本文目录导读：
我来用一个完整的案例演示Python批量文件操作，这个案例包含常见场景：批量重命名、批量复制、批量删除、批量修改内容。
完整案例：批量处理txt文件
import os
import shutil
import glob
from pathlib import Path
class FileBatchProcessor:
"""文件批量处理器"""
def __init__(self, workspace_dir="batch_files"):
self.workspace_dir = Path(workspace_dir)
self.create_workspace()
def create_workspace(self):
"""创建工作目录和示例文件"""
self.workspace_dir.mkdir(exist_ok=True)
# 创建多个示例txt文件
for i in range(1, 11): # 创建10个文件
file_path = self.workspace_dir / f"document_{i:03d}.txt"
with open(file_path, 'w', encoding='utf-8') as f:
f.write(f"这是第{i}个文档\n日期：2024-01-{i:02d}\n内容示例\n")
print(f"已创建10个示例文件在 {self.workspace_dir}")
def batch_rename(self, pattern="*", prefix="new_", keep_original=False):
"""批量重命名文件
Args:
pattern: 文件匹配模式
prefix: 新文件名前缀
keep_original: 是否保留原文件
"""
print(f"\n=== 批量重命名（前缀: {prefix}）===")
for file_path in self.workspace_dir.glob(pattern):
if file_path.is_file():
new_name = f"{prefix}{file_path.name}"
new_path = file_path.with_name(new_name)
if keep_original:
shutil.copy2(file_path, new_path)
print(f"复制并重命名: {file_path.name} -> {new_name}")
else:
file_path.rename(new_path)
print(f"重命名: {file_path.name} -> {new_name}")
def batch_copy(self, pattern="*.txt", dest_dir="backup"):
"""批量复制文件到指定目录"""
dest_path = self.workspace_dir / dest_dir
dest_path.mkdir(exist_ok=True)
print(f"\n=== 批量复制到 {dest_dir} ===")
for file_path in self.workspace_dir.glob(pattern):
shutil.copy2(file_path, dest_path / file_path.name)
print(f"已复制: {file_path.name}")
print(f"共复制 {len(list(dest_path.glob('*')))} 个文件")
def batch_delete(self, pattern="*.bak", confirm=True):
"""批量删除文件"""
files_to_delete = list(self.workspace_dir.glob(pattern))
if not files_to_delete:
print(f"没有找到匹配 {pattern} 的文件")
return
print(f"\n=== 批量删除（模式: {pattern}）===")
print(f"找到 {len(files_to_delete)} 个文件:")
for f in files_to_delete:
print(f" - {f.name}")
if confirm and input("确认删除? (y/n): ").lower() != 'y':
print("取消删除")
return
for file_path in files_to_delete:
file_path.unlink()
print(f"已删除: {file_path.name}")
def batch_modify_content(self, pattern="*.txt", old_text=None, new_text=None):
"""批量修改文件内容"""
if old_text is None and new_text is None:
# 添加行号
print(f"\n=== 批量添加行号 ===")
for file_path in self.workspace_dir.glob(pattern):
with open(file_path, 'r', encoding='utf-8') as f:
lines = f.readlines()
# 添加行号
new_lines = []
for i, line in enumerate(lines, 1):
new_lines.append(f"{i:03d}: {line}")
with open(file_path, 'w', encoding='utf-8') as f:
f.writelines(new_lines)
print(f"已处理: {file_path.name}")
else:
# 替换文本
print(f"\n=== 批量替换文本: '{old_text}' -> '{new_text}' ===")
for file_path in self.workspace_dir.glob(pattern):
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
new_content = content.replace(old_text, new_text)
with open(file_path, 'w', encoding='utf-8') as f:
f.write(new_content)
print(f"已修改: {file_path.name}")
def list_files(self, pattern="*"):
"""列出工作目录下的文件"""
print(f"\n=== 文件列表 ===")
for file_path in sorted(self.workspace_dir.glob(pattern)):
if file_path.is_file():
size = file_path.stat().st_size
print(f"{file_path.name:20s} {size:>6d} 字节")
print(f"共 {len(list(self.workspace_dir.glob(pattern)))} 个文件")
# 使用示例
if __name__ == "__main__":
processor = FileBatchProcessor("my_test_files")
# 1. 查看初始状态
processor.list_files()
# 2. 批量重命名（添加前缀）
processor.batch_rename(pattern="*.txt", prefix="processed_")
processor.list_files()
# 3. 批量复制到备份目录
processor.batch_copy(dest_dir="backup_2024")
# 4. 批量修改内容（添加行号）
processor.batch_modify_content(old_text="这是第", new_text="文档编号:")
# 5. 查看最终文件
processor.list_files()
# 6. 清理示例
# processor.batch_delete(pattern="*.txt")
更多实用案例
案例1：批量处理图片（压缩/调整大小）
from PIL import Image
from pathlib import Path
def batch_resize_images(source_dir, target_dir, size=(800, 600)):
"""批量调整图片大小"""
source_path = Path(source_dir)
target_path = Path(target_dir)
target_path.mkdir(exist_ok=True)
for img_path in source_path.glob("*.jpg"):
with Image.open(img_path) as img:
# 保持比例调整大小
img.thumbnail(size, Image.Resampling.LANCZOS)
target_file = target_path / img_path.name
img.save(target_file, "JPEG", quality=85)
print(f"已处理: {img_path.name}")
案例2：批量处理Excel文件
import pandas as pd
from pathlib import Path
def batch_merge_excel(pattern="*.xlsx"):
"""批量合并Excel文件"""
all_data = []
for file_path in Path().glob(pattern):
df = pd.read_excel(file_path)
df['来源文件'] = file_path.name
all_data.append(df)
print(f"读取: {file_path.name}")
if all_data:
result = pd.concat(all_data, ignore_index=True)
result.to_excel("合并结果.xlsx", index=False)
print(f"合并完成，共 {len(result)} 行数据")
批量操作技巧总结
使用pathlib替代os.path
# 推荐使用
from pathlib import Path
p = Path("path/to/file.txt")
p.exists() # 检查是否存在
p.is_file() # 是否是文件
p.rename("new_name.txt") # 重命名
p.unlink() # 删除
安全操作模式
def safe_batch_operation():
"""安全的批量操作"""
import traceback
success_count = 0
error_count = 0
for file_path in Path().glob("*.txt"):
try:
# 执行操作
success_count += 1
except Exception as e:
error_count += 1
print(f"处理 {file_path.name} 时出错: {e}")
traceback.print_exc()
print(f"成功: {success_count}, 失败: {error_count}")
进度显示
def batch_with_progress(pattern="*"):
"""带进度显示的批量操作"""
files = list(Path().glob(pattern))
total = len(files)
for i, file_path in enumerate(files, 1):
progress = i / total * 100
print(f"\r进度: {progress:.1f}% ({i}/{total})", end="")
# 执行批量操作
print("\n完成!")
配置文件驱动
import json
def batch_from_config(config_file):
"""从配置文件读取批量操作"""
with open(config_file, 'r') as f:
config = json.load(f)
operation = config.get("operation")
pattern = config.get("pattern")
options = config.get("options", {})
if operation == "rename":
batch_rename(pattern, **options)
elif operation == "copy":
batch_copy(pattern, **options)
这个案例涵盖了大多数常见的批量文件操作场景,关键点是：
- 使用pathlib提供更现代的API
- 做好错误处理
- 添加进度显示
- 考虑备份和回滚
需要更具体的某个场景的案例吗？
