# Sima Land Product Search Scraper (`stealth_mode/sima-land-product-search-scraper`) Actor
Scrape product listings from Sima-land.ru search results with precision. Collect product names, prices, ratings, reviews, stock status, discounts, and 20+ additional fields per item. Perfect for price monitoring, market analysis, and product data aggregation.
- **URL**: https://apify.com/stealth\_mode/sima-land-product-search-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Automation, Developer tools, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Sima-land Product Search Scraper: Extract E-Commerce Data at Scale
---
### What Is Sima-land.ru?
Sima-land.ru is a major Russian e-commerce platform offering a wide range of products across multiple categories. The site hosts thousands of product listings updated regularly with pricing, stock status, and promotional information. Manually collecting product data from search results is labor-intensive — the **Sima-land Product Search Scraper** automates this process, delivering structured product intelligence instantly.
---
### Overview
The **Sima-land Product Search Scraper** extracts comprehensive product data from search results pages on Sima-land.ru, transforming raw listings into clean, structured datasets. It is ideal for:
- **Price monitoring** — Track competitor pricing and promotional activity
- **Market research** — Analyze product availability, ratings, and trends
- **Product aggregators** — Feed product data into price comparison platforms or catalogs
- **Business intelligence** — Build datasets for inventory and sales analysis
- **Retailers** — Monitor category performance and product positioning
The scraper handles pagination automatically, supports configurable item limits, and gracefully manages failed URLs, making it robust for large-scale operations.
---
### Input Format
The scraper accepts a JSON configuration object with three main parameters:
```json
{
"urls": [
"https://www.sima-land.ru/search/p3/?per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"
],
"ignore_url_failures": true,
"max_items_per_url": 200
}
````
| Parameter | Type | Description | Example |
|---|---|---|---|
| `urls` | Array | Sima-land search result page URLs you want to scrape | `["https://www.sima-land.ru/search/..."]` |
| `max_items_per_url` | Integer | Maximum products to collect per URL (1–200 recommended) | `200` |
| `ignore_url_failures` | Boolean | If `true`, continues scraping even if some URLs fail; if `false`, halts on first error | `true` |
**How to get URLs:**
1. Go to Sima-land.ru and perform a product search
2. Use the filters and sorting options (category, price range, popularity, etc.)
3. Copy the full URL from your browser (includes query parameters like `q=`, `sort=`, `per-page=`)
4. Paste into the `urls` array
> **Tip:** URLs typically include query parameters (`q=` for search term, `sort=` for sorting, `per-page=` for page size). Keep these intact for accurate scraping.
***
### Output Format
**Sample output**
```json
{
"badges": [
{
"hint": {
"text": "На товар действует скидка в указанном размере.",
"text_html": "На товар действует скидка в указанном размере. Посмотреть все товары со скидкой.",
"title": "Скидка"
},
"type": "b-discount",
"href": "/sale/?is_label=1",
"rel": null,
"color": "#2962FF",
"fields": [
{
"type": "text",
"value": "-20%"
}
]
},
{
"hint": {
"text": "Товар с небольшими недочётами.",
"text_html": "Товар с небольшими недочётами. Посмотреть все уценённые товары.",
"title": "Уценка"
},
"type": "b-markdown",
"href": "/markdown/?is_label=1",
"rel": null,
"color": "#607D8B",
"coloring": "outline",
"fields": [
{
"type": "text",
"value": "Уценённый товар"
}
]
}
],
"discount_badge": {
"hint": {
"text": "На товар действует скидка в указанном размере.",
"text_html": "На товар действует скидка в указанном размере. Посмотреть все товары со скидкой.",
"title": "Скидка"
},
"type": "b-discount",
"href": "/sale/?is_label=1",
"rel": null,
"color": "#2962FF",
"fields": [
{
"type": "text",
"value": "-20%"
}
]
},
"is_enough": true,
"can_add_to_waiting_list": true,
"rating": 5,
"reviews_count": 324,
"prices": {
"main": 8019,
"old": 9999,
"wholesale": 7533
},
"modifiers_type": "",
"item_modifiers": null,
"not_in_stock": false,
"data_layer": 6504701,
"category_id": 19578,
"balance": {
"text": "",
"unit": "",
"value": 0
},
"photos": [
"https://goods-photos.static1-sima-land.com/items/6504701/0/400.jpg?v=1754637732",
