Hemnet Scraper
Pricing
$39.00/month + usage
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Hemnet Scraper
Extracts comprehensive Swedish real estate data from Hemnet.se. Supports search by location/filters or specific URLs. Crawls 50+ property attributes including prices, specs, broker details. TypeScript/Crawlee-powered with rate limiting, error handling & CSV/JSON output
0.0 (0)
Pricing
$39.00/month + usage
1
Total users
1
Monthly users
1
Runs succeeded
89%
Last modified
2 days ago
You can access the Hemnet Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
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Leave empty to get the latest properties from all of Sweden." }, "priceMin": { "title": "Minimum Price (SEK)", "minimum": 0, "type": "integer", "description": "Minimum price filter in Swedish Kronor. Leave empty for no minimum limit." }, "priceMax": { "title": "Maximum Price (SEK)", "minimum": 0, "type": "integer", "description": "Maximum price filter in Swedish Kronor. Leave empty for no maximum limit." }, "roomsMin": { "title": "Minimum Rooms", "minimum": 1, "type": "integer", "description": "Minimum number of rooms. Leave empty for no minimum limit." }, "roomsMax": { "title": "Maximum Rooms", "minimum": 1, "type": "integer", "description": "Maximum number of rooms. Leave empty for no maximum limit." }, "propertyTypes": { "title": "Property Types", "type": "array", "description": "Types of properties to include in the search. Leave empty for all types.", "items": { "type": "string", "enum": [ "villa", "lägenhet", "fritidshus", "tomt", "gård", "radhus", "parhus" ] }, "default": [] }, "maxItems": { "title": "Maximum Items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of properties to extract (recommended for fast results). This limits the total results regardless of pages crawled.", "default": 8 }, "maxPages": { "title": "Maximum Pages", "minimum": 0, "maximum": 100, "type": "integer", "description": "Maximum number of search result pages to crawl. Set to 0 for unlimited pages (limited only by maxItems). Note: Each page typically contains ~50 properties.", "default": 0 }, "extractImages": { "title": "Extract Images", "type": "boolean", "description": "Whether to extract property images", "default": false }, "outputFormat": { "title": "Output Format", "enum": [ "json", "csv" ], "type": "string", "description": "Format for the output data", "default": "json" } } }, "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 } } } } } } } } }}Hemnet Scraper OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
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