YouTube Playlist Manager Project

Video Demo URL

Watch the Demo

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Project Overview

The YouTube Playlist Manager project automates and manages a YouTube playlist by fetching video statistics, cleaning data, managing new song releases, and identifying top artists. It integrates various components and services to provide a seamless playlist management experience with efficient data handling and visualization.

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Main Components

1. YouTube API Manager (authenticate.py)

Handles authentication and interaction with the YouTube Data API v3.

Features

• OAuth 2.0 Authentication: Manages user authentication and token storage.
• Token Management: Refreshes expired tokens automatically.
• YouTube API Integration: Sets up the YouTube Data API client for further interactions.

Prerequisites

• Python 3.x
• Libraries: google-auth, google-auth-oauthlib, google-api-python-client, python-dotenv
• Environment Variables: Store paths to credentials and token files in a .env file.

Setup

1. Google API Credentials: Set up in Google API Console, enable YouTube Data API v3, create OAuth 2.0 credentials, and download credentials.json.
2. Token Management: The script generates token.json for future interactions.

Key Class: YouTubeAPIManager

• Initialization: __init__(self, credentials_file, token_file, scopes)
• Authentication: authenticate(self)
• Private Method: _run_auth_flow(self)

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2. Automate New Songs (new_releases.py)

Automates the addition of new songs from a source YouTube playlist to a personal playlist.

Features

• Authenticate YouTube API
• Fetch Playlist Items
• Identify and Add New Songs
• Error Handling & Logging

Prerequisites

• Python 3.x
• Library: google-api-python-client

Script Breakdown

• Class: AutomateNew (inherits from YouTubeAPIManager)
• Methods:
  • get_playlist_items(playlist_id)
  • add_song_to_playlist(playlist_id, video_id)
  • add_new_songs(from_playlist_id, to_playlist_id, number_of_songs_to_add)

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3. Playlist Manager (manager.py)

Manages playlist data by retrieving videos, parsing titles, and saving to CSV.

Features

• Retrieve Playlist Videos
• Parse Video Titles
• Save Data to CSV

Prerequisites

• Python 3.x
• Libraries: pandas

Script Breakdown

• Class: PlaylistManager (inherits from YouTubeAPIManager)
• Methods:
  • __init__()
  • get_playlist_items(playlist_id)
  • parse_video_title(title)

Example Usage

1. Replace PLAYLIST_ID in main().
2. Run the Script: python playlist_manager.py

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4. YouTube Playlist Manager (Video_stats.py)

Handles fetching video statistics, saving to CSV, and visualizing data.

Features

• Fetch Playlist Videos
• Fetch Video Statistics
• Save to CSV
• Visualize Data

Method Breakdown

• get_playlist_videos(playlist_id)
• get_video_statistics(video_id)
• collect_playlist_statistics(playlist_id, output_csv)
• visualize_statistics(df)

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5. Data Cleaning and Visualization

• Data Cleaning: Removes unwanted text and ensures uniform formatting in CSV files.
• Top Artists Visualization: Identifies and visualizes the most common artists from the playlist data.

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Main Program Flow (main.py)

Integrates functionalities to:

• Clean Playlist Statistics and Data
• Plot Top Common Artists
• Fetch New Songs
• Fetch Video Statistics
• Fetch Song Data

Configuration

• PLAYLIST_ID: ID of the playlist to manage.
• FROM_PLAYLIST_ID: ID of the source playlist for new songs.
• STATS_OUTPUT_CSV: Output file for video statistics.
• NUMBER_OF_SONGS_TO_ADD: Limit for new songs to be added.

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Logging

Tracks operations and errors to assist in debugging.

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Project Structure

YouTubePlaylistManager
│
├── Video_stats.py           # YouTube playlist statistics handling logic
├── manager.py               # General playlist management and parsing logic
├── new_releases.py          # Automated fetching and addition of new songs
├── playlist_data.csv        # Playlist song data (generated if not present)
├── playlist_stats.csv       # Playlist video statistics data (generated if not present)
├── cleaned_playlist_data.csv # Cleaned playlist data file
├── clean_playlist_stats.csv # Cleaned playlist statistics data file
├── README.md                # Project documentation (this file)
└── project.py               # Main script integrating all functionalities

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Running the Program

1. Execute: python project.py
2. Follow Prompts: Use the console menu to select operations.

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Requirements

The project requires the following Python libraries:

• pandas: For handling CSV files and DataFrame operations.
• matplotlib: For visualizing data through graphs.
• logging: For logging information, warnings, and errors during execution.
• re: For text cleaning using regular expressions.
• csv: For reading from and writing to CSV files.
• os: For checking file existence.
• collections.Counter: For counting occurrences of elements (e.g., artists).

Ensure that these libraries are installed before running the project.

Dependencies Installation

pip install google-auth google-auth-oauthlib google-api-python-client python-dotenv pandas matplotlib

OR

pip install -r requirements.txt

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Unit Test Description

This unit test file validates key functionalities of the YouTube Playlist Manager project:

• test_clean_stats: Verifies that playlist statistics are cleaned and written to a CSV file.
• test_clean_playlist_data: Ensures playlist data is cleaned and saved to a new CSV file.
• test_common_artists: Checks if common artists in the playlist are correctly identified and counted.
• test_parse_video_title: Confirms the parsing of video titles to extract artist and song names.
• test_automate_new_add_songs: Simulates adding new songs to playlists.
• test_youtube_playlist_statistics: Tests the collection of playlist statistics into a DataFrame.

Mocking is used to simulate file operations and method behavior.

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