Linkedin Jobs Scraper
Pricing
$1.00 / 1,000 results
Scrape jobs from linkedin jobs search results along with company details. Get key information to find contact info
Pricing
$1.00 / 1,000 results
Rating
4.9
(51)
Developer
Curious Coder
Actor stats
694
Bookmarked
23K
Total users
2.9K
Monthly active users
18 hours
Issues response
9 days ago
Last modified
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You can access the Linkedin Jobs 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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You can pass multiple search URLs", "items": { "type": "string" } }, "scrapeCompany": { "title": "Scrape company details", "type": "boolean", "description": "This will require additional scraping requests for each job record and take longer to scrape", "default": true }, "count": { "title": "Number of jobs needed", "minimum": 10, "type": "integer", "description": "Limit number of jobs scraped" }, "splitByLocation": { "title": "Split search by city locations", "type": "boolean", "description": "Enable this to split your search by cities within a country. This helps bypass LinkedIn's 1000 job limit per search URL by creating separate searches for each city. This will overwrite the location filter in input search URLs.", "default": false }, "splitCountry": { "title": "Country to split by", "enum": [ "US", "CA", "MX", "GB", "DE", "FR", "NL", "CH", "SE", "NO", "DK", "FI", "IE", "ES", "IT", "PT", "BE", "AT", "PL", "CZ", "RO", "HU", "GR", "BG", "HR", "RS", "UA", "SK", "LT", "LV", "EE", "SI", "LU", "MT", "IS", "CY", "TR", "RU", "GE", "AM", "AZ", "BY", "BA", "XK", "MD", "ME", "MK", "AL", "MC", "AD", "LI", "SM", "VA", "IN", "CN", "JP", "KR", "SG", "HK", "TW", "TH", "VN", "ID", "MY", "PH", "BD", "PK", "LK", "NP", "MM", "KH", "KZ", "UZ", "KG", "TJ", "TM", "MN", "BN", "MV", "BT", "LA", "TL", "AF", "KP", "AE", "SA", "IL", "QA", "KW", "BH", "OM", "JO", "LB", "IQ", "IR", "PS", "SY", "YE", "AU", "NZ", "FJ", "PG", "WS", "TO", "VU", "SB", "KI", "MH", "FM", "PW", "NR", "TV", "BR", "AR", "CO", "CL", "PE", "EC", "UY", "VE", "BO", "PY", "GY", "SR", "CR", "PA", "GT", "DO", "PR", "JM", "TT", "HN", "SV", "NI", "BS", "BB", "CU", "HT", "BZ", "AG", "DM", "GD", "LC", "KN", "VC", "ZA", "NG", "KE", "EG", "MA", "GH", "ET", "TZ", "RW", "UG", "SN", "TN", "CI", "CM", "DZ", "AO", "MU", "ZM", "ZW", "MZ", "CD", "BW", "NA", "MG", "LY", "SD", "SS", "SO", "ML", "GA", "BJ", "BF", "MW", "NE", "TD", "SL", "LR", "ER", "GM", "GN", "GW", "TG", "MR", "SZ", "LS", "DJ", "CG", "CF", "BI", "CV", "KM", "GQ", "ST", "SC" ], "type": "string", "description": "Select the country whose cities will be used to split the search. Only used when 'Split search by city locations' is enabled. Required to when 'Split search by city locations' is enabled." } } }, "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 } } } } } } } } }}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.
You can download the OpenAPI definitions for Linkedin Jobs Scraper from the options below:
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