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How to Scrape Google Reviews With Python | Web Scraping Tutorial

#Web scraping
2025-07-10 17:528 min read

Content Introduction

This video offers a guide on how to scrape Google reviews at scale using Python and proxies. It highlights the importance of Google reviews for market analysis and brand image tracking, while addressing the challenges of collecting data manually. Viewers are instructed to have the latest version of Python, Playwright, and proxies ready for the task. After setting up, the video explains using script code to collect reviews from Google Maps, including how to manage proxies, handle errors, and extract specific elements like review ratings and text. The process is aimed at gathering unique reviews efficiently, with the final output being saved in a CSV file. The video provides details on running the script and accessing missing elements during data collection, ensuring effective scraping practices.

Key Information

  • Google reviews are useful for market analysis and brand image tracking.
  • Collecting Google reviews manually is time-consuming.
  • The video tutorial demonstrates how to scrape Google reviews using Python and proxies.
  • Users need to install the latest version of Python's Playwright library and configure proxies to bypass IP blocks.
  • Residential proxies are recommended for scraping Google reviews.
  • The tutorial includes steps for setting up the Python environment and defining the scraping function.
  • The functional code snippet is designed to handle errors, duplicate reviews, and allows for scrolling through reviews to collect more data.
  • At the end of the scraping process, the reviews will be saved into a CSV file.

Timeline Analysis

Content Keywords

Google Reviews Scraping

Google reviews are valuable for market analysis and tracking brand image. This video demonstrates how to scrape Google reviews at scale using Python and proxies, emphasizing the need for the latest Python Playwright framework and residential proxies.

Python Libraries

The video covers essential Python libraries for scraping, including Playwright for browser automation, and CSV for saving outputs, alongside the use of regular expressions for data cleaning.

Scraping Process

Viewers learn to set up the scraping script by defining variables for the Google Maps search and the number of reviews to collect, managing proxy details, and navigating to the required web pages.

Data Extraction

The script captures business details, including name, star rating, and reviews, managing dynamic elements and reviewing capabilities efficiently.

Error Handling

The video addresses error management throughout the scraping process and the importance of efficiently handling duplicates and loading delays while collecting reviews.

Output and CSV Saving

Final steps include printing collected reviews and saving them to a CSV file, ensuring users can review the scraped data easily post-execution.

Kodu Residential Proxies

A mention of Kodu residential proxies for effective scraping, along with a link for viewers to access a free trial for the service.

Related questions&answers

What are Google reviews and why are they important?

Google reviews are packed with insights that are perfect for market analysis and tracking your brand image.

How can I scrape Google reviews?

In this video, we'll show you how to scrape Google reviews at scale using Python and proxies.

What do I need to follow along with the scraping tutorial?

Make sure you have the latest version of Python, the Playwright framework, and proxies to bypass IP blocks and scraping errors.

What type of proxies are recommended for scraping Google reviews?

For scraping Google reviews, residential proxies are recommended.

Where can I find my proxy credentials?

If you have the Kodo subscription, you can find your proxy credentials in the dashboard under residential proxies.

What does the Playwright sync API allow you to do?

The Playwright sync API allows you to use a headless Chrome-like browser through code.

How do I clean and extract specific parts of text during scraping?

You can use the regular expression module to clean and extract specific parts of the text.

How does the scraping process handle different review formats?

The scraping process can handle different formats by checking for text or the number of star icons, and employs methods to extract the star rating.

What happens if no new reviews are found during scraping?

If no new unique reviews were found, the loop breaks early, and the script will handle scrolling to try and load more reviews.

How are the collected reviews saved?

All collected data will be saved into a CSV file, including metadata and reviews.

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