# sorted()的基本用法
numbers = [3, 1, 4, 1, 5, 9, 2, 6]
sorted_numbers = sorted(numbers)
print(sorted_numbers)  # [1, 1, 2, 3, 4, 5, 6, 9]
print(numbers)          # [3, 1, 4, 1, 5, 9, 2, 6]  ← 原列表不變！

# list.sort()——原地排序，直接修改原列表
numbers.sort()
print(numbers)          # [1, 1, 2, 3, 4, 5, 6, 9]  ← 被修改了

# ?? 關(guān)鍵區(qū)別：
# sorted(iterable)  → 返回新列表，原數(shù)據(jù)不變，可用于任何可迭代對(duì)象
# list.sort()       → 原地排序，不返回新列表，只能用于列表

# sorted(iterable, key=None, reverse=False)
# iterable: 要排序的可迭代對(duì)象
# key: 排序依據(jù)的函數(shù)（接收每個(gè)元素，返回用于比較的值）
# reverse: 是否降序（True=降序，F(xiàn)alse=升序）

# reverse參數(shù)——升降序控制
numbers = [3, 1, 4, 1, 5]
print(sorted(numbers))             # [1, 1, 3, 4, 5]  升序
print(sorted(numbers, reverse=True))  # [5, 4, 3, 1, 1]  降序

# key參數(shù)——自定義排序依據(jù)
words = ["banana", "apple", "Cherry", "date", "Elderberry"]

# 默認(rèn)排序——按Unicode碼點(diǎn)（大寫字母在小寫字母前）
print(sorted(words))
# ['Cherry', 'Elderberry', 'apple', 'banana', 'date']

# 按字母順序（忽略大小寫）
print(sorted(words, key=str.lower))
# ['apple', 'banana', 'Cherry', 'date', 'Elderberry']

# 按單詞長(zhǎng)度排序
print(sorted(words, key=len))
# ['date', 'apple', 'banana', 'Cherry', 'Elderberry']

# ?? key函數(shù)的規(guī)則：
# 1. key接收一個(gè)參數(shù)（序列中的每個(gè)元素）
# 2. key返回一個(gè)用于比較的值
# 3. 排序根據(jù)key的返回值進(jìn)行（不是原始元素）
# 4. 原始元素不變——只是排序的依據(jù)變了

# 絕對(duì)值排序
numbers = [-5, 3, -1, 4, -2]
print(sorted(numbers, key=abs))  # [-1, -2, 3, 4, -5]

# 按字符串中數(shù)字的大小排序
codes = ["item2", "item10", "item1", "item20"]
print(sorted(codes))
# ['item1', 'item10', 'item2', 'item20']  ← 字典序！item10在item2前！

import re
def extract_number(s):
    """提取字符串中的數(shù)字"""
    match = re.search(r'\d+', s)
    return int(match.group()) if match else 0

print(sorted(codes, key=extract_number))
# ['item1', 'item2', 'item10', 'item20']  ← 按數(shù)字大小排！

# 按時(shí)間排序
times = ["2024-03-15", "2023-12-01", "2024-01-20", "2023-06-10"]
print(sorted(times))  # 字符串比較恰好對(duì)日期格式有效！
# ['2023-06-10', '2023-12-01', '2024-01-20', '2024-03-15']

# ?? 排序字典列表——職場(chǎng)中最常用的技能

employees = [
    {"name": "張三", "age": 28, "salary": 15000, "department": "技術(shù)部"},
    {"name": "李四", "age": 35, "salary": 20000, "department": "管理部"},
    {"name": "王五", "age": 22, "salary": 12000, "department": "技術(shù)部"},
    {"name": "趙六", "age": 30, "salary": 18000, "department": "市場(chǎng)部"},
    {"name": "錢七", "age": 25, "salary": 13000, "department": "技術(shù)部"},
]

# 按年齡排序
by_age = sorted(employees, key=lambda e: e["age"])
print("按年齡：", [e["name"] for e in by_age])
# ['王五', '錢七', '張三', '趙六', '李四']

# 按薪資降序
by_salary = sorted(employees, key=lambda e: e["salary"], reverse=True)
print("按薪資降序：", [(e["name"], e["salary"]) for e in by_salary])
# [('李四', 20000), ('趙六', 18000), ('張三', 15000), ('錢七', 13000), ('王五', 12000)]

# 按年齡排序，同年齡按薪資降序（多級(jí)排序）
by_age_salary = sorted(employees, key=lambda e: (e["age"], -e["salary"]))
print("年齡+薪資：", [(e["name"], e["age"], e["salary"]) for e in by_age_salary])

# ?? 多級(jí)排序：key返回一個(gè)元組
# Python按元組的元素順序依次比較

# 先按部門，再按薪資降序
results = sorted(employees, key=lambda e: (e["department"], -e["salary"]))
for e in results:
    print(f"  {e['department']} - {e['name']}: ￥{e['salary']}")
# 管理部 - 李四: ￥20000
# 技術(shù)部 - 張三: ￥15000
# 技術(shù)部 - 錢七: ￥13000
# 技術(shù)部 - 王五: ￥12000
# 市場(chǎng)部 - 趙六: ￥18000

