quickfetch 0.1.0

Fast, simple, and beautifully minimal web scraping

🚀 quickfetch - Quick Fetch

Fast, simple, and beautifully minimal web scraping.

✨ The Problem

Python developers who need to grab HTML or JSON from the web must currently:

1. Import requests to fetch content
2. Import BeautifulSoup or lxml to parse HTML
3. Write 6–10 lines of boilerplate code just to get basic data

This is slow, repetitive, and messy for quick scripts.

🎯 The Solution

quickfetch makes web scraping a 1–2 line task with auto-detection of HTML/JSON content.

🚀 Quick Start

Installation

pip install quickfetch

Basic Usage

from quickfetch import get

# Fetch a webpage
page = get("https://example.com")
print(page.select("h1").text)  # Get first h1 text
print(page.links)              # Get all links
print(page.images)             # Get all images

# Fetch JSON API
data = get("https://api.github.com/users/octocat")
print(data.json["name"])       # Access JSON data directly

🎨 Features

Core Features

• get(url) → Returns a response object with:
  • .html → Raw HTML content (if HTML response)
  • .json → Parsed JSON data (if JSON response)
  • .select(css_selector) → CSS selector matching
  • .xpath(xpath_expr) → XPath expression matching
  • .links → All hyperlinks on the page
  • .images → All image URLs on the page

Auto-Detection

quickfetch automatically detects if the response is HTML or JSON:

# HTML page
page = get("https://example.com")
print(page.html)    # Raw HTML
print(page.json)    # None

# JSON API
data = get("https://api.github.com/users/octocat")
print(data.html)    # None
print(data.json)    # Parsed JSON dict

CSS Selectors

page = get("https://example.com")

# Get first element
title = page.select("h1")[0].text

# Get all elements
links = page.select("a[href]")
for link in links:
    print(link.text, link["href"])

# Nested selection
articles = page.select("article")
for article in articles:
    title = article.select("h2")[0].text
    content = article.select("p")[0].text

XPath Support

page = get("https://example.com")

# XPath expressions
elements = page.xpath("//h1[@class='title']")
for elem in elements:
    print(elem.text)

Link & Image Extraction

page = get("https://example.com")

# Get all links
all_links = page.links
print(f"Found {len(all_links)} links")

# Get all images
all_images = page.images
print(f"Found {len(all_images)} images")

Element Properties

page = get("https://example.com")
element = page.select("a")[0]

print(element.text)     # Text content
print(element.html)     # HTML content
print(element.attrs)    # All attributes
print(element["href"])  # Specific attribute

📚 Examples

Scraping News Headlines

from quickfetch import get

# Get headlines from a news site
page = get("https://news.ycombinator.com")
headlines = page.select(".titleline > a")

for headline in headlines[:5]:
    print(f"• {headline.text}")
    print(f"  {headline['href']}\n")

API Data Extraction

from quickfetch import get

# Get GitHub user data
user = get("https://api.github.com/users/octocat")
data = user.json

print(f"Name: {data['name']}")
print(f"Location: {data['location']}")
print(f"Followers: {data['followers']}")

Image Gallery Scraper

from quickfetch import get

# Get all images from a gallery
page = get("https://example.com/gallery")
images = page.images

print("Found images:")
for img_url in images:
    print(f"  {img_url}")

Form Data Extraction

from quickfetch import get

# Get form fields
page = get("https://example.com/contact")
forms = page.select("form")

for form in forms:
    inputs = form.select("input")
    for input_elem in inputs:
        name = input_elem.get("name", "")
        type_attr = input_elem.get("type", "text")
        print(f"Input: {name} ({type_attr})")

🔧 Advanced Usage

Custom Headers

from quickfetch import get

# Add custom headers
page = get("https://api.example.com", 
           headers={"User-Agent": "MyBot/1.0"})

Error Handling

from quickfetch import get

try:
    page = get("https://example.com")
    if page.html:
        print("Successfully fetched HTML")
    elif page.json:
        print("Successfully fetched JSON")
    else:
        print("No content found")
except Exception as e:
    print(f"Error: {e}")

Batch Processing

from quickfetch import get

urls = [
    "https://example1.com",
    "https://example2.com", 
    "https://example3.com"
]

for url in urls:
    page = get(url)
    title = page.select("title")[0].text if page.select("title") else "No title"
    print(f"{url}: {title}")

📦 Installation

From PyPI

pip install quickfetch

From Source

git clone https://github.com/quickfetch/quickfetch.git
cd quickfetch
pip install -e .

🛠 Dependencies

• requests ≥ 2.25.0 - HTTP library
• selectolax ≥ 0.3.0 - Fast HTML parser

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with requests for HTTP
• Powered by selectolax for HTML parsing
• Inspired by the need for simpler web scraping workflows

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Made with ❤️ for Python developers who just want to get things done quickly.