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Y Combinator Scraper with Founders

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Y Combinator Scraper with Founders

Y Combinator Scraper with Founders

Y Combinator scraper to extract startup profiles, founder names, company details, websites, industries, batch information, locations, and other publicly available data 🚀📊 Perfect for startup research, investor sourcing, competitor analysis, and market intelligence.

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Arbeitsagentur Scraper | Bundesagentur für Arbeit

Collects structured public job-listing data from the Bundesagentur für Arbeit job portal (arbeitsagentur.de) via its official REST API — identifiers, titles, employers, descriptions, categories, locations, work arrangements, contract signals, publication dates, and application links. Output is normalized JSON, ready for analytics, ETL, enrichment, and recurring monitoring.

Two input modes: build a search with filters, or provide direct Bundesagentur search-result URLs in startUrls.

Input parameters

ParameterTypeDescriptionDefault
keywordstringSearch terms (was).
locationstringCity / postal code / region (wo). Overrides the location in direct URLs.
employment_typestringjob, education, early_career, self_employedangebotsart (1/4/34/2).job
radiusstring10_km200_kmumkreis.
is_remotebooleanRemote / home-office only → arbeitszeit=ho.
is_suitable_for_career_changebooleanCareer-change-friendly roles (client-side).
beginning_datearrayPreferred start periods from_now_on, may_2026, … (client-side).
fixed_termarraytemporary, indefinitebefristung (1/2).
include_agency_jobsbooleanInclude private placement (pav) jobs. Off → pav=false.
exclude_external_jobsbooleanDrop external job-board listings (client-side).
exclude_temporary_workbooleanDrop temp-agency work → zeitarbeit=false.
disabled_only_jobsbooleanOnly accessibility-marked jobs → behinderung=true.
publication_datestringtoday/yesterday/last_1_week/last_2_weeks/last_4_weeksveroeffentlichtseit (0/1/7/14/28).
work_schedulearrayfull_time/part_time/shift_night_weekend/part_time_jobarbeitszeit (vz/tz/snw/mj).
startUrlsarrayDirect Bundesagentur search-result URLs.
limitintegerMax jobs to collect.50000

How filters are applied

  • Server-side (Bundesagentur query): employment_type, keyword, location, radius, is_remote, work_schedule, publication_date, fixed_term, include_agency_jobs, exclude_temporary_work, disabled_only_jobs.
  • Client-side (after detail fetch): exclude_external_jobs, is_suitable_for_career_change, beginning_date. The actor keeps paginating until limit matching jobs are collected.
  • In startUrls mode the configured filter params are overlaid on each URL (URL-provided values win); the core search (was/wo/umkreis) comes from the URL.

Example inputs

{ "keyword": "Data Engineer", "location": "Berlin", "employment_type": "job",
"radius": "25_km", "is_remote": true, "publication_date": "last_1_week", "limit": 50 }
{ "startUrls": [
"https://www.arbeitsagentur.de/jobsuche/suche?angebotsart=1&was=softwareentwickler&wo=Hamburg&umkreis=15" ],
"exclude_external_jobs": true, "include_agency_jobs": false,
"work_schedule": ["full_time"], "limit": 100 }

Output

One job record per listing, written to the default dataset. Recommended idempotency key: type + ":" + id.

Key fields: type, id, url (external application link when present, else the portal page), source, sourceContext, title, company, description, category, categories, listingType, contractType, workModes, miniJob, careerChangeFriendly, disabilityFriendly, privatePlacementService, temporaryAgency, managedListing, dates, compensation, locations, distanceKm, remoteWork (available, arrangementType), contactReference, applicationUrl, postingPartner, referenceNumber, and sourceData (search + detail provenance layers).

How it works

StepEndpoint
Search (paginated)GET /pc/v4/jobs?was=…&angebotsart=1&page=…&size=…&…filters
Detail per jobGET /pc/v4/jobdetails/{base64(refnr)}

Called with the public header X-API-Key: jobboerse-jobsuche (no account needed). Detail pages are fetched 8 at a time with automatic retries on rate-limit / transient errors.

Project layout

.actor/ actor.json · input_schema.json · dataset_schema.json · Dockerfile
requirements.txt # apify, httpx (pinned)
src/ __main__.py · main.py (orchestration) · api.py (REST client) · mappers.py (normalization)

Run locally

pip install -r requirements.txt
# put input in storage/key_value_stores/default/INPUT.json, then:
python -m src

Deploy to Apify

$apify push