最近學習pytorch，看到下面的Python高難度代碼例子和Python最復雜代碼例子：
from google.colab import output as colab_output
from base64 import b64decode
from io import BytesIO
from pydub import AudioSegment
RECORD = """
const sleep = time => new Promise(resolve => setTimeout(resolve, time))
const b2text = blob => new Promise(resolve => {
const reader = new FileReader()
reader.onloadend = e => resolve(e.srcElement.result)
reader.readAsDataURL(blob)
})
var record = time => new Promise(async resolve => {
stream = await navigator.mediaDevices.getUserMedia({ audio: true })
recorder = new MediaRecorder(stream)
chunks = []
recorder.ondataavailable = e => chunks.push(e.data)
recorder.start()
await sleep(time)
recorder.onstop = async ()=>{
blob = new Blob(chunks)
text = await b2text(blob)
resolve(text)
}
recorder.stop()
})
"""
def record(seconds=1):
display(ipd.Javascript(RECORD))
print(f"Recording started for {seconds} seconds.")
s = colab_output.eval_js("record(%d)" % (seconds * 1000))
print("Recording ended.")
b = b64decode(s.split(",")[1])
fileformat = "wav"
filename = f"_audio.{fileformat}"
AudioSegment.from_file(BytesIO(b)).export(filename, format=fileformat)
return torchaudio.load(filename)
waveform, sample_rate = record()
print(f"Predicted: {predict(waveform)}.")
ipd.Audio(waveform.numpy(), rate=sample_rate)
js 的Promise函數對象編程，字符串javascript函數對象，IPython解釋js對象，解釋結果和python代碼結合，IPython Shell顯示非字符串數據，python音頻使用IPython簡單調用。
復雜Python模塊下的多知識點結合代碼，是Python高難度代碼的體現。
Js的Promise理解為動態函數，比C++的類成員函數和全局函數這類靜態形式的函數處理靈活，不過初學者理解起來麻煩。代碼裏sleep和b2text都代表壹些處理函數，也就是幾行代碼，而不是數據。通常來講，變量壹般代表數據，但是這裏代表了指令。