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Utility that recreates a torrent download directory from fully and partially downloaded files
Looks pretty overkill to me requiring 1.2 GB in package dependencies just for checking hashes
Idk if it really needs torch (probably not) but I'm almost 100% sure it doesn't need CUDA at all since it's not an AI software but a program for checking hashes (something qbittorrent does without said requirements)
Not to mention I'm not using an NVIDIA GPU so I'm pretty sure I'm downloading 600 MB for nothing
If CUDA is strictly necessary for its tasks, please put it in the README.md so I won't try to install torram in first place
This python package shares its name with https://github.com/simon-schaefer/torram used in AI development and this may cause problems in packages installation
torram.py", line 75 print fmt.format(pattern.format(num_of_success, len(mixed_pieces), len(file_infos)), 'RED', 'BOLD') ^ SyntaxError: invalid syntax
Add support for Deluge output directory autodetection
Hi. I have been looking for a linux(ubuntu) torrent cli client, or python torrent/magnet downloader that could download large files and split them WHILE IT IS DOWNLOADING, for example: a large file like file.iso
with 10GB size, gets downloaded as ten 1GB files like file.iso.part1
, file.iso.part2
(without download the whole file and then split it).
it is because my server has limited storage capacity. then i can join them together using cat
in my PC.
Is it possible to add this feature to this library? or do you know any client/library that can do this?
thank you.
Create a setup.py in order this to be easy installable
Example folder name:
【P】게임모음집
WindowsError: [Error 123] The filename, directory name, or volume label syntax is incorrect: 'm:\downloads\P\2\?P?????'
It does work when I run it from my NAS though (a flavor of linux).
I do not consent to having my code on GitHub. Please take it down
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