# Geizhals Price History Scraper (`thescrappa/geizhals-price-history-scraper`) Actor

Track Geizhals prices by product and market with history timestamps, observed prices, and current range values. Batch product IDs and choose a lookback window.

- **URL**: https://apify.com/thescrappa/geizhals-price-history-scraper.md
- **Developed by:** [Scrappa](https://apify.com/thescrappa) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.20 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Geizhals Price History Scraper

Retrieve Geizhals price-history points for a product ID, including timestamps and recorded prices. Choose a lookback window and market to compare changes over time.

### What data can you extract?

| Field | Type | Description |
| --- | --- | --- |
| `timestamp_ms` | Integer | Unix timestamp in milliseconds for this price observation. |
| `timestamp` | Integer | Unix timestamp in seconds for this price observation. |
| `price` | Number | Product price recorded at this timestamp, in the selected Geizhals market currency. |
| `marker` | Integer | Geizhals chart marker describing the type of price-history point. |
| `input_product_id` | String | Product id submitted to retrieve this price point. |
| `scraped_at` | String | UTC ISO 8601 timestamp when this dataset record was collected. |

### Use cases

- Price analysts can chart historical changes for a product catalog.
- Retail teams can review low and high points before updating price rules.
- Shoppers can compare recent price movement across multiple product IDs.

### How to use

1. Add one Geizhals product ID to `product_ids` for each history lookup.
2. Choose the market and number of days to include.
3. Set `maxResults` to cap the saved history points, then export the rows.

```json
{
  "product_ids": [
    {
      "product_id": 3103639
    }
  ],
  "loc": "de",
  "days": 7,
  "maxResults": 10
}
```

### Input

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| `product_ids` | Array\<object> | Yes | Geizhals product IDs whose price history you want to review. |
| `product_ids[].product_id` | integer | Yes per entry | Known Geizhals product id from product URLs such as ...-a2194110.html. |
| `product_ids[].days` | integer | No | History window in days. Defaults to 31. Maximum 3650. |
| `product_ids[].loc` | string | No | Market code: de, at, eu, pl, or uk. Defaults to de. |
| `days` | integer | No | History window in days. Defaults to 31. Maximum 3650. |
| `loc` | string | No | Market code: de, at, eu, pl, or uk. Defaults to de. |
| `maxResults` | integer | No | Maximum dataset items to save across this entire run. |

### Output example

```json
{
  "timestamp_ms": 1790000000000,
  "timestamp": 1790086400,
  "price": 549,
  "marker": 8,
  "input_product_id": 3103639,
  "scraped_at": "2026-10-01T12:00:00Z"
}
```

### Pricing

$0.30 per 1,000 results. Apify saves one dataset item per result and applies the Actor’s per-result price to saved items.

Set **maxResults** to cap the number of dataset items saved in one run.

### FAQ

#### Is scraping this information legal?

Rules depend on the source, location, data type, and intended use. Check applicable laws and source terms, and make sure your workflow follows privacy and data protection requirements.

#### What limits apply?

Submit up to 100 batch entries per run. Use **maxResults** to cap saved items. Results also depend on source availability and your Scrappa API plan.

#### Can I start runs through the Apify API?

Yes. Send a POST request to `https://api.apify.com/v2/acts/thescrappa~geizhals-price-history-scraper/runs` with your Actor input, or use an Apify client library. Read the output from the run dataset.

#### Can I connect the results to other tools?

Yes. Apify integrations and APIs can pass dataset results to Make, Zapier, n8n, Google Sheets, and other data workflows.

#### What happens when one input fails?

The Actor logs a short source error and continues with the remaining entries. Transient rate limits and gateway errors are retried; if every entry fails, the run reports an error.

#### What does one result represent?

Each row is one recorded price point with its source timestamp and price value.

### Related Scrappa Actors

- [Geizhals Product & Offers Scraper](https://apify.com/thescrappa/geizhals-product-scraper)
- [Geizhals Price Comparison Search Scraper](https://apify.com/thescrappa/geizhals-search-scraper)
- [Billiger.de Product Offers Scraper](https://apify.com/thescrappa/billiger-offers-scraper)

# Actor input Schema

## `product_ids` (type: `array`):

Geizhals product IDs whose price history you want to review.

## `days` (type: `integer`):

History window in days. Defaults to 31. Maximum 3650.

## `loc` (type: `string`):

Market code: de, at, eu, pl, or uk. Defaults to de.

## `maxResults` (type: `integer`):

Maximum dataset items to save across this entire run.

## Actor input object example

```json
{
  "product_ids": [
    {
      "product_id": 3103639
    }
  ],
  "days": 7,
  "loc": "de",
  "maxResults": 10
}
```

# Actor output Schema

## `results` (type: `string`):

All results from this run in the default dataset.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "product_ids": [
        {
            "product_id": 3103639
        }
    ],
    "days": 7,
    "loc": "de",
    "maxResults": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("thescrappa/geizhals-price-history-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "product_ids": [{ "product_id": 3103639 }],
    "days": 7,
    "loc": "de",
    "maxResults": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("thescrappa/geizhals-price-history-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "product_ids": [
    {
      "product_id": 3103639
    }
  ],
  "days": 7,
  "loc": "de",
  "maxResults": 10
}' |
apify call thescrappa/geizhals-price-history-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thescrappa/geizhals-price-history-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/nGml9bNQB8NiFLb67/builds/V5uUUGrHfImIeWBxX/openapi.json