thanks gpt

spot/stats.py

@@ -0,0 +1,102 @@
+from pymongo import MongoClient
+from collections import Counter
+from datetime import datetime
+import requests
+
+client = MongoClient('MANGODBSRV')
+db = client['cluster0']
+collection = db['spotify']
+
+# Retrieve all the song documents from the collection
+songs = collection.find()
+
+# Initialize counters for song counts per month
+song_counts = {}
+
+# Group songs by month and calculate statistics for each month
+for song in songs:
+    song_name = song['song_name']  # Replace 'name' with the correct field name for song name
+    artist_name = song['artist']  # Replace 'artist' with the correct field name for artist name
+    song_id = song['song_id']  # Replace 'song_id' with the correct field name for the song ID
+    play_date = song['date']  # Replace 'date' with the correct field name for the date
+    
+    # Parse the play date as a datetime object
+    play_date = datetime.strptime(play_date, "%B %d, %Y at %I:%M%p")
+    
+    # Extract the month and year from the play date
+    month = play_date.strftime("%B %Y")
+    
+    # Initialize the counter for the month if not already present
+    if month not in song_counts:
+        song_counts[month] = Counter()
+    
+    # Increment the song count for the month
+    song_counts[month][(song_name, artist_name, song_id)] += 1
+
+# Calculate the total plays for each month
+total_plays = {month: sum(songs.values()) for month, songs in song_counts.items()}
+
+# Spotify API endpoint for retrieving track information
+endpointArtists = 'https://api.spotify.com/v1/artists'
+endpointTracks = 'https://api.spotify.com/v1/tracks'
+
+# Spotify API access token
+access_token = 'ACCESSTOKENSPOTIFY'  # Replace with your actual access token
+
+# Function to retrieve the genre for a given song ID
+def get_song_info(song_id):
+    headers = {'Authorization': f'Bearer {access_token}'}
+    url = f"{endpointTracks}/{song_id}"
+    response = requests.get(url, headers=headers)
+    data = response.json()
+    
+    if 'artists' in data and data['artists']:
+        artist = data['artists'][0]
+        artist_id = artist['id']
+        
+        if 'genres' in artist and artist['genres']:
+            genre = artist['genres'][0]
+        else:
+            genre = 'Unknown Genre'
+    else:
+        artist_id = 'Unknown Artist'
+        genre = 'Unknown Genre'
+        
+    return genre, artist_id
+
+# Function to retrieve the genre for a given song ID
+def get_song_genre(artist_id):
+    headers = {'Authorization': f'Bearer {access_token}'}
+    url = f"{endpointArtists}/{artist_id}"
+    response = requests.get(url, headers=headers)
+    data = response.json()
+    if 'genres' in data and data['genres']:
+        genres = data['genres'][0]
+        return genres
+    return 'Unknown Genre'
+
+# Print the statistics for each month
+print("Song Statistics by Month:")
+for month, songs in song_counts.items():
+    print(f"Month: {month}")
+    print(f"Total Plays: {total_plays[month]}")
+    
+    most_played_song = songs.most_common(1)[0]
+    most_played_song_name = most_played_song[0][0]
+    most_played_song_artist = most_played_song[0][1]
+    most_played_song_id = most_played_song[0][2]
+    
+    genre = get_song_genre(get_song_info(most_played_song_id)[1])
+    print(f"Most Played Song: {most_played_song_name} by {most_played_song_artist} ({most_played_song[1]} plays)")
+    print(f"Most Played Song Genre: {genre}")
+    
+    print()  # Add a new line for better readability
+
+# Calculate the total plays of all time
+total_plays_all_time = sum(total_plays.values())
+
+# Print the total plays of all time
+print(f"Total Plays of All Time: {total_plays_all_time}")
+
+# Close the MongoDB connection
+client.close()