SoFunction
Updated on 2025-03-03

The use mechanism of Python default parameters

In Python, the default parameters of a function are a mechanism that simplifies function calls and enhances flexibility. Default parameters allow us to specify default values ​​for certain parameters when defining a function. This way, when calling a function, if you do not pass values ​​for these parameters, they will use default values, making function calls more concise and flexible.

1. Definition and use of default parameters

Default parameters are the default values ​​given to certain parameters when the function is defined. If the values ​​of these parameters are not provided when calling a function, Python uses the default values ​​to execute the function logic. The following are the definition and usage of the default parameters:

def greet(name, message="Hello"):
    print(f"{message}, {name}!")

# Call the function, message parameter not passedgreet("Zhang San")  # Output: Hello, Zhang San!
# Call the function and pass the message parametergreet("Li Si", "Good morning")  # Output: Good morning, Li Si!

In the above code, the functiongreet()There are two parametersnameandmessage,inmessageThere is a default value"Hello". When calling a function, if not passedmessageThe default value will be used"Hello", otherwise the passed parameter value will be used.

This mechanism is very useful because it makes the function more flexible, and we can selectively provide the values ​​of certain parameters as needed without specifying all parameters every time we call it.

2. Application scenarios of default parameters

The use of default parameters is very convenient in many scenarios, especially if the parameters have a common or commonly applicable value. It can help reduce the redundancy and complexity of the code. Let’s take a look at some practical application scenarios:

Print greetings: In some programs, we want to print a greeting, and this greeting is the same most of the time.

def print_greeting(name, greeting="Hello"):
    print(f"{greeting}, {name}!")

# If the greeting parameter is not passed, the default "Hello" will be used.print_greeting("Alice")  # Output: Hello, Alice!
# If the greeting parameter is passed, the passed value will be usedprint_greeting("Bob", "Good morning")  # Output: Good morning, Bob!

In this example, the default parametersgreeting="Hello"simplifies the calling process of the function, if the user does not passgreetingParameters, the program will use them automatically"Hello", making the code more versatile.

Calculate taxes: For example, when calculating commodity prices, the tax rate is fixed in most cases, we can set the tax rate to the default parameter:

def calculate_total_price(price, tax_rate=0.1):
    return price * (1 + tax_rate)

# Use the default tax ratetotal_price = calculate_total_price(100)
print(f"The total price of the product is：{total_price}")  # Output: Total price of the product is: 110.0
# Use different tax ratestotal_price = calculate_total_price(100, tax_rate=0.2)
print(f"The total price of the product is：{total_price}")  # Output: Total price of the product is: 120.0

Here, we set the tax rate to the default value0.1(i.e. 10%), invokingcalculate_total_price()You can choose to use the default tax rate when you are in use, or you can pass a different tax rate as needed.

3. Precautions for default parameters

When using default parameters, there are some things to be paid attention to to avoid unnecessary errors and confusion.

The default parameters must be followed by the positional parameters：

When a function is defined, all default parameters must be followed by non-default parameters (such as positional parameters). This is because when calling a function, Python matches the parameters according to the position of the parameters. If the default parameters are placed before the positional parameters, Python will not be able to parse the parameters correctly.

# The correct way to define itdef example_function(a, b=5):
    return a + b

# Error definition method: default parameter b is before position parameter a# def example_function(b=5, a): # This will cause an error#     return a + b

In the correct example above, the positional parametersaMust be ahead, and the default parametersbMust be in the back. This ensures that Python can correctly match the passed parameters when calling the function.

The default parameter's value is a trap when a mutable object is：

When defining default parameters, be careful if the default value is a mutable object (such as lists, dictionaries, etc.). Because the default parameters are created only once at the function definition, all calls share the same default object, which may lead to unexpected behavior.

def add_item_to_list(item, item_list=[]):
    item_list.append(item)
    return item_list

# The first call is used, the default empty list is usedresult1 = add_item_to_list("apple")
print(result1)  # Output: ['apple']
# The second call, no item_list is passed, so the same default list is still usedresult2 = add_item_to_list("banana")
print(result2)  # Output: ['apple', 'banana']

In the above code,add_item_to_list()Default parameters of the functionitem_listis a list. When we call this function multiple times without providingitem_listWhen using parameters, the same list object is actually performed multiple operations. Therefore, the list after each call accumulates the previous result, which is usually not the behavior we want.

Solution: The default parameters can be set toNone, and process it inside the function.

def add_item_to_list(item, item_list=None):
    if item_list is None:
        item_list = []
    item_list.append(item)
    return item_list

# Now every call will have a new listresult1 = add_item_to_list("apple")
print(result1)  # Output: ['apple']
result2 = add_item_to_list("banana")
print(result2)  # Output: ['banana']

In this modified code, we useNoneAs the default value, then create a new list object inside the function to ensure that you get a brand new list every time the function is called.

4. Example: Application in Personal Financial Management Tools

In the Personal Financial Management Tools project, we can use default parameters to simplify the call of functions. For example, when recording expenditures, if most of the expenditures are "miscellaneous", they can be set as default parameters, thereby simplifying function calls and improving the simplicity of the code.

def add_expense(amount, category="Miscellaneous"):
    print(f"Record expenditure：Amount：{amount}Yuan，category：{category}")

# Use default categoriesadd_expense(100)  # Output: Record expenditure: Amount: 100 yuan, Category: Miscellaneous
# Use custom categoriesadd_expense(200, category="FOOD")  # Output: Record expenditure: Amount: 200 yuan, Category: Catering

In the above code, the functionadd_expense()There is a default parametercategory="Miscellaneous", When the caller does not provide a category, the system will automatically set the category to "miscellaneous", which reduces the hassle of user input and makes the code more tidy.

5. Suggestions for using default parameters

  • Simplify function calls: When a parameter has a commonly used value in most cases, it can be set as the default parameter to simplify function calls.
  • Avoid using mutable objects as default parameters: If the default parameter is a mutable object (such as a list or a dictionary), it may result in unexpected results of shared state. Can be usedNoneAs the default value and handled inside the function.
  • Pay attention to the order of parameters: The default parameters must be placed after the positional parameters to ensure that the matching of parameters will not occur when called.

By understanding and using default parameters reasonably, programmers can make function calls more flexible and concise, improving the readability and maintainability of the code. In the subsequent content, we will continue to explore the use of mutable parameters to help you further master the flexible calling methods of functions in Python.

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