8.python中的数字

  python中数字对象的创建如下,

a = 123
b = 1.23
c = 1+1j

  可以直接输入数字,然后赋值给变量。

  同样也可是使用类的方式:

a = int(123)
b = float(1.23)
c = complex(1+1j)

  但一般不用类的方式创建,直接输入数字就好了。

  python中的数字包括了整型 int ,长整型 long , 浮点型 float , 复数 complex ,其差别为:

int(整型)

  也称有符号整数,只有正或负整数,不带小数点。
  其和长整型在于整数有一定的位数限制:
    在32位机器上,整数的位数为32位,取值范围为-2**31~2**31-1,即-2147483648~2147483647
    在64位系统上,整数的位数为64位,取值范围为-2**63~2**63-1,即-9223372036854775808~9223372036854775807
  一旦超过位数,则会自动转换为长整型(python2.2以后的版本)
 
long(长整型)
  理论上是无限长的,但数据终究是储存在内存中的,所以实际长度限制取决于内存的大小
float(浮点型)
  带有小数的数字都被称为浮点型
 
complex(复数)
  就是数学中的复数,定义和数学中的一样(z=a+bi,这里a和b是实数,i是虚数单位,例如1+5j)
 

一.整型

 
Help on class int in module __builtin__: class int(object)
| int(x=0) -> int or long
| int(x, base=10) -> int or long
|
| Convert a number or string to an integer, or return 0 if no arguments
| are given. If x is floating point, the conversion truncates towards zero.
| If x is outside the integer range, the function returns a long instead.
|
| If x is not a number or if base is given, then x must be a string or
| Unicode object representing an integer literal in the given base. The
| literal can be preceded by '+' or '-' and be surrounded by whitespace.
| The base defaults to 10. Valid bases are 0 and 2-36. Base 0 means to
| interpret the base from the string as an integer literal.
| >>> int('0b100', base=0)
| 4
|
| Methods defined here:
|
| __abs__(...)
| x.__abs__() <==> abs(x)
|
| __add__(...)
| x.__add__(y) <==> x+y
|
| __and__(...)
| x.__and__(y) <==> x&y
|
| __cmp__(...)
| x.__cmp__(y) <==> cmp(x,y)
|
| __coerce__(...)
| x.__coerce__(y) <==> coerce(x, y)
|
| __div__(...)
| x.__div__(y) <==> x/y
|
| __divmod__(...)
| x.__divmod__(y) <==> divmod(x, y)
|
| __float__(...)
| x.__float__() <==> float(x)
|
| __floordiv__(...)
| x.__floordiv__(y) <==> x//y
|
| __format__(...)
|
| __getattribute__(...)
| x.__getattribute__('name') <==> x.name
|
| __getnewargs__(...)
|
| __hash__(...)
| x.__hash__() <==> hash(x)
|
| __hex__(...)
| x.__hex__() <==> hex(x)
|
| __index__(...)
    '''用于切片,但不接受参数,返回的是整个数字,所以切片对数字而言没有意义'''
| x[y:z] <==> x[y.__index__():z.__index__()]  
|
| __int__(...)
| x.__int__() <==> int(x)
|
| __invert__(...)
| x.__invert__() <==> ~x
|
| __long__(...)
| x.__long__() <==> long(x)
|
| __lshift__(...)
| x.__lshift__(y) <==> x<<y
|
| __mod__(...)
| x.__mod__(y) <==> x%y
|
| __mul__(...)
| x.__mul__(y) <==> x*y
|
| __neg__(...)
| x.__neg__() <==> -x
|
| __nonzero__(...)
| x.__nonzero__() <==> x != 0
|
| __oct__(...)
| x.__oct__() <==> oct(x)
|
| __or__(...)
| x.__or__(y) <==> x|y
|
| __pos__(...)
| x.__pos__() <==> +x
|
| __pow__(...)
| x.__pow__(y[, z]) <==> pow(x, y[, z])
|
| __radd__(...)
| x.__radd__(y) <==> y+x
|
| __rand__(...)
| x.__rand__(y) <==> y&x
|
| __rdiv__(...)
| x.__rdiv__(y) <==> y/x
|
| __rdivmod__(...)
| x.__rdivmod__(y) <==> divmod(y, x)
|
| __repr__(...)
| x.__repr__() <==> repr(x)
|
| __rfloordiv__(...)
| x.__rfloordiv__(y) <==> y//x
|
| __rlshift__(...)
| x.__rlshift__(y) <==> y<<x
|
| __rmod__(...)
| x.__rmod__(y) <==> y%x
|
| __rmul__(...)
| x.__rmul__(y) <==> y*x
|
| __ror__(...)
| x.__ror__(y) <==> y|x
|
| __rpow__(...)
| y.__rpow__(x[, z]) <==> pow(x, y[, z])
|
| __rrshift__(...)
| x.__rrshift__(y) <==> y>>x
|
| __rshift__(...)
| x.__rshift__(y) <==> x>>y
|
| __rsub__(...)
| x.__rsub__(y) <==> y-x
|
| __rtruediv__(...)
| x.__rtruediv__(y) <==> y/x
|
| __rxor__(...)
| x.__rxor__(y) <==> y^x
|
| __str__(...)
| x.__str__() <==> str(x)
|
| __sub__(...)
| x.__sub__(y) <==> x-y
|
| __truediv__(...)
| x.__truediv__(y) <==> x/y
|
| __trunc__(...)
| Truncating an Integral returns itself.
|
| __xor__(...)
| x.__xor__(y) <==> x^y
|
| bit_length(...)
| int.bit_length() -> int
| '''返回改数字用二进制要几位来表示'''
| Number of bits necessary to represent self in binary.
| >>> bin(37)  #得出其二进制表示形式
| '0b100101'  #0b是二进制的标识,用来说明其是二进制形式,其后的100101才是真正的二进制代码
| >>> (37).bit_length()
| 6  #37的二进制表示是 100101,一共6位,所以返回6
|
| conjugate(...)
| Returns self, the complex conjugate of any int.
|
| ----------------------------------------------------------------------
| Data descriptors defined here:
|
| denominator
| the denominator of a rational number in lowest terms
|
| imag
| the imaginary part of a complex number
|
| numerator
| the numerator of a rational number in lowest terms
|
| real
| the real part of a complex number
|
| ----------------------------------------------------------------------
| Data and other attributes defined here:
|
| __new__ = <built-in method __new__ of type object>
| T.__new__(S, ...) -> a new object with type S, a subtype of T

int

可以看出其内置方法分为3种:

  1.普通方法(已经在代码中注释说明)

  2.相当于某些内置函数的方法(参考这里

  3.与运算符相关的方法

这里详细介绍一下python的运算符:

1.算数运算符

  以下假设变量a=10,变量b=20

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" alt="" />

2.比较运算符

  以下假设变量a=10,变量b=20

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" 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  关于python中比较运算符使用的总结:

  1.python中任意对象都可以比较

  2.相同类型的对象(实例),如果是数字型(int/float/long/complex),则按照简单的大小来比较;如果是非数字型,且类(型)中定义了__cmp__(含__gt__,__lt__等)则按照__cmp__来比较,否则按照地址(id)来比较。

  3.不同类型的对象(实例),如果其中一个比较对象是数字型(int/float/long/complex等),则数字型的对象<其它非数字型的对象;如果两个都是非数字型的对象,则按照类型名的顺序比较,如{} < "abc"(按照"dict" < "str"),而"abc" > [1,2], "abc" < (1,2)。

  4.对于自定义的类(型)实例,如果继承自基本类型,则按照基本类型的规则比较(1-3)。否则,old-style class < new-style class, new-style class之间按照类型名顺序比较,old-style class之间按照地址进行比较。

  5.bool类型是int的子类,且True=1, False=0,比较时按照1-4来比较,如True > -1, True < 4.2, True < "abc"等
  
