Python 的内联 if 语句（也称为三元运算符）允许您在一行中编写条件表达式。让我们探索如何有效地使用它们，以及何时它们会使您的代码变得更好。

基本内联 If 语法

下面是基本模式：

# Standard if statement
if condition:
    result = value1
else:
    result = value2

# Same logic as an inline if
result = value1 if condition else value2

# Example with numbers
age = 20
status = "adult" if age >= 18 else "minor"
print(status)  # Output: "adult"

# Example with strings
name = "Alice"
greeting = f"Hello, {name}" if name else "Hello, stranger"
print(greeting)  # Output: "Hello, Alice"

内联 if 读起来像一个英文句子：“如果条件为 True，则将结果设置为 value1，否则将其设置为 value2”

与 Functions 组合

内联 ifs 非常适合函数调用：

def get_discount(is_member, purchase_amount):
    """Calculate discount based on membership status."""
    return purchase_amount * 0.15 if is_member else purchase_amount * 0.05

# Examples
print(get_discount(True, 100))   # Output: 15.0 (15% discount)
print(get_discount(False, 100))  # Output: 5.0 (5% discount)

# Multiple conditions in the function
def get_shipping(distance, is_prime):
    """Calculate shipping cost based on distance and membership."""
    base_rate = 5.0 if distance <= 50 else 10.0
    return 0.0 if is_prime else base_rate

# Test the shipping function
print(get_shipping(30, True))   # Output: 0.0 (Prime member)
print(get_shipping(30, False))  # Output: 5.0 (Within 50 miles)
print(get_shipping(80, False))  # Output: 10.0 (Over 50 miles)

使用 Inline If 的列表推导式

内联 ifs 在列表推导式中大放异彩：

# Filter and transform numbers in one line
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
processed = [n * 2 if n % 2 == 0 else n for n in numbers]
print(processed)  # Output: [1, 4, 3, 8, 5, 12, 7, 16, 9, 20]

# Process strings with conditions
names = ["Alice", "Bob", "", "Charlie", None, "David"]
cleaned_names = [name.upper() if name else "UNKNOWN" for name in names if name is not None]
print(cleaned_names)  # Output: ['ALICE', 'BOB', 'UNKNOWN', 'CHARLIE', 'DAVID']

# Data processing example
data = [
    {"name": "Alice", "score": 85},
    {"name": "Bob", "score": 92},
    {"name": "Charlie", "score": 78}
]
grades = [f"{d['name']}: A" if d['score'] >= 90 
         else f"{d['name']}: B" if d['score'] >= 80 
         else f"{d['name']}: C" 
         for d in data]
print(grades)  # Output: ['Alice: B', 'Bob: A', 'Charlie: C']

使用词典

内联 ifs 可以帮助创建和修改词典：

def create_user_profile(user_data):
    """Create a user profile with default values for missing data."""
    return {
        "name": user_data.get("name", "Anonymous"),
        "age": user_data.get("age", "Not specified"),
        "status": "active" if user_data.get("last_login") else "inactive",
        "role": "admin" if user_data.get("is_admin", False) else "user",
        "display_name": user_data.get("nickname") if user_data.get("nickname") else user_data.get("name", "Anonymous")
    }

# Example usage
user1 = {
    "name": "Alice",
    "age": 28,
    "last_login": "2024-01-15",
    "is_admin": True
}

user2 = {
    "name": "Bob",
    "nickname": "Bobby"
}

print(create_user_profile(user1))
print(create_user_profile(user2))

实际示例：数据处理管道

以下是在数据处理管道中使用内联 ifs 的实际示例：

def process_sales_data(sales_records):
    """Process sales records and generate summary statistics."""
    
    # Clean and transform data
    processed_records = [
        {
            "date": record["date"],
            "amount": float(record["amount"]) if isinstance(record["amount"], str) else record["amount"],
            "product": record["product"].strip().lower(),
            "category": record["category"].strip() if "category" in record else "uncategorized",
            "status": "completed" if record.get("payment_received") else "pending"
        }
        for record in sales_records
        if record.get("amount") and record.get("product")
    ]
    
    # Calculate statistics
    total_sales = sum(record["amount"] for record in processed_records)
    avg_sale = total_sales / len(processed_records) if processed_records else 0
    
    # Generate category summaries
    category_totals = {}
    for record in processed_records:
        cat = record["category"]
        category_totals[cat] = category_totals.get(cat, 0) + record["amount"]
    
    return {
        "total_sales": total_sales,
        "average_sale": avg_sale,
        "status": "profitable" if total_sales > 10000 else "needs_improvement",
        "top_category": max(category_totals.items(), key=lambda x: x[1])[0] if category_totals else None,
        "records": processed_records
    }

# Example usage
sales_data = [
    {"date": "2024-01-15", "amount": "1500.50", "product": "Laptop", "category": "Electronics", "payment_received": True},
    {"date": "2024-01-15", "amount": 899.99, "product": "Phone", "category": "Electronics", "payment_received": True},
    {"date": "2024-01-16", "amount": "75.00", "product": "Headphones", "payment_received": False},
    {"date": "2024-01-16", "amount": "2500.00", "product": "TV ", "category": "Electronics", "payment_received": True}
]

result = process_sales_data(sales_data)
for key, value in result.items():
    if key != "records":  # Skip printing full records for brevity
        print(f"{key}: {value}")

使用 Inline If 进行错误处理

内联 ifs 可以使错误处理更加简洁：

def safe_divide(a, b):
    """Safely divide two numbers with error handling."""
    return a / b if b != 0 else None

def safe_get(dictionary, key, default="Not found"):
    """Safely get a value from a dictionary."""
    return dictionary[key] if key in dictionary else default

def safe_process(data):
    """Process data with multiple safety checks."""
    try:
        return {
            "value": float(data["value"]) if isinstance(data["value"], (str, int)) else None,
            "status": "valid" if data.get("value") is not None else "invalid",
            "message": data.get("error", "Success") if data.get("status") == "error" else "OK"
        }
    except Exception as e:
        return {
            "value": None,
            "status": "error",
            "message": str(e)
        }

# Examples
print(safe_divide(10, 2))   # Output: 5.0
print(safe_divide(10, 0))   # Output: None

test_dict = {"name": "Alice", "age": 30}
print(safe_get(test_dict, "name"))     # Output: "Alice"
print(safe_get(test_dict, "email"))    # Output: "Not found"

print(safe_process({"value": "123.45"}))
print(safe_process({"value": "invalid"}))

结论

内联 if 语句在以下情况下最有用：
- 您需要一个快速、简单的条件赋值
- 您正在使用列表推导式
- 您希望提供默认值
- 您正在处理可选的数据处理

记得：
- 保持条件简单易读
- 避免嵌套过多的内联 if
- 对复杂逻辑使用常规 if 语句
- 考虑可读性而不是简洁性