1、在数据的每一行前面添加一个前缀：

prefix = "prefix."
filename = "Text.txt"
new_filename = prefix + filename

# 读取txt文件
with open(filename, 'r', encoding='utf-8') as txt_file:
    data = txt_file.readlines()

# 处理每行数据
new_data = []
for line in data:
    # 分隔每个字段
    fields = line.strip().split('\t')
    if fields == ['']:
        # 在每个字段前不添加前缀
        new_fields = [field for field in fields]
        # 组合新的一行数据
        new_line = '\t'.join(new_fields) + '\n'
        new_data.append(new_line)
    elif any(item.startswith('/') or item.startswith('*') for item in fields):
        continue
    else:
        # 在每个字段前添加前缀
        new_fields = [prefix + field for field in fields]
        # 组合新的一行数据
        new_line = '\t'.join(new_fields) + '\n'
        new_data.append(new_line)

# 将更改后的数据写入新的txt文件
with open(new_filename, 'w', encoding='utf-8') as new_txt_file:
    new_txt_file.writelines(new_data)

2、去除文本中的所有数字：

import re

with open('Test.txt', 'r',encoding='UTF-8') as f:
    content = f.read()

new_content = re.sub(r'\d+', '', content)

with open('prefix.Test.txt', 'w') as f:
    f.write(new_content)

3、扫描一个目录，将文件（自动匹配编码格式）中存在关键字的所有行提取出来并保存的一个文件中：

import os
import re
import chardet

# 要扫描的目录
dir_path = r'/project'

# 要查找的字符串
search_str = 'keyWorld'

# 要保存结果的文件名
output_file = r'output.txt'

# 遍历目录中的所有文件
for root, dirs, files in os.walk(dir_path):
    for file in files:
        # 对 .java 后缀的文件进行处理
        if file.endswith('.java'):
            # 使用 chardet 检测文件编码
            with open(os.path.join(root, file), 'rb') as f:
                data = f.read()
                result = chardet.detect(data)
                if not result['encoding']:
                    print(f'Skipping {file} due to unrecognized encoding')
                    continue
                encoding = result['encoding']

            try:
                # 打开文件并按行读取
                with open(os.path.join(root, file), 'r', encoding=encoding) as f:
                    for line in f.readlines():
                        # 查找包含指定字符串的行
                        if search_str in line:
                            # 将符合条件的行写入输出文件
                            with open(output_file, 'a', encoding=encoding) as of:
                                of.write(f'{os.path.join(file)}:{line}')
            except UnicodeDecodeError:
                print(f'Skipping {file} due to decoding error')

print('Done.')

4、解析cvs文件：

import csv

new_filename = "Test.txt"
# 打开CSV文件并读取数据
with open('gift.csv', newline='') as csvfile:
     reader = csv.DictReader(csvfile)
     
     # 仅读取message列
     messages = [row['rowName'] for row in reader]

# 打印message数据
new_data = []
for message in messages:
    print(message)
    new_data.append('\t'+ message + '\n')
    
    
    
# 将更改后的数据写入新的txt文件
with open(new_filename, 'w', encoding='utf-8') as new_txt_file:
   new_txt_file.writelines(new_data)

5、解析每一行的数据：

import re
from collections import defaultdict

# 用于匹配行数据中的不同字段
PATTERN = r"id:(\d+),.*twoId:(\d+),num:(\d+),"

# 用于存储分组后的结果
result = defaultdict(lambda: defaultdict(int))

# 打开数据文件
with open("Test.txt") as f:
    for line in f:
        # 使用正则表达式解析当前行的数据
        print(line.strip())
        match = re.search(PATTERN, line.strip())
        print(match)
        if match:
            id = match.group(1)
            twoId = match.group(2)
            num = int(match.group(3))

            # 更新分组后的结果
            result[id][twoId] += num

# 将结果写入文件
with open("output.txt", "w") as f:
    for id, Items in result.items():
        for twoId, num in Items.items():
            f.write(f"{id},{twoId},{num}\n")

6、解析txt文件并保存到excel文件中：

import re
from openpyxl import Workbook

# 读取 txt 文件
with open('Text.txt', 'r') as f:
    content = f.readlines()

# 创建 Excel 文件
wb = Workbook()
ws = wb.active

# 将数据写入 Excel 文件
for line in content:
    match = re.match(r'^([^=]+)=(.+)$', line)
    print(match)
    if match:
        key = match.group(1).strip()
        value = match.group(2).strip('"').lstrip('"').lstrip('-"').lstrip(' "')

        ws.append([key, value])

