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advanced Level⏱️ 15 min read⏳ 3 hr build
Python Web Scraper Project: Step-by-Step Code & Tutorial
Build an ethical, polite web scraper in Python using built-in urllib or requests to extract title headlines and structured data from sample HTML pages, format results into CSV, and respect robots.txt rules.
✅ Prerequisites Checklist
- ✓Understanding of HTML structure and DOM elements
- ✓Familiarity with HTTP GET requests
- ✓Understanding of string parsing or regular expressions
- ✓Familiarity with Python CSV module
📁 Folder & File Structure
web_scraper/ ├── scraper.py ├── output.csv └── README.md
📐 Architecture & Execution Blueprint
High-level data flow and component dispatch
[Target URL] ➔ [robots.txt Check] ➔ [HTTP Request: HTML Fetch] ➔ [Parse Data Elements] ➔ [Format CSV Output]
Algorithm & Process Flow
- Verify target URL permits crawling by inspecting robots.txt.
- Send HTTP GET request with standard User-Agent headers.
- Receive HTML response body as a text string.
- Parse specific HTML tags (e.g., <h2> or <li> items) using string methods or regex.
- Clean extracted text and write structured rows into output.csv.
### Step 1: Project Setup
Create folder `web_scraper` and script `scraper.py`. We use `urllib.request` and `csv`.
### Step 2: Core Logic Implementation
Implement the HTML fetching function with custom User-Agent headers to ensure polite requests.
```python
import urllib.request
import urllib.error
import re
import csv
def fetch_html(url: string) -> string:
req = urllib.request.Request(
url,
headers={'User-Agent': 'Mozilla/5.0 (Education Bot)'}
)
with urllib.request.urlopen(req) as response:
return response.read().decode('utf-8')
```
### Step 3: Parsing & Exporting
Extract headlines and write to CSV.
```python
def parse_headlines(html: string) -> list:
# Extracting standard h2 tags using regex for demonstration
matches = re.findall(r'
(.*?)<\/h2>', html, re.DOTALL) clean = [re.sub(r'<.*?>', '', m).strip() for m in matches] return clean ```
### Step 4: Politeness & Exceptions
Always catch HTTP errors (404, 500) and respect crawl delays.
🐛 Common Bugs & Troubleshooting
How to resolve typical implementation hurdles
| Symptom / Bug | Solution / Fix |
|---|---|
| HTTP 403 Forbidden error. | Add User-Agent header to HTTP request. |
| UnicodeEncodeError when writing to CSV. | Use encoding='utf-8' when opening file. |
⚡ How to Extend This Project
- ★Use BeautifulSoup or lxml for robust DOM parsing instead of regex.
- ★Add pagination scraping across multiple sequential pages.
- ★Implement automatic robots.txt verification before fetching.
💡 Helpful AI Prompts
- 💬"Show how to parse tables from HTML pages using Python."
- 💬"Explain how to handle rate-limiting and exponential backoff."
❓ Frequently Asked Questions
Q: Is web scraping legal?
Public data scraping is generally permitted for educational/research purposes, but you must respect website terms of service and robots.txt rules.
Q: Why use urllib instead of requests?
urllib is built directly into Python, making this script run without pip installs.