Code I use to automatically update my videos' metadata on YouTube

Overview

mCodingYouTube

This repository contains the code I use to automatically update my videos' metadata on YouTube, including: titles, descriptions, tags, etc.

mCoding YouTube channel

The code in this repository is MIT licensed, see the file named LICENSE.

Disclaimer

The code is for educational purposes, not production use. Do not run any code that you do not understand. I am not responsible if you end up deleting or otherwise irreparably damaging your YouTube account, or getting banned from YouTube/Google services by using/misusing this code.

If you do decide to play with the code, I recommend using a dummy YouTube account so that you don't put your real account in danger. Pay close attention to the amount of quota that you use in order to avoid YouTube/Google thinking you are abusing their API.

I do not condone using or modifying the code in this API to do anything that violates YouTube/Google terms of service or any applicable laws.

Official code and docs from Google/YouTube

If you would like an official set of samples for how to use the YouTube Data API in Python, see https://github.com/youtube/api-samples/tree/master/python.

The official YouTube Data API documentation (not language specific) can be found at: https://developers.google.com/youtube/v3/docs.

Trying to follow my YouTube video?

Video: I Used the YouTube API to Update My Video Descriptions

Install dependencies (execute this from the directory containing requirements.txt):

pip install -r requirements.txt

Here are the important files:

  • app_config.py: In order to avoid publishing my secret client data, I use this config to read a non-uploaded file containing the location of my secret file. If you want to modify the code to work for yourself, you can hard-code the location of your client secret file here, or use dotenv like I did.

  • youtube.py: Contains the code to make an authenticated YouTube service object. You shouldn't need to change anything in this file.

  • download_single_video_data.py: Script to download the snippet metadata to a file for a video with known video id. I recommend making a data directory and putting all your downloaded data there to avoid clutter.

  • download_my_uploads.py: Script to download the playlist item snippets for all your uploads and save each page of results to a file.

  • update_description_on_youtube.py: Functions for updating a single video description.

  • simple_prepend_to_descriptions.py: Script to load data saved using download_my_uploads.py and prepend text read from a file to all your uploaded videos by using functions from update_description_on_youtube.py in a loop.

Owner
James Murphy
I'm James Murphy, founder of mCoding. I'm interested in helping as many people learn about programming and math as possible.
James Murphy
Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)

RSPNet Official Pytorch implementation for AAAI2021 paper "RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning" [Suppleme

35 Jun 24, 2022
Code for our ACL 2021 paper "One2Set: Generating Diverse Keyphrases as a Set"

One2Set This repository contains the code for our ACL 2021 paper “One2Set: Generating Diverse Keyphrases as a Set”. Our implementation is built on the

Jiacheng Ye 63 Jan 05, 2023
Imagededup - 😎 Finding duplicate images made easy

imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.

idealo 4.3k Jan 07, 2023
Python PID Tuner - Based on a FOPDT model obtained using a Open Loop Process Reaction Curve

PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e

6 Jan 14, 2022
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I

Jiwoon Ahn 472 Dec 29, 2022
Self-Regulated Learning for Egocentric Video Activity Anticipation

Self-Regulated Learning for Egocentric Video Activity Anticipation Introduction This is a Pytorch implementation of the model described in our paper:

qzhb 13 Sep 23, 2022
A PyTorch implementation of "From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network" (ICCV2021)

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network The official code of VisionLAN (ICCV2021). VisionLAN successfully a

81 Dec 12, 2022
DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos.

DRLib:A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos A concise deep reinforcement learning libr

329 Jan 03, 2023
NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework

NLP From Scratch Without Large-Scale Pretraining This repository contains the code, pre-trained model checkpoints and curated datasets for our paper:

Xingcheng Yao 224 Dec 08, 2022
TransReID: Transformer-based Object Re-Identification

TransReID: Transformer-based Object Re-Identification [arxiv] The official repository for TransReID: Transformer-based Object Re-Identification achiev

569 Dec 30, 2022
Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).

Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma 🔥 News 2021-10

Jingtao Zhan 99 Dec 27, 2022
Angle data is a simple data type.

angledat Angle data is a simple data type. Installing + using Put angledat.py in the main dir of your project. Import it and use. Comments Comments st

1 Jan 05, 2022
Experiments on continual learning from a stream of pretrained models.

Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them

Antonio Carta 6 Dec 04, 2022
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji

Quande Liu 178 Jan 06, 2023
这是一个yolox-keras的源码,可以用于训练自己的模型。

YOLOX:You Only Look Once目标检测模型在Keras当中的实现 目录 性能情况 Performance 实现的内容 Achievement 所需环境 Environment 小技巧的设置 TricksSet 文件下载 Download 训练步骤 How2train 预测步骤 Ho

Bubbliiiing 64 Nov 10, 2022
Implementation of the CVPR 2021 paper "Online Multiple Object Tracking with Cross-Task Synergy"

Online Multiple Object Tracking with Cross-Task Synergy This repository is the implementation of the CVPR 2021 paper "Online Multiple Object Tracking

54 Oct 15, 2022
EMNLP 2021 Findings' paper, SCICAP: Generating Captions for Scientific Figures

SCICAP: Scientific Figures Dataset This is the Github repo of the EMNLP 2021 Findings' paper, SCICAP: Generating Captions for Scientific Figures (Hsu

Edward 26 Nov 21, 2022
A copy of Ares that costs 30 fucking dollars.

Finalement, j'ai décidé d'abandonner cette idée, je me suis comporté comme un enfant qui été en colère. Comme m'ont dit certaines personnes j'ai des c

Bleu 24 Apr 14, 2022
Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

Raschka Research Group 14 Dec 27, 2022