Metadata-Version: 2.1
Name: pygelbooru
Version: 0.3.2
Summary: PyGelbooru is an unofficial and lightweight asynchronous library for the Gelbooru API.
Home-page: https://github.com/FujiMakoto/pygelbooru
Author: Makoto
Author-email: FujiMakoto@users.noreply.github.com
License: gpl-3.0
Download-URL: https://github.com/FujiMakoto/pygelbooru/archive/v0.3.2.tar.gz
Description: # PyGelbooru
        ![GitHub](https://img.shields.io/github/license/FujiMakoto/pygelbooru)
        
        PyGelbooru is an unofficial and lightweight asynchronous library for the [Gelbooru](https://gelbooru.com/) API.
        
        # Installation
        This library requires [Python 3.6](https://www.python.org) or above.
        
        You can install the library through pip as follows,
        ```shell script
        pip install pygelbooru
        ```
        
        ## Usage
        
        ### Searching
        The primary use for this library is, naturally, to search for images with specific tags.
        
        This can be done as so:
        ```python
        from pygelbooru import Gelbooru
        
        # API key/user ID is optional, but access may be limited without them
        gelbooru = Gelbooru('API_KEY', 'USER_ID')
        
        results = await gelbooru.search_posts(tags=['dog ears', '1girl'], exclude_tags=['nude'])
        [<GelbooruImage(id=5105386, filename='b77e69be0a4b...dde071dc.jpeg', owner='anon2003')>,
         <GelbooruImage(id=5105161, filename='bf169f891ebe...02bceb5e.jpeg', owner='cpee')>,
         <GelbooruImage(id=5104148, filename='46df3ebe2d41...4316d218e.jpg', owner='danbooru')>,
         <GelbooruImage(id=5104080, filename='e8eec23d151e...419293401.png', owner='anon2003')>,
         <GelbooruImage(id=5103937, filename='5bf279f3c546...be3fc53c8.jpg', owner='danbooru')>,
         ...
         ```
        Tags **can** contain spaces when passed as arguments, they will simply be reformated with underscores before being queried, so you don't need to reformat them yourself.
        
        Results are returned as a list of GelbooruImage containers. When cast to a string, this will return the image_url,
        ```python
        str(results[0])
        'https://img2.gelbooru.com/images/b7/7e/b77e69be0a4b581eac597527dde071dc.jpeg'
        ```
        
        You can also pull other information returned by the API,
        https://github.com/FujiMakoto/pygelbooru/blob/master/pygelbooru/gelbooru.py#L32-L47
        
        ### Searching (Random)
        In addition to searching for a large list of images, PyGelbooru also provides a helper method for when you're really just after a single, random image that matches the specified tags.
        
        This method will automatically pull a random image from the last 20,000 Gelbooru image submissions.
        
        ```python
        result = await gelbooru.random_post(tags=['cat ears', '1girl', 'cat hood', 'bell'], exclude_tags=['nude'])
        <GelbooruImage(id=5106718, filename='bbbdfbf9e883...161753514.png', owner='6498')>
        ```
        
        ### Comments
        
        You can fetch post comments directly from the GelbooruImage container,
        ```python
        post = await gelbooru.get_post(5099841)
        await post.get_comments()
        [<GelbooruComment(id=2486074, author='Anonymous', created_at='2020-01-28 08:47')>]
        ```
        
        ### Tags
        Besides searching for images, you can also pull information on tags as follows,
        ```python
        await gelbooru.tag_list(name='dog ears')
        <GelbooruTag(id=773, name='dog_ears', count=22578)>
        
        # Use "name_pattern" to search for partial matches to a specified tag
        await gelbooru.tag_list(name_pattern='%splatoon%', limit=4)
        [<GelbooruTag(id=892683, name='splatoon_(series)', count=11353)>,
         <GelbooruTag(id=759189, name='splatoon_2', count=3488)>,
         <GelbooruTag(id=612372, name='aori_(splatoon)', count=2266)>,
         <GelbooruTag(id=612374, name='hotaru_(splatoon)', count=2248)>]
        ```
        
Keywords: gelbooru,anime,artwork,anime artwork,booru
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Multimedia :: Graphics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
