pytok

This is a Playwright based version of David Teacher's unofficial api wrapper for TikTok.com in python. It re-implements a currently limited set of the features of the original library, with a shifted focus on using browser automation to allow manual captcha solves with a hopefully minor trade-off in performance.

Installation

pip install git+https://github.com/networkdynamics/pytok.git@master

Quick Start Guide

Here's a quick bit of code to get the videos from a particular hashtag on TikTok. There's more examples in the examples directory.

import asyncio

from pytok.tiktok import PyTok

async def main():
    async with PyTok() as api:
        user = api.user(username="therock")
        user_data = await user.info()
        print(user_data)

        videos = []
        async for video in user.videos():
            video_data = video.info()
            print(video_data)

if __name__ == "__main__":
    asyncio.run(main())

Please note pulling data from TikTok takes a while! We recommend leaving the scripts running on a server for a while for them to finish downloading everything. Feel free to play around with the delay constants to either speed up the process or avoid TikTok rate limiting, like so: PyTok(request_delay=10)

Please do not hesitate to make an issue in this repo to get our help with this!

Format and Schema

The JSONable dictionary returned by the info() methods contains all of the data that the TikTok API returns. We have provided helper functions to parse that data into Pandas DataFrames, utils.get_comment_df(), utils.get_video_df() and utils.get_user_df() for the data from comments, videos, and users respectively.

The video dataframe will contain the following columns:

Field name	Description
video_id	Unique video ID
createtime	UTC datetime of video creation time in YYYY-MM-DD HH:MM:SS format
author_name	Unique author name
author_id	Unique author ID
desc	The full video description from the author
hashtags	A list of hashtags used in the video description
share_video_id	If the video is sharing another video, this is the video ID of that original video, else empty
share_video_user_id	If the video is sharing another video, this the user ID of the author of that video, else empty
share_video_user_name	If the video is sharing another video, this is the user name of the author of that video, else empty
share_type	If the video is sharing another video, this is the type of the share, stitch, duet etc.
mentions	A list of users mentioned in the video description, if any
digg_count	The number of likes on the video
share_count	The number of times the video was shared
comment_count	The number of comments on the video
play_count	The number of times the video was played

The comment dataframe will contain the following columns:

Field name	Description
comment_id	Unique comment ID
createtime	UTC datetime of comment creation time in YYYY-MM-DD HH:MM:SS format
author_name	Unique author name
author_id	Unique author ID
text	Text of the comment
mentions	A list of users that are tagged in the comment
video_id	The ID of the video the comment is on
comment_language	The language of the comment, as predicted by the TikTok API
digg_count	The number of likes the comment got
reply_comment_id	If the comment is replying to another comment, this is the ID of that comment

The user dataframe will contain the following columns:

Field name	Description
id	Unique author ID
unique_id	Unique user name
nickname	Display user name, changeable
signature	Short user description
verified	Whether or not the user is verified
num_following	How many other accounts the user is following
num_followers	How many followers the user has
num_videos	How many videos the user has made
num_likes	How many total likes the user has had
createtime	When the user account was made. This is derived from the id field, and can occasionally be incorrect with a very low unix epoch such as 1971