Naukri Job Scraper

It is designed for scrapping Naukri job you provide search input (keyword, location, max jobs, etc.), the actor runs the underlying scraper, and pushes filtered job records to the dataset.

What this actor does

1. Initializes the Apify Actor runtime.
2. Reads input from Actor.getInput().
3. Builds scraper input with defaults.
4. Reads the run dataset items.
5. Maps each item to a compact output schema.
6. Pushes normalized results to this actor's dataset.

Project structure

• main.js - Actor logic (input mapping, scraper call, output transformation).
• package.json - Node package metadata and runtime dependencies.
• Dockerfile - Container image definition used to run the actor.

Runtime and dependencies

• Node.js via apify/actor-node:20 Docker base image.
• Main dependency: apify (JavaScript SDK).
• Start command: npm start (runs node main.js).

Input

The actor accepts the following input fields:

Field	Type	Default	Description
searchQuery	string	"developer"	Keyword/job title query.
location	string	"india"	Target location for jobs.
maximumJobs	number	20	Maximum jobs requested from underlying scraper.
platform	string	"naukri"	Platform passed to underlying scraper.
startUrls	array	[]	Optional start URLs for scraping.
includeAmbitionBoxDetails	boolean	false	Whether to include AmbitionBox-related details from source actor.
proxy	object	{ useApifyProxy: true, apifyProxyGroups: ["RESIDENTIAL"] }	Proxy setup passed to source actor.

Example input

{
  "searchQuery": "data scientist",
  "location": "Bengaluru",
  "maximumJobs": 50,
  "platform": "naukri",
  "startUrls": [],
  "includeAmbitionBoxDetails": false,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Output dataset schema

Each output item is normalized to the fields below:

• companyName
• applyCount
• roleCategory
• jobRole
• companyDetail
• functionalArea
• description
• industry
• url
• title
• walkIn
• maximumExperience
• minimumExperience
• locations
• keySkills
• shortDescription

Field mapping notes

• companyName prefers item.companyDetail.name, then item.staticCompanyName.
• description prefers item.jobDescription, then item.description.
• url prefers item.staticUrl, then item.jdURL, then item.applyUrl.
• locations is taken from item.locations or fallback item.location.
• keySkills is taken from item.tagsAndSkills or fallback item.keySkills.

Error handling behavior

• If the called scraper run is not SUCCEEDED, the actor fails with run ID details.
• Any runtime exception is caught and reported using Actor.fail.

Important limitations

• Output fields are transformed and may omit source fields not included in the mapping.
• Current fetch limit for reading items from the source dataset is 99999.

Script entrypoint

• Main entrypoint: main.js
• NPM script: npm start