SauceNAO

unofficial python module to make working with SauceNAO in projects easier

Installing

This script runs with Python 3.
There is a currently working Python 2 branch, but I'm not going to update it anymore.
Download this repository and run the setup.py to install all necessary dependencies

Dependencies

Required:

• BeautifulSoup - html parser
• requests - http library

Optional:

• Pillow - Python Imaging Library, used to generate images for unittests
• python-dotenv - .env file loader used for unittests
• requests-mock - requests mock responses used for unittests

Usage

You can run SauceNAO either as module:

import logging
from saucenao import SauceNao

saucenao = SauceNao(directory='directory', databases=999, minimum_similarity=65, combine_api_types=False, api_key='',
                    exclude_categories='', move_to_categories=False,  use_author_as_category=False,
                    output_type=SauceNao.API_HTML_TYPE, start_file='', log_level=logging.ERROR,
                    title_minimum_similarity=90)

or as application:

python usage.py --dir [--databases] [--minimum-similarity] [--combine-api-types] [--api-key] [--exclude-categories] [--move-to-categories] [--use-author-as-category] [--output-type] [--start-file] [--log-level] [--filter-creation-date] [--filter-modified-date] [--title-minimum-similarity]

you can also use it to get the gathered information for your own script:

filtered_results = saucenao.check_file(file_name='test.jpg')

or get a generator object for a bulk of files using the worker class, all parameters work here too:

from saucenao import Worker

results = Worker(directory='directory', files=('test.jpg', 'test2.jpg')).run()

Running the tests

In the tests folder you can run each unittest individually.
The test cases should be self-explanatory.

Development

Want to contribute? Great!
I'm always glad hearing about bugs or pull requests.

License

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

Thanks

A big thanks to SauceNAO who are indexing all the images and compare them.
This script would be completely useless without them.