic names intact, prices in SAR, live availability. تصدير منتجات سلة.
Pricing
Pay per usage
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Developer
Hussein Al-Mansori
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10 days ago
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All notable changes to the Salla Store Scraper are recorded here.
First working version, not yet published to the Store. The launch scorecard has been run — 31 live stores and 855 products on 2026-08-22 — and its numbers are in the README and under Measured below.
platform on every row, always "salla". The Zid Store Scraper publishes the same field with
its own value and is otherwise field-for-field identical, so the two datasets concatenate into
one sheet and each row still says which storefront platform it came from. A column present in
one export and missing from the other would not survive that join, which is why this Actor
carries a field whose value never changes.
Reads Salla storefronts on both address shapes — a store on salla.sa/<store> and a store on
its own domain — from a store home page, a category page, or a single product page.
Two published row shapes, told apart by event: one product-scraped row per product and one
store-analyzed row per store. Every row is self-contained.
Discovery via the storefront catalogue service, with the store's sitemap as a fallback and a
direct read for a single product address. Which one was used is published as discoveryMethod.
Arabic and English product names kept in separate fields, assigned by the script the store actually wrote them in. Nothing is machine-translated.
maxItems, includeOutOfStock, includeVariants, language, respectRobots, and
proxyConfiguration inputs.
ErrorCode and HTTP_STATUS_BY_ERROR — the stable, published failure contract, including
NOT_A_SALLA_STORE, ROBOTS_DISALLOWED, STORE_UNREACHABLE, STORE_TIMEOUT, and
PRODUCT_PARSE_FAILED.
Bounded scheduler with deterministic, migration-safe row IDs, so a resurrected run never republishes or recharges a product it has already delivered.
Pay-per-event commit binding on the shared protocol with product-scraped and store-analyzed
events, declared but not priced. The Actor is free; only Apify's platform usage applies.
Docker build on the plain Python base — this Actor needs no browser.
hasOptions on each product row, so a product whose variants Salla will not publish is
distinguishable from a product that genuinely has none.
A bounded sample of each store's products is read a second time, from the product's own page,
and the two are compared. A disagreement about price or stock degrades that row to warning
with PRICE_MISMATCH or AVAILABILITY_MISMATCH; the store row publishes pricesCrossChecked
and pricesDisagreed.
Brand assets drawn from code (scripts/prepare_brand_assets.py), a pricing script that refuses
to publish an unmeasured tier (scripts/set_pricing.py), and the launch scorecard sweep
(scripts/run_store_scorecard.py).
salePrice no longer misreports a third of rows. Salla's catalogue uses 0 as its
no-discount sentinel rather than null, and its price field is the list price on some rows
and what the shopper actually pays on others — price=290 sale_price=145 regular_price=290 and
price=749 sale_price=749 regular_price=1099 are both real rows from live stores. Passing those
numbers through published salePrice: 0.0 on products that cost money, and salePrice equal to
price on products that were not discounted at all. Measured across 480 products on 8 live
stores: 67 rows (14%) advertised as free, a further 91 (19%) carrying a discount to their own
price, and every one of them status: "verified" with no warning.
price is now read from regular_price and a sale is claimed only when sale_price is a real
number below it, which is what the dataset schema has always labelled the two fields. The same
480 products now produce no zero sale prices and no self-discounts, and 117 genuine reductions
are visible where 26 were before — the regular_price the old mapping discarded was the one
that made a markdown legible.
The store cross-check could not have caught this: it accepts a page price matching either published number, and the number it matched was the one that was right.
robots.txt is now honoured for every address, not only the one submitted. The start URL
was checked and everything discovered afterwards was not, so a store that welcomed crawlers to
its front page and closed its product pages had those pages read anyway — by sitemap discovery
and by the price cross-check alike. Both now consult the policy before fetching. Skipped
product addresses raise ROBOTS_LIMITED_DISCOVERY, spelled as the Zid Actor spells it, so the
catalogue is never quietly short. A cross-check skipped this way is silent: not checking is not
a claim, and pricesCrossChecked already reports the smaller number.
A closed store is a warning, not an error. Salla serves a maintenance page, with HTTP 200,
for a store its owner has switched off. The store is real, so NOT_A_SALLA_STORE would be
wrong and silence would imply an empty catalogue.
maxItems is applied per store, not per run. A shared counter would make a row's identity
depend on how far another store had got when the container migrated, which breaks the
deterministic ID that stops double-charging. For a single-store run the two readings are
identical.
A store publishing no product options is counted, not warned about. Measured on live stores,
most Salla catalogues publish none; warning about it would make warning the usual status and
drain the field of meaning. The count is on the store row as productsWithOptions.
A URL slug is never published as a SKU. Salla fills the product page's structured sku with
the product's own address tail when the merchant set no SKU. No SKU stays null.
A disagreement is only claimed when the page matches neither price. Salla's product-page structured data publishes the regular price even while the shop shows a sale price, so a discounted product legitimately carries two different numbers. Comparing against the effective price alone reported a mismatch on every discounted product on a live store — a warning that fires on normal operation is worse than no warning at all.
Only a sample of each store is cross-checked. Checking every product would double the requests made of the store. The store row publishes how many were checked, so the strength of the claim is visible rather than implied.
The catalogue service has its own byte ceiling. One page of 15 products from a live store measured 2.15 MB, over the shared 2 MB page bound. Exceeding the ceiling is reported rather than truncated: a JSON body cut short would either fail to parse or, worse, parse into a partial catalogue that looks complete.
An output preview in the README built from rows a live run actually produced
(scripts/capture_output_rows.py + scripts/render_output_preview.py). No sample data is
written by hand.
Run against 31 live stores and 855 products on 2026-08-22
(scripts/run_store_scorecard.py): name, price and availability 100%, images 99.4%, categories
89.8%, SKU 13.7%, variants 0%. Of 153 products also read from their own product page, 11
disagreed — 92.8% agreement.
options payload under any parameter, the product page renders the option
group with an empty values array, and products/options prices a selection rather than
enumerating one. Those products carry hasOptions: true so the gap is visible instead of
looking like a product with no variants. Closing it means adding a browser, which this Actor
otherwise does not need.language reports whether a store publishes the requested language and warns when it does not.
It does not yet switch the catalogue, because the catalogue service answers in the store's own
default language.