Python中的內存管理之python list內存使用詳解
前言
使用 Python 的時候,我們知道 list 是一個長度可變對的數組, 可以通過 insert,append 和 extend 輕易的拓展其中的元素個數。 也可以使用運算符 如: [1] + [2] 生成新的數組[1, 2]
extend()、 “+”、”+=” 的區別
- “+”將兩個 list 相加,會返回到一個新的 list 對象
- append 在原 list 上進行修改,沒有返回值
從以下代碼可以看到, 調用 b = b + [3, 4] 之後, 通過id(b) 查看 b 變成瞭一個新對象。
In [5]: b = [1, 2] In [6]: id(b) Out[6]: 1628740249224 In [7]: b = b + [3, 4] In [8]: id(b) Out[8]: 1628740456520
使用extend() 完成相同的步驟, 可以看到 對象c 的id保持和原來的一致
In [9]: c = [1, 2] In [10]: id(c) Out[10]: 1628740392584 In [11]: c.extend([3, 4]) In [12]: id(c) Out[12]: 1628740392584
使用 “+=” 連接列表, 看到效果和 extend() 是相同的。
In [1]: a = [1, 2] In [2]: id(a) Out[2]: 1628740021448 In [3]: a += [3, 4] In [4]: id(a) Out[4]: 1628740021448
結論: 減少內存的拷貝, 修改一個列表的數據時, 應避免使用 list1 = list1 + list2 這樣的語法。
List的內存使用
一個示例:
In [1]: import sys In [2]: lst1 = [1] In [3]: lst2 = [] In [4]: lst2.append(1) In [5]: lst1 == lst2 Out[5]: True In [6]: sys.getsizeof(lst1) Out[6]: 72 In [7]: sys.getsizeof(lst2) Out[7]: 96
可以看到,lst1 == lst2, 但是當使用 sys.getsizeof 獲取對象的內存大小時, 兩者卻是不同的。
如下圖所示, list_a 長度為4, 當執行 append(4) 時, 底層的數據長度其實申請瞭4個元素的空間,當再次執行 append(5) 的時候,不需要再次申請內存。
因為 執行 append() 操作時,Python將一次拓展N個元素的內存,因為一個 append 操作很可能是很多 append 操作的開始,通過額外分配內存來減少可能的內存分配和內存copy的次數。
In [1]: import sys
In [2]: l = []
…: print(f’list initial size {sys.getsizeof(l)}’)
…: for i in range(80):
…: cur_size = sys.getsizeof(l)
…: l.append(i)
…: new_size = sys.getsizeof(l)
…: print(f’list len {i+1}:\t current_size {new_size}\t new_allocated 8 * {(new_size-cur_size)/8}’)
…:
list initial size 64
list len 1: current_size 96 new_allocated 8 * 4.0
list len 2: current_size 96 new_allocated 8 * 0.0
list len 3: current_size 96 new_allocated 8 * 0.0
list len 4: current_size 96 new_allocated 8 * 0.0
list len 5: current_size 128 new_allocated 8 * 4.0
list len 6: current_size 128 new_allocated 8 * 0.0
list len 7: current_size 128 new_allocated 8 * 0.0
list len 8: current_size 128 new_allocated 8 * 0.0
list len 9: current_size 192 new_allocated 8 * 8.0
list len 10: current_size 192 new_allocated 8 * 0.0
list len 11: current_size 192 new_allocated 8 * 0.0
list len 12: current_size 192 new_allocated 8 * 0.0
list len 13: current_size 192 new_allocated 8 * 0.0
list len 14: current_size 192 new_allocated 8 * 0.0
list len 15: current_size 192 new_allocated 8 * 0.0
list len 16: current_size 192 new_allocated 8 * 0.0
list len 17: current_size 264 new_allocated 8 * 9.0
list len 18: current_size 264 new_allocated 8 * 0.0
list len 19: current_size 264 new_allocated 8 * 0.0
list len 20: current_size 264 new_allocated 8 * 0.0
list len 21: current_size 264 new_allocated 8 * 0.0
list len 22: current_size 264 new_allocated 8 * 0.0
list len 23: current_size 264 new_allocated 8 * 0.0
list len 24: current_size 264 new_allocated 8 * 0.0
list len 25: current_size 264 new_allocated 8 * 0.0
list len 26: current_size 344 new_allocated 8 * 10.0
list len 27: current_size 344 new_allocated 8 * 0.0
list len 28: current_size 344 new_allocated 8 * 0.0
list len 29: current_size 344 new_allocated 8 * 0.0
