问python看不到导入的os库

EN

import os
from os  import *
from multiprocessing import freeze_support
import matplotlib.pyplot as plt
import numpy as np
import librosa
import librosa.display
import pandas as pd
from pandarallel import pandarallel
pandarallel.initialize()
Base_Directory = "UltraSound/"
PATH = os.path.abspath(Base_Directory)
def feature_extractor(file_name):
    file_name = os.path.join(PATH, file_name)
    audio,sample_rate = librosa.load(file_name, res_type='kaiser_fast')
    mfccs_features = librosa.feature.mfcc(y=audio, sr=sample_rate, n_mfcc=40)
    mfccs_scaled_features = np.mean(mfccs_features.T, axis=0)
    return mfccs_scaled_features
"""
audio_file ='UltraSound/100263-2-0-3.wav'
signal,sample_rate =librosa.load(audio_file)
plt.figure(figsize=(12, 4))
plt.plot(signal)
plt.show()
"""
metadata =pd.read_csv('UltraSound/UrbanSound8K.csv')
if __name__ == '__main__':
    freeze_support()
    metadata['mfccs_scaled_features'] = metadata['slice_file_name'].parallel_apply(feature_extractor)
    print(metadata.head())

NameError: name 'os' is not defined

INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
INFO: Pandarallel will run on 6 workers.
INFO: Pandarallel will use standard multiprocessing data transfer (pipe) to transfer data between the main process and workers.

WARNING: You are on Windows. If you detect any issue with pandarallel, be sure you checked out the Troubleshooting page:
https://nalepae.github.io/pandarallel/troubleshooting/
multiprocessing.pool.RemoteTraceback: 
"""
Traceback (most recent call last):
  File "C:\Users\User\AppData\Local\Programs\Python\Python310\lib\multiprocessing\pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "C:\Users\User\AppData\Local\Programs\Python\Python310\lib\multiprocessing\pool.py", line 51, in starmapstar
    return list(itertools.starmap(args[0], args[1]))
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandarallel\core.py", line 158, in __call__
    results = self.work_function(
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandarallel\data_types\series.py", line 26, in work
    return data.apply(
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandas\core\series.py", line 4433, in apply
    return SeriesApply(self, func, convert_dtype, args, kwargs).apply()
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandas\core\apply.py", line 1082, in apply
    return self.apply_standard()
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandas\core\apply.py", line 1137, in apply_standard
    mapped = lib.map_infer(
  File "pandas\_libs\lib.pyx", line 2870, in pandas._libs.lib.map_infer
  File "C:\Users\User\PycharmProjects\DataScience\glass_csv.py", line 15, in feature_extractor
    audio,sample_rate = librosa.load(file_name, res_type='kaiser_fast')
NameError: name 'os' is not defined
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\User\PycharmProjects\DataScience\glass_csv.py", line 29, in <module>
    metadata['mfccs_scaled_features'] = metadata['slice_file_name'].parallel_apply(feature_extractor)
  File "C:\Users\User\PycharmProjects\DataScience\venv\lib\site-packages\pandarallel\core.py", line 433, in closure
    results = results_promise.get()
  File "C:\Users\User\AppData\Local\Programs\Python\Python310\lib\multiprocessing\pool.py", line 771, in get
    raise self._value
NameError: name 'os' is not defined

Process finished with exit code 1