python学习笔记（基本语法脚本）

　　基本语法1. 简单控制语句
　　字符串推荐用  ＂＂   单引号引用list: List[int] = [1, 2, 3] for elem in list:     if elem > 1:         print(f＂data {elem} > 1＂)  # 这里是format语句，属于语法糖     else:         print(f＂data {elem} < 1＂)  ＂＂＂ data 1 < 1 data 2 > 1 data 3 > 1 ＂＂＂2. 异常x = -1 try:     if x < 0:         raise Exception(＂Sorry, no numbers below zero＂) except Exception as err:     print(＂find err: %s＂ % err) ＂＂＂ find err: Sorry, no numbers below zero ＂＂＂ 3. 推导式(比较晦涩难懂)参考： https://www.cnblogs.com/desireyang/p/12160332.html
　　推导式好处: 效率更高，底层是c执行  1. 列表推导式
　　一共两种形式：(参考: https://zhuanlan.zhihu.com/p/139621170) ， 它主要是输出是列表( list  )[xforxindataifcondition]   这里的含义是data只有满足if条件中的情况才保留 (if)[exp1ifconditionelseexp2forxindata]   ， 这里的含义是data满足if条件时执行exp1 否则 exp2 （if - else）import re  ＂＂＂ 获取所有的数字 ＂＂＂ list = [＂1＂, ＂2＂, ＂3＂, ＂4＂, ＂5＂, ＂a＂, ＂b＂, ＂c＂] print([elem for elem in list if re.match(＂d＂, elem)]) ＂＂＂ [＂1＂, ＂2＂, ＂3＂, ＂4＂, ＂5＂] ＂＂＂  ＂＂＂ 获取所有的字母 ＂＂＂ print([elem for elem in list if re.match(＂[a-z]＂, elem)]) ＂＂＂ [＂a＂, ＂b＂, ＂c＂] ＂＂＂  ＂＂＂ 如果元素是数字则存储，否则则upper ＂＂＂ print([elem if re.match(＂d＂, elem) else elem.upper() for elem in list]) ＂＂＂ [＂1＂, ＂2＂, ＂3＂, ＂4＂, ＂5＂, ＂A＂, ＂B＂, ＂C＂] ＂＂＂
　　最佳实践： 参考(https://github.com/httpie/httpie/blob/master/httpie/core.py#L235) def decode_raw_args(         args: List[Union[str, bytes]],         stdin_encoding: str ) -> List[str]:     ＂＂＂     Convert all bytes args to str     by decoding them using stdin encoding.      ＂＂＂     return [         arg.decode(stdin_encoding)         if type(arg) is bytes else arg         for arg in args     ]   def decode_raw_args_parse(         args: List[Union[str, bytes]],         stdin_encoding: str ) -> List[str]:     ＂＂＂     Convert all bytes args to str     by decoding them using stdin encoding.     不使用推导式     ＂＂＂     result: List[str] = []     for arg in args:         if type(arg) is bytes:             result.append(arg.decode(stdin_encoding))         else:             result.append(arg)     return result   # arg.decode(stdin_encoding) if type(arg) is bytes else arg for arg in args print(decode_raw_args(args=[b＂111＂, b＂222＂], stdin_encoding=＂utf-8＂)) print(decode_raw_args(args=[＂111＂, ＂222＂], stdin_encoding=＂＂)) ＂＂＂ [＂111＂, ＂222＂] [＂111＂, ＂222＂] ＂＂＂  print(decode_raw_args_parse(args=[b＂111＂, b＂222＂], stdin_encoding=＂utf-8＂)) print(decode_raw_args_parse(args=[＂111＂, ＂222＂], stdin_encoding=＂＂)) ＂＂＂ [＂111＂, ＂222＂] [＂111＂, ＂222＂] ＂＂＂2. 字典推导式
　　{key_expr:value_exprforvalueincollectionifcondition}   ，输出是dict  ＂＂＂ { key_expr: value_expr for value in collection if condition }  反转key value，且获取 value 为在set {＂a＂, ＂b＂, ＂c＂}中的元素 ＂＂＂ dict_old = {＂a＂: ＂A＂, ＂b＂: ＂B＂, ＂c＂: ＂C＂, ＂d＂: ＂D＂} print({dict_old[value]: value for value in dict_old if value in {＂a＂, ＂b＂, ＂c＂}}) ＂＂＂ {＂A＂: ＂a＂, ＂B＂: ＂b＂, ＂C＂: ＂c＂} ＂＂＂  print({key: value for value, key in dict_old.items() if value in {＂a＂, ＂b＂, ＂c＂}}) ＂＂＂ {＂A＂: ＂a＂, ＂B＂: ＂b＂, ＂C＂: ＂c＂} ＂＂＂3. 集合推导式
