代做program、SQL编程语言代写

日期：2024-09-28 09:27

AM05 Workshop 2 - Data acquisition from Spotify API

Overview

In this workshop, you will learn how to:

Create a Spotify App Obtain the necessary credentials to access the Spotify API.

Request an Access Token Authenticate your app to interact with the API.  Request Artist Data Fetch data for the UK's top 10 chart artists and their

songs.

Store Data in an SQL Database Design a simple database schema and insert the retrieved data.

Prerequisites:

Basic understanding of R programming.

R and RStudio installed on your computer.

Internet access.

A Spotify account (free account is sufficient).

No prior experience with APIs is required.

Optional: An SQL database system installed (e.g., MySQL, SQLite).

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Table of Contents

Part 1 Setting Up Your Spotify Developer Account Step 1 Create a Spotify Account

Step 2 Create a Spotify App

Part 2 Authenticating and Obtaining an Access Token Step 1 Install Required R Packages

Step 2 Set Up Authentication Credentials

Step 3 Obtain an Access Token

Part 3 Fetching Artist and Track Data

Step 1 Identify the UK's Top 10 Chart Artists Step 2 Retrieve Artist Data

Step 3 Retrieve Tracks for Each Artist

Part 4 Designing and Populating the SQL Database Step 1 Define the Database Schema

Step 2 Connect to the SQL Database from R Step 3 Create Tables in the Database

Step 4 Insert Data into the Database Conclusion

Appendix: Additional Resources

Part 1: Setting Up Your Spotify Developer Account

Step 1: Create a Free Spotify Account

If you don't already have a Spotify account:

 Go to Spotify Sign Up.

 Follow the instructions to create a free account.

Step 2: Create a Spotify App

 Navigate to the Spotify for Developers Dashboard.

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 Log in with your Spotify account credentials.  Click on "Create an App".

Provide an App Name and App Description (e.g., "AM05 workshop").

Accept the Terms of Service and click "Create".

 Your app will be created, and you'll be redirected to the app's dashboard.

Important:

Client ID and Client Secret:

On your app dashboard, you will see your Client ID.

Click on "Show Client Secret" to view your Client Secret.

Keep these credentials secure. Do not share them publicly or commit them to version control systems like GitHub.

Part 2: Authenticating and Obtaining an Access Token

To interact with the Spotify API, you need to authenticate your app and obtain an access token.

Step 1: Set Up Authentication Credentials

Create a file named .Renviron in your R project directory to store your credentials securely.

 In RStudio, go to File > New File > Text File.

 Add the following lines, replacing placeholders with your actual credentials:

 Save the file as .Renviron in your project directory.

Note The .Renviron file is used by R to store environment variables securely.

Step 2: Install Required R Packages

Open R or RStudio on your computer. We'll use the httr and jsonlite packages for handling HTTP requests and parsing JSON data.

  SPOTIFY_CLIENT_ID='your_client_id_here'

SPOTIFY_CLIENT_SECRET='your_client_secret_here'

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install.packages("httr")

install.packages("jsonlite")

install.packages("tidyverse")  # For data manipulation

Load the packages:

Step 3: Obtain an Access Token

Create a function to retrieve the access token.

library(httr)

library(jsonlite)

library(tidyverse)

get_spotify_access_token <- function() {

 client_id <- Sys.getenv("SPOTIFY_CLIENT_ID")

 client_secret <- Sys.getenv("SPOTIFY_CLIENT_SECRET")

 response <- POST(

   url = '<https://accounts.spotify.com/api/token>',

   accept_json(),

   authenticate(client_id, client_secret),

   body = list(grant_type = 'client_credentials'),

   encode = 'form'

)

 if (response$status_code != 200) {

   stop("Failed to retrieve access token")

}

 content <- content(response)

 return(content$access_token)

}

# Obtain the access token

access_token <- get_spotify_access_token()

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Part 3: Fetching Artist and Track Data Step 1: Identify the UK's Top 10 Chart Artists

Since Spotify does not provide a direct API endpoint for charts, we'll manually list the UK's top 10 artists.

