标签：related ber 下划线 erro 逗号 全局 des map geek
PEP 是 Python Enhancement Proposal 的缩写，翻译过来叫“Python 增强规范”。
PEP 8 规范告诉我们，请选择四个空格的缩进，不要使用 Tab，更不要 Tab 和空格混着用。 第二个要注意的是，每行最大长度请限制在 79 个字符。
PEP 8 规定，全局的类和函数的上方需要空两个空行，而类的函数之间需要空一个空行。
控制每行的最大长度不超过 79 个字符，但是有时候，函数调用逻辑过长而不得不超过这个数字时按以下规范:
def solve1(this_is_the_first_parameter, this_is_the_second_parameter, this_is_the_third_parameter, this_is_the_forth_parameter, this_is_the_fifth_parameter, this_is_the_sixth_parameter): return (this_is_the_first_parameter + this_is_the_second_parameter + this_is_the_third_parameter + this_is_the_forth_parameter + this_is_the_fifth_parameter + this_is_the_sixth_parameter) def solve2(this_is_the_first_parameter, this_is_the_second_parameter, this_is_the_third_parameter, this_is_the_forth_parameter, this_is_the_fifth_parameter, this_is_the_sixth_parameter): return this_is_the_first_parameter + this_is_the_second_parameter + this_is_the_third_parameter + this_is_the_forth_parameter + this_is_the_fifth_parameter + this_is_the_sixth_parameter (top_secret_func(param1=12345678, param2=12345678, param3=12345678, param4=12345678, param5=12345678).check() .launch_nuclear_missile().wait()) top_secret_func(param1=12345678, param2=12345678, param3=12345678, param4=12345678, param5=12345678).check() .launch_nuclear_missile().wait()
1.通过括号来将过长的运算进行封装.
2.通过换行符来实现.
行注释并不是很推荐的方式。
docstring 的写法，它是用三个双引号开始、三个双引号结尾。我们首先用一句话简单说明这个函数做什么，然后跟一段话来详细解释；再往后是参数列表、参数格式、返回值格式。
class SpatialDropout2D(Dropout): """Spatial 2D version of Dropout. This version performs the same function as Dropout, however it drops entire 2D feature maps instead of individual elements. If adjacent pixels within feature maps are strongly correlated (as is normally the case in early convolution layers) then regular dropout will not regularize the activations and will otherwise just result in an effective learning rate decrease. In this case, SpatialDropout2D will help promote independence between feature maps and should be used instead. Arguments: rate: float between 0 and 1. Fraction of the input units to drop. data_format: ‘channels_first‘ or ‘channels_last‘. In ‘channels_first‘ mode, the channels dimension (the depth) is at index 1, in ‘channels_last‘ mode is it at index 3. It defaults to the `image_data_format` value found in your Keras config file at `~/.keras/keras.json`. If you never set it, then it will be "channels_last". Input shape: 4D tensor with shape: `(samples, channels, rows, cols)` if data_format=‘channels_first‘ or 4D tensor with shape: `(samples, rows, cols, channels)` if data_format=‘channels_last‘. Output shape: Same as input References: - [Efficient Object Localization Using Convolutional Networks](https://arxiv.org/abs/1411.4280) """ def __init__(self, rate, data_format=None, **kwargs): super(SpatialDropout2D, self).__init__(rate, **kwargs) if data_format is None: data_format = K.image_data_format() if data_format not in {‘channels_last‘, ‘channels_first‘}: raise ValueError(‘data_format must be in ‘ ‘{"channels_last", "channels_first"}‘) self.data_format = data_format self.input_spec = InputSpec(ndim=4)
不写重复代码。
如：
if i_am_rich: money = 100 send(money) else: money = 10 send(money)
都有send函数，可改为:
if i_am_rich: money = 100 else: money = 10 send(money)
代码嵌套过深:
def send(money): if is_server_dead: LOG(‘server dead‘) return else: if is_server_timed_out: LOG(‘server timed out‘) return else: result = get_result_from_server() if result == MONEY_IS_NOT_ENOUGH: LOG(‘you do not have enough money‘) return else: if result == TRANSACTION_SUCCEED: LOG(‘OK‘) return else: LOG(‘something wrong‘) return
可改为:
def send(money): if is_server_dead: LOG(‘server dead‘) return if is_server_timed_out: LOG(‘server timed out‘) return result = get_result_from_server() if result == MONET_IS_NOT_ENOUGH: LOG(‘you do not have enough money‘) return if result == TRANSACTION_SUCCEED: LOG(‘OK‘) return LOG(‘something wrong‘)
以一个简单的二分搜索来举例说明。给定一个非递减整数数组，和一个 target，要求找到数组中最小的一个数 x，可以满足 x*x > target。一旦不存在，则返回 -1。
代码实现如果如下所示，那么可以再以一个函数只干一件事情的原则再优化下。
def solve(arr, target): l, r = 0, len(arr) - 1 ret = -1 while l <= r: m = (l + r) // 2 if arr[m] * arr[m] > target: ret = m r = m - 1 else: l = m + 1 if ret == -1: return -1 else: return arr[ret] print(solve([1, 2, 3, 4, 5, 6], 8)) print(solve([1, 2, 3, 4, 5, 6], 9)) print(solve([1, 2, 3, 4, 5, 6], 0)) print(solve([1, 2, 3, 4, 5, 6], 40))
优化如下：
def comp(x, target): return x * x > target def binary_search(arr, target): l, r = 0, len(arr) - 1 ret = -1 while l <= r: m = (l + r) // 2 if comp(arr[m], target): ret = m r = m - 1 else: l = m + 1 return ret def solve(arr, target): id = binary_search(arr, target) if id != -1: return arr[id] return -1 print(solve([1, 2, 3, 4, 5, 6], 8)) print(solve([1, 2, 3, 4, 5, 6], 9)) print(solve([1, 2, 3, 4, 5, 6], 0)) print(solve([1, 2, 3, 4, 5, 6], 40))
类中属性很多时可以抽出相同特性的单独作为类，如：
class Person: def __init__(self, name, sex, age, job_title, job_description, company_name): self.name = name self.sex = sex self.age = age self.job_title = job_title self.job_description = description self.company_name = company_name
job_title , job_description , company_name 都与工作有关，表达是同一个意义实体，就可以抽出单独作为类:
class Person: def __init__(self, name, sex, age, job_title, job_description, company_name): self.name = name self.sex = sex self.age = age self.job = Job(job_title, job_description, company_name) class Job: def __init__(self, job_title, job_description, company_name): self.job_title = job_title self.job_description = description self.company_name = company_name
极客时间《Python核心技术与实战》专栏
类
极客时间版权所有: https://time.geekbang.org/column/article/104689
标签：related ber 下划线 erro 逗号 全局 des map geek
原文地址：https://www.cnblogs.com/xiaoguanqiu/p/11285511.html