"https://goods-photos.static1-sima-land.com/items/6504701/1/400.jpg?v=1754637734",
"https://goods-photos.static1-sima-land.com/items/6504701/2/400.jpg?v=1754637735",
"https://goods-photos.static1-sima-land.com/items/6504701/3/400.jpg?v=1754637736",
"https://goods-photos.static1-sima-land.com/items/6504701/4/400.jpg?v=1754637738"
],
"without_discounts": true,
"is_only_for_legal_entities": false,
"currency_grapheme": "₽",
"id": 6504701,
"name": "УЦЕНКА Бассейн каркасный Steel Pro, 305×76 см, фильтр-насос, круглый. 56679 Bestway",
"properties": [
{
"name": "Торговая марка",
"slug": "/trademark/bestway/",
"text": "Bestway"
},
{
"name": "Страна производитель",
"text": "Китай"
},
{
"name": "Состав",
"text": "Металл, ПВХ, пластик"
}
],
"sid": 7704609,
"url": "/7704609/ucenka-basseyn-karkasnyy-steel-pro-305-76-cm-filtr-nasos-kruglyy-56679-bestway/",
"position": 3,
"from_url": "https://www.sima-land.ru/search/?mode=pagination&per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"
}
```
Each scraped product returns a detailed record with 23 fields:
#### Product Identification
| Field | Description & Purpose |
|---|---|
| `ID` | Unique Sima-land product identifier; use for database keys or deduplication |
| `Name` | Official product title as displayed on the listing; critical for search and categorization |
| `SID` | System ID; internal identifier for tracking product variants or editions |
| `URL` | Direct product page link; enables drill-down analysis or customer access |
| `Position` | Ranking position in the search results; indicates product prominence and relevance |
#### Pricing & Discounts
| Field | Description & Purpose |
|---|---|
| `Prices` | Current selling price in local currency; used for price tracking and comparison |
| `Without Discounts` | Original/list price before promotions; enables discount calculation and margin analysis |
| `Discount Badge` | Visual indicator or text (e.g., "–30%"); signals promotional intensity for market analysis |
| `Badges` | Any special labels (e.g., "New", "Best Seller", "Limited"); indicates product status |
| `Currency Grapheme` | Currency symbol (e.g., ₽ for RUB); ensures correct monetary interpretation |
#### Stock & Availability
| Field | Description & Purpose |
|---|---|
| `Not In Stock` | Boolean flag; `true` if product is unavailable; critical for inventory monitoring |
| `Is Enough` | Indicates whether stock is sufficient for immediate purchase; affects conversion analysis |
| `Can Add To Waiting List` | Boolean; whether customer can request notification when back in stock; shows demand signals |
| `Balance` | Exact stock quantity available; enables inventory trend tracking |
#### Customer Feedback
| Field | Description & Purpose |
|---|---|
| `Rating` | Product rating (typically 1–5 stars); key trust indicator for customer insights |
| `Reviews Count` | Number of customer reviews; correlates with sales volume and engagement |
#### Product Details
| Field | Description & Purpose |
|---|---|
| `Properties` | Product attributes (e.g., color, size, material); enable filtering and variant tracking |
| `Category ID` | Product category classification; used for category-level analysis and segmentation |
#### Modifiers & Variants
| Field | Description & Purpose |
|---|---|
| `Modifiers Type` | Type of product variations (e.g., size, color); defines variant structure |
| `Item Modifiers` | Specific variant options available (e.g., "Size: S, M, L"); affects SKU management |
#### Buyer Restrictions & Marketing
| Field | Description & Purpose |
|---|---|
| `Is Only For Legal Entities` | Boolean; if `true`, product is restricted to B2B buyers; critical for business model filtering |
#### Media & Visual Data
| Field | Description & Purpose |
|---|---|
| `Photos` | Array of product image URLs; essential for visual catalog building |
#### Tracking & Analytics
| Field | Description & Purpose |
|---|---|
| `Data Layer` | GA/tracking data embedded in the page; enables integration with analytics platforms |
***
### How to Use
**Step 1: Prepare URLs**
- Visit Sima-land.ru and search for products using your desired filters (category, price, popularity).
- Copy the search result page URL (e.g., `https://www.sima-land.ru/search/p3/?per-page=20&q=...`).
- You can add multiple URLs to scrape different searches or categories in one run.
**Step 2: Configure Input**
- Set `max_items_per_url` to control volume (e.g., `50` for quick test, `200` for full collection).