　　表达式: {exprforvalueincollectionifcondition}  {exp1ifconditionelseexp2forxindata}  输出是set
　　其实就是上面列表推导式 []   换成{}   ，输出由list   变成了set  4. for 循环 迭代器import os from collections.abc import Iterable  with open(＂text.log＂, ＂wt＂) as file:     file.truncate()     file.writelines(＂line 1＂ + os.linesep)     file.writelines(＂line 2＂ + os.linesep)     file.writelines(＂line 3＂ + os.linesep)     pass  with open(＂text.log＂, ＂rt＂) as file:     for line in file:         print(＂type: {type}, isinstance: {isinstance}, line: {line}＂.format(type=type(file),                                                                             isinstance=isinstance(file, Iterable),                                                                             line=line))     pass  ＂＂＂ type: , isinstance: True, line: line 1  type: , isinstance: True, line: line 2  type: , isinstance: True, line: line 3 ＂＂＂
　　这里面 _io.TextIOWrapper   实现了 __next__()   方法
　　比如我们自己实现一个可迭代的对象 下面可以看到我使用了类型申明  List[str]   其实这个python运行时并不会检测，需要工具进行检测！
　　变量默认都是  Any   类型 ，具体可以看 https://docs.python.org/zh-cn/3/library/typing.htmlfrom typing import List  class Items(object):     def __init__(self, list: List[str]):         self.list = list         self.index = 0      def __next__(self, *args, **kwargs):         ＂＂＂         next，没有抛出StopIteration         ＂＂＂         if self.index >= len(self.list):             raise StopIteration         result = self.list[self.index]         self.index = self.index + 1         return result      def __iter__(self, *args, **kwargs):         ＂＂＂         返回一个迭代器         ＂＂＂         return self   data = Items([＂1＂, ＂2＂, ＂3＂])  for x in data:     print(x) ＂＂＂ 1 2 3 ＂＂＂5. 包管理from ..a import foo  # 上级目录 from .a import foo_a  # 当前目录  import sys  # 引用源码或者lib from copy import deepcopy  # 引用源码或者lib  from pygments.formatters.terminal import TerminalFormatter  # 引用 lib.lib.file  import demo.utils.a   def c_foo():     demo.utils.a.foo_a()     TerminalFormatter()     deepcopy()     print(sys.api_version)   def b_foo():     foo()基本数据类型1. 定义方式mylist:list[str]=[＂apple＂,＂banana＂,＂cherry＂]  mylist=[＂apple＂,＂banana＂,＂cherry＂]
　　Text Type:
　　str
　　Numeric Types:
　　int  ,float  ,complex
　　Sequence Types:
　　list  ,tuple  ,range
　　Mapping Type:
　　dict
　　Set Types:
　　set  ,frozenset
　　Boolean Type:
　　bool
　　Binary Types:
