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yt_dl_project's Introduction

yt_dl_project

SET UP BOTO3

  • Set up AWS credentials in AWSCredentials class in aws_helpers.py script.
  • Create and place the key file in the ./aws directory (where Boto3 checks, check documentation).

CONFIGURE INPUT FILE

  • Upload input.json from ./data to the S3 bucket named 'ytdlinput'.

FOR RUNNING LOCALLY

  • Install requirements from requirements.txt
  • Create and add ffmpeg in the ./dep directory (./dep/ffmpeg/bin/ffmpeg.exe).
  • Upload input.json from ./data to the S3 bucket named 'ytdlinput'.
  • Set RUN_LOCALLY=True and USE_RAY to True or False if you want to run it using Ray or sequentially.

FOR RUNNING ON AWS CLUSTER

  • For Windows, in WSL CLI run:
    • Create the cluster: 
      ray up -y /mnt/c/Users/Stefan/Desktop/Personal/Projects/Soniox/yt_dl_project/ray/yt_dl_cluster.yaml
    • Forward ports locally: 
      ray dashboard /mnt/c/Users/Stefan/Desktop/Personal/Projects/Soniox/yt_dl_project/ray/yt_dl_cluster.yaml
    • Submit task: 
      RAY_ADDRESS='http://localhost:8265' ray job submit --runtime-env-json='{"working_dir": "./", "pip": ["boto3", "boto3-stubs[dynamodb]", "scrapetube", "youtube-transcript-api", "youtube-wpm"]}' -- python ./pipeline.py

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