For this exercise, you can use the current UK Top 10 chart from a reliable source (e.g., Official Charts, BBC Radio 1. For demonstration purposes, we'll use a sample list:

top_artists <- c(

 "Ed Sheeran",

 "Dua Lipa",

 "Adele",

 "Stormzy",

 "Lewis Capaldi",

 "Calvin Harris",

 "Sam Smith",

 "Little Mix",

 "Harry Styles",

 "Rita Ora"

)

Step 2: Retrieve Artist Data

Create a function to search for an artist and retrieve their Spotify ID.

get_artist_id <- function(artist_name, access_token) {

 base_url <- '<https://api.spotify.com/v1/search>'

 response <- GET(

   url = base_url,

   query = list(q = artist_name, type = 'artist', limit =

1),

   add_headers(Authorization = paste('Bearer', access_toke

n)) )

 if (response$status_code != 200) {

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    stop("Failed to retrieve artist data")

 }

 content <- content(response)

 if (length(content$artists$items) == 0) {

   warning(paste("Artist not found:", artist_name))

   return(NA)

 }

 artist <- content$artists$items[[1]]

 # Return a list with artist details

 list(

   id = artist$id,

   name = artist$name,

   followers = artist$followers$total,

   genres = paste(artist$genres, collapse = ", "),

   popularity = artist$popularity,

   url = artist$external_urls$spotify

) }

# Retrieve data for all top artists

artist_data <- map_df(top_artists, ~ {

 Sys.sleep(1)  # To respect rate limits

 artist_info <- get_artist_id(.x, access_token)

 if (!is.na(artist_info$id)) {

   return(as_tibble(artist_info))

 } else {

   return(NULL)

 }

})

Explanation:

We define get_artist_id to search for an artist and extract relevant

information.

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map_df from purrr (part of tidyverse ) applies the function to each artist in top_artists and combines the results into a data frame.

We include Sys.sleep(1) to pause between requests and respect API rate limits.

Step 3: Retrieve Tracks for Each Artist

Create a function to get the top tracks for each artist.

     get_artist_top_tracks <- function(artist_id, access_token,

market = "GB") {

 base_url <- paste0('<https://api.spotify.com/v1/artists/

>', artist_id, '/top-tracks')

 response <- GET(

   url = base_url,

   query = list(market = market),

   add_headers(Authorization = paste('Bearer', access_toke

n)) )

 if (response$status_code != 200) {

   stop("Failed to retrieve top tracks")

 }

 content <- content(response)

 tracks <- content$tracks

 track_list <- map_df(tracks, ~ {

   list(

     track_id = .x$id,

     track_name = .x$name,

     artist_id = artist_id,

     album_id = .x$album$id,

     album_name = .x$album$name,

     release_date = .x$album$release_date,

     popularity = .x$popularity,

     duration_ms = .x$duration_ms,

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      track_url = .x$external_urls$spotify

   )

})

 return(track_list)

}

# Retrieve tracks for all artists

track_data <- map_df(artist_data$id, ~ {

 Sys.sleep(1)  # To respect rate limits

 get_artist_top_tracks(.x, access_token)

})

Explanation:

get_artist_top_tracks fetches the top tracks for a given artist.

We use map_df to apply this function to each artist ID in artist_data .

Part 4: Designing and Populating the SQL Database

Step 1: Define the Database Schema

We'll design a simple relational database with the following tables:  artists

artist_id Primary Key) name

followers

genres

popularity

url  tracks

track_id Primary Key) track_name

artist_id Foreign Key)

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album_id album_name release_date popularity duration_ms track_url

Note We establish a relationship between artists and tracks via the artist_id . Step 2: Connect to the SQL Database from R

For simplicity, we'll use SQLite, a lightweight, file-based database that doesn't require a server setup.

Install and load the RSQLite package:

Create a connection to an SQLite database file:

Step 3: Create Tables in the Database Create the artists and tracks tables.

  install.packages("RSQLite")

library(RSQLite)

# Create or connect to the database file

con <- dbConnect(SQLite(), dbname = "spotify_data.db")

# Create 'artists' table

dbExecute(con, "

 CREATE TABLE IF NOT EXISTS artists (

   artist_id TEXT PRIMARY KEY,

   name TEXT,

   followers INTEGER,

   genres TEXT,

   popularity INTEGER,

   url TEXT

) ")

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# Create 'tracks' table

dbExecute(con, "

 CREATE TABLE IF NOT EXISTS tracks (

   track_id TEXT PRIMARY KEY,

   track_name TEXT,

   artist_id TEXT,

   album_id TEXT,

   album_name TEXT,

   release_date TEXT,

   popularity INTEGER,

   duration_ms INTEGER,

   track_url TEXT,

   FOREIGN KEY (artist_id) REFERENCES artists (artist_id)

) ")

Explanation:

We use dbExecute to run SQL statements that modify the database structure. We define the data types for each column.

Step 4: Insert Data into the Database Insert data into the artists table.

 # Insert artist data

dbWriteTable(

 conn = con,

 name = "artists",

 value = artist_data,

 append = TRUE,

 row.names = FALSE

)

Insert data into the tracks table.

# Insert track data

dbWriteTable(

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  conn = con,

 name = "tracks",

 value = track_data,

 append = TRUE,

 row.names = FALSE

)

Verify the data insertion:

# Query the artists table

dbGetQuery(con, "SELECT * FROM artists")

# Query the tracks table

dbGetQuery(con, "SELECT * FROM tracks")

After you're done, close the connection:

Note: dbWriteTable automatically handles inserting data frames into the specified table.

Conclusion

Congratulations! You have successfully:

Set up a Spotify Developer account and created an app. Authenticated and obtained an access token.

Retrieved data for the UK's top 10 chart artists and their top tracks. Designed a simple relational database schema.

Inserted the retrieved data into an SQL database using R.

Bonus Step:

Extend the schema to include additional data (e.g., album details, track

features).

dbDisconnect(con)

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Appendix: Additional Resources Spotify Web API Documentation:

https://developer.spotify.com/documentation/web-api/

httr Package Documentation: https://cran.r- project.org/web/packages/httr/httr.pdf

jsonlite Package Documentation: https://cran.r- project.org/web/packages/jsonlite/jsonlite.pdf

RSQLite Package Documentation: https://cran.r- project.org/web/packages/RSQLite/RSQLite.pdf

DBI Package Documentation: https://cran.r- project.org/web/packages/DBI/DBI.pdf

Official Charts: https://www.officialcharts.com/ Important Notes:

API Usage Compliance Ensure you comply with Spotify's Developer Terms of Service. Use the data responsibly and for educational purposes.

Rate Limiting Be mindful of API rate limits. Avoid making excessive requests in a short period.

Data Privacy Do not share personal or sensitive data. The data retrieved is publicly available information about artists and tracks.

Security Keep your Client ID and Client Secret secure. Do not share them or include them in publicly accessible code repositories.

Frequently Asked Questions

Q1 I get an error saying "Failed to retrieve access token". What should I do?

A Check that your Client ID and Client Secret are correctly set in the .Renviron file. Ensure there are no extra spaces or missing quotes.

Q2 The artist_data or track_data data frames are empty. Why?

A This could happen if the artist names are not found in the Spotify database. Ensure the artist names are correctly spelled. Also, check if the access token is valid.

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Q3 How can I view the data stored in the SQLite database?

A You can use SQL queries within R using dbGetQuery . For example:

 # Get all artists

artists <- dbGetQuery(con, "SELECT * FROM artists")

# Get all tracks

tracks <- dbGetQuery(con, "SELECT * FROM tracks")

Alternatively, you can use a database browser tool like DB Browser for SQLite to view the database file.

Q4 Can I use a different SQL database system?

A Yes. You can use other databases like MySQL or PostgreSQL. You'll need to install the appropriate R packages ( RMySQL , RPostgres ) and adjust the connection parameters accordingly.

Additional Exercises

To deepen your understanding, consider the following exercises:

 Data Analysis Use SQL queries to find the most popular track among the top artists.

 Data Visualization Create plots showing the popularity distribution of tracks or the number of followers per artist.

 Extended Data Retrieval:

Fetch additional data such as album details or audio features of tracks. Update the database schema to accommodate the new data.

 Error Handling:

Improve the robustness of your functions by adding more

comprehensive error handling and logging.

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