This project is an ongoing initiative aimed at developing an automated pipeline to extract and process video data from YouTube based on specific keywords. Leveraging the YouTube Data API, the pipeline retrieves the most-viewed videos matching the criteria and systematically stores the data in a GitHub repository. The goal is to automate data retrieval, analysis, and storage, enabling actionable insights.
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Source: Kaggle -> Google Cloud Console (YouTube Data API v3) -> Data Extraction -> GitHub File Storage
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Data Cleaning: Kaggle -> Fetch Source File from GitHub -> Data Cleaning -> GitHub File Storage
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Requirement: Kaggle -> Fetch ISO Code from Rest API -> Process -> GitHub File Storage
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Feature Engineering: Kaggle Fetch Data Cleaned and Requirement Files -> Process -> GitHub File Storage
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Streamlit: Streamlit Cloud -> Fetch Feature Engineering File from GitHub -> Process and Visualize on Streamlit -> Deployed App
Every process fetches the most recent file to ensure up-to-date data. The process runs daily for real-time data.
This project ensures efficient and automated extraction, processing, and storage of YouTube video data, making it a valuable resource for content trend analysis.
This project uses a dual-license approach:
1. Non-Code Content License
This project’s documentation, descriptions, and visualizations are licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
- You must provide appropriate credit.
- The content may not be used for commercial purposes.
- Redistribution is allowed only in its original form without modifications.
For more details, visit: CC BY-NC-ND 4.0
2. Source Code License
The source code of this project is licensed under the Mozilla Public License 2.0 (MPL-2.0).
- You may modify and distribute the code, but any modified files must also be licensed under MPL-2.0.
- Only MPL-licensed files must remain open-source if used with proprietary software.
- The code is provided as-is, without any guarantees or warranty.
For more details, visit: MPL-2.0
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