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No-bullshit file hosting and URL shortening service https://0x0.st
9c4a0fd5a6
This PR removes the short_url dependency as per issue #41. This implementation is pretty much the same as in short_url except I've rewritten the enbase() function to be iterative instead of recursive. The only functions of the class are enbase() and debase() since those were the only functions being used by fhost. Co-authored-by: 7415963987456321 <hrs70@hi.is> Reviewed-on: https://git.0x0.st/mia/0x0/pulls/53 Co-authored-by: mia <mia@0x0.st> Co-committed-by: mia <mia@0x0.st> |
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migrations | ||
nsfw_model | ||
templates | ||
tests | ||
.gitignore | ||
.mailmap | ||
cleanup.py | ||
fhost.py | ||
LICENSE | ||
nsfw_detect.py | ||
pyproject.toml | ||
README.rst | ||
requirements.txt |
The Null Pointer ================ This is a no-bullshit file hosting and URL shortening service that also runs `0x0.st <https://0x0.st>`_. Use with uWSGI. Configuration ------------- To change settings, modify ``instance/config.py``. For more information on instance configuration, see `the Flask documentation <https://flask.palletsprojects.com/en/2.0.x/config/#instance-folders>`_. To customize the home and error pages, simply create a ``templates`` directory in your instance directory and copy any templates you want to modify there. If you are running nginx, you should use the ``X-Accel-Redirect`` header. To make it work, include this in your nginx config’s ``server`` block:: location /up { internal; } where ``/up`` is whatever you’ve configured as ``FHOST_STORAGE_PATH``. For all other servers, set ``FHOST_USE_X_ACCEL_REDIRECT`` to ``False`` and ``USE_X_SENDFILE`` to ``True``, assuming your server supports this. Otherwise, Flask will serve the file with chunked encoding, which sucks and should be avoided at all costs. To make files expire, simply create a cronjob that runs ``cleanup.py`` every now and then. Before running the service for the first time, run ``FLASK_APP=fhost flask db upgrade``. NSFW Detection -------------- 0x0 supports classification of NSFW content via Yahoo’s open_nsfw Caffe neural network model. This works for images and video files and requires the following: * Caffe Python module (built for Python 3) * ``ffmpegthumbnailer`` executable in ``$PATH``