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Colly: Elegant Scraper and Crawler Framework for Golang

Colly is a fast and elegant Go library for web scraping and crawling, providing a clean interface and handling complexity like concurrency, distributed scraping, and session management.

Go
Added on 2025年6月7日
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Colly: Elegant Scraper and Crawler Framework for Golang preview
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Project Introduction

Summary

Colly is an open-source Go library designed to make web scraping and crawling easy, fast, and scalable. It offers a clean API for developers to define how to visit pages and extract data.

Problem Solved

Building web scrapers from scratch in Go can be complex, requiring handling of concurrent requests, error management, session states, and politeness towards target sites. Colly abstracts these complexities, allowing developers to focus on data extraction.

Core Features

Event-Driven Architecture

Provides a simple, event-driven API for building scraping logic.

Distributed Scraping Support

Supports distributed scraping by coordinating multiple instances.

Session and Cookie Management

Handles cookies, sessions, redirects, and maintains order of requests.

Crawler Etiquette Features

Built-in mechanisms for rate limiting, random user agents, and request delays.

Tech Stack

Golang
HTTP
HTML Parsing
Concurrency

使用场景

Colly is suitable for a wide range of web data collection and automation tasks, including but not limited to:

E-commerce Data Collection

Details

Automatically collecting product information, prices, and reviews from e-commerce websites for market analysis or competitive monitoring.

User Value

Gain competitive insights and automate market data aggregation.

Content Monitoring and Aggregation

Details

Building tools to monitor news websites, blogs, or social media for specific keywords or updates.

User Value

Stay informed on relevant topics or build content aggregation services.

Academic Research Data Gathering

Details

Gathering data from public websites for academic research, such as collecting public records or large text corpora.

User Value

Efficiently collect data needed for studies without manual effort.

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