import re

text = "Hello World 2024"
result = re.match(r"Hello", text)
if result:
    print("匹配成功:", result.group())  # 輸出: Hello

text = "The year is 2024"
result = re.search(r"\d{4}", text)
if result:
    print("找到數(shù)字:", result.group())  # 輸出: 2024

text = "蘋(píng)果10元, 香蕉5元, 橙子8元"
prices = re.findall(r"\d+元", text)
print(prices)  # 輸出: ['10元', '5元', '8元']

text = "聯(lián)系: 123-4567, 987-6543"
for match in re.finditer(r"\d{3}-\d{4}", text):
    print(f"找到電話: {match.group()} 位置: {match.span()}")

text = "今天是2023年12月15日"
# 將年份替換為2024
new_text = re.sub(r"2023", "2024", text)
print(new_text)  # 輸出: 今天是2024年12月15日

text = "張三 李四 王五"
# 交換姓和名的位置
new_text = re.sub(r"(\w+) (\w+)", r"\2 \1", text)
print(new_text)  # 輸出: 李四 張三 王五

def double_number(match):
    number = int(match.group())
    return str(number * 2)
text = "數(shù)字: 5, 10, 15"
new_text = re.sub(r"\d+", double_number, text)
print(new_text)  # 輸出: 數(shù)字: 10, 20, 30

def format_phone_number(text):
    # 將各種格式的電話號(hào)碼統(tǒng)一為: (xxx) xxx-xxxx
    pattern = r"(\d{3})[-.\s]?(\d{3})[-.\s]?(\d{4})"
    replacement = r"(\1) \2-\3"
    return re.sub(pattern, replacement, text)
phone_text = "聯(lián)系: 123-456-7890, 123.456.7890, 123 456 7890"
formatted = format_phone_number(phone_text)
print(formatted)
# 輸出: 聯(lián)系: (123) 456-7890, (123) 456-7890, (123) 456-7890

def remove_html_tags(text):
    # 移除HTML標(biāo)簽，保留文本內(nèi)容
    return re.sub(r"<[^>]+>", "", text)
html_text = "<h1>標(biāo)題</h1><p>這是一個(gè)<strong>段落</strong></p>"
clean_text = remove_html_tags(html_text)
print(clean_text)  # 輸出: 標(biāo)題這是一個(gè)段落

def mask_sensitive_data(text):
    # 隱藏身份證號(hào)中間部分
    text = re.sub(r"(\d{4})\d{8}(\d{4})", r"\1********\2", text)
    # 隱藏手機(jī)號(hào)中間部分
    text = re.sub(r"(\d{3})\d{4}(\d{4})", r"\1****\2", text)
    return text
sensitive_text = "身份證: 510123199001011234, 手機(jī): 13800138000"
masked_text = mask_sensitive_data(sensitive_text)
print(masked_text)
# 輸出: 身份證: 5101********1234, 手機(jī): 138****8000

import re
def update_flow_version(rows, flow_name, old_version, new_version):
    """
    更新Salesforce Flow的多語(yǔ)言鍵名版本號(hào)
    """
    updated_rows = []
    
    for row in rows:
        if row and len(row) >= 1:
            key = row[0]
            if key and isinstance(key, str):
                patterns = [
                    (f"Flow\.Flow\.{flow_name}\.{old_version}\.", 
                     f"Flow.Flow.{flow_name}.{new_version}."),
                    (f"Flow\.AutoLaunchedFlow\.{flow_name}\.{old_version}\.", 
                     f"Flow.AutoLaunchedFlow.{flow_name}.{new_version}."),
                ]
                
                new_key = key
                for pattern, replacement in patterns:
                    if re.search(pattern, key):
                        new_key = re.sub(pattern, replacement, key)
                        break
                
                # 更新行的第一個(gè)元素
                updated_row = list(row)
                updated_row[0] = new_key
                updated_rows.append(updated_row)
            else:
                updated_rows.append(row)
        else:
            updated_rows.append(row)
    
    return updated_rows
# 使用示例
rows = [
    ["Flow.Flow.CustomerOnboarding.1.title", "客戶入駐流程"],
    ["Flow.AutoLaunchedFlow.CustomerOnboarding.1.description", "自動(dòng)啟動(dòng)流程"],
    ["Other.Key", "其他值"]
]
updated = update_flow_version(rows, "CustomerOnboarding", "1", "2")
for row in updated:
    print(row)
# 輸出:
# ['Flow.Flow.CustomerOnboarding.2.title', '客戶入駐流程']
# ['Flow.AutoLaunchedFlow.CustomerOnboarding.2.description', '自動(dòng)啟動(dòng)流程']
# ['Other.Key', '其他值']

def parse_log_file(log_content):
    """
    解析日志文件，提取時(shí)間戳、級(jí)別和消息
    """
    log_pattern = r"(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}) [(\w+)] (.+)"
    logs = []
    
    for line in log_content.split('\n'):
        match = re.match(log_pattern, line)
        if match:
            timestamp, level, message = match.groups()
            logs.append({
                'timestamp': timestamp,
                'level': level,
                'message': message
            })
    
    return logs
# 示例日志內(nèi)容
log_content = """2024-01-15 10:30:25 [INFO] 用戶登錄成功
2024-01-15 10:31:10 [ERROR] 數(shù)據(jù)庫(kù)連接失敗
2024-01-15 10:32:45 [WARNING] 內(nèi)存使用率過(guò)高"""
parsed_logs = parse_log_file(log_content)
for log in parsed_logs:
    print(f"{log['timestamp']} - {log['level']}: {log['message']}")

# 對(duì)于需要多次使用的模式，先編譯
phone_pattern = re.compile(r"(\d{3})-(\d{3})-(\d{4})")
texts = ["123-456-7890", "987-654-3210"]
for text in texts:
    match = phone_pattern.search(text)
    if match:
        print(f"完整匹配: {match.group()}, 分組: {match.groups()}")

text = "日期: 2024-01-15"
pattern = r"(?P<year>\d{4})-(?P<month>\d{2})-(?P<day>\d{2})"
match = re.search(pattern, text)
if match:
    print(f"年: {match.group('year')}, 月: {match.group('month')}, 日: {match.group('day')}")

text = "<div>內(nèi)容1</div><div>內(nèi)容2</div>"
# 貪婪匹配
greedy = re.findall(r"<div>(.*)</div>", text)
print("貪婪匹配:", greedy)  # 輸出: ['內(nèi)容1</div><div>內(nèi)容2']
# 非貪婪匹配
non_greedy = re.findall(r"<div>(.*?)</div>", text)
print("非貪婪匹配:", non_greedy)  # 輸出: ['內(nèi)容1', '內(nèi)容2']

text = "價(jià)格: $100, 折扣: $20"
# 查找$后面的數(shù)字
prices = re.findall(r"(?<=$)\d+", text)
print("價(jià)格:", prices)  # 輸出: ['100', '20']