Neuton Scrapes

LinkedIn job details · 1:23

Your first useful Apify scrape

Watch the one-result LinkedIn Job Details walkthrough, then copy its starter input and check the fields against the public source.

This is an illustrated workflow based on the Actor guide. No paid run was captured; the on-screen employer, job ID, URL, and Dataset row are placeholders. A one-result input is a bounded test, not a guaranteed charge cap. Check the Actor’s live Pricing tab and set a run charge limit before you start. Synthetic narration.

Open the Actor on Apify Read the full guide

Copy the starter input

Review the Actor’s current input schema and pricing before you run this bounded example.

{
  "jobUrlsOrIds": [],
  "starterSearchQuery": "data engineer",
  "starterSearchLocation": "London",
  "maxResults": 1
}

Source and limits

Public LinkedIn job pages; no LinkedIn login is required for this workflow. A current public listing may change or disappear, so verify the job URL and fields at the time of your run.

Check job ID and source URL first, then title, company, location, description, and application path. Missing salary or applicant text should remain unknown. If the Dataset is empty, inspect RUN_SUMMARY and the run Log before retrying.

Full transcript

  1. 00:00.000 - Your first useful Apify scrape

    Let's turn one public LinkedIn job into a useful record. We'll run the Neuton Job Details Actor once, inspect the result, then export a checked CSV.

  2. 00:10.024 - Open the Actor. Check Pricing.

    Open the Actor on Apify and read the current Pricing tab. You need an Apify account, but no LinkedIn login. Set a charge limit before starting.

  3. 00:19.429 - Paste a one-row starter

    In Input, open the JSON editor. Leave job URLs empty, enter data engineer and London, and set max results to one. The Actor finds a current public listing at run time.

  4. 00:31.373 - Start once. Inspect Dataset.

    Select Start once. When the run finishes, open Dataset. A succeeded run can still have zero useful rows, so check the data itself.

  5. 00:40.715 - Verify the row against its source

    Check job ID and URL, then title, company, location, description, and application path against the public listing. The row on screen is illustrative. Missing salary stays null.

  6. 00:52.424 - Read RUN_SUMMARY

    If the Dataset is empty, open Storage, the default key-value store, and Run Summary. Check its failed inputs and rows saved. The Log has further diagnostics.

  7. 01:03.024 - Export only after review

    Once the row passes review, export Dataset as CSV. Open the file and verify job ID and source URL before sending it to a spreadsheet.

  8. 01:13.176 - One input. One checked row. One export.

    That's the workflow: one bounded input, one checked row, one export. Links to the Actor and full guide are below. Review live pricing before your own run.

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