  这部分内容转载于:戳这里

3.赋值运算符

  以下假设变量a=10,变量b=20

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" alt="" />

4.位运算符

  按位运算符是把数字看作二进制来进行计算的。Python中的按位运算法则如下:

  下表中变量 a = 60,b = 13

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" alt="" />

5.逻辑运算符

  以下假设变量 a = 10, b=20

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" 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6.成员运算符

  除了以上的一些运算符之外,Python还支持成员运算符,测试实例中包含了一系列的成员,包括字符串,列表或元组。

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/pW+wwSY7XsXmvYErOXosrO9USKO36IZbmSGVFTyrokd8+mzfpZzf1TB4WZhub6P58+VRc/hf5YKQe5m6Tiwi/lEhO5JzsZUiVl+SJR6SUq8LcH0d5pJNuII9/Qe9lReWYQKlXQfm4jpU03GD+Hp2kJao1+8xde7f6AiW8zv+u2AV/+vq7UqCIzqrVSv9FOwAHywSNKyjelpG0QJGtstLQmTx5AqU3kAqG/EIeXWAzuUDj0A5gTQWKbvZgrv5N+T8yOeDfyRcX/FQVxn9/xu/d46TslOkKin7dDuryOjQZmKkkaihQxPGY/F0vt3o2GxSsfMWX800irhQou/CDHJImruVAdhmAOmEjz2Rk0nRIXSnNeJ49TsqiKDtlfyYWrp7HHX7fIxH37bOdwvlLbFQKPLl1Xj4TINnDBlerAsV+XP+xbQXlAzlWS5xwSV1fpg3nIEJNFq0rUHaSuw5jWwgU5pefX8/3KlDsrTJ/iALF6+hi6exxUhZRBU32jqgxVdhrIg14Yk8KlnhoWYIIFHvSea8Uo/ppVJaj+yeqzzYTKLUsiFXTYE+gUG+EqtFvyePz/PGZHTabjGcuOOMVFJMIZoNyNHGbiNlGljYEitRX2dhsRu5Uet3IrEAhE7WwgtKyH7w9KELaMpcpO4EetjPP7MXEJZ4/Xz4V8X059/2iKEfPxqv3/UC+F8VgLgt9Puj+d3V+++fv+/fLwLEuoh/v+x3ps+qOz56pgGhZoLj4tUVQQaBQq9p38sEca9L7vFeORwNSNPX3TW4lUA6Xu9q2Y62g6I7r0nEoUOrsn6Dbp11/Zf81Qy/XQ2JHdCNBRKDwJR7WbCpQeoN4y1U0DsZ2jsInNA33oOhhTziYRs4o4knreRXT3tNJnTK9idgtcjXbg+JN3VRPICN0S0s81UFOCcfpqEXXqq0DlVv0BVYJlLb8EA/J75f2s2Igex7Y3DOZmLwH5ffteeRanscdHQveTnNXtC8KvkgRnejrmZ4eTdlb817Z78UTg1oX7k1soPEJTyt7UFSws60noUBp+ADOB3MsD2ftT6JUWlni2VnuOkgwbixQNtiD0t4Sz19v4SNZQdFLKp1Bv+fvjS1Hz54iSS7xpCooZK7gHcY3HATrsmQcChvPVnNUtBB54Q/bjZd49OsssO2jPbpVYvEpqKBQgRLd1Cb+zIkkUKoqKLTB3rxqXxWUDWcekRzqKmfKLaZ2XSFQWvNDdIknKBeLR7pdZbnPySpNzDbfL4ury89hYYn53PfqbFB0JuNeOX70bnp8HH3/8+XT1WWwDCEMTmzRQdWASaIg28va3YPilVSTFZTncafs98qyN+hHiygfzLHqU7x2TgeRPVVQjiZCtxIo0l4b9exT5CmedgWKmffH96AYHepGWSW6+djZUKDEKig0ompXUMj3uNLfI/+UK97Qt57HHWFLfKPHjPnB6mdRTGnK+3hsbhG038SbyxQJqaSteQVlzp7W01M6kztaeIrH7+R6kvHny6cioc79i5J341cLFOOTSXiLPYHSoh/EkPRjlldJ6YWn984/RX4xKEuLPcb4xy5km9e9DRCJxdP642isohD8+kgQNfp16Yncln8HRUVkfA+KmaG5rVSqA4Tn+nCOnQ3K0T3ZJWa2J9qsu/VTPJvmLmExIQM72l+SdXN0tccz/B0U9kNh/Mbrg92DOdtXUFTVwQwP9fagvAcnFXqnFHJq45g0KWkiUIJfUtFNk05Xr4LyRJ6YNVuPefuJ1nHtb1BBeR53irJT2se2vXWljX+gLBXkepm8KIrzL7dXgjqXaqTxpffqJR7y2IJwjeYJnZb9EJkz2Gsvzj9fnRdX3/waqkF8ikd7RvWBmhP0g1uQbX5+PTdlpPTjh62Mo39/fj0PboTQnaQH64Ld9NY2EShSl3C/7qi6Wfg7KOQhNb/l+mDb7I/m2MdJWZRlx8yoC3/CWWNnQkOBUj932ScV8ppFHKdASfeqZptklTjoxX4erRyPBkVBZ6VSBSUo2UkdS6igkPAOHiK1PVX45RVRQpkGh1Ekdjv9ov0gXymgrzDXuWGPlY7k31Yx+chFHWuet7VWnWgc3T1TjkeDwG+hnzepoLRu8Z85rqqg+KUXO7oTB86Oxg/sRueV+2K2eQJMj6P92M3iAf779jxY72Bpx0aNVOmUJzPhWaoarOz7JRvRhR619SbZD+RY90BDLGr1w4zNKigtGSooW7Xy4G2AwWAfwQ6Ybf58+ZTTpsWfX79k/Qzq0ToWVtcgUGAwGMwZsg0MlolBoMBgMJgzZBsYLBODQIHBYDBnyDYwWCYGgQKDwWDOkG1gsEwMAgUGg8GcIdvAYJkYBAoMBoM5Q7aBwTIxCBQYDAZzhmwDg2ViECgwGAzmDNkGBsvEIFBgMBjMGbINDJaJyQIFAAAAAOCw+AIFAAAAACArIFAAAAAAkB0QKAAAAADIDggUAAAAAGTH/wEGAzmbRsAhQQAAAABJRU5ErkJggg==" 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7.身份运算符

