Kariyer Internship Scraper

A focused data extraction tool that collects up-to-date internship listings from Kariyer.net, including roles, companies, locations, and application links. It helps students, recruiters, and analysts quickly access structured internship data without manual searching.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

The Kariyer Internship Scraper is designed to gather structured internship listings from Kariyer.net with accuracy and consistency. It solves the problem of manually browsing and tracking internship opportunities by turning listings into clean, reusable data. This project is ideal for students, job researchers, HR teams, and market analysts interested in the Turkish job market.

Internship Market Data Collection

• Targets internship-specific job listings with clear role categorization
• Captures company, location, and application details in one pass
• Supports configurable limits and respectful request pacing
• Outputs consistent, analysis-ready structured data

Features

Feature	Description
Internship Listings Extraction	Collects internship roles with titles, companies, and locations.
Detailed Job Descriptions	Optionally fetches full descriptions from individual job pages.
Configurable Limits	Control how many listings are collected per run.
Request Delay Control	Adjustable delay between requests for stable operation.
Structured Output	Produces clean, predictable records for downstream use.

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What Data This Scraper Extracts

Field Name	Field Description
title	Internship position title.
company	Company offering the internship.
location	Job location, typically city-based.
application_url	Direct link to apply for the internship.
employment_type	Employment type, commonly internship roles.
description	Full job description and requirements.
source	Source platform identifier.
posted_date	Timestamp indicating when the listing was collected.

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Example Output

[
      {
        "title": "Software Development Intern",
        "company": "Tech Company Ltd",
        "location": "Istanbul",
        "application_url": "https://www.kariyer.net/is-ilani/...",
        "employment_type": "Stajyer",
        "description": "Participate in software development tasks, assist senior engineers, and learn modern development workflows.",
        "source": "kariyer.net",
        "posted_date": "2025-07-02T10:30:00"
      }
]

---

Directory Structure Tree

Kariyer/
├── src/
│   ├── main.py
│   ├── runner.py
│   ├── fetchers/
│   │   ├── listings_fetcher.py
│   │   └── detail_fetcher.py
│   ├── parsers/
│   │   ├── listing_parser.py
│   │   └── description_parser.py
│   ├── config/
│   │   └── settings.py
│   └── utils/
│       └── rate_limiter.py
├── data/
│   ├── sample_output.json
│   └── inputs.example.json
├── requirements.txt
└── README.md

---

Use Cases

• Students use it to monitor internship openings, so they can apply faster and stay competitive.
• Career advisors use it to analyze internship trends, so they can guide students effectively.
• Recruiters use it to track market activity, so they can benchmark internship demand.
• Data analysts use it to study hiring patterns, so they can generate workforce insights.

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FAQs

Does this tool only collect internships? Yes, it is optimized specifically for internship listings and related roles to ensure focused and relevant results.

Can I limit how many listings are collected? Yes, you can define a maximum number of results to control dataset size and runtime.

Are full job descriptions required? No, fetching detailed descriptions is optional and can be disabled for faster runs.

Is the scraping speed configurable? Yes, request delays can be adjusted to balance speed and stability.

---

Performance Benchmarks and Results

Primary Metric: Processes approximately 40–60 internship listings per minute with descriptions enabled.

Reliability Metric: Maintains a success rate above 98% across repeated runs under normal conditions.

Efficiency Metric: Uses asynchronous requests to minimize idle time and reduce overall runtime.

Quality Metric: Achieves high data completeness with consistent field coverage across listings.

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