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A data pipeline analyzing trends in music data from the Spotify API. Snowflake and Databricks integration.

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DavidThomas-coder/spotalyze

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Spotalyze

Overview

This project is designed to analyze trends in music popularity by extracting, processing and analyzing data from the Spotify API. The pipeline integrates with Snowflake for data storage and Databricks for data analysis, offering insights into the evolving music landscape.

Getting Started

To get started with this project, follow these steps:

Prerequisites

Ensure you have Python installed on your machine. This project requires Python 3.6 or newer.

Installation

Clone the Repository

Clone this repository to your local machine using Git bash git clone https://github.com/DavidThomas-coder/spotalyze.git cd spotalyze

Set Up a Virtual Environment

Navigate to the project directory and create a new virtual environment. Activate it using the following commands:

  • On Windows: bash .venv\Scripts\activate

  • On macOS/Linux: bash source.venv/bin/activate

Install Dependencies

Install the required Python packages by running: bash pip install requests pandas snowflake-connector-python

Usage

Obtain Spotify API Credentials

To access the Spotify API, you'll need to register your application on the Spotify Developer Dashboard and obtain your client ID and secret.

Configure the Project

Update the spotify_api/api_handler.py file with your Spotify client ID and secret.

Run the Pipeline

Execute the main script or module responsible for running the pipeline. This will typically involve calling a function or class method that orchestrates the data extraction, processing, and analysis stages.

Contributing

Contributions are welcome. Please feel free to submit pull requests or open issues for discussion.

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A data pipeline analyzing trends in music data from the Spotify API. Snowflake and Databricks integration.

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