  身份运算符用于比较两个对象的存储单元

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAt0AAABgCAIAAABOnlknAAAWkUlEQVR4nO2cv04jPRfGv3vylWQUtIibSCKlgZW4AISSIs1qt6GLBAVKs9LSUSAhqPJqtdtl7wBRINp8hf8dHx97PCFhhvD8dKRlk8mM7fE5fnzsmf+tAQAAAAC6wf/aLgAAAAAAgAG6BAAAAABd4X/r9foAAAAAAKBtoEsAAAAA0BWgSwAAAADQFaBLAAAAANAVoEsAAAAA0BWgSwAAAADQFaBLAAAAANAVZF1y9vi0Xl0fHBwcXK/iB4v1N/oo/z997NPjWXQm+uH1KvjJW6CXc3+HZbhehQWypeGfAwA6hA4tYqC4XqU/h1MDsA+IusSIkRovDyTL0+PjSlAvoayJDnpTHDGByIQwztPjmb26j2JGlzw+Pj0hiAHQIaQZkDAdul6t10+r1RP/HLoEgL1BzpccHJw9Pj2trjNeTlXB6trnQWh4MF+6nIn5/xYiCAliTv8I+ZKDg+vVevV4vRKly5byNgCAN5PLpPrvrH+fPT4FydKtRBUAQCdI6RJNag6zur5ePT3Jg30gFkyg0FHk0WZgaVDZnOaBSFcHwQuAzmG0h53ouFkN+c78QVKh67WLK9AlAOwLgi5xCyMkQSrNZBKBgIQTf7bw1+yQDbHXF8WT3kRi/yT10FlgBDAAusjZmfHo1SpKoJjI5DeI6RAAXQLAfpHIl/jEqY4FT49nUZojtyDMt8Ymjn3z/hIbv8gqUSCY3J/6y0eyFwWLOAB0i2CXfLyw43TJ48pPPXRwgS4BYH+o0SXBvngiUewx+XyJVSNcArw9X0JzIal8iS/jtc3ZuLjn8sEAgK7gkyXX0ZN8BwcHB9fXdmahsylcncCjAdgH8rqEP+uih3gy5mfzJdcrk6GwSYwgi7LVdZxsvmT1+Lh68skf/VXtxl4AwLuReKyOTzVIzjaYZECXALA/1ORLYpj7R+8LYbHBioWzszNxR9sbKNYlvkDSHAwA0DGcSpHeh6Q/8ylP6BIA9gtRl7hMSFI71M9ufFoiPs12Xq5Wt++1pB4AgE5Btt3ztwEcOF3ClpQPDvD+EgD2B0mXXK+kl6JR6NfsbSGJfAn53zakgt+ZL1yUCBaydTcpnQAA7ePCTeSW5Jm+s8cn81o1YQc+/BmAvUDSJQAAAAAAbQBdAgAAAICuAF0CAAAAgK4AXQIAAACArgBdAgAAAICuAF0CAAAAgK5gdMnv37/bLkk9H6KQAIBC4NEAAMbv37+9Lkm9q6Q7fIhCAgAKgUcDABjQJQCA1oBHAwAY0CUAgNaARwMAGNAlAIDWgEcDABjQJQCA1oBHAwAY0CUAgNaARwMAGNAlAIDWgEcDABjQJQCA1oBHAwAY0CUAgNaARwMAGNAlAIDWgEcDABhZXfLv4kid3r5/odJsEsWWs76S6M+W/Dj+0Xq9GKvxYr1ezvrjReKg5ayvVH+2SFyGoE8Rnj0qhj2nu558FneEWD970uWsH1xgMY6vV9c+i3FNtcyBdeeJv3ft4SuTv1xUdnN7tkHyXiSPl0rT5Axg3Youob0tQaYTbqu/FRcv7lVZj9x5+TYi6ai6Lv3Zsi7QuDaIQnDsiW3ePrANPn6+pFY8iXqDdGbr9/a4IA4QXTIeq/FCH7QYq/HMDrPxyQPNkHaExVj1ZzNxLCsIne6Y6Fhf4dA/++NxX/DRuvYRii16d8Pz0GIzXeLPHvw6uGVbjjuJexFcqCYaRoWCRimgQdjZ1jQpuHOhWiYdTOyQwvAqlyr49N/F0dHFP+EQ4VOm3rnP5oKNyJaLF3F7qlTRXXFNF/oJKXtukhH4PjtK1CWlt8/RvUn4Z6Y4X3J7antSmzdvR/mShZMcM9NziUhx+ZLlrK/6mtlSiAepC4kRxY/uy1mfeWfpKLucjaWCMIHl3Fb/P5IPpfkkf3T6m/LzvFGXJIuwiS5J3gt+akEPmaNZxEPmpJR3nQ7xLjpeBGp6i8KXhM70AB9/o/uf78bcheU6Ne/zGxbvbRgfSVamRJek5lzh7Wl8+8zoBl3SFQp1ye0p6cYt3r5NxFPpPD44TtIl5vNoIYWcwM4IogE0vBxfM4hSEE3WJxK6hHxsVZX9f1iYJnmOtCopOQ8PFxuv42wzX5K9F3SEiIQlGc/SRYY+yRN79O2p0sMhDzVl06QgVMkJCeqlSV2yUb7EFuvo9DQKnVK9fGFN0cLAUa/Em+VLaooXtVtYPBGSL/l3caRSd4UgeIuum21cdoD5zITj8NBE2zTKl9yeKqWOLm6RL+kQ5bpkq9J5UzYRT833PZCsQriOQw9h+0n01IvpEqru6ZgqhL/lrO/Hw8Ws3+/3+yq8pr+W+TghkEKBIAow+oPyPMdirJTOFkkOXnuesFxdyJcU3AtzSvMPOYjM4MbjsJjZmAkCpHyJduRoUCycJt2eulE1J0v8jX1bviRUGX5AN2MzrYVQL17J+j0Wtdu9wiKWF09qt3ph4k717+JImfObkd63/YLGK+4SdIGHapB19JmPMMYXU7Fmk3kL1nG6RPE6jhfDbQqUXYqnYDxJ5EvIQOY/IgLH6333F5uc8bk5Vwj92XI5G4/H/f5skRi52Se5fa/iesJmqx12sDb1Xerdvk3G3HQSKNQlKVFVrktKYves6F7ov/rjMUkfx+G10V5dQBHXcXSw4c5c6ulmXBVlSZTBlHVJ+ItsEk5SS/7TMGcT1yu/VlKiaovzJbXFE9qtfikn1CWZRAndDjfzy6VBjqhGl+hPZs0cqjT1DF3SJZo/j9Nq6qSpeCp4lmQhDusLQZeYdIEZa5K6xEr78WymxYXqz5YNQt5iTBddjN+6DS6xUsntL0nWUI/N0oYJeVT1gozUxGuTkvOIeSlWl5pbtot1nOy98PWMQqX8PI5iQmS5hCrJIu8v+XdxFEeZ0mmSHkxlWWLVtRsOBV1S7BRhqcJoaVQAi5ZRvYKBP79BLdG/S3VJffGEdmugS+zfFj5wsPyUvhEzGtHq13HINzppK92YZrcvbijQAcp0Ce2+XdYljkQh5S0QBr5NP17Hces7i7FyuXumS4I9a144jIt1yXI2C5aE3D5ck7vk2ZkUS6OKXBTI5F7y7ROmRth4HJw5f57oGKlEmUWone17NedM6pLFWIhmZB2HRFAeFPvjBYRJDlGX3J6q09NoCaHY0/9dHJ2eirJE4xOadfkS7ehqPB4X5P/r8yVxvcr2lr5h32vDdA5rt2a6hF4z+lCXkzY3T7mW5Us88YLQBrcvKDR0SVcozZcQKdyx53HqxZP3BT4hIb01MZQK+17ZzqtAl/T7iX2SDVPE0eI3yYKG20oWY+3tin0d1So+V3yQ1D58KSi7A6++ncW6kxLxDcLt65LEY0zyOo5OatGMG8gie/TRxb94TCyfJonpFofrnen9JfaW+j1FojYNSlW7gUOqV7TxtWauH3fRYl1Su/1FaLcG+0vophJJrNiUs5tv2bxV6pm2gHiXeX82y+iS4tsX1B26pCvs1ftLRPFE91wl5/HRAzHkCxO9guhA8o/x/hKJTXQJFRlxGsYUabxgwiFYdBArHJazqH1qa9L4PMEhwV4Z2iLv9v6S1L0gBWK3lz5+TdPPZI0PTwvXE3m0OJAK38SeHp5EWLxYrwP3WIyjRU67CYz2I74hOrWOY/+jlPjAS0ogCOV3ru2LsIV8Sb54YbsZMluPySHSOg5XhYux6vf7PpaGnlT4XjV2Z+R1nIa3L1M10B4fX5fk8C6QmolYh0jsFUgMdOGzZzld4q9bdx7+M59AICXlvxVXUcIlpHBxKjxXYfuwc4tKp+w8NJSEySpZz7BlZTmpIjZbYxKPGKU7Bs8N2VRJUNIoCIOQnYQdMrzentLBJr7J+XUc+TeNC7PhC0JIfxIKxjviFooXyhKxeGF7FkKzvTLGzRvN6+rXcfSn8L+Px37rEgBAp9m6R5PnVdfr9b+Li/bnwG96oeru0QUJ2y1d6A60J9h7oEsAAK0BjwYAMKBLAACtAY8GADCgSwAArQGPBgAwoEsAAK0BjwYAMKBLAACtAY8GADCgSwAArQGPBgAwoEsAAK0BjwYAMKBLAACtAY8GADCgSwAArQGPBgAwAl0CAAAAANAuXpe8vjx33D5EIWEwWKHBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGDPoEhgM1prBo2EwGLOsLvnz7VAd32zxem8+4XtHsfvzSklU5w/BkXfTqje9Zz+fj9Tg6uX5YdIbXT6/vjw/THrV5C4+fzWZT+XLEIZzVrarYVwMe059sFD4wZUprf7j+WHSi65kK3J/XilaqflIRXWsa5+rYU21TIPUnScup27SV9K8NZeL2upq6E/CG7a2zKkCJ64VXSJqyctB7a/20j6YLnHOlbZM/xH727asga8FVYj9ej7KnKWu+h/JLgeJ6ugW6E3vn18vB9k2tT57f16F/hv7eFsd4yPa++ZLdqFLdiqeot72+vL8+jIfkXG3mtx5XRKMLkSXDAdqONe65GqoRhM7qsUn91HDqwfBLgeqOp8OFRc6L0Wh0x1DB3V7UeNOoRf1RsNQGTjpk20fodhKqlTD89BiM13iq3M5II0T3LJm0UEsc6aRbV2CC9XErGgk+DQapUHY6cI0KehUd8F0gnQwsUMKOlguwH8/DtXXX+a/f79/Ofz+n1Dyw29/64oq+VpY5siv43gShYh3qcKvY6X8GbZ2u09+sg/dTQnDAmm3pHZ5ZlGFtZKoS0o7Rk3z7r8V50t+Hdt7FjXTn2+Hh99+nJivSWf6+TX4CfvvhsXdeaMwXSKOYGTYuBqq0eXdtOpNJ6YH27wIzZfcTStVVb2q6pnZNuvrjebfPuLcTSvap4PhLa/BHyaD6X1alxiB5RxPT6qitFBpPsmdXBJSjc/zRl0SZ7b4eerLXKBL2MGCHjJnMP2E3ES5hHtpbeZLGgV93kUHV0GW9A3ClxsZ1NODtzzYe5P77cOkpydIpiTczQWr0SU7rMJ27edXpVSkS5z3pcJCkS7xLp9INQ3nm3QMM+ZCl7Cvvd/+/Gpb5+/3L/zu/vl2qJTpYb+Ole2FNyfRh7vOl2xdPJXO44MBW9Il5nOfZoh1if7Ej6ZEE9DLXQ4UX14Ju3XOkbgldAlJ1dyfVzSQscI0yXM8THrJNED9ebjDb7yO0yg6JMuckhpKjSamLjT6sxGCBMFszvwTZE1ij3Zxg4ea3U+Tbk7yo6nzC90zk7pko3yJLc/h8Vc7qLvySG3iY3Jscr8lXqZ7oO+HURelpyrOl9RUIWrbdBVIvuTv9y/OIXgGRQ89J8eH+rJO5fz5dmh+8eXHn2etkwwJkST4sm4rG07ZAaNLf9NtMwYTjDfmS25OlFJffvxCvqRGl+gbLBntmpKU8T/frS7ZgXhqvu+hmtwJumRIFyl708vwtMO5oEuoBqdjqhD+7qaVX/e9mvSqqlepwUgcgIeDkfer3DpOUBhnTFGV5zkuB0r1qqo3vWfpgbLzhMLlnfIlmTIX5UvMMGbOTPSiLcPdtBqMhkGDE02Zm8XujUn5Eu3I0aD1DtOkX8fuGGEqT3duDeevb8+XkAIExTMDMAuhvE38SM8s02/rd0tkhbKJIfNNqiC1bbIK7gzkbpqh+g9rQC01tPIgivPkp+ke5idxvmROIyEPC84TvS7xB9g4Mx9V5w8+dum8S9xe4sp4tmNIzfuprHgdhyvQzGHHN7xB//tx+D66pC3xFPh/Il8yH0Vbz3xf95+Y/k0Wa9zkLEjMMpVtZkj356PhoKrOrxIjN/skt+9V3IlZsnkltvvzSqnRpa2v2e0rz89kSyeBQl2SElXNdUm+zMH9CuMLlVD351U1GJEtO3EQbLRXd/9MXMfRU2SuDN7D039+Pfz29+X55kQ6v+tR5g9Zl1DLbR1IFs8ugoQ5m7hN5HWQJr6WXLwgVpwvqa2C0LbJpZxQlyTXMrhqOb4JtAg9QF7HsbW7m1aDqctn0ztbq0v0J5NmrlrTMcTO/Jms+fM4ZAoiHNZmvmTL4qlgf7v0HE11fiXokvlIqarqKfc0h6xLrAAfnk8rnVbpTe8bhLyr4eAq2Dnbs5tIgp0oVJck95fYusiVT6xihO1jF6Ts38S376aVGXdLziPmpVhdXre5jlNTZuEOujsSpXbirdDy8ziKCZG7h0+wy0TeX/Ln22G9C2u2O03SX5kRlJXqYdILt5UIuqTYKTLFs1kEFmmjNpEG9Wy/zW9i00Tqv1SX1FdBaNt6XfJC1+wUFyi1usTLkawuufdrr0pRgVKyjkMyTNX5Q5yR2qBjiJ35M1mZLqHdq1SXtLG/xNkOxJPwlK+3QDqI6zhufedqqPR/XyNdEuxH8xnjQbEuuZtOgiUhtw/XrCOQ5aesWr8zqsj5qvPSdL5Ebp9wusbG4+DMRe3sj5GyQZlFqCb5kpIyF+uSq6FS0T5Wso5DxgMe0XqjyyYppY9poi65OVFfT46lBZqde/rf71++nkiLOK4j+cE7ny+Zj9RgNFSj4aAgS1+fL4nbhA/qzX3NF3Xjfa8NUz6sbYt0CTmYf7ilfAmNOQ+TXuCwZfkSb3zte6OOke/zn8BK8yU3Jy5cShvNJF0i7Syjq4AbFjdZyJ2IJx96+JSdOHliKE2+v0TI59+fV1XPDvmsKzdMEUeL3yRXGW4ruRxon3TyJYhcZHz1FeS6JN8+/NGSdN64qJ3Fuif35G6oS8rKXLiOo7Vg9t0G/gzDua57NZlLr8PZT5M92uwYiDcT7H6aJKZq6H333TKlS/QE2uw2GF3K2jRXvHhzhtQm4eaMkn57V/ueJHHrd+G+17otMkLb1u8v+XWsVHxaekKuS0wurX5/iaudW4W3otOuhb2+lD4nbCcVvekko0uKO4bYmT+Tffz3ve5SPJkxI3j6NypV6p0cRJcEnj85r+zx8f4SyTbRJVRkxGkYU6Th/Cp8A0qw6CA+IxOWs6h9gjLLTtjwPPzpJ/64k70vW3l/SZ0ukd4159Z67I1mwd39yk+8lFLBGt9neVo48mjyiKmwkPEO06T/fhwKCxPmzpI9jHwZ124CU8FDGeHm9NQ6ji+M+DCL2Ca553HknmnNub/9ZCv5knwVwrb1dyTR1Il1HGnLUaRL7OdKKbrMZ/sMudDlQFW9ykdp6XH92p3CWqrSdZ/4mKYdQ27eT2QfX5fsyvxDLtLmUNeTpPHDdc26uX5el/jr1p0nMHIqOwaLT6yxd5+QwkvvTHOFsf5T2D7suok5XMl5qMOHySqbDeI76qvJXXwvGr6/pEaXsFYlBZZeAewK4x/Y0f8fXJG1f/Exq321zoWdP/7tWzcndEiInyN7877XksJs+vKPgj2tJH0iPqWv5OixeRX+BG82e9/3l4jVH1y95N4dZQJIoxlj/TqOvjt4x2vOoEtgMFhr1imPDrdM/vfje/warhaKtOH7Xjtjugph236wKsDe2aBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzKBLYDBYawaPhsFgzAJdAgAAAADQLkaXAAAAAAB0AegSAAAAAHQF6BIAAAAAdAXoEgAAAAB0hf8D7YKps2CAzmcAAAAASUVORK5CYII=" alt="" />

