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Linkedin Job Scraper

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Linkedin Job Scraper

Linkedin Job Scraper

ivanvs/linkedin-job-scraper
Try for free

Pay $10.00 for 1,000 results

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.

Developer
Maintained by Community

Actor Metrics

  • 56 Monthly users

  • 5.0 / 5 (1)

  • 9 bookmarks

  • >99% runs succeeded

  • 0.5 hours response time

  • Created in Nov 2024

  • Modified 4 days ago

Categories

You can access the 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.

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132        "type": "object",
133        "properties": {
134          "maxRecords": {
135            "title": "Maximum number of records",
136            "minimum": 1,
137            "type": "integer",
138            "description": "Maximum number of records to be scraped",
139            "default": 10
140          },
141          "keywords": {
142            "title": "Keywords",
143            "minLength": 1,
144            "type": "string",
145            "description": "Job title or something identifies jobs that you would like to scrape"
146          },
147          "location": {
148            "title": "Location",
149            "type": "string",
150            "description": "Job location e.g. New York"
151          },
152          "contractType": {
153            "title": "Contract type",
154            "enum": [
155              "1",
156              "2",
157              "3"
158            ],
159            "type": "string",
160            "description": "Select contract type"
161          },
162          "datePosted": {
163            "title": "Date Posted",
164            "pattern": "^(\\d+)\\s*(hour|day|week|month|year)s?$",
165            "type": "string",
166            "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"
167          },
168          "experienceLevel": {
169            "title": "Experience Level",
170            "enum": [
171              "1",
172              "2",
173              "3",
174              "4",
175              "5",
176              "6"
177            ],
178            "type": "string",
179            "description": "What is expereince level needed"
180          },
181          "geoId": {
182            "title": "Geolocation Unique ID",
183            "type": "integer",
184            "description": "Global unique id of each location on earth.Each city, town, region or country is associated with a global unique id"
185          },
186          "distance": {
187            "title": "Distance",
188            "minimum": 1,
189            "type": "integer",
190            "description": "Filter results based on their proximity to a specific location or point of interest"
191          },
192          "companyId": {
193            "title": "Company UD",
194            "minimum": 1,
195            "type": "integer",
196            "description": "Filter jobs by company. You need to enter company ID from linkedIn, for example: 145208"
197          },
198          "salary": {
199            "title": "Salary",
200            "enum": [
201              "1",
202              "2",
203              "3",
204              "4",
205              "5",
206              "6",
207              "7",
208              "8",
209              "9"
210            ],
211            "type": "string",
212            "description": "Filtering by salary"
213          },
214          "jobIds": {
215            "title": "Job IDs",
216            "type": "array",
217            "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",
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238                "type": "string"
239              },
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241                "type": "string",
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243                "example": "2025-01-08T00:00:00.000Z"
244              },
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328              "containerUrl": {
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333                "properties": {
334                  "ACTOR_COMPUTE_UNITS": {
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337                  },
338                  "DATASET_READS": {
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341                  },
342                  "DATASET_WRITES": {
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345                  },
346                  "KEY_VALUE_STORE_READS": {
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349                  },
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353                  },
354                  "KEY_VALUE_STORE_LISTS": {
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Linkedin Job 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.

You can download the OpenAPI definitions for 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: