# 方法1：直接使用花括號
dict1 = {'name': 'Alice', 'age': 25, 'city': 'Beijing'}
# 方法2：使用dict()構(gòu)造函數(shù)
dict2 = dict(name='Bob', age=30, city='Shanghai')
# 方法3：從鍵值對序列創(chuàng)建
dict3 = dict([('name', 'Charlie'), ('age', 35), ('city', 'Guangzhou')])
# 方法4：使用fromkeys()方法創(chuàng)建默認(rèn)字典
keys = ['name', 'age', 'city']
dict4 = dict.fromkeys(keys, 'unknown')
print(f"fromkeys創(chuàng)建: {dict4}")  # 輸出: {'name': 'unknown', 'age': 'unknown', 'city': 'unknown'}

# 實(shí)際應(yīng)用示例
student = {'name': '張三', 'score': 85, 'grade': 'A'}
# 安全訪問示例
score = student.get('score', 0)  # 存在時(shí)返回實(shí)際值
height = student.get('height', '未記錄')  # 不存在時(shí)返回默認(rèn)值
print(f"分?jǐn)?shù): {score}, 身高: {height}")
# 遍歷字典的三種方式
print("=== 遍歷鍵 ===")
for key in student.keys():
    print(f"鍵: {key}")
print("=== 遍歷值 ===")
for value in student.values():
    print(f"值: {value}")
print("=== 遍歷鍵值對 ===")
for key, value in student.items():
    print(f"{key}: {value}")

# 創(chuàng)建測試字典
person = {'name': '李四', 'age': 28}

# 1. 直接賦值修改
person['age'] = 29  # 修改已有鍵的值
person['city'] = '深圳'  # 添加新鍵值對
print(f"修改后: {person}")  # {'name': '李四', 'age': 29, 'city': '深圳'}

# 2. 使用update()方法批量更新
new_info = {'age': 30, 'gender': '男', 'salary': 15000}
person.update(new_info)
print(f"批量更新后: {person}")  # 包含所有更新后的鍵值對 

# 3. 使用setdefault()方法
# 鍵存在時(shí)返回當(dāng)前值，不存在時(shí)設(shè)置默認(rèn)值并返回
current_age = person.setdefault('age', 0)  # 存在，返回29
email = person.setdefault('email', 'unknown@example.com')  # 不存在，設(shè)置并返回默認(rèn)值
print(f"年齡: {current_age}, 郵箱: {email}")
print(f"setdefault后字典: {person}")

# 創(chuàng)建測試字典
inventory = {'apple': 10, 'banana': 5, 'orange': 8, 'grape': 15}
# 1. del語句刪除特定鍵值對
del inventory['banana']
print(f"刪除banana后: {inventory}")  # {'apple': 10, 'orange': 8, 'grape': 15}
# 2. pop()方法刪除并返回值
orange_count = inventory.pop('orange')
print(f"刪除的orange數(shù)量: {orange_count}")  # 8
print(f"pop后字典: {inventory}")  # {'apple': 10, 'grape': 15}
# 3. popitem()方法刪除最后插入的鍵值對
last_item = inventory.popitem()
print(f"最后刪除的項(xiàng): {last_item}")  # ('grape', 15) 
print(f"popitem后字典: {inventory}")  # {'apple': 10}
# 4. clear()方法清空字典
inventory.clear()
print(f"清空后字典: {inventory}")  # {}

# 原始字典
original = {'data': [1, 2, 3], 'info': {'name': 'test'}}

# 1. 直接賦值（引用傳遞）
reference = original
reference['data'].append(4)
print(f"原始字典也被修改: {original}")  # {'data': [1, 2, 3, 4], 'info': {'name': 'test'}}

# 2. shallow copy()方法（淺拷貝）
shallow_copy = original.copy()
shallow_copy['data'].append(5)  # 修改嵌套對象會影響原字典
shallow_copy['info'] = 'changed'  # 修改頂層對象不影響原字典
print(f"淺拷貝后原字典: {original}")  # {'data': [1, 2, 3, 4, 5], 'info': {'name': 'test'}}

# 3. 深拷貝需要import copy模塊
import copy
deep_copy = copy.deepcopy(original)
deep_copy['data'].append(6)  # 不會影響原字典
print(f"深拷貝后原字典: {original}")  # 保持不變

def count_words(text):
    """統(tǒng)計(jì)文本中單詞出現(xiàn)頻率"""
    words = text.lower().split()
    word_count = {}
    for word in words:
        # 使用get方法簡化計(jì)數(shù)邏輯
        word_count[word] = word_count.get(word, 0) + 1
    return word_count
# 測試統(tǒng)計(jì)功能
sample_text = "hello world hello python world python python"
result = count_words(sample_text)
print("單詞頻率統(tǒng)計(jì):")
for word, count in result.items():
    print(f"  {word}: {count}")

# 字典視圖會實(shí)時(shí)反映字典的變化
config = {'debug': True, 'log_level': 'info', 'max_connections': 100}

keys_view = config.keys()
values_view = config.values()
items_view = config.items()

print(f"初始鍵視圖: {list(keys_view)}")

# 修改字典
config['timeout'] = 30
config['debug'] = False

print(f"修改后鍵視圖: {list(keys_view)}")  # 視圖實(shí)時(shí)更新
print(f"修改后值視圖: {list(values_view)}")

# 使用字典推導(dǎo)式快速創(chuàng)建字典
numbers = [1, 2, 3, 4, 5]

# 創(chuàng)建數(shù)字平方字典
squares = {x: x**2 for x in numbers}
print(f"平方字典: {squares}")  # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

# 帶條件的字典推導(dǎo)式
even_squares = {x: x**2 for x in numbers if x % 2 == 0}
print(f"偶數(shù)平方字典: {even_squares}")  # {2: 4, 4: 16}