  这里要讲讲python中的内存池(缓冲池)了,python使用内存池来管理小的整型数和小的字符串等等。
  什么意思呢?

  当我们执行以下赋值运算时

a = 123
b = 123

  理论上是要分别在内存中创建两个值,然后赋值给变量的,但是这样做实在是有点浪费,明明是一样的数,却要占用两个内存空间。

  所以python为了节约内存,引入了内存池,当小的整型(-5~257,不包括257)要多次创建时,只创建一次,后面的都将引用指向同一个地方,此时使用身份运算符会出现:

aaarticlea/png;base64,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" alt="" />

  字符串的则以256个ascll码为分界

  有兴趣的可以参考:戳这里

8.运算符的优先级

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QgIiISSjAKqUBERCSUYBRSgYiIqEMJAAAAwHEpQ8kG4HhQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAhBKIAioQAAAIJRAFVCAAABBKIAqoQAAAIJRAFFCBAABAKIEooAIBAKA5lDzfno3u/I+f3T7r7buREEII/djz7ZnwvtJ4rXsQ+Mp0DCVFJiRpvu545OolIivKh9Z5qje2PkzzFazzVD9TZPJn60HzeP6DdD1XeT7jrdhbh3rvAAAfRDCUPN+eibPRaDQa1eOFEyfU5t1IxZK7USiSkEnAiyeUrPNUuOwwnBaZyAqdD8qEkGdbH0sni3WeZoWTHKyjr70XL4RI80I9oU7v7pkVnc5VP4FxbHWkg713AIAPobFT8nx7JnzBwckcalPFjMa4Ub22IbjA16OtU+LpNXREDsxGz6LMD8W2Q7MTFMyuhHzKyglZsWnolNiv1dehLqr1XNXBy2eKTAiRZllemPsc7L0DAHwIDaFEpgZPdnAfsjslDTM3GzIJBKhVYG0Kw9N16BRSikxkudG+0KOxHqQ7UcscugFhtSL0wO9inbotlLSeyz2BjkFV5jjYewcA+BB2WOjqaYQYa0qqKKMe8L+WyRuwCFZgOcDaf/tvNkXedUQtMpFlmZzLEGnqzJVkWeex2e1e6Dhh5IoyKWRFIJS4sy5pXnTplHjPtdkUWfWOqgeLTG8c7L0DAHwI24eSxjghn6wvMnFfSyYBm3oF2os0jVAiH8vXW4SSwug0bDa19aDdqM/OuIFhs87TNE1l0Miy4IyNFRy6dUrcc8kdjImdIs/zTPdV5E8He+8AAB/C9qGkad6lfM5dZFJ/LZM3YNPSKVnnqZyvqUbtotgqlGyKLM0y3+LTziN0rXtR/qBHeWO2pGn6prqUNF93XFNSP1fbBJfZV9r/vQMAfAhbh5JtbqxxOyVkEgjhq0DVLsiyTKRp1YPYckSt3YGy2b1TItdrmBdQZMbiliLP17U1rUXm2ZYXUGTCzhlOKGk6l+fq6m/pYO8dAOBD2DaUhOddrGe8a0qYvIEgtQo0bjIRqRrri8ZVEP5n1chutg5U18EfbHzHWZt38lq9ESceldcdaGOkeZ7ZR/B0Sjqfy7yNZu3eDrzbewcAOCZ8oytEgb8CdW/AzCiBYBK4a9i8FcUYwWuPtR3H3qOcUlITMNaXkxmvLjKR5kWeeTJO4/eUdDuXE0qCnZLu7x0A4KgQSiAK/LcEW7ew6rG+WuXpvMKbJZzv5CibB40Nl7Z7UsocYX+TqqiWfhgTL24bw9Me8U7ftJ4r9385mxNvtn7vAABHhVACUUAFAgAAoQSigAoEAABCCUQBFQgAAIQSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAB1KAAAAAI5LGUreXl8QjyUViIiIhBKMQioQEREJJRiFVCAiIhJKMAqpQEREJJRgFFKBiIhIKMEopAIREZFQglFIBSIiIqEEo5AKREREQglGIRWIiIiEEoxCKhAREQklGIX+CrwfJ4NZw6sWAyGcHe7HSTJetZ7xfpwMxtNEiGS82uc4iIh4OAklGIVdQslq0hOa/kI+Pu8LMz24YWI5TXrT+5YjdzgOIiK+u62h5PulOP957KvET2+tApfTRJgM5y+rSS+ZLNWzKpRI533hob94reKFe8AKdcy24yAi4jtLKMEo9FfgvC9nVVaTni+UzIai1gXxdThWk95wbucYq1PS9TiIiPiuhkPJj3Pnr8XT64ejXy5+VncKJfIHMZwbLwmGieU06U/VBFAy6CeDmTG50/04iIj4Xu7YKfl5oaLKxfejvwf8BDaHksWgN71vmL6ZDf0zM3JqRiaP2kuS8cpdWdJ8nON/SoiIn1umbzAKvRVYpZCGULIYmB2OWsPj9aXMH6+zoegv1JKR4Xw2FP2h8doOx0FExPeVu28wCr0VWAWFcCix+x+6s2JECvmgnI6Z95PJUi0xMW8D7nAcRER8ZwklGIW+CpwNRdUOCYQSc/7FXgWyGNitlHk/mSzfrE6J8XiH4yAi4ntLKMEorFfgYiCMCFKGEuc2XbkA9u31RSeY+7G+83cwU4+rBa0ygsjZmck4ScYLtYS27TjH/4gQET+9hBKMQrcCVbtiMZALTcer13qnxFpZopak6ibHatIvb/Qts8iLem05KbOa9ITY5jiIiPieEkowCqlAREQklGAUUoGIiEgowSikAhERkVCCUUgFIiIioQSjkApERERCCUYhFYiIiIQSjEIqEBERCSUYhVQgIiISSjAKqUBERCSUYBRSgYiIqEMJAAAAwHEpQ8kG4HhQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAhBKIAioQAAAIJRAFVCAAABBKIAqoQAAAIJRAFFCBAABAKIEo+FoVWGQiK6zNNF8f73IAACKBUAJR0FKB6zwND9vrPBVqVHeG++1pOUDzudZ5Wj6yzlNRQz7nPpWmznZ1dPPw6zzd850BAEQPoQSioLkCA5lEDe/VYF1kvhSwDTpW7Hau4Os3+mVpvjYSTZHJt2a3S5zkkmX22WisAMCnJBxK7kZCnN0+d3jQy/PtmRCjuw4PAngq0Ntq8CWOKgas89QYrLfqLLgBo0Z53C7nao0lTe/N6LNkhX26rNi/DQQAEDfNnZLn2zMhhJNDvA/u8xKApk5JeOqmqLUP1nkqRFY4Ux/dCQ/7W50rGHIa2ynVw6p5on7U2x0SDwDA30u36ZuObY89myvwhQlXoDFC+7A7IusiS8WOgWT/c5VZRD8SWMHa2impdqunHSZuAOATQ6cEoiAUSkI9BzVaq/E9zfNMCLlqdOdxu+Vknc5lJImqxeP2X9o6Jepk9Z0IJQDwqWFNCUSBN5TIFFAfhvUgX2RplqVZoR7Za6VrkTUuDOl2Lv1KM0DYsaTTmhKh5oZ8EE0A4FPC3TcQBZ4KLDKR5oVvQYka4td5mhXWalBztN5yWai1ez2UdD2X2mWdZ/rWXichta8pEVb2McMNcQQAPjGEEoiCWgWWY7J3lWs1Xuf5Wg3lcuwuF59uiizQTQh9T5lznnps6HouvYsbRWSgaL3Rx/MtKFZniFACAJ8XQglEQagCQzMdwaZGaMqnejaw8tR+uMuqD8+59KqT1uTgrBnxpCBfo4dQAgCfGkIJREFDKGlaU7KptSaaB23/oN7ew7C/pyR0rurozbcEF1n9tW2hpDoidwQDwCeGUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAhBKIAioQAAAIJRAFVCAAABBKIAqoQAAAIJRAFFCBAABAKIEooAIBAIBQAlFABQIAAKEEooAKBAAAHUoAAAAAjksZSt5eXxCPJRWIiIiEEoxCKhAREQklGIVUICIiEkowCqlAREQklGAUUoGIiEgowSikAhERkVCCUUgFIiIioQSjkApERERCCUYhFYiIiIQSjEIqEBERW0LJzwshhBDi/OexLxQ/t6EKXAzEcK5/TibLo18qIiK+k42h5Me5OL36/fry+/pEXHw/+rXiJzYQSmbDZLzSm8tp4s8lv69PTq8f1Ob3S3Fy86iefbw6FeLyh7H/49WpzNmPV6fCotrNPiAiIn6EhBKMQn8FzvvJZLkYCC9VB+XNyRA/zi8vzvVmmTyMbp8VSswu4PdLlUsIJYiIH2/z9M3Dzak4PT1h+gbfW18FLqeJlTwa/H19opocDzenJzeP3y9Pr37LZ2Xy+HGug3UwlLy8PV6dqiBuNVcQEfH9bQwlqrnNb2d8bz0VOO+rdshsKPoL46mmxSUqVfy8UHWrkkf9EU8ocaZ+EBHxAw2Hkur39Y9zIU5uHvllje9orQKX06SXqE7JatIzUshsKHrTe/9x9LRL1RrRyUO1T5pCiWy0HP8DQUT8ggZDibmO5Pf1iRCCZSX4ftYqcDYczPStN/fjpFrxOu+LwSxwnIcba+WqmzzKyEKnBBExSjt0Sl5ls0SIapIe8dB6JxCN+4GX06Tsjpg3CbuquRu5Wc7XWMnj4eb05OZHOJSoxd1H/0AQEb+gbXffGH9x/rwQ3I+A72RbKKlmcJybhC3d1alyBsdJHubNOOG7bxAR8ePlG10xCltDidReXOL4cHPqm4v54bZDfl+fiLbvKUFExI+XUIJRGA4ls6H/a0r4dldExM8moQSjkApERERCCUYhFYiIiIQSjEIqEBERCSUYhVQgIiISSjAKqUBERCSUYBRSgYiISCjBKKQCERGRUIJRSAUiIiKhBKOQCkREREIJRiEViIiIOpQAAAAAHJcylGwAjgcVCAAAhBKIAioQAAAIJRAFVCAAABBKIAqoQAAAIJRAFFCBAABAKIEooAIBAIBQAlFABQIAAKEEooAKBAAAQglEARUIAACEEoiC963AIhNZYW2m+fodzwcAALvQGEqeb8/E6M599G7keRBgL0KhxIwT9SyxztPy2XWeihryOfepNHW25TGLTJjJZZ2nVpABAIB3pymU3I3ORqOzWgAhlMDhCYSSIrNiyDpPnVyiY0kAlWSqdKMOaUccJ7lkWeYLLgAA8J40hJK7kRjdPd/WUgmhBA6PP5QUWZqvCzsfOH2Q9lgSaKM4xxBZoQ9VbjuzPgAA8L6EQ0mZPeqphFACh8cXSrrPoIRyi57A8R2netjox5QxSG13SDwAAHAogqGkih53I3F2++x7BuBgeEJJkalU4XYsjCkZo92xCa5gbe2UVLu5CcSZPgIAgPdkh7tvCCVweGoVuM7TNE11q8MIB1b0MJJEtZcbYto6JeWGpy1DKAEA+EAIJRAFtQossqzQ4cJMJXbk0MnCDBC1fdrXlAghsiI0D0Q0AQD4AAglEAXeCjSihU4lThtEhZJ1nulbe525mfY1JUInIKsPQ6cEAOADIZRAFLSFkiqVuDGhTBaeKCL3DK6Bdbsgxsn0j4QSAIAPhFACUdAaSiT24pJqXqZDcnDWjNSbJ977fwklAAAfCKEEoiAcSoKtjjTPs9SdsvGtGSmyem5pCyXVEbkjGADgw+D/+waigAoEAABCCUQBFQgAAIQSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAOpQAAAAAHJcylLy9viAeSyoQEREJJRiFVCAiIhJKMAqpQEREJJRgFFKBiIhIKMEopAIREZFQglFIBSIiIqEEo5AKREREQglGIRWIiIiEEoxCKhAREQklGIXHr8B5Xwxm1mYyXh37Y0FE/FISSjAKPRU47yeTpblphQbtbGilB2fzZTXpDecvb68vb/fjRNSQx3Sf6iX2dnkl874Q/UV18PtxYm4iIuJ+EkowCncPJc5ury+rSc/eczlNmqPDbCh603vjFOqYi4EwDr6cWkmlPxz4ggsiIu5qt1DyeHUqxOWPbQ5df8mPcyFObh4D+zc/i5/dLUPJbCj6C7u9kQz69UaI7pH4uyza1aRXb6PI8LGodhjM9KHKNslsSLMEEfFANoeSh5tTIYQQp1e/5SM/zp1f2LWkUnvJPs+2nw4/iduEEtXYeH2pd0FW98u315e3+2VtOchsGAgdMrjoWR7L6vjGrNC8n0yWi4G6hg6JBxERuxgOJTu0Lrq/pLn1skNjBv9yvaHEalfIUOKs6ijzgeqI6GdnwzJtlFlEB47ACtbWTkm1m5tdavNHiIi4m1t2Sto9aKcEv4ydOiVCOMtKZLuiDCW1RSdVWDGSxHKayA6HO+3S1ikp9/GsayGUICIeyC3XlHSfTznImhKmb76MOy10tVaeJpOlcTuMlTl04DCPaR+w05oSIcRgthj49yOaICLuKXffYBRuG0rMxoaevlH3y6wmPfO1aufldCAnbvT6kuqF7WtKqikk564cOiWIiAeSUIJR2BRK7sdJMl7ZoUSvM319KVsXiRE4vF9VohepVE0UuXw1uFqIu6YAABFzSURBVAbW7YIY12AuZCGUICIeREIJRqE/lMi7fGXCsELJcpr0pnN9S7D19WhJL6lPu+gbdsI6X4ZWv63G+10phBJExANJKMEorFfgatITzle1mr0Lq2sihnO5vsS6MUcIMZxXt/I23xLs6a+0hpJqcYlv3gcREbeWUIJRSAUiIiKhBKOQCkREREIJRiEViIiIhBKMQioQEREJJRiFVCAiIhJKMAqpQEREJJRgFFKBiIhIKMEopAIREZFQglFIBSIiIqEEo5AKREREHUoAAAAAjksZSjYAx4MKBAAAQglEARUIAACEEogCKhAAAAglEAVUIAAAEEogCqhAAAAglEAUUIEAAEAogSigAgEAgFACUUAFAgAAoQSigAoEAABCCUTB8SuwyERWWJtpvj7e5QAAfEGOHUqeb8/E2e3zcU4O8eCvwCKzgsE6T63gIB8JIl+7ztPyNd6d5XPuU2nqbMvLKDJhXkD9egAAYA8IJRAFvgosMjs+ZM52LQ44GUahY0kA1RWpmiXqQHa7xEku7vXQWAEA2JNuoeT59kyI0d1mczcSB84QdyNCCfgqUAaCKmeUXYnGgBEIJR1iSVPPxeizmBdQbjuzPgAAsDvNoeT59kwI4eQQ74ObzUZGFguVY2oPWq85u31u3Q0+OW4F6rFepgBrEiaUAoKhpDxiU+gIHLZ62Dh2kZlpqUviAQCALoRDSWtTpGqf7MXdiPgBvgpsXC4iyqZF0x5CCJHmeWa2OzbBFaytnZJqNzeBNEYhAADozkE7JbvwfHtGKIHWVU2d2hGheGC8eJ2n1XKRtrRRe9i/sJVQAgBwIA66pmSX6RsVSpi++dp4pm/auyBuFGgPJeYedizptKZECJEVoUsjmgAA7Mmx774B2Gw23Stwp4Wu6kXrPNO39jpzM+1rSmQeyYqNMwVEpwQA4EAcO5RwSzBsNhtPBba2SjxJoCWUeKKIfEV7W0Z/T4l6qf6RUAIAcCCOHUoANptNuAJlXtCj/vadEjUv0yE5OGtG6ufy3v9LKAEAOBCEEoiCtgo0mhn1WKDXgzREhuZbgousnlvaQkl1RO4IBgA4CIQSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAhBKIAioQAAAIJRAFVCAAAOhQAgAAAHBcylDy9vqCeCypQEREJJRgFFKBiIhIKMEopAIREZFQglFIBSIiIqEEo5AKREREQglGIRWIiIiEEoxCKhAREQklGIVUICIiEkowCqlAREQklGAU7lGBy2nSX1Sb834yWe5ynHlfDGbWZjJeHftjQUT8Uu4eSn5eCCGEOL36XT7ycHMqLn90P8LDzenJzWP33Tru/64+3Jye/9xx561e++WsV+BiIBS96b1+fDXpDQdG8rgfJ4OZsbPFcP6ymvSGc7VnfQ8ZRNyneom9XZ5u3hfCCED348TcRETE/dw1lDxenZ5e/X59+XkhTq8f3l5f3n6ci4vvOxyh624d9383f1+fiNPzy4vzyw7Zy9l5q9d+TX2hpMwii0FvOq9CQ3866Q3ny2lSPqszh9TTKbFbKR5nQ5l7qmaJOshiIIyjLadWUukPB77ggoiIu7prKFER5Pf1yen1wy5tjI4hptpt29DTye+XYpvuxePVqej8Np2dt3rt19MfSubjJBlPB7VOiU4hKp34uiBON6X5AlaTnr/Zonohq0lPDGb6UGWbZDakWYKIeCDDoeTHufO72foT3+6U/L4+cRND88tfX35eiMsfnXfrvH/3C3h7fXFDSctL5M7qJVvtvN1rv6LNoWQ48CSGZLJ8m/fLyZ37cWIvAVlNenbrYjasH0IIIYSMOG7HpbTqssyG1fHn/WSyrBo5XRIPIiJ28SBrSqoRVwihZnNaPPaCklos6HbZ+F526ZTI3GCkh+U06SUtnZIyi+jAEVjB2topqXZzs8vOS2sREdH2AHffyBkcNY/z/bLLJMX7LCgpc5IQnSd6tpy+wXezJZTMx8lgVoUSFQJm08lMT9+EOyVOjpnev7zVpl3aOiXlPqLeFCGUICIeyF2nb7TluK7mWVRLo/nl5kqRjrt12X/r699q+ma3z+fQr/2kBkPJYLYwQokQIkl69uLT9jUlOnCYAcK+B7jTmhIhRPhOH6IJIuKe7tspUQ2Sl606JdVKkY67ddwf/179oWSiVm8YnRJ7Dcdym07JcjqQ++j1JVV3pH1NiegvVI6x7sqhU4KIeCD3CyXWrEr3NSXHXlCC8emtQNmTqIKIyg2zYTJelflgm07JvO80P9Ty1eAaWPdQRnNlMRCe7gsiIu4h3+iKUeipQLUi1ZjHEUIIMRhPk/6ijALtnRI1L2PdV+zX+TK0+m01zre+qgcJJYiIB5FQglFYq0BrIapumchHqjuBZSiZ9MMdjrG6lbf5luDZUAj3rpy2UFItLvHN+yAi4tYSSjAKqUBERCSUYBRSgYiISCjBKKQCERGRUIJRSAUiIiKhBKOQCkREREIJRiEViIiIhBKMQioQEREJJRiFVCAiIhJKMAqpQEREJJRgFFKBiIioQwkAAADAcSlDyQbgeFCBAABAKIEooAIBAIBQAlFABQIAAKEEooAKBAAAQglEARUIAACEEogCKhAAAAglEAVUIAAAEEogCqhAAAAglEAUUIEAAEAogSg4fgUWmcgKazPN18e7HACAL0g4lDzfnonRXesBOu7WnYMfEP4GmkOJExhCzxaZyIp1nlo7r/O03Fznqaghn3OfSlNnW+aTIhPmsd1TAQDAXsTXKSGUfEn8FVhk9RShI0K1k9xe56n8wW1y6FgSQL3ASDe+IznJJcuyhqsCAICt6dYpuRupX7y1uNB9t7Pb21H96Tv7sTvPLvAFCIWS+khfZQ9703p461gSaKMYvRTVFqkOVW43N3EAAGALuoSSu5GKCJ4uxha7ibPb53LH8ifjx+onOiVfkh07Jes8FWm+dpOKfqL1WMYEji9cVA8b+ajI0nyttzskHgAA6ELHUKJCRJ2td/PnGP1yQsmXZKdOiexupHnu2U21MsosomNDYAVra6ek2s1NIL6LBACAHeg2ffN8e1b+gq7Fjh13G905D8oJnmdCyRdl207JOk+zosirjkV9T3tBqtoyF560pY3aw/6FrYQSAIADseXdN/VuyA670SmBGtt1SrKs6paYu4SmVPSWvbd7J01jp6Tcoeq9+KLSvp8CAMDXpkMoMRNGQ9rouJv9M2tKQFKrwOASEGf8N2KGkURqgSMrNpvNOs/0rb1OP6V9TYnMI1mxcaaA6JQAAByITp0SfVdN4903HXezY0f9dhs5CUQu+Vp0uSm9yIQQWW6vadWRwAwi3lDiiSLy1Y0ByExBxmH1j4QSAIADEd/3lMCXJFyBel6luk3GE0rsu23MfdTrOyQHZ81IvXnivf+XUAIAcCAIJRAFtQqssoh9q00tXpT354pq+aqzTxUZmm8JLrJ6bmkLJdURuSMYAOAgEEogCqhAAAAglEAUUIEAAEAogSigAgEAgFACUUAFAgAAoQSigAoEAABCCUQBFQgAAIQSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAoEMJAAAAwHEpQ8nb6wvisaQCERGRUIJRSAUiIiKhBKOQCkREREIJRiEViIiIhBKMQioQEREJJRiFVCAiIhJKMAqpQEREJJRgFFKBiIhIKMEopAIREZFQglF4/Aqc98VgZm0m49WxPxZExC9lOJQ8Xp2K858HPFn9gAc/Bf61dgkli4EYzl8WA+GmBy9qn9WkN5y/vL2+vN2Pk9Bu7lO9xN5OJkt1rv6iOvX9ODE3ERFxPz+wU0IEwbBdKrCKFzpnvNY6HJ4Hl9OkOTrMhqI3vTdeNe/LFLIYqDhSHscMKv3hwBdcEBFxVzt0Sh6vTk+vbi7K37yXP2q7+Z/9flk+JoOIs7nNKfAL6AslTghwKXNJW6fk7fXl7X6c1IOL7WrSC5ynDDSrSU8MZvpQZZtkNqRZgoh4ILuFEiFOrx/eXl/efpyL06vf7m6eZ39e1B5smL5pPgV+AQOhxBrvrQbJ1s6GjeEmcPDqGmbDaonJvJ9MlotBb3r/8vbaKfEgImIXO4YSFSaa14Xon79f6t2+X4qTm8fWUBI+BX4Bu4SSalbFmJ1p6KbI0FBmEWu6x7eCtbVTUu3mZpfqqhARcT/fJ5RYuz3cnBJKsMXW6ZtkslTD/3KaqC5FeL2I7mRYSaJ6rTvt0tYpKffxrl8hlCAiHkQ6JRiFvlCic8Nq0ksmSzlRYicDMzRYAcIfSswAYa+Q7bSmRAgxmC0G/v2IJoiIe/pOoWSHNSWEki+tpwLvx4maZylDSTkXY3Y4zCBiNT98oWQ5HcgD6vUlVXekfU2J6C9UjrHuyqFTgoh4IN8rlPhut3m4ORXBu28IJV9bTwUanQz5DSUyTNg9DyOUlLfhlJueUKLv0zFyTDJehdfAul0QzyURShARDybf6IpRWK9A/VVpZYyYDYVIBn35fWV2Y0OuPqlaGkLOs8hn1byMzihBnS9Dq99WE/hOFEIJIuJBJJRgFNYq0LgFV25WPZLy21d70/tqJawvcMz7QojhvDpO8y3Bs6EQ7l05baGkWlyyx43KiIioJZRgFFKBiIhIKMEopAIREZFQglFIBSIiIqEEo5AKREREQglGIRWIiIiEEoxCKhAREQklGIVUICIiEkowCqlAREQklGAUUoGIiEgowSikAhERUYcSAAAAgONShpINwPGgAgEAgFACUUAFAgAAoQSigAoEAABCCUQBFQgAAIQSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAQCiBKKACAQCAUAJRcPwKLDKRFdZmmq+PdzkAAF+QQ4SS59szMbo72CVFekp4V+oVuM5TmQqKTPioEkSRyf3WeerbZZ2n5a71HarDuE+lqbMt80mRCTO5rPPUCjIAALAXhBKIAl8FlrFEho5yo4wYRltDZRKdYqpX6zDSHB1UV6Q6qjqm3S5xkkuWZb7gAgAAuxIOJc+3Z2e3t6PyF66RAO7sx+48u3gff749OxuNzmp7Pt+eCXvX1lOfjUaEks+FPxav8yxfh0OJ1UNJs8zbKZHHaYklgTaKeZSyLVIdqtx2Zn0AAGB3GkOJEGe3z5vNZnM3Uj8ZP1Y/+doWgd3qScI4dHWcLqf2HAr+Yhp6dY3TN1WfpJXAYYwJHF+4qB42TlRkqYpKDa8EAIBtaQ4lRpND90WqMKBCgieUdNzNQb2q/dRM33w2ahUoM4ROHN6OxDpPs6Ka5fEEjjTPM7tpElrB2topMc7oXikTNwAAB2HLUGKFgefbs0Da6LiboprpEQ2hxH65mVDgE+DtlJjLRWppY+08nOZ55qxCVVv2j9Vykba0UXvYv7CVUAIAcCCO3im5G5lLSeiUfFUaQsk6T+3ehtPrCN+mUw8lZoAo3AzT3Ckpd8iK0DwQ0QQAYE+2DSV7rimpBQn3LLX4Ejo1a0o+F8FQUhiTM2m+LrLa6F+GhA6dknWe6Vt7nbmZ9jUlMo9kxcaJRXRKAAAOxNahxHe7jbx/psPdN74goW++qe6pCZ5a7cvdN5+O5umbjdGo0E+XD6Vpx06JJ4rIMwTXwLpdEOtOZOHpvgAAwB7wja4QBfUKVEmhnC8JD/z1ZSI6ZKT5Ws3LdEgOzpqRevPEu9qWUAIAcCAIJRAFnrtvGr/P1UgZMpSY+5nf5FpFhuZbgn3Bpy2UVEfkjmAAgINAKIEoOHwF8vUhAAB/G4QSiAIqEAAACCUQBVQgAAAQSiAKqEAAACCUQBRQgQAAQCiBKKACAQCAUAJRQAUCAAChBKKACgQAAEIJRAEVCAAAhBKIAioQAAB0KAEAAAA4Lv87djACAAAA2Gw2G0IJAAAARAGhBAAAAKKAUAIAAABRQCgBAACAKPg/EbM1PleIOZYAAAAASUVORK5CYII=" alt="" />

  另外,我们也可以像数学一样使用括号() ,来指定某个运算先进行

  更多参考:戳这里

  有别人做好的*就是不一样,一路复制粘贴就好了,真轻松。


二、长整型

  和整型基本一样,这里就不重复了。自己可以用 help() 函数查看。
  遇事不决喊救命


三、浮点型

  这里就不全部列举了,只讲讲不同的。

 |  __setformat__(...)
| float.__setformat__(typestr, fmt) -> None
|
| You probably don't want to use this function. It exists mainly to be
| used in Python's test suite.
|
| typestr must be 'double' or 'float'. fmt must be one of 'unknown',
| 'IEEE, big-endian' or 'IEEE, little-endian', and in addition can only be
| one of the latter two if it appears to match the underlying C reality.
|
| Override the automatic determination of C-level floating point type.
| This affects how floats are converted to and from binary strings.

  一个内部方法,用于内部测试的,官方都说了You probably don't want to use this function(你可能不想使用这个函数),而实际上我们也用不到,我也不知道有什么用,一般可以无视。

 |  __trunc__(...)
| Return the Integral closest to x between 0 and x.

  返回最接近x从0积分和x,貌似和积分运算有关,没用过

 |  as_integer_ratio(...)
| float.as_integer_ratio() -> (int, int)
|
| Return a pair of integers, whose ratio is exactly equal to the original
| float and with a positive denominator.
| Raise OverflowError on infinities and a ValueError on NaNs.
|
| >>> (10.0).as_integer_ratio()
| (10, 1)
| >>> (0.0).as_integer_ratio()
| (0, 1)
| >>> (-.25).as_integer_ratio()
| (-1, 4)

  返回一个由两个数字组成的元祖,而两个数字相除就等于原浮点数,其实就是返回一个最简分数,分子在前面,分母在后面。

 |  conjugate(...)
| Return self, the complex conjugate of any float.

  返回本身的共轭复数

 |  fromhex(...)
| float.fromhex(string) -> float
|
| Create a floating-point number from a hexadecimal string.
| >>> float.fromhex('0x1.ffffp10')
| 2047.984375
| >>> float.fromhex('-0x1p-1074')
| -4.9406564584124654e-324

  用一个十六进制的字符串来创建一个浮点数

 |  hex(...)
| float.hex() -> string
|
| Return a hexadecimal representation of a floating-point number.
| >>> (-0.1).hex()
| '-0x1.999999999999ap-4'
| >>> 3.14159.hex()
| '0x1.921f9f01b866ep+1'

  上面方法的逆运算,返回一个浮点数的十六进制表示的字符串

 |  is_integer(...)
| Return True if the float is an integer.

  判断一个浮点数是否为整数

aaarticlea/png;base64,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" alt="" />

  其实就是看小数位是否都为0


四、复数

  都是一些运算和内置函数相关的,唯一特别的是

 |  conjugate(...)
| complex.conjugate() -> complex
|
| Return the complex conjugate of its argument. (3-4j).conjugate() == 3+4j.

  返回一个原复数的共轭复数

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