Parsera is a lightweight library designed for efficient web scraping using large language models (LLMs). It simplifies data extraction from websites, making it an essential tool for developers and data enthusiasts looking to automate their scraping tasks with Python.
claude install raznem/parserahttps://docs.parsera.org
Extract product data from e-commerce sites to analyze pricing trends.
Gather market research data from competitor websites for strategic insights.
Automate content scraping for analysis, such as news articles or blog posts.
Collect user reviews from multiple platforms to evaluate customer sentiment.
claude install raznem/parseragit clone https://github.com/raznem/parseraCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I want to extract specific data from [WEBSITE] related to [DATA TYPE]. Can you help me create a Parsera script to scrape this information efficiently?
### Parsera Web Scraping Script
```python
from parsera import Parsera
# Initialize Parsera with the target URL
url = 'https://example.com/products'
# Create a Parsera instance
parser = Parsera(url)
# Define the data structure to scrape
data = parser.scrape(
target_element='div.product',
fields={
'name': 'h2.product-name',
'price': 'span.price',
'availability': 'span.availability'
}
)
# Output the scraped data
print(data)
```
### Output
```json
[
{
"name": "Product 1",
"price": "$19.99",
"availability": "In Stock"
},
{
"name": "Product 2",
"price": "$29.99",
"availability": "Out of Stock"
}
]
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