Entry-Level IT Jobs Scraper India - Export to Excel

What It Does

This actor scrapes entry-level IT jobs in India from LinkedIn and 12 ATS-style sources:

• LinkedIn
• Greenhouse
• Lever
• SmartRecruiters
• Workday
• iCIMS
• Jobvite
• BambooHR
• Zoho Recruit
• Freshteam
• Keka
• Darwinbox
• Recruitee

It normalizes all results into one schema, filters by posting recency, removes duplicates, and exports:

• JSON records to Apify dataset
• OUTPUT.xlsx to Apify key-value store

Input Fields

• keywords (string): Job search terms. Example: software engineer fresher, python developer, data analyst
• location (string): Target location. Example: India, Bengaluru, Hyderabad
• posted_within (enum): Time window filter. Options: 1 hour, 2 hours, 5 hours, 12 hours, today, 2 days, this week
• sources (array): Which boards to scrape. Default includes all 13 sources.
• job_type (enum): full-time, internship, or both
• max_results_per_source (integer): Max jobs fetched per source
• max_keyword_variants (integer): Number of auto-generated keyword variants tested per source (default: 20)
• linkedin_li_at_cookie (secret string, optional): LinkedIn li_at cookie for improved LinkedIn fetch reliability on stricter rate limits
• execution_mode (enum): ultra, fast, balanced, deep (default: fast)
  • ultra: fastest turnaround, smaller scan depth
  • fast: speed + coverage balance (recommended for frequent runs)
  • balanced: deeper than fast, slower
  • deep: maximum depth, slowest
• run_timeout_seconds (integer): Global runtime budget before pending sources are cancelled
• source_timeout_seconds (integer): Per-source timeout budget
• source_concurrency / variant_concurrency / linkedin_variant_concurrency (integer): Advanced parallelism controls

Smart keyword expansion

• The actor auto-expands user keywords for better entry-level coverage.
• Example: QA jobs expands to variants like qa intern, manual testing intern, automation testing trainee, software tester, junior qa engineer, quality analyst, and more.
• Prefix/suffix generation adds terms such as junior, associate, entry-level, fresher, intern, trainee, plus role endings like engineer, analyst, and tester.

Time Filter

Every job goes through a common parser that handles:

• Relative strings: 2 hours ago, Posted 3 days ago, Today
• ISO strings: 2024-01-15T10:30:00Z
• Unix timestamps: 1705312200000
• Calendar strings: Jan 15, 2024, 15/01/2024, 15 Jan 2024

When to use each option

• 1 hour: Very fresh alerting workflow
• 2 hours: Slightly wider near-real-time scan
• 5 hours: Same-shift refresh
• 12 hours: Half-day batch run
• today: Daily run
• 2 days: Catch-up run
• this week: Weekly sourcing run

Speed Notes

• Scraping now runs in parallel across sources and keyword variants.
• Sources that do not support server-side keyword search are auto-run with a single keyword pass to avoid redundant calls.
• In fast mode, typical runs complete within roughly 1-3 minutes depending on selected sources, keyword breadth, and target result counts.

Output

The Excel file includes 4 sheets:

• All Jobs
• By Source Board
• By City
• Dashboard

All Jobs has styled headers, freeze pane, filters, alternating rows, and clickable apply links.

Recommended screenshot path for store listing:

• assets/excel-output-sample.png (add your real run screenshot before publishing)

Recommended actor icon path:

• assets/actor-icon.svg (upload this in Actor Settings > Profile > Icon)

Pricing

Recommended Apify store pricing setup:

• Pay-per-use: $0.50 per 100 results
• Subscription: $19/month unlimited runs
• Free tier: 50 results for trial users

Local Setup

pip install -r requirements.txt
playwright install chromium
python -m unittest discover -s tests -v
python main.py

Apify Deploy

apify login
apify push

After deployment:

1. Run actor on Apify.
2. Verify OUTPUT.xlsx exists in key-value store.
3. Verify JSON rows exist in dataset.
4. Review logs for per-source counts and errors.

Data Seed Files

Company/portal seeds are in data/:

• lever_companies.json
• greenhouse_companies.json
• jobvite_companies.json
• bamboohr_companies.json
• zoho_companies.json
• freshteam_companies.json
• keka_companies.json
• darwinbox_companies.json
• recruitee_companies.json
• icims_clients.json
• workday_portals.json

Populate these lists with your target companies for higher coverage.