Python 中的 Prepend 是什么意思？

前置意味着将一个或多个元素添加到列表的开头。虽然 Python 没有专用的“prepend()”方法，但提供了多种方法来实现此目的：

numbers = [2, 3, 4]

# Using insert(0, element)
numbers.insert(0, 1)  # [1, 2, 3, 4]

# Using list concatenation
numbers = [0] + numbers  # [0, 1, 2, 3, 4]

方法 1：使用 insert() — 直接方法

`insert()` 方法是 Python 的内置方法，用于在列表中的任何位置添加元素，包括开头：

fruits = ['orange', 'banana', 'mango']
fruits.insert(0, 'apple')
print(fruits)  # ['apple', 'orange', 'banana', 'mango']

# You can also insert multiple times
fruits.insert(0, 'grape')
print(fruits)  # ['grape', 'apple', 'orange', 'banana', 'mango']

何时使用 insert()

- 当需要添加单个元素时
- 当代码可读性比性能更重要时- 当处理小列表时

重要的 insert() 细节

# Insert works with any data type
numbers = [2, 3, 4]
numbers.insert(0, 1.5)      # [1.5, 2, 3, 4]
numbers.insert(0, "one")    # ["one", 1.5, 2, 3, 4]
numbers.insert(0, [0, 0.5]) # [[0, 0.5], "one", 1.5, 2, 3, 4]

# Insert returns None - common beginner mistake
numbers = numbers.insert(0, 1)  # Wrong! numbers will be None

方法 2：列表串联 — 干净的方法

使用“+”运算符连接列表是另一种添加元素的常见方法：

colors = ['blue', 'green']

# Single element prepend
colors = ['red'] + colors
print(colors)  # ['red', 'blue', 'green']

# Multiple element prepend
colors = ['purple', 'pink'] + colors
print(colors)  # ['purple', 'pink', 'red', 'blue', 'green']

真实示例：构建交易历史记录

这是一个实际的例子，其中前置是有用的 - 维护交易历史记录：

class TransactionHistory:
    def __init__(self):
        self.transactions = []
        
    def add_transaction(self, transaction):
        # New transactions go at the start - most recent first
        self.transactions.insert(0, {
            'timestamp': transaction['time'],
            'amount': transaction['amount'],
            'type': transaction['type']
        })
        
    def get_recent_transactions(self, limit=5):
        return self.transactions[:limit]

# Usage example
history = TransactionHistory()
history.add_transaction({
    'time': '2024-03-15 10:30',
    'amount': 50.00,
    'type': 'deposit'
})
history.add_transaction({
    'time': '2024-03-15 14:20',
    'amount': 25.00,
    'type': 'withdrawal'
})

recent = history.get_recent_transactions()
# Most recent transaction appears first

方法3：使用deque进行高效预挂

对于需要频繁添加到大型列表的情况，“collections.deque”是最佳选择：

from collections import deque

# Create a deque from a list
numbers = deque([3, 4, 5])

# Prepend single elements
numbers.appendleft(2)
numbers.appendleft(1)

# Convert back to list if needed
numbers_list = list(numbers)
print(numbers_list)  # [1, 2, 3, 4, 5]

性能比较示例

下面是一个比较不同前置方法性能的实际示例：

import time
from collections import deque

def measure_prepend_performance(size):
    # Regular list with insert
    start = time.time()
    list_insert = []
    for i in range(size):
        list_insert.insert(0, i)
    list_time = time.time() - start
    
    # List concatenation
    start = time.time()
    list_concat = []
    for i in range(size):
        list_concat = [i] + list_concat
    concat_time = time.time() - start
    
    # Deque
    start = time.time()
    d = deque()
    for i in range(size):
        d.appendleft(i)
    deque_time = time.time() - start
    
    return {
        'insert': list_time,
        'concat': concat_time,
        'deque': deque_time
    }

# Test with 10,000 elements
results = measure_prepend_performance(10000)
for method, time_taken in results.items():
    print(f"{method}: {time_taken:.4f} seconds")

处理极端情况和常见错误

让我们看看一些可能会让您陷入困境的情况以及如何处理它们：

# 1. Prepending None or empty lists
numbers = [1, 2, 3]
numbers.insert(0, None)  # [None, 1, 2, 3] - Valid
numbers = [] + numbers   # [1, 2, 3] - Empty list has no effect

# 2. Prepending to an empty list
empty_list = []
empty_list.insert(0, 'first')  # Works fine: ['first']

# 3. Type mixing - be careful!
numbers = [1, 2, 3]
numbers = ['1'] + numbers  # ['1', 1, 2, 3] - Mixed types possible but risky

# 4. Modifying list while iterating
numbers = [1, 2, 3]
for num in numbers:
    numbers.insert(0, num * 2)  # Don't do this! Use a new list instead

使用列表前置的实用技巧

以下是一些基于实际使用情况的具体提示：

# 1. Bulk prepending - more efficient than one at a time
old_items = [4, 5, 6]
new_items = [1, 2, 3]
combined = new_items + old_items  # Better than multiple insert() calls

# 2. Converting types safely
string_nums = ['1', '2', '3']
numbers = []
for num in string_nums:
    try:
        numbers.insert(0, int(num))
    except ValueError:
        print(f"Couldn't convert {num} to integer")

# 3. Maintaining a fixed-size list
max_size = 5
recent_items = [3, 4, 5]
recent_items.insert(0, 2)
if len(recent_items) > max_size:
    recent_items.pop()  # Remove last item if list too long