python使用__slots__让你的代码更加节省内存

前言

在默认情况下,Python的新类和旧类的实例都有一个字典来存储属性值。这对于那些没有实例属性的对象来说太浪费空间了，当需要创建大量实例的时候，这个问题变得尤为突出。

因此这种默认的做法可以通过在新式类中定义了一个__slots__属性从而得到了解决。__slots__声明中包含若干实例变量，并为每个实例预留恰好足够的空间来保存每个变量，因此没有为每个实例都创建一个字典，从而节省空间。

本文主要介绍了关于python使用__slots__让你的代码更加节省内存的相关内容，分享出来供大家参考学习，下面话不多说了，来一起看看详细的介绍吧

现在来说说python中dict为什么比list浪费内存？

和list相比，dict 查找和插入的速度极快，不会随着key的增加而增加；dict需要占用大量的内存，内存浪费多。

而list查找和插入的时间随着元素的增加而增加；占用空间小，浪费的内存很少。

python解释器是Cpython，这两个数据结构应该对应C的哈希表和数组。因为哈希表需要额外内存记录映射关系，而数组只需要通过索引就能计算出下一个节点的位置，所以哈希表占用的内存比数组大，也就是dict比list占用的内存更大。

如果想更加详细了解，可以查看C的源代码。python官方链接：https://www.python.org/downloads/source/

如下代码是我从python官方截取的代码片段：

List 源码：

typedef struct { PyObject_VAR_HEAD /* Vector of pointers to list elements. list[0] is ob_item[0], etc. */ PyObject **ob_item;  /* ob_item contains space for 'allocated' elements. The number * currently in use is ob_size. * Invariants: * 0 <= ob_size <= allocated * len(list) == ob_size * ob_item == NULL implies ob_size == allocated == 0 * list.sort() temporarily sets allocated to -1 to detect mutations. * * Items must normally not be NULL, except during construction when * the list is not yet visible outside the function that builds it. */ Py_ssize_t allocated;} PyListObject;

Dict源码：

/* PyDict_MINSIZE is the minimum size of a dictionary. This many slots are * allocated directly in the dict object (in the ma_smalltable member). * It must be a power of 2, and at least 4. 8 allows dicts with no more * than 5 active entries to live in ma_smalltable (and so avoid an * additional malloc); instrumentation suggested this suffices for the * majority of dicts (consisting mostly of usually-small instance dicts and * usually-small dicts created to pass keyword arguments). */#define PyDict_MINSIZE 8 typedef struct { /* Cached hash code of me_key. Note that hash codes are C longs. * We have to use Py_ssize_t instead because dict_popitem() abuses * me_hash to hold a search finger. */ Py_ssize_t me_hash; PyObject *me_key; PyObject *me_value;} PyDictEntry; /*To ensure the lookup algorithm terminates, there must be at least one Unusedslot (NULL key) in the table.The value ma_fill is the number of non-NULL keys (sum of Active and Dummy);ma_used is the number of non-NULL, non-dummy keys (== the number of non-NULLvalues == the number of Active items).To avoid slowing down lookups on a near-full table, we resize the table whenit's two-thirds full.*/typedef struct _dictobject PyDictObject;struct _dictobject { PyObject_HEAD Py_ssize_t ma_fill; /* # Active + # Dummy */ Py_ssize_t ma_used; /* # Active */  /* The table contains ma_mask + 1 slots, and that's a power of 2. * We store the mask instead of the size because the mask is more * frequently needed. */ Py_ssize_t ma_mask;  /* ma_table points to ma_smalltable for small tables, else to * additional malloc'ed memory. ma_table is never NULL! This rule * saves repeated runtime null-tests in the workhorse getitem and * setitem calls. */ PyDictEntry *ma_table; PyDictEntry *(*ma_lookup)(PyDictObject *mp, PyObject *key, long hash); PyDictEntry ma_smalltable[PyDict_MINSIZE];};