- Keep `ignore_url_failures: true` for bulk operations to prevent interruptions.
**Step 3: Run the Scraper**
- Submit the JSON configuration and monitor the run progress.
- Check logs for any failed URLs or parsing issues.
**Step 4: Export & Analyze**
- Download results as JSON, CSV, or Excel.
- Use `ID` and `URL` fields for deduplication and linking.
- Compare `Prices` vs. `Without Discounts` to calculate promotional intensity.
- Filter by `Not In Stock` and `Balance` for inventory analysis.
**Best Practices:**
- Test with `max_items_per_url: 10` first to verify output structure
- Use `sort=rank` or other stable sorting to avoid duplicate results across runs
- Store `ID` and timestamps to track price changes over time
- Monitor `Reviews Count` and `Rating` for competitive positioning
***
### Use Cases & Business Value
- **Price Intelligence:** Track competitor pricing, discounts, and promotional patterns to optimize your own strategy
- **Inventory Monitoring:** Monitor stock levels and identify trending vs. slow-moving products
- **Market Research:** Analyze customer ratings, review counts, and product availability by category
- **Product Feed Management:** Build automated product catalogs for price comparison sites or marketplaces
- **Demand Forecasting:** Correlate review volume, ratings, and stock status with demand signals
By automating product data collection, you eliminate hours of manual work, reduce human error, and unlock timely insights for competitive advantage.
***
### Conclusion
The **Sima-land Product Search Scraper** delivers fast, reliable extraction of e-commerce data from one of Russia's major retail platforms. With 23 fields covering pricing, inventory, reviews, and customer restrictions, it supports price monitoring, market research, and product aggregation use cases. Configure your search, run the scraper, and transform raw listings into actionable business intelligence.
# Actor input Schema
## `urls` (type: `array`):
Add the URLs of the product search list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
## `ignore_url_failures` (type: `boolean`):
If true, the scraper will continue running even if some URLs fail to be scraped.
## `max_items_per_url` (type: `integer`):
The maximum number of items to scrape per URL.
## `proxy` (type: `object`):
Select proxies to be used by your scraper.
## Actor input object example
```json
{
"urls": [
"https://www.sima-land.ru/search/p3/?per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "RU"
}
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"urls": [
"https://www.sima-land.ru/search/p3/?per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "RU"
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/sima-land-product-search-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"urls": ["https://www.sima-land.ru/search/p3/?per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"],
"ignore_url_failures": True,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "RU",
},
}
# Run the Actor and wait for it to finish
run = client.actor("stealth_mode/sima-land-product-search-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"urls": [
"https://www.sima-land.ru/search/p3/?per-page=20&q=%D1%83%D1%86%D0%B5%D0%BD%D0%BA%D0%B0&sort=rank&viewtype=cards"
],
"ignore_url_failures": true,
"max_items_per_url": 20,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
],
"apifyProxyCountry": "RU"
}
}' |
apify call stealth_mode/sima-land-product-search-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=stealth_mode/sima-land-product-search-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Sima Land Product Search Scraper",
"description": "Scrape product listings from Sima-land.ru search results with precision. Collect product names, prices, ratings, reviews, stock status, discounts, and 20+ additional fields per item. Perfect for price monitoring, market analysis, and product data aggregation.",
"version": "0.0",
"x-build-id": "W8y1aN5fGEqDDnDYS"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/stealth_mode~sima-land-product-search-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-stealth_mode-sima-land-product-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/stealth_mode~sima-land-product-search-scraper/runs": {
"post": {
"operationId": "runs-sync-stealth_mode-sima-land-product-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/stealth_mode~sima-land-product-search-scraper/run-sync": {
"post": {
"operationId": "run-sync-stealth_mode-sima-land-product-search-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"urls": {
"title": "URLs of the product search list urls to scrape",
"type": "array",
"description": "Add the URLs of the product search list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.",
"items": {
"type": "string"
}
},
"ignore_url_failures": {
"title": "Continue running even if some URLs fail to be scraped",
"type": "boolean",
"description": "If true, the scraper will continue running even if some URLs fail to be scraped."
},
"max_items_per_url": {
"title": "Max items per URL",
"type": "integer",
"description": "The maximum number of items to scrape per URL."
},
"proxy": {
"title": "Proxy configuration",
"type": "object",
"description": "Select proxies to be used by your scraper."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```