# 保存 Excel 文件
wb.save('new.xlsx')

2024-02-23 start:

from PIL import Image


def run():
    # 打开PNG图像
    image = Image.open('【图片路径】')

    # 修改像素大小
    new_width = 108
    new_height = 108
    resized_image = image.resize((new_width, new_height), Image.Resampling.BICUBIC)

    # 保存修改后的图像
    resized_image.save('108.png')


if __name__ == '__main__':
    run()

end

2024-12-06 start：

输入mysql的表名，输出该表所有字段的注释（没有注释的显示无注释）并输出字段的个数

import mysql.connector
from mysql.connector import Error


def get_table_column_comments(host, port, user, password, database, table_name):
    connection = None  # 提前声明并初始化connection变量
    try:
        # 创建数据库连接，并指定端口号
        connection = mysql.connector.connect(
            host=host,
            port=port,  # 指定端口号
            user=user,
            password=password,
            database=database,
            charset='utf8mb4',  # 指定字符集
            collation='utf8mb4_general_ci'  # 指定排序规则
        )

        if connection.is_connected():
            cursor = connection.cursor(dictionary=True)

            # 查询指定表的所有字段及其注释
            query_columns = """
                SELECT COLUMN_NAME, COLUMN_COMMENT
                FROM INFORMATION_SCHEMA.COLUMNS
                WHERE TABLE_SCHEMA = %s AND TABLE_NAME = %s;
            """
            cursor.execute(query_columns, (database, table_name))
            columns = cursor.fetchall()

            # 构建字段注释列表
            column_comments = []
            for column in columns:
                column_comment = column['COLUMN_COMMENT'] or '无注释'  # 如果字段没有注释，则默认为'无注释'
                column_comments.append(f"{column_comment}")

            # 使用中文逗号分隔并打印
            print("、".join(column_comments))
            print("\n")
            print(len(column_comments))

    except Error as e:
        print("Error while connecting to MySQL", e)
    finally:
        # 关闭数据库连接
        if connection.is_connected():
            cursor.close()
            connection.close()

# 使用你的实际数据库信息替换以下参数

host = '123'
port = '3306'
user = '123'
password = '123'

database = '123'
table_name = '123'

get_table_column_comments(host, port, user, password, database, table_name)

输入mysql表名的注释，打印对应的表名：

import mysql.connector
from mysql.connector import Error

def get_tables_with_filtered_comments(host, port, user, password, database, filter_texts):
    connection = None  # 提前声明并初始化connection变量
    try:
        # 创建数据库连接，并指定端口号
        connection = mysql.connector.connect(
            host=host,
            port=port,  # 指定端口号
            user=user,
            password=password,
            database=database,
            charset='utf8mb4',  # 指定字符集
            collation='utf8mb4_general_ci'  # 指定排序规则
        )

        if connection.is_connected():
            cursor = connection.cursor(dictionary=True)

            # 查询所有表名及其注释
            query_tables = """
                SELECT TABLE_NAME, TABLE_COMMENT
                FROM INFORMATION_SCHEMA.TABLES
                WHERE TABLE_SCHEMA = %s;
            """
            cursor.execute(query_tables, (database,))
            tables = cursor.fetchall()

            # 存储结果
            filtered_tables = []

            for table in tables:
                table_name = table['TABLE_NAME']
                table_comment = table['TABLE_COMMENT'] or '无注释'  # 如果表没有注释，则默认为'无注释'

                # 检查表注释是否包含任意一个过滤关键字
                if not filter_texts or any(filter_text in table_comment for filter_text in filter_texts):
                    filtered_tables.append(f"{table_name}({table_comment})")

            # 打印结果
            if filtered_tables:
                print("\n".join(filtered_tables))
            else:
                print("No matching tables found with the given filter texts.")

    except Error as e:
        print("Error while connecting to MySQL", e)
    finally:
        # 关闭数据库连接
        if connection.is_connected():
            cursor.close()
            connection.close()

# 使用你的实际数据库信息替换以下参数

host = '123'
port = '3306'
user = '123'
password = '123'



database = '123'
filter_texts = ["123"]

get_tables_with_filtered_comments(host, port, user, password, database, filter_texts)

end