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NanmiCoder avatar

NanmiCoder/CrawlerTutorial

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4,262 stars·471 forks·Python·2 vuesnanmicoder.github.io/CrawlerTutorial↗

CrawlerTutorial

CrawlerTutorial est un tutoriel complet de web scraping en Python et un framework conçu pour extraire des données de sites web statiques et dynamiques. Il fonctionne comme un pipeline d'extraction de données web et un orchestrateur de requêtes HTTP, couvrant tout le cycle de vie des applications de scraping, de la récupération initiale au stockage final des données.

Le projet fournit des conseils spécialisés sur les techniques de contournement anti-bot et l'ingénierie inverse d'API web. Il inclut des méthodes pour échapper à la détection par navigateur via le masquage d'identité et la rotation de proxies, ainsi que des techniques pour identifier les points de terminaison d'API cachés en analysant le trafic réseau et les signatures de requêtes.

Le framework englobe un large ensemble de capacités, incluant l'automatisation de navigateur pour les pages riches en JavaScript, l'authentification utilisateur automatisée via codes QR ou SMS, et la gestion de la persistance de session. Il dispose également d'outils de prétraitement de données pour nettoyer le texte brut, supprimer les enregistrements en double et persister les informations recueillies dans des fichiers plats ou des bases de données relationnelles.

Features

  • Web Data Extraction - Functions as a comprehensive system for programmatically scraping and processing web content from various sources.
  • Web Scraping Tutorials - Provides an extensive educational guide and project-based materials for performing web scraping using Python.
  • HTML Parsing - Provides tools for extracting structured data from HTML using selectors to isolate repeating data blocks.
  • Web Data Pipelines - Implements an automated pipeline for fetching, cleaning, and storing scraped web data into flat files or databases.
  • Web Page Parsing - Extracts specific text, links, and images by analyzing the structure of downloaded web pages.
  • Browser Automation Frameworks - Implements a framework for simulating user interactions to extract content from JavaScript-heavy, dynamic webpages.
  • Headless Browser Automation - Automates headless browser engines to render JavaScript and interact with dynamic web content.
  • Browser Automation - Provides programmatic control of browsers to simulate user interactions and manage isolated execution contexts.
  • HTTP Request Execution - Executes synchronous and asynchronous HTTP requests to retrieve data from web servers.
  • Outbound IP Rotation - Distributes requests across a pool of rotating proxy addresses to bypass server-side IP rate limits.
  • Anti-Bot Evasion - Implements browser fingerprint masquerading and proxy rotation to evade sophisticated bot detection systems.
  • Browser Fingerprint Spoofing - Provides tools to spoof browser fingerprints and TLS parameters to evade automated bot detection systems.
  • Browser Automation - Simulates user interactions in headless browsers to extract data from JavaScript-heavy dynamic pages.
  • Concurrent Crawling Engines - Executes multiple network requests simultaneously using asynchronous tasks to accelerate data extraction.
  • JavaScript-Rendered Content Extractors - Includes capabilities to wait for JavaScript execution and ensure dynamic content is fully rendered before extraction.
  • Network Request Interception - Captures API responses and JSON data directly from network traffic to avoid complex DOM parsing.
  • HTTP Header and Cookie Management - Manages HTTP headers and cookies to mimic real browser behavior and maintain request identity.
  • Anti-Detection Automations - Utilizes anti-detection automations to modify browser properties and bypass bot detection mechanisms.
  • Browser Automation - Controls browser processes and isolated contexts to perform complex web actions and manage sessions.
  • Large-Scale Domain Crawlers - Provides a unified framework to manage the full lifecycle of large-scale web scraping applications.
  • Web Scraping Evasion Tools - Provides specialized tools and techniques to mask automation traces and evade bot detection systems.
  • Web Page Retrievers - Downloads HTML content from websites while managing request frequency and concurrency rules.
  • Web Scraping and Extraction - Provides tools for parsing HTML documents to extract structured text and links from static websites.
  • API Reverse Engineering - Offers methods for analyzing network traffic to identify hidden API endpoints and bypass request signatures.
  • Regex Data Extraction - Uses regular expressions to isolate specific values from unstructured text strings.
  • Web Parsing - Retrieves information from web pages using CSS selectors and XPath expressions.
  • Text Cleaning - Cleans raw scraped text by removing HTML tags and fixing encoding for structured analysis.
  • Data Cleaning Pipelines - Implements data cleaning pipelines to transform raw scraped content into usable formats for analysis.
  • Data Processing - Transforms raw crawled data into structured formats suitable for visualization and analysis.
  • Text Preprocessing - Includes tools for cleaning raw scraped text, removing duplicate records, and transforming data into analysis-ready formats.
  • Web Document Parsing - Extracts specific data from HTML and XML documents using specialized parsing libraries.
  • Extracted Data Storage - Saves gathered information into databases or indexes to support searching and analysis.
  • Flat-File Storage - Writes extracted information to simple text files like CSV or JSON using asynchronous I/O.
  • Multi-Format Data Persistence - Saves extracted information across multiple storage types including JSON and CSV flat files.
  • Relational Database Persistence - Persists structured scraped data into relational databases using upsert logic to prevent duplicates.
  • Pagination Pattern Analysis - Includes methods for analyzing URL structures and HTML elements to determine how to navigate paginated results.
  • API-Based Extractions - Retrieves structured data by constructing authenticated HTTP requests to identified API endpoints.
  • Tabular Data Manipulations - Performs tabular data manipulations using data frames to structure and transform extracted information.
  • Token Bucket Implementations - Implements a token bucket algorithm to control request frequency and prevent server overloading.
  • QR Code & Phone Verification Logins - Automates the login process by simulating QR code scanning and polling for authentication status.
  • Phone Verification Code Logins - Handles SMS-based authentication by automating the entry of phone numbers and verification codes.
  • HTTP Request Orchestrators - Ships a system for orchestrating concurrent network requests with integrated proxy rotation and session persistence.
  • HTTP Traffic Inspection - Identifies hidden API endpoints by capturing and analyzing HTTP request and response traffic.
  • Bot Detection Bypass - Avoids IP bans by applying random request delays and capping crawl volume to mimic human behavior.
  • API Endpoint Discovery - Provides techniques for discovering hidden API endpoints by analyzing network traffic and request signatures.
  • Session State Management - Manages local session state by tracking authentication tokens and cookies throughout the extraction process.
  • Anti-Captcha Strategies - Reduces the occurrence of verification walls by managing request frequency and reusing session cookies.
  • Rate Limit Bypasses - Circumvents server-side IP blocks through identity randomization and request frequency management.
  • Session Authentication Strategies - Implements session authentication strategies including QR-based authorization to access restricted data.
  • Session-Cookie Persistences - Persists and reuses session cookies and tokens to maintain authenticated states across scraping runs.
  • Authentication Token Extraction - Retrieves authentication tokens and session cookies from browser contexts for use in programmatic requests.
  • Protection Bypassers - Implements signature algorithms and header management to circumvent automated API security challenges.
  • User Authentications - Handles user identity verification and session persistence through the management of cookies and CAPTCHA resolution.
  • Concurrent Task Execution - Implements concurrent execution of network requests to improve the throughput of data extraction.
  • Retry Policies - Handles network instability and transient errors by automatically retrying failed scraping operations.
  • Request Rate Limiting - Controls outgoing request frequency using a token bucket mechanism to avoid server overloading.
  • Crawl Request Deduplications - Prevents redundant crawling by filtering and deduplicating extracted URLs using a tracking system.
  • Browser Session Managers - Reuses existing browser sessions to minimize resource overhead and improve execution efficiency.
  • Resource Blocking - Blocks non-essential resources like images and fonts to reduce bandwidth and increase extraction speed.
  • Crawler Identity Masking - Configures HTTP headers and TLS fingerprints to simulate real browser behavior and evade detection.
  • Request Proxying - Hides the origin IP address by routing web requests through a pool of intermediate proxy servers.

