如何只计算目录中的文件?这将目录本身计算为一个文件:
len(glob.glob('*'))
如何只计算目录中的文件?这将目录本身计算为一个文件:
len(glob.glob('*'))
当前回答
我找到了另一个可能是正确的公认答案。
for root, dirs, files in os.walk(input_path):
for name in files:
if os.path.splitext(name)[1] == '.TXT' or os.path.splitext(name)[1] == '.txt':
datafiles.append(os.path.join(root,name))
print len(files)
其他回答
简单的一个:
import os
number_of_files = len(os.listdir(directory))
print(number_of_files)
我这样做了,这返回了文件夹(Attack_Data)中的文件数量…这很好。
import os
def fcount(path):
#Counts the number of files in a directory
count = 0
for f in os.listdir(path):
if os.path.isfile(os.path.join(path, f)):
count += 1
return count
path = r"C:\Users\EE EKORO\Desktop\Attack_Data" #Read files in folder
print (fcount(path))
我发现有时我不知道是否会收到文件名或文件的路径。所以我打印了os walk解决方案的输出:
def count_number_of_raw_data_point_files(path: Union[str, Path], with_file_prefix: str) -> int:
import os
path: Path = force_expanduser(path)
_, _, files = next(os.walk(path))
# file_count = len(files)
filename: str
count: int = 0
for filename in files:
print(f'-->{filename=}') # e.g. print -->filename='data_point_99.json'
if with_file_prefix in filename:
count += 1
return count
out:
-->filename='data_point_780.json'
-->filename='data_point_781.json'
-->filename='data_point_782.json'
-->filename='data_point_783.json'
-->filename='data_point_784.json'
-->filename='data_point_785.json'
-->filename='data_point_786.json'
-->filename='data_point_787.json'
-->filename='data_point_788.json'
-->filename='data_point_789.json'
-->filename='data_point_79.json'
-->filename='data_point_790.json'
-->filename='data_point_791.json'
-->filename='data_point_792.json'
-->filename='data_point_793.json'
-->filename='data_point_794.json'
-->filename='data_point_795.json'
-->filename='data_point_796.json'
-->filename='data_point_797.json'
-->filename='data_point_798.json'
-->filename='data_point_799.json'
-->filename='data_point_8.json'
-->filename='data_point_80.json'
-->filename='data_point_800.json'
-->filename='data_point_801.json'
-->filename='data_point_802.json'
-->filename='data_point_803.json'
-->filename='data_point_804.json'
-->filename='data_point_805.json'
-->filename='data_point_806.json'
-->filename='data_point_807.json'
-->filename='data_point_808.json'
-->filename='data_point_809.json'
-->filename='data_point_81.json'
-->filename='data_point_810.json'
-->filename='data_point_811.json'
-->filename='data_point_812.json'
-->filename='data_point_813.json'
-->filename='data_point_814.json'
-->filename='data_point_815.json'
-->filename='data_point_816.json'
-->filename='data_point_817.json'
-->filename='data_point_818.json'
-->filename='data_point_819.json'
-->filename='data_point_82.json'
-->filename='data_point_820.json'
-->filename='data_point_821.json'
-->filename='data_point_822.json'
-->filename='data_point_823.json'
-->filename='data_point_824.json'
-->filename='data_point_825.json'
-->filename='data_point_826.json'
-->filename='data_point_827.json'
-->filename='data_point_828.json'
-->filename='data_point_829.json'
-->filename='data_point_83.json'
-->filename='data_point_830.json'
-->filename='data_point_831.json'
-->filename='data_point_832.json'
-->filename='data_point_833.json'
-->filename='data_point_834.json'
-->filename='data_point_835.json'
-->filename='data_point_836.json'
-->filename='data_point_837.json'
-->filename='data_point_838.json'
-->filename='data_point_839.json'
-->filename='data_point_84.json'
-->filename='data_point_840.json'
-->filename='data_point_841.json'
-->filename='data_point_842.json'
-->filename='data_point_843.json'
-->filename='data_point_844.json'
-->filename='data_point_845.json'
-->filename='data_point_846.json'
-->filename='data_point_847.json'
-->filename='data_point_848.json'
-->filename='data_point_849.json'
-->filename='data_point_85.json'
-->filename='data_point_850.json'
-->filename='data_point_851.json'
-->filename='data_point_852.json'
-->filename='data_point_853.json'
-->filename='data_point_86.json'
-->filename='data_point_87.json'
-->filename='data_point_88.json'
-->filename='data_point_89.json'
-->filename='data_point_9.json'
-->filename='data_point_90.json'
-->filename='data_point_91.json'
-->filename='data_point_92.json'
-->filename='data_point_93.json'
-->filename='data_point_94.json'
-->filename='data_point_95.json'
-->filename='data_point_96.json'
-->filename='data_point_97.json'
-->filename='data_point_98.json'
-->filename='data_point_99.json'
854
注意,你可能需要排序。
我用glob。Iglob的目录结构类似于
data
└───train
│ └───subfolder1
│ | │ file111.png
│ | │ file112.png
│ | │ ...
│ |
│ └───subfolder2
│ │ file121.png
│ │ file122.png
│ │ ...
└───test
│ file221.png
│ file222.png
以下两个选项都返回4(正如预期的那样,即不计算子文件夹本身)
len (list (glob。iglob(“数据/火车/ * / * . png ", recursive = True)) sum(我在环球公司工作过一次)
import os
def count_files(in_directory):
joiner= (in_directory + os.path.sep).__add__
return sum(
os.path.isfile(filename)
for filename
in map(joiner, os.listdir(in_directory))
)
>>> count_files("/usr/lib")
1797
>>> len(os.listdir("/usr/lib"))
2049