　　bytes  ,bytearray  ,memoryview  2. 数字基本类型x = 1  # int y = 1.1  # float z = 1j  # 复数(complex) a = complex(1, 2)  # 复数(complex) print(type(x)) print(type(y)) print(type(z)) print(z.imag, z.real) print(type(a)) print(a.imag, a.real) ＂＂＂    1.0 0.0  2.0 1.0 ＂＂＂3. 字符串str = ＂hello＂ print(str) print(str[0:]) print(str[:5]) print(str[:-1]) print(str[0:5]) print(str[0:5:1]) print(str[0:5:2]) ＂＂＂ hello hello hello hell hello hello hlo ＂＂＂  # format print(＂My name is {} and age is {}＂.format(＂tom＂, 18)) ＂＂＂ My name is tom and age is 18 ＂＂＂  quantity = 3 itemno = 567 price = 49.95 myorder = ＂I want to pay {2} dollars for {0} pieces of item {1}.＂ print(myorder.format(quantity, itemno, price)) ＂＂＂ I want to pay 49.95 dollars for 3 pieces of item 567. ＂＂＂  # func str = ＂hello world! ＂ print(str.upper()) print(str.lower()) print(str.strip()) print(str + ＂ ...＂) ＂＂＂ HELLO WORLD!  hello world!  hello world! hello world!  ... ＂＂＂  # format myorder = ＂I have a {carname}, it is a {model}.＂ print(myorder.format(carname=＂Ford＂, model=＂Mustang＂)) ＂＂＂ I have a Ford, it is a Mustang. ＂＂＂4. lambda
　　其实就是一个func def add(num):     return lambda x: x + num   print(add(10)(10)) ＂＂＂ 20 ＂＂＂
　　lanbda 例子2 import json  class Obj:     def __init__(self):         self.name = ＂tom＂         self.age = 1   print(json.dumps(Obj(), default=lambda obj: obj.__dict__)) ＂＂＂ {＂name＂: ＂tom＂, ＂age＂: 1} ＂＂＂集合
　　list  ,tuple  ,range  ,dict  ,set  ,frozenset  list , 例如: mylist=[＂apple＂,＂banana＂,＂cherry＂]  tuple 是特殊的数组，就是不能改变， 例如 mytuple=(＂apple＂,＂banana＂,＂cherry＂)  range 可以理解是个迭代器, 例如： dict 就是个map， 例如： thisdict={＂brand＂:＂Ford＂,＂model＂:＂Mustang＂,＂year＂:1964}  set 就是个去重复的list , 例如： myset={＂apple＂,＂banana＂,＂cherry＂}  1. listmylist = [＂apple＂, ＂banana＂, ＂cherry＂]  # 切片 print(mylist[0]) print(mylist[2]) print(mylist[-1]) print(mylist[0:3:2]) ＂＂＂ apple cherry cherry [＂apple＂, ＂cherry＂] ＂＂＂  # 基本操作 mylist.append(＂orange＂) print(mylist) ＂＂＂ [＂apple＂, ＂banana＂, ＂cherry＂, ＂orange＂] ＂＂＂  mylist.insert(0, ＂mango＂) print(mylist) ＂＂＂ [＂mango＂, ＂apple＂, ＂banana＂, ＂cherry＂, ＂orange＂] ＂＂＂  # 循环 for x in mylist:     print(x)  ＂＂＂ apple banana cherry orange ＂＂＂  for index in range(len(mylist)):     print(＂index: %d＂ % index) ＂＂＂ index: 0 index: 1 index: 2 index: 3 index: 4 ＂＂＂  if ＂apple＂ in mylist:     print(＂success!＂)  ＂＂＂ success! ＂＂＂  # [执行表达式(也就是for循环中的，如果有if则是if中执行的), for item in list 条件表达式] new_list = [elem.upper() for elem in mylist if ＂a＂ in elem]  # contains ＂a＂ char elem str print(new_list) ＂＂＂ [＂MANGO＂, ＂APPLE＂, ＂BANANA＂, ＂ORANGE＂] ＂＂＂  newList = [] for elem in mylist:     if ＂a＂ in elem:         newList.append(elem.upper()) print(newList) ＂＂＂ [＂MANGO＂, ＂APPLE＂, ＂BANANA＂, ＂ORANGE＂] ＂＂＂2. mapthisdict = {＂brand＂: ＂Ford＂, ＂model＂: ＂Mustang＂, ＂year＂: 1964}  for key, value in thisdict.items():     print(＂key: {}, value: {}＂.format(key, value))  ＂＂＂ key: brand, value: Ford key: model, value: Mustang key: year, value: 1964 ＂＂＂  for key in thisdict:     print(＂key: {}, value: {}＂.format