Metadata-Version: 2.2
Name: quickscrape
Version: 0.1.1
Summary: A simple library for extracting common data types from web pages
Author-email: Utku Ayaz Akkas <akkas@ieee.org>
Project-URL: Homepage, https://github.com/akkasayaz/quickscrape
Project-URL: Bug Tracker, https://github.com/akkasayaz/quickscrape/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: beautifulsoup4>=4.9.0
Requires-Dist: requests>=2.25.0
Requires-Dist: pandas>=1.2.0

# QuickScrape

A simple Python library for extracting common data types from web pages.

## Installation

```bash
pip install quickscrape
```

## Usage

```python-repl
import quickscrape

# Extract emails from a webpage
emails = quickscrape.extract("email", "https://example.com/contact")

# Extract tables
tables = quickscrape.extract("table", "https://example.com/data")
# Get tables as pandas DataFrames
tables_df = quickscrape.extract("table", "https://example.com/data", output_format="dataframe")

# Extract multiple data types at once
results = quickscrape.extract(["email", "table"], "https://example.com")email", "https://example.com/contact")

# Extract tables
tables = quickscrape.extract("table", "https://example.com/data")
```

## License

MIT

### Development Workflow

1. **Local Development**: Install your package in development mode:

   ```bash
   pip install -e .
   ```
2. **Testing** : Use pytest for writing and running tests.

   ```bash
   pip install pytest
   pytest
   ```