Historique des stars

Graphique de l'historique des stars pour nanmicoder/crawlertutorialGraphique de l'historique des stars pour nanmicoder/crawlertutorial

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Questions fréquentes

Que fait nanmicoder/crawlertutorial ?

CrawlerTutorial est un tutoriel complet de web scraping en Python et un framework conçu pour extraire des données de sites web statiques et dynamiques. Il fonctionne comme un pipeline d'extraction de données web et un orchestrateur de requêtes HTTP, couvrant tout le cycle de vie des applications de scraping, de la récupération initiale au stockage final des données.

Quelles sont les fonctionnalités principales de nanmicoder/crawlertutorial ?

Les fonctionnalités principales de nanmicoder/crawlertutorial sont : Web Data Extraction, Web Scraping Tutorials, HTML Parsing, Web Data Pipelines, Web Page Parsing, Browser Automation Frameworks, Headless Browser Automation, Browser Automation.

Quelles sont les alternatives open-source à nanmicoder/crawlertutorial ?

Les alternatives open-source à nanmicoder/crawlertutorial incluent : apify/crawlee — Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction… wistbean/learn_python3_spider — This project is a comprehensive educational guide and framework for building web scrapers using Python. It provides a… apify/crawlee-python — Crawlee-python is a web crawling framework for building scalable scrapers using Python. It serves as a comprehensive… guyungy/damaihelper — Damaihelper is a ticketing automation bot and browser automation framework designed to monitor ticket availability and… kr1s77/python-crawler-tutorial-starts-from-zero — This project is a Python web scraping tutorial and framework designed for building automated data extraction tools and… lorien/web-scraping — This project is a comprehensive resource directory for web data extraction, providing a curated collection of tools…

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