Build a Python Web Crawler for comparis.ch Real Estate Listings (Config-Driven, Full Data Extraction) -- 2

Build a Python Web Crawler for [login to view URL] Real Estate Listings (Config-Driven, Full Data Extraction) ________________________________________ Project Description I am looking for an experienced Python developer to build a robust, production-ready web crawler for the Swiss real estate platform comparis.ch. The crawler must reliably extract all real estate listings from [login to view URL] based on configurable search parameters, including all detail information from each individual listing page, and export the results into Excel. This is not a theoretical exercise – the solution must work in practice and handle the technical constraints of comparis.ch. ________________________________________ Core Requirements 1. Input Configuration (Mandatory) The crawler must read all search parameters from a JSON configuration file, for example: • Location (e.g. ZIP codes like 5722) • Radius (km) • Deal type (rent / buy) • Property type(s) • Rooms (from / to) • Price (from / to) • Sorting • Page size • Maximum pages The configuration file must be easy to modify without touching the Python code. ________________________________________ 2. Crawling Logic The crawler must: • Open [login to view URL] with the given search parameters • Iterate through all result pages (page 1, page 2, page 3, … until no more listings) • Extract all listings shown on each page • For each listing, open the detail page and extract full information Important: • [login to view URL] uses client-side rendering / JavaScript • A browser-based solution (Playwright, Selenium, or equivalent) is required • Simple requests + BeautifulSoup solutions are not sufficient ________________________________________ 3. Data to Extract (Minimum) For each listing, extract as many of the following as available: • Listing ID (if available) • Title • Price • Rooms • Living space (sqm) • Address / location • ZIP code • Canton / city • Property type • Floor (if available) • Availability date • Description text • Features / equipment • Images (URLs only, no downloads required) • Listing URL • Provider / agency name • Provider profile URL (if available) ________________________________________ 4. Output • Export results to Excel (.xlsx) • One row per listing • Clear column headers • UTF-8 clean (no broken characters) • File name should include the date (e.g. [login to view URL]) If no listings are found, the script must log a clear message explaining why. ________________________________________ 5. Reliability & Stability The solution must: • Handle pagination correctly • Avoid duplicate listings • Be resilient against minor HTML changes • Include basic logging (console output is sufficient) • Fail gracefully (clear error messages instead of silent failure) ________________________________________ 6. Technical Requirements • Python 3.10+ • Clean, well-structured code • No hard-coded search parameters inside the code • All dependencies clearly documented • Must run on Windows • Preferably runnable via a .bat file ________________________________________ 7. Deliverables 1. Fully working Python crawler 2. Example [login to view URL] 3. Requirements file ([login to view URL]) 4. Short README explaining: o How to start the crawler o How to change search parameters o Expected output ________________________________________ What I Will Provide • Example [login to view URL] search URLs • Expected structure of the configuration file • Sample output expectations ________________________________________ What I Will NOT Accept • Partial solutions • API-only approaches that do not work in practice • “Works on my machine” code without documentation • Scrapers that stop after page 1 • Solutions without detail page extraction ________________________________________ Preferred Skills • Strong Python experience • Proven experience with Playwright / Selenium • Experience scraping JavaScript-heavy websites • Experience exporting structured data to Excel ________________________________________ Project Goal (Summary) A stable, configurable, browser-based Python crawler that extracts all real estate listings and their details from [login to view URL] into Excel, based on a JSON input configuration.

Projekt-ID: 40101040