# ?? 技巧：降序字段用負(fù)號(hào)
# 數(shù)字降序：-e["salary"]（注意：這只對(duì)數(shù)字有效）
# 字符串降序：沒法用負(fù)號(hào)，需要分兩次排序或用functools.cmp_to_key

# 多級(jí)排序的另一種方法：多次sorted()（利用穩(wěn)定性）
# Python的排序是穩(wěn)定的——相同key的元素保持原來的相對(duì)順序
# 先按次要key排，再按主要key排
result = sorted(employees, key=lambda e: e["salary"], reverse=True)
result = sorted(result, key=lambda e: e["department"])
# 結(jié)果：同一部門內(nèi)，按薪資降序

from operator import itemgetter, attrgetter, methodcaller

# itemgetter——獲取字典的指定字段（相當(dāng)于lambda e: e["key"]）
# 比lambda稍快一些，而且更簡(jiǎn)潔
by_department = sorted(employees, key=itemgetter("department"))
print([e["department"] for e in by_department])

# itemgetter多級(jí)排序
by_dept_salary = sorted(employees, key=itemgetter("department", "salary"))

# attrgetter——獲取對(duì)象的屬性
class Student:
    def __init__(self, name, score):
        self.name = name
        self.score = score

students = [
    Student("Alice", 85),
    Student("Bob", 92),
    Student("Charlie", 78),
]

by_score = sorted(students, key=attrgetter("score"), reverse=True)
for s in by_score:
    print(f"{s.name}: {s.score}")

from functools import total_ordering

# 方法一：實(shí)現(xiàn)比較方法
class Task:
    def __init__(self, name, priority, due_date):
        self.name = name
        self.priority = priority
        self.due_date = due_date

    def __lt__(self, other):
        """小于比較：先按priority，再按due_date"""
        if self.priority != other.priority:
            return self.priority < other.priority
        return self.due_date < other.due_date

    def __repr__(self):
        return f"Task({self.name}, pri={self.priority}, due={self.due_date})"

tasks = [
    Task("寫報(bào)告", 2, "2024-06-15"),
    Task("修復(fù)Bug", 1, "2024-06-10"),
    Task("開會(huì)", 2, "2024-06-12"),
    Task("代碼審查", 1, "2024-06-08"),
]
print(sorted(tasks))
# [Task(代碼審查, pri=1, due=2024-06-08), Task(修復(fù)Bug, pri=1, due=2024-06-10),
#  Task(開會(huì), pri=2, due=2024-06-12), Task(寫報(bào)告, pri=2, due=2024-06-15)]

# 方法二：使用key（更靈活，不修改類）
tasks_sorted = sorted(tasks, key=lambda t: (t.priority, t.due_date))

# 場(chǎng)景：排序雜亂的日志條目
logs = [
    "[2024-03-15 14:30:22] ERROR 數(shù)據(jù)庫連接失敗",
    "[2024-03-15 14:25:10] INFO 服務(wù)器啟動(dòng)",
    "[2024-03-15 14:32:05] WARNING 內(nèi)存使用率85%",
    "[2024-03-15 14:25:10] DEBUG 加載配置文件",
    "[2024-03-15 14:28:45] INFO 用戶登錄成功",
]

def extract_timestamp(log_line):
    """從日志行中提取時(shí)間戳"""
    return log_line[1:20]  # 提取 "[2024-03-15 14:30:22]" 中的時(shí)間

sorted_logs = sorted(logs, key=extract_timestamp)
for log in sorted_logs:
    print(log)
# 按時(shí)間正序排列

# 對(duì)于同時(shí)間的日志，按級(jí)別排序
LEVEL_PRIORITY = {"DEBUG": 0, "INFO": 1, "WARNING": 2, "ERROR": 3}

def sort_key(log_line):
    timestamp = extract_timestamp(log_line)
    # 提取日志級(jí)別
    level = log_line[22:].split()[0]
    priority = LEVEL_PRIORITY.get(level, 99)
    return (timestamp, priority)

sorted_logs = sorted(logs, key=sort_key)

import re

# 人類期望的排序（自然排序）：file1, file2, ..., file10, file11
# 而不是字典序：file1, file10, file11, file2, ...

def natural_sort_key(s):
    """自然排序的key函數(shù)"""
    # 將字符串分割為文本和數(shù)字的交替序列
    parts = re.split(r'(\d+)', s)
    # 將數(shù)字部分轉(zhuǎn)為整數(shù)
    return [int(part) if part.isdigit() else part.lower() for part in parts]

files = ["file10.txt", "file1.txt", "file2.txt", "file20.txt", "file11.txt"]
print(sorted(files))
# ['file1.txt', 'file10.txt', 'file11.txt', 'file2.txt', 'file20.txt']  ← 字典序

print(sorted(files, key=natural_sort_key))
# ['file1.txt', 'file2.txt', 'file10.txt', 'file11.txt', 'file20.txt']  ← 自然序