Our Web Scraping Tech Stack

Our Web Scraping Tech Stack

Scraping Practices and Technologies used at Web Scraping.

At webscraping.net, we believe in cutting through complexity. Here’s what drives our web scraping projects:

Python: The Backbone

Python is our bedrock, providing power and simplicity for seamless web scraping and data manipulations.

Scrapy: Navigating with Ease

We rely on Scrapy, a Python web scraping framework for smooth data collection from the Internet.

Redis: Handling Scale

For larger distributed projects, we turn to Redis, an in-memory data store that keeps things running efficiently.

Playwright: JavaScript rendering

While we try to avoid JS rendering, for dynamic websites, we harness the power of Playwright, a JavaScript library that enables browser automation and rendering. It allows us to interact with websites as if a real user were browsing, ensuring we capture data from JavaScript-rendered pages.

Data Storage: Your Choice

Our mainstay is PostgreSQL, a robust open-source database.
We have also worked with:

  • MySQL, MariaDB: Performance-focused databases.
  • Amazon RDS, Amazon S3: Cloud storage options.
  • Airtable, Google Sheets: Collaborative tools.
  • Google Cloud Storage: Integrated solution.
  • ClickHouse: Fast and scalable analytical database.

Simplicity, Meets Efficiency
Our tech stack is all about making web scraping simple and effective.

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How will customers benefit from our services?

eCommerce companies:

Be ahead of your competitors by intelligent price setting. Access to additional information can boost your sales by up to 85%

Wholesalers and manufacturers:

Know the stocks of your customers in near real-time. This information will help you predict the demand better and reduce your stockpile.

Data science teams:

Web scraping can be tedious. We will take care of that headache for you.

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