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“Larger the area longer it will take.” -Yoda

This project provides a suite of Python scripts to scrape and extract information from Google Maps and Instagram based on a specified location and search term. It generates Excel files containing useful links and detailed information related to your search.

• scrape_step_0_location.py: Geocodes the place to get its bounding box.
• scrape_step_1_links.py: Scrapes Google Maps links based on the search term and location.
• scrape_step_2_extract.py: Extracts detailed information from the Google Maps links.
• scrape_step_3_insta.py: Scrapes Instagram links related to the search term.
• scrape_step_4_check.py: Checks if the current location is within the specified "place name."
• scrape_step_5_compile.py: Orchestrates the execution of the above scripts and manages file creation.
• scrape_step_6_generate.py: Generates Excel files for storing the scraped data.
• scrape_step_7_user.py: User-configurable script to specify place and search term.

• Python 3.7 or laterDownload
• Visual Studio Code or any other code editor,VScode Download
• Internet access for scraping,I wish I could give you free internet too...

1. Clone the Repository

   git clone https://github.com/Vergil1000x/Google_Map_Scraper.gitcd Google-Map-Scraper

2. Install Dependencies

   pip install geopy openpyxl selenium playwright beautifulsoup4 pandasplaywright install

1. Configurescrape_step_7_user.py

   Openscrape_step_7_user.py and set theplace_name andsearch_term variables, on line 6 and line 7:

   place_name="Varanasi"search_term="Aesthetic Clinic"

2. Run the Script

   Executescrape_step_7_user.py to start the scraping process:

   python scrape_step_7_user.py

   This will generate three Excel files in your folder with the following format:

   • {place_name}_{search_term}_{timestamp}_input.xlsx: Contains Google Maps links.
   • {place_name}_{search_term}_{timestamp}_output.xlsx: Contains details of the search term in the given place.
   • {place_name}_{search_term}_{timestamp}_insta.xlsx: Contains Instagram links related to the search term.

Example files generated might look like:

• Varanasi_Aesthetic Clinic_2002-02-20_input.xlsx
• Varanasi_Aesthetic Clinic_2002-02-20_output.xlsx
• Varanasi_Aesthetic Clinic_2002-02-20_insta.xlsx

1. Configurescrape_step_2_extract.py

   In line 93, you can adjust the value3 to any number to optimize performance based on your needs. For example:

   semaphore=asyncio.Semaphore(3)

   Increasing the value allows more concurrent tasks, which might speed up scraping but could also increase resource usage.

2. Configurescrape_step_3_insta.py

   Similarly, in line 62, you can change the value5 to better suit your performance requirements:

   semaphore=asyncio.Semaphore(5)

   Adjusting this value can help balance between scraping speed and system load.

• Error:Yada Yada Anything: AskChatGPT or AskGoogle or AskMe.

Contributions are welcome!