Pricing
$25.00/month + usage
Extract job listings from Linkedin. Scrape details job details like when it is posted, number of applicants, location and salary range. Download listings data in JSON, XML, Excel.
5.0 (1)
Pricing
$25.00/month + usage
4
91
15
Last modified
3 months ago
You can access the Fast LinkedIn Job Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "GJvrh16luoe8w0cLF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ivanvs~fast-linkedin-job-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ivanvs-fast-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/ivanvs~fast-linkedin-job-scraper/runs": { "post": { "operationId": "runs-sync-ivanvs-fast-linkedin-job-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/ivanvs~fast-linkedin-job-scraper/run-sync": { "post": { "operationId": "run-sync-ivanvs-fast-linkedin-job-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "maxRecords": { "title": "Maximum number of records", "minimum": 1, "type": "integer", "description": "Maximum number of records to be scraped", "default": 10 }, "keywords": { "title": "Keywords", "minLength": 1, "type": "string", "description": "Job title or something identifies jobs that you would like to scrape" }, "location": { "title": "Location", "type": "string", "description": "Job location e.g. New York" }, "contractType": { "title": "Contract type", "enum": [ "1", "2", "3" ], "type": "string", "description": "Select contract type" }, "employmentTypes": { "title": "Employment type", "type": "array", "description": "Select one or more employment types", "items": { "type": "string", "enum": [ "F", "P", "C", "T", "V", "I" ], "enumTitles": [ "Full-time", "Part-time", "Contract", "Temporary", "Volunteer", "Internship" ] } }, "datePosted": { "title": "Date Posted", "pattern": "^(\\d+)\\s*(hour|day|week|month|year)s?$", "type": "string", "description": "Maximum amount of time that has passed since job was posted. Format is {number} {unit}. Example: 7 days, 12 hours, 1 month. Valid units: hour, hours, day, days, week, weeks, month, months, year, years" }, "experienceLevel": { "title": "Experience Level", "enum": [ "1", "2", "3", "4", "5", "6" ], "type": "string", "description": "What is expereince level needed" }, "geoId": { "title": "Geolocation Unique ID", "type": "integer", "description": "Global unique id of each location on earth.Each city, town, region or country is associated with a global unique id" }, "distance": { "title": "Distance", "minimum": 1, "type": "integer", "description": "Filter results based on their proximity to a specific location or point of interest" }, "companyId": { "title": "Company UD", "minimum": 1, "type": "integer", "description": "Filter jobs by company. You need to enter company ID from linkedIn, for example: 145208" }, "salary": { "title": "Salary", "enum": [ "1", "2", "3", "4", "5", "6", "7", "8", "9" ], "type": "string", "description": "Filtering by salary" }, "jobIds": { "title": "Job IDs", "type": "array", "description": "The ID(s) of the job ad(s) (e.g. 3845939573, 4169804050...). Provide only the id numbers. Results obtained using this method do not count toward the maximum records limit", "default": [], "items": { "type": "string" } } } }, "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 Fast LinkedIn Job Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: