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Small module to work with SauceNAO locally

Project description

SauceNAO

Build Status Scrutinizer Code Quality Coverage Status
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:

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.

Project details


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