我正在获取我的50位顶级艺术家artistList的列表。从此列表中，我得到artistAlbumsList中每位艺术家的专辑，然后从中循环浏览艺术家专辑的曲目，直到在albumTracks中找到明确的曲目。

（Spotify不会将专辑标记为明确的专辑，仅将曲目标记为...这就是为什么我必须遍历曲目。）

如果有明确的曲目，我将专辑标记为明确的曲目并将专辑添加到我的new_albums列表中。

我怎么返回None？ 所有这些专辑中都有明确的曲目，所以这不是问题。

另外，如果我改用update字典而不是albums来调用new_albums字典中的AttributeError: 'NoneType' object has no attribute 'update'，则会收到此错误：import time import spotipy import spotipy.util as util from config import spotify_token def albumDrop(): sp = spotipy.Spotify(auth=spotify_token) albums = {} new_albums = {} artistList = sp.current_user_top_artists(limit=50,offset=0,time_range='long_term')['items'] for artist in artistList: print(artist["name"],artist["id"]) artistAlbumsList = sp.artist_albums( artist["id"],album_type='album',limit=3)['items'] for album in artistAlbumsList: print(album['release_date'],artist['name'],album['name'],album['external_urls']['spotify'],album['id']) albumTracks = sp.album_tracks(album['id'],limit=50)['items'] for track in albumTracks: if track['explicit'] == True: new_albums = albums.update({'{artistName} - {albumName}'.format(artistName = artist['name'],albumName = album['name']) : {'Release Date': album['release_date'],'Artist Name': artist['name'],'Album Name': album['name'],'Album URI': album['external_urls']['spotify'],'Album ID': album['id'],'Explicit': track['explicit']}}) break return(new_albums) if __name__ == "__main__": start = time.time() latestAlbums = albumDrop() end = time.time() print(latestAlbums) print(end - start)

import cv2                                
import numpy as np                       
import pyrealsense2 as rs
import matplotlib as mpl
import matplotlib.pyplot as plt          
import time
from mpl_toolkits.mplot3d import Axes3D
fig1 = plt.figure(1)
ar = fig1.gca(projection='3d')
ar.set_xlim(-1,1)
ar.set_ylim(-1,1)
ar.set_zlim(-1,1)


# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.depth,640,480,rs.format.z16,30)
config.enable_stream(rs.stream.color,rs.format.bgr8,30)


# Start streaming
pipe_profile =pipeline.start(config)

points =[[[]]]
def get_3dPoints():#Function to be written
    pass    

try:
    while True:
        # Wait for a coherent pair of frames: depth and color
        frames = pipeline.wait_for_frames()
        depth_frame = frames.get_depth_frame()
        color_frame = frames.get_color_frame()

        if not depth_frame or not color_frame: #or not infrared_frame:
            continue
        # Convert images to numpy arrays
        depth_image = np.asanyarray(depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())

        cv2.namedwindow('RealSense',cv2.WINDOW_AUTOSIZE)
        colorizer = rs.colorizer()
        depth_colormap = np.asanyarray(colorizer.colorize(depth_frame).get_data())
        cv2.imshow('RealSense',depth_colormap)
        """
        points = get_3dPoints()
        tgt = ar.scatter(points,'red')
        ar.set_xlabel('X - axis')
        ar.set_ylabel('Y - axis')
        ar.set_zlabel('Z - axis')
        plt.pause(0.00000000000000001)
        tgt.remove()
        """
        cv2.waitKey(1)

finally:

    # Stop streaming#img = cv2.resize(img,(1280,720),interpolation=cv2.INTER_AREA)
    pipeline.stop()

有没有更快的方法可以做到这一点？