Python shutil.rmtree:FileNotFoundError:[Errno 2]没有这样的文件或目录:'_xxx和x27; 代码和错误(减少,如果您想查看完整代码,请参阅最后一节):
^显示隐藏文件(按下shift+命令+)和其他目录显示隐藏文件(如果存在) 将_df_导出到_csv.pyPython shutil.rmtree:FileNotFoundError:[Errno 2]没有这样的文件或目录:'_xxx和x27; 代码和错误(减少,如果您想查看完整代码,请参阅最后一节):,python,csv,shutil,hidden-files,Python,Csv,Shutil,Hidden Files,^显示隐藏文件(按下shift+命令+)和其他目录显示隐藏文件(如果存在) 将_df_导出到_csv.py input_file = '/Volumes/Extreme SSD/Raymond Lab/Day_4_Rotarod_Videos_Rotated_if_Necessary copy/cleaned_WT/cleaned_Experiment2-190630_Day4_145m1_rotarod3_Cam2onRotarodDeepCut_resnet50_rotarod3Jul17s
input_file = '/Volumes/Extreme SSD/Raymond Lab/Day_4_Rotarod_Videos_Rotated_if_Necessary copy/cleaned_WT/cleaned_Experiment2-190630_Day4_145m1_rotarod3_Cam2onRotarodDeepCut_resnet50_rotarod3Jul17shuffle1_1030000.csv'
output_file = '/Volumes/Extreme SSD/Raymond Lab/Day_4_Rotarod_Videos_Rotated_if_Necessary copy/cleaned_WT/cleaned_Experiment2-190630_Day4_145m1_rotarod3_Cam2onRotarodDeepCut_resnet50_rotarod3Jul17shuffle1_1030000.csv'
def export_df_to_csv(df, csv):
df.to_csv(csv, index=False)
提取\u parent\u current.py
import os
def extract_parent_current(dir):
if str.endswith(dir, '/'):
dir = dir[:-1]
return os.path.split(dir)
导入_df.py
import os
import random
from copy import deepcopy
import pandas as pd
def import_csvs(WT_file_path, YAC_file_path):
csv_paths_arr = []
for root, dirs, files in os.walk(WT_file_path, topdown=False):
for file in files:
if not file.startswith('.'):
csv_paths_arr.append([os.path.join(root, file), 0])
for root, dirs, files in os.walk(YAC_file_path, topdown=False):
for file in files:
if not file.startswith('.'):
csv_paths_arr.append([os.path.join(root, file), 1])
return csv_paths_arr
def csvs_to_paths_dfs_labels_arr(csvpaths_labels_arr):
paths_dfs_labels_arr = deepcopy(csvpaths_labels_arr)
for i, csvpath_label_arr in enumerate(csvpaths_labels_arr):
(paths_dfs_labels_arr[i])[0] = pd.read_csv(csvpath_label_arr[0], encoding='unicode_escape')
paths_dfs_labels_arr[i].insert(0, csvpath_label_arr[0])
return paths_dfs_labels_arr
def import_df(WT_file_path, YAC_file_path):
csv_paths_arr = import_csvs(WT_file_path, YAC_file_path)
dfs_labels = csvs_to_paths_dfs_labels_arr(csv_paths_arr)
random.shuffle(dfs_labels)
return dfs_labels
。\u filtered\u combined\u Experiment2-190630\u Day4\u 145m2\u rotarod2\u cam2\u rotaroddeepcut\u resnet50\u rotarod3 2017年7月17日shuffle1\u 1030000.csv
是一个符号链接吗?我不知道什么是符号链接,我只是简单地读了一下。它似乎是指向文件的指针,就像在桌面上创建的快捷方式,它指向不同目录中的文件,而实际上它不在桌面上。如果我是对的,那么我不知道它是如何被创建的,为什么会被创建。我的猜测是否定的。您是否尝试重现\u somename.csv
的创建过程?我的意思是,使用不同的文件名,调用df.to_csv
,你会得到更多这些“隐藏文件”吗?如果无法复制,则可能是在创建文件时出现了某种通信错误或其他故障。\u filtered\u combined\u Experiment2-190630\u Day4\u 145m2\u rotarod2\u cam2 nrotaroddeepcut\u resnet50\u rotarod317shuffle1\u 1030000.csv
是符号链接吗?我不知道什么是符号链接,只是简单地读了一下。它似乎是指向文件的指针,就像在桌面上创建的快捷方式,它指向不同目录中的文件,而实际上它不在桌面上。如果我是对的,那么我不知道它是如何被创建的,为什么会被创建。我的猜测是否定的。您是否尝试重现\u somename.csv
的创建过程?我的意思是,使用不同的文件名,调用df.to_csv
,你会得到更多这些“隐藏文件”吗?如果无法复制,则可能是在创建文件时出现了某种通信错误或其他故障。
input_file = '/Volumes/Extreme SSD/Raymond Lab/Day_4_Rotarod_Videos_Rotated_if_Necessary copy/cleaned_WT/cleaned_Experiment2-190630_Day4_145m1_rotarod3_Cam2onRotarodDeepCut_resnet50_rotarod3Jul17shuffle1_1030000.csv'
output_file = '/Volumes/Extreme SSD/Raymond Lab/Day_4_Rotarod_Videos_Rotated_if_Necessary copy/cleaned_WT/cleaned_Experiment2-190630_Day4_145m1_rotarod3_Cam2onRotarodDeepCut_resnet50_rotarod3Jul17shuffle1_1030000.csv'
def export_df_to_csv(df, csv):
df.to_csv(csv, index=False)
import os
def extract_parent_current(dir):
if str.endswith(dir, '/'):
dir = dir[:-1]
return os.path.split(dir)
import os
import random
from copy import deepcopy
import pandas as pd
def import_csvs(WT_file_path, YAC_file_path):
csv_paths_arr = []
for root, dirs, files in os.walk(WT_file_path, topdown=False):
for file in files:
if not file.startswith('.'):
csv_paths_arr.append([os.path.join(root, file), 0])
for root, dirs, files in os.walk(YAC_file_path, topdown=False):
for file in files:
if not file.startswith('.'):
csv_paths_arr.append([os.path.join(root, file), 1])
return csv_paths_arr
def csvs_to_paths_dfs_labels_arr(csvpaths_labels_arr):
paths_dfs_labels_arr = deepcopy(csvpaths_labels_arr)
for i, csvpath_label_arr in enumerate(csvpaths_labels_arr):
(paths_dfs_labels_arr[i])[0] = pd.read_csv(csvpath_label_arr[0], encoding='unicode_escape')
paths_dfs_labels_arr[i].insert(0, csvpath_label_arr[0])
return paths_dfs_labels_arr
def import_df(WT_file_path, YAC_file_path):
csv_paths_arr = import_csvs(WT_file_path, YAC_file_path)
dfs_labels = csvs_to_paths_dfs_labels_arr(csv_paths_arr)
random.shuffle(dfs_labels)
return dfs_labels