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An automatic TikTok video uploader w/ CLI. Uses cookies from your browser to manage authentication and upload your videos automatically.

Project description

⬆️ TikTok Uploader

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A Selenium-based uploader for TikTok Videos S

Installation

A prequisite to using this program is the installation of a Selenium-compatable Web Browser. Google Chrome is recommended

MacOS, Windows and Linux

$ pip install tiktok-uploader

Usage

While TikTok is strict about login in from Selenium, simply copying your session tokens is enough to bypass this restriction and be able to upload your videos.

$ tiktok-uploader -v video.mp4 -d "this is my description" -c cookies.txt
from tiktok_uploader.upload import upload_video, upload_videos
from tiktok_uploaader.auth import AuthBackend

# single video
upload_video('video.mp4', description='this is my description', cookies='cookies.txt')

# Multiple Videos
videos = [
    {'path': 'video.mp4', 'description': 'this is my description'},
    {'path': 'video2.mp4', 'description': 'this is also my description'}
]
auth = AuthBackend(cookies='cookies.txt')
upload_videos(videos=videos, auth=auth)

Uploading videos

This library revolves around the upload_videos function which takes in a list of videos which have filenames and descriptions and are passed as follows:

from tiktok_uploader.upload import upload_videos
from tiktok_uploader.auth import AuthBackend

videos = [
{'video': 'video0.mp4', 'description': 'Video 1 is about ..'},
{'video': 'video1.mp4', 'description': 'Video 1 is about ..'}
]

auth = AuthBackend(cookies='cookies.txt')
failed = upload_videos(videos=videos, auth=auth)

for fail in failed: # each input video object which failed
    print(fail)

Authentication

Authentication uses your browser's cookies. This workaround was done due to TikTok's stricter stance on authetication.

To get your cookies, download 🍪 Get cookies.txt from the chrome web store.

Right click while on TikTok and click 🍪 Get cookies.txt to download the file.

Optionally, if you would like to pass your own cookies you may do as an array of dictionaries with keys name, value, domain, path and expiry

The login script does have a login_accounts function, but this gets detected by the

Browser Selection

Google Chrome is the prefered browser for TikTokUploader. The default anti-detection techniques used in this packaged are optimized for this. However, if you wish to use a different browser you may specify that in upload_videos.

from random import choice

upload_videos(browser=choice(['chrome', 'safari', 'chromium', 'edge', 'firefox'])) # randomly picks a web browser (not recommended)

Supported Browsers:

  • Chrome (Recommended)
  • Safari
  • Chromium
  • Edge
  • FireFox

Custom Driver Options

This package has a set of default modifications to Selenium which help it avoid being detected by TikTok. However, you may pass custom driver configuration options as a keyword argument.

from selenium.webdriver.chrome.options import Options

options = Options()

options.add_argument('start-maximized')

upload_videos(options=options)

Note: Make sure to use the right selenium options for your browser

Headless Browsers

Headless browsers do not work at this time

If more experienced in Webscraping, I would really appreciate helping make this work. undetected-chromedriver was already tried and did not work

Initial Setup

WebDriverManager is used to manage driver versions. On intial startup, you will be promted to install the correct driver for your selected broswer.

Notes

This bot is not fool proof. I have personally not gotten banned while using this bot, but to do this, my use was kept minimal and large time gaps were placed between each action.

Without a doubt, publishing hundreds or thousands of videos sequentially will likely get you ip banned.

Please think of this package as more of a scheduled uploader for TikTok videos, rather than a spam bot

Accounts made using TikTok Uploader

  • @C_Span, a C-Span clips channel with split-screen video in the background

Project details


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tiktok_uploader-0.1.1-py3-none-any.whl (11.7 kB view hashes)

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