list len 30: current_size 344 new_allocated 8 * 0.0
list len 31: current_size 344 new_allocated 8 * 0.0
list len 32: current_size 344 new_allocated 8 * 0.0
list len 33: current_size 344 new_allocated 8 * 0.0
list len 34: current_size 344 new_allocated 8 * 0.0
list len 35: current_size 344 new_allocated 8 * 0.0
list len 36: current_size 432 new_allocated 8 * 11.0
list len 37: current_size 432 new_allocated 8 * 0.0
list len 38: current_size 432 new_allocated 8 * 0.0
list len 39: current_size 432 new_allocated 8 * 0.0
list len 40: current_size 432 new_allocated 8 * 0.0
list len 41: current_size 432 new_allocated 8 * 0.0
list len 42: current_size 432 new_allocated 8 * 0.0
list len 43: current_size 432 new_allocated 8 * 0.0
list len 44: current_size 432 new_allocated 8 * 0.0
list len 45: current_size 432 new_allocated 8 * 0.0
list len 46: current_size 432 new_allocated 8 * 0.0
list len 47: current_size 528 new_allocated 8 * 12.0
list len 48: current_size 528 new_allocated 8 * 0.0
list len 49: current_size 528 new_allocated 8 * 0.0
list len 50: current_size 528 new_allocated 8 * 0.0
list len 51: current_size 528 new_allocated 8 * 0.0
list len 52: current_size 528 new_allocated 8 * 0.0
list len 53: current_size 528 new_allocated 8 * 0.0
list len 54: current_size 528 new_allocated 8 * 0.0
list len 55: current_size 528 new_allocated 8 * 0.0
list len 56: current_size 528 new_allocated 8 * 0.0
list len 57: current_size 528 new_allocated 8 * 0.0
list len 58: current_size 528 new_allocated 8 * 0.0
list len 59: current_size 640 new_allocated 8 * 14.0
list len 60: current_size 640 new_allocated 8 * 0.0
list len 61: current_size 640 new_allocated 8 * 0.0
list len 62: current_size 640 new_allocated 8 * 0.0
list len 63: current_size 640 new_allocated 8 * 0.0
list len 64: current_size 640 new_allocated 8 * 0.0
list len 65: current_size 640 new_allocated 8 * 0.0
list len 66: current_size 640 new_allocated 8 * 0.0
list len 67: current_size 640 new_allocated 8 * 0.0
list len 68: current_size 640 new_allocated 8 * 0.0
list len 69: current_size 640 new_allocated 8 * 0.0
list len 70: current_size 640 new_allocated 8 * 0.0
list len 71: current_size 640 new_allocated 8 * 0.0
list len 72: current_size 640 new_allocated 8 * 0.0
list len 73: current_size 768 new_allocated 8 * 16.0
list len 74: current_size 768 new_allocated 8 * 0.0
list len 75: current_size 768 new_allocated 8 * 0.0
list len 76: current_size 768 new_allocated 8 * 0.0
list len 77: current_size 768 new_allocated 8 * 0.0
list len 78: current_size 768 new_allocated 8 * 0.0
list len 79: current_size 768 new_allocated 8 * 0.0
list len 80: current_size 768 new_allocated 8 * 0.0
通過觀察可以發現, 列表從0 增加到 80長度的過程中, 新申請的內存長度為 [4, 4, 8, 9, 10, 11, 12, 13, 14, 16] 。 反之, 當執行 remove 或者 pop 減少列表中的數據時, 列表也會自動縮容。
- 擴容條件 ,新長度大於底層數組長度;
- 縮容條件 ,新長度小於底層數組長度的一半;
結論: 避免使用類似 append 語法初始化列表, 優先使用列表表達式
# Bad ❌ list_a = [] for i in range(50): list_a.append(i) # Good ✔️ list_b = [i for i in range(50)]
結論:
① 避免使用 “+” 修改數組
② 盡量避免多次使用 append 函數
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