Real Estate Scraper

This Python script scrapes real estate price data for all cities from imot.bg.
It saves the results in a CSV file, making it easy to analyze trends in the real estate market.

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⚙️ Tech Stack

• Language: Python 3.11+
• Libraries: requests, BeautifulSoup, pandas
• Data Format: CSV
• Automation: cron (Linux/macOS), Task Scheduler (Windows)
• Deployment: Can be run locally or automated with cloud services

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Features

• Scrapes real estate price data for all cities in imot.bg
• Saves results as CSV files
• Can be automated with cron (Linux/macOS) or Task Scheduler (Windows)
• Uses BeautifulSoup for web scraping
• Works in Python 3.11+

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Installation

1. Clone the Repository

First, download the project to your local machine:

git clone https://github.com/KrumYakimov/Real-Estate-Scraper.git
cd real-estate-scraper

2. Install Dependencies

Make sure you have Python 3.11+, then install the required libraries:

pip install -r requirements.txt

3. Run the Scraper

To scrape data for all cities, run:

python scraper.py

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📂 Output (Saved Data)

The script downloads real estate data for the date when it is run.

Date	City	District	1-Bedroom Price	1-Bedroom Price/m²	2-Bedroom Price	2-Bedroom Price/m²	3-Bedroom Price	3-Bedroom Price/m²	Link
25.02.2025	София	Бъкстон	120,000	2,000	180,000	1,800	250,000	1,700	View

Saved file format:

real_estate_prices_YYYYMMDD.csv

Example: If the script is run on March 1, 2025, the file will be:

real_estate_prices_20250301.csv

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⚙️ Automating the Script

You can schedule the script to run automatically every day.

Linux & macOS (Using cron)

1. Open a terminal and edit your crontab:

   crontab -e

2. Add the following line to schedule the script every day at 03:30 (change the time as needed):

   30 3 * * * /path/to/python /path/to/scraper.py >> /path/to/logs/scraper.log 2>&1

   • /path/to/python → Path to your Python interpreter (e.g., /usr/bin/python3 or from a virtual environment).
   • /path/to/scraper.py → Full path to scraper.py.
   • /path/to/logs/scraper.log → Optional log file to track execution.

Windows (Using Task Scheduler)

1. Open Task Scheduler (Win + R, then type taskschd.msc and press Enter).
2. Click Create Basic Task → Give it a name (e.g., RealEstateScraper).
3. Trigger: Choose Daily and set the time (e.g., 03:30).
4. Action: Select Start a program.
5. Browse to Python executable:
   • If using Anaconda:

     C:\path\to\anaconda\envs\myenv\python.exe
     

   • If using standard Python:

     C:\path\to\python.exe
     

6. Add arguments:

   C:\path\to\real-estate-scraper\scraper.py
   

7. Click Finish.

Now the script will run automatically every day at 03:30!

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Want More Automation?

If you need database storage, API integration, or advanced analytics, feel free to reach out!

Contact me via GitHub Issues or email: krum.yakimov@gmail.com
Let's build something great together!

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License

This project is open-source under the MIT License.