Spotify API Interaction and Data Collection Script

🎵 Download your recently played Spotify tracks data

This Python project automates the process of retrieving and storing recently played tracks from Spotify. It integrates with the Spotify API to fetch data, including track details, artist information, and playback timestamps. The data is then cleaned, processed, and saved into a CSV file, ensuring that no duplicate entries are stored. Additionally, the project includes a feature to insert the collected data into a PostgreSQL database, facilitating further analysis or integration with other systems. This solution is ideal for music enthusiasts and developers looking to maintain a personal log of their Spotify listening history or integrate it into larger applications.

Cloning the Repository

git clone https://github.com/Sissaz/spotify

Create an App in Spotify for Developers

Spotify for Developers

Go to the App's settings and copy your Client_ID and Client_Secret

Create a new .env file in the cloned project 'src' folder with all the lines below, replacing only CLIENT_ID and CLIENT_SECRET

CLIENT_ID=YOUR_CLIENT_ID
CLIENT_SECRET=YOUR_CLIENT_SECRET
REDIRECT_URI=http://localhost:8888/callback
REFRESH_TOKEN=

Run the following commands in PowerShell

pip install poetry

cd src

poetry env use 3.12.1

poetry install

cd assets

poetry shell

poetry run python musicas_recentes.py

Database Connection

This example demonstrates connecting to a PostgreSQL database using DBeaver. The connection was made possible through a free PostgreSQL instance provided by Render, which offers 1GB of capacity and is available for up to one month, allowing seamless interaction with the database.

Data Base

Power BI Connection

Python Code: Download your recently played Spotify tracks data

...
def escrever_csv(musicas, output_filepath):
    df = pd.DataFrame(musicas)  # Converte a lista de músicas em um DataFrame
    
    # Verifica se o arquivo já existe
    if os.path.isfile(output_filepath):
        # Carrega o CSV existente
        df_existente = pd.read_csv(output_filepath)
        
        # Concatena as novas linhas com as existentes, adicionando as novas linhas no topo
        df_final = pd.concat([df, df_existente], ignore_index=True)
    else:
        # Se o arquivo não existir, apenas use as novas linhas
        df_final = df
    
    # Remove duplicatas com base em todas as colunas
    df_final.drop_duplicates(inplace=True)
    
    # Salva o DataFrame final no arquivo CSV, mantendo o cabeçalho
    df_final.to_csv(output_filepath, index=False, encoding='utf-8')
    
    print(f"Arquivo CSV atualizado com novas linhas no topo e duplicatas removidas. Salvo em {output_filepath}")
...

Flowchart for Spotify Authentication and Recent Tracks Retrieval Process