A complete series on building an AI-powered web scraper. We'll crawl Douban Top 250 movies, use DeepSeek AI to parse unstructured data, store it in SQLite, and generate visualizations.
What You'll Learn
- Web scraping with httpx and BeautifulSoup
- AI-powered data parsing with DeepSeek API
- SQLite database design and operations
- Data visualization with matplotlib
- CLI development with argparse
- Error handling and logging best practices
Tutorial Series
1
Building an AI-Powered Web Scraper
Project overview, environment setup, analyzing HTML structure, and basic spider implementation.
Beginner • 15 min read2
Using DeepSeek AI for Data Parsing
DeepSeek API integration, prompt design, error handling, and cost optimization.
Intermediate • 20 min read3
SQLite Database Design
Schema design, creating tables, batch operations, and querying data.
Beginner • 15 min read4
Data Visualization with Matplotlib
Creating charts - year distribution, top directors, genres, ratings.
Beginner • 20 min read5
Building a Python CLI Application
CLI with argparse, error handling, logging, and best practices.
Intermediate • 15 min readProject Repository
Complete source code on GitHub:
github.com/stars1324/python-ai-spiderPrerequisites
- Python 3.10 or higher
- Basic Python knowledge
- DeepSeek API key (free tier available)
- Familiarity with HTML/CSS (helpful but not required)
What You'll Build
Douban AI Spider - Intelligent Movie Data Crawler
Features:
- Automated crawling of 250 top-rated movies
- AI-powered parsing of unstructured data
- SQLite database for data persistence
- Statistical charts and analysis
Tech Stack:
- httpx (HTTP client)
- BeautifulSoup (HTML parsing)
- OpenAI SDK (LLM integration)
- SQLite (database)
- matplotlib (visualization)