Search Results for "common"

spider_collection is a collection of Python web crawler scripts created primarily for experimentation, learning, and practical scraping tasks. spider_collection gathers multiple independent spiders designed to collect data from different platforms and services, demonstrating a variety of scraping techniques and workflows. These crawlers make use of common Python scraping tools such as requests, parsel, BeautifulSoup, and the Scrapy framework to extract structured information from web pages. Several scripts also incorporate multi-threading and proxy usage to improve scraping efficiency and help avoid common anti-scraping limitations. In addition to raw data collection, some spiders include basic data processing and analysis using tools such as pandas and simple visualization with matplotlib. ...

...Many examples illustrate techniques such as debugging scripts, intercepting requests, analyzing encrypted parameters, and understanding authentication flows. crawler also explores common anti-scraping defenses and demonstrates how developers can examine them through debugging tools and reverse engineering techniques.

...It handles many low-level tasks involved in web data extraction, including parsing responses, managing platform-specific logic, and handling errors, allowing developers to focus on implementing application features rather than scraping mechanics. Each supported service is implemented through its own extractor components that conform to a common interface, enabling consistent access to data across different platforms.

DotnetSpider is a web crawling and data extraction framework built on the .NET Standard platform. It is designed to help developers create efficient and scalable crawlers for collecting structured data from websites. It provides a high-level API that simplifies the process of defining spiders, managing requests, and extracting content from web pages. Developers can create custom spiders by extending base classes and configuring pipelines that handle downloading, parsing, and storing...

...Instead of using external drivers, it connects directly to the Chrome DevTools Protocol through WebSocket, allowing scripts to control browser behavior more efficiently and with fewer compatibility issues. It provides a high-level API that simplifies common browser automation tasks while still offering access to low-level protocol features for advanced control. Its architecture is built around asynchronous programming using Python’s asyncio framework, enabling concurrent automation of multiple tabs and browser contexts. Pydoll also includes tools for monitoring and intercepting network traffic, allowing developers to analyze or modify requests and responses during automation workflows. ...

...Serverless Chrome takes care of building and bundling the Chrome binaries and making sure Chrome is running when your serverless function executes. In addition, this project also provides a few example services for common patterns (e.g. taking a screenshot of a page, printing to PDF, some scraping, etc.). Why? Because it's neat. It also opens up interesting possibilities for using the Chrome DevTools Protocol (and tools like Chromeless or Puppeteer) in serverless architectures and doing testing/CI, web-scraping, pre-rendering, etc. You must configure your AWS credentials either by defining AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environmental variables, or using an AWS profile.