The GitHub repository for this project can be viewed here.

Phone Number Scraper

In this project, I created a simple Python script designed to collect publicly available phone numbers from Google Search results. The tool automates queries, extracts visible phone numbers, and populates them into a structured CSV file for easy enrichment and further use.

⚡️ Disclaimer: This tool is designed to strictly scrape publicly available phone numbers. Ensure your usage complies with Google’s Terms of Service and local data privacy regulations.

🚀 Features

Automated querying via Google Search.
Extraction of publicly visible phone numbers from result pages.
CSV output (Enriched_Dataset.csv) with enriched data.
Built-in basic error handling for common scraping issues.
Written in Jupyter Notebook (Scrapping_script.ipynb).

📂 Files in the Repository

File	Description
`Scrapping_script.ipynb`	Jupyter Notebook containing the scraping script and all processing logic.
`Enriched_Dataset.csv`	Output CSV containing the extracted and enriched phone number data.
`requirements.txt`	Contains the dependencies required to run this script.

🛠️ Requirements

Python 3.7+
Jupyter Notebook
Key Libraries:
- requests
- beautifulsoup4
- gspread
- oauth2client
- re (regular expressions)

Install the required packages using:

pip install -r requirements.txt

🧹 How to Use

Clone this repository:

git clone https://github.com/your-username/phone-number-scraper.git
cd phone-number-scraper

Install dependencies.
Run the Notebook:

Open Scrapping_script.ipynb using Jupyter Notebook or JupyterLab, and execute the cells sequentially.
Customize Search Terms (Optional):

Modify the query section inside the notebook to change the search keywords according to your needs.
View Results:

After execution, the enriched phone numbers will be saved in Enriched_Dataset.csv.

⚠️ Important Notes

Respect Robots.txt: Always check and respect the robots.txt file of any site you scrape.
Rate Limiting: Add delays between requests to avoid being IP-banned.
Legal Compliance: Scrape responsibly and ensure you adhere to all applicable data privacy laws.

🧺 Future Improvements

Integrate proxy support.
Implement CAPTCHA handling.
Add multi-threaded scraping for faster data collection.
Deploy as a Python package or CLI tool.

📜 License

This project is licensed under the MIT License. See the LICENSE file in the GitHub repository for more details.

Python Web Scrape