處理CSV文件時：如何優(yōu)雅應(yīng)對編碼錯誤、數(shù)據(jù)類型轉(zhuǎn)換異常？

import chardet  def detect_encoding(file_path):     with open(file_path, 'rb') as f:         raw_data = f.read()     result = chardet.detect(raw_data)     return result['encoding']  file_path = 'your_file.csv' encoding = detect_encoding(file_path)  # 再次嘗試，如果chardet失敗，則使用備選方案 if not encoding:     try:         with open(file_path, 'r', encoding='utf-8') as f:             f.read()         encoding = 'utf-8'     except UnicodeDecodeError:         encoding = 'latin1' # 備選編碼，通常latin1能處理大部分情況  print(f"Detected encoding: {encoding}")  import csv with open(file_path, 'r', encoding=encoding) as csvfile:     reader = csv.reader(csvfile)     for row in reader:         print(row)

import csv from datetime import datetime  def convert_row(row, column_types):     converted_row = []     for i, value in enumerate(row):         converter = column_types[i]         try:             converted_value = converter(value)         except (ValueError, TypeError):             converted_value = None  # 或者使用默認(rèn)值，記錄錯誤等         converted_row.append(converted_value)     return converted_row  # 定義列的類型轉(zhuǎn)換器 column_types = [int, float, str, lambda x: datetime.strptime(x, '%Y-%m-%d')]  file_path = 'your_file.csv' with open(file_path, 'r') as csvfile:     reader = csv.reader(csvfile)     header = next(reader) # 跳過標(biāo)題行     for row in reader:         converted_row = convert_row(row, column_types)         print(converted_row)

import csv  def process_large_csv(file_path, chunk_size=1000):     with open(file_path, 'r') as csvfile:         reader = csv.reader(csvfile)         header = next(reader) # 跳過標(biāo)題行          chunk = []         for i, row in enumerate(reader):             chunk.append(row)             if (i + 1) % chunk_size == 0:                 yield chunk                 chunk = []          if chunk: # 處理剩余的行             yield chunk  file_path = 'your_large_file.csv' for chunk in process_large_csv(file_path):     # 在這里處理每個chunk     for row in chunk:         print(row)

import csv import logging  # 配置日志 logging.basicConfig(filename='csv_processing.log', level=logging.ERROR,                     format='%(asctime)s - %(levelname)s - %(message)s')  def process_row(row):     try:         # 模擬一些可能出錯的操作         value1 = int(row[0])         value2 = float(row[1])         result = value1 / value2         return result     except (ValueError, ZeroDivisionError) as e:         logging.error(f"Error processing row: {row}. Error: {e}")         return None  file_path = 'your_file.csv' with open(file_path, 'r') as csvfile:     reader = csv.reader(csvfile)     header = next(reader)     for row in reader:         result = process_row(row)         if result is not None:             print(f"Result: {result}")