Metadata-Version: 2.1
Name: pdfharvester
Version: 0.2.1
Summary: A package for extracting tables and images from PDFs
Project-URL: Homepage, https://github.com/hashimputhiyakath/pdfharvester
Project-URL: Bug Tracker, https://github.com/hashimputhiyakath/pdfharvester/issues
Author-email: Hashim Puthiyakath <hashputhiyakath@gmail.com>
License: MIT License
        
        Copyright (c) 2023 Hashim Puthiyakath
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in
        all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
        THE SOFTWARE.
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Requires-Dist: pandas
Requires-Dist: pypdf2
Requires-Dist: textract
Requires-Dist: yake
Description-Content-Type: text/markdown

# PDFHarvester

PDFHarvester is a Python package for extracting tables, images, and keywords from PDF documents.

## Installation

You can install PDFHarvester using pip:

```sh
pip install PDFHarvester
```

# Usage

To extract tables, images, and keywords from a PDF document using PDFHarvester, you can use the following functions:

```
import pdfharvest as ph

tables = ph.extract_table('path/to/pdf')
images = ph.extract_images('path/to/pdf')
keywords = ph.extract_keywords('path/to/pdf')
```

`extract_table` returns a list of pandas dataframes, one for each table in the PDF. `extract_images` returns a list of images as numpy arrays, and `extract_keywords` returns a list of keywords as strings.

#Contributing
Bug reports and pull requests are welcome on GitHub at <https://github.com/yourusername/PDFHarvester>. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](https://www.contributor-covenant.org/) code of conduct.

#License
The package is available as open source under the terms of the [MIT License](https://github.com/yourusername/PDFHarvester/blob/main/LICENSE.md), © 2023 Hashim Puthiyakath.

Please let me know if you have any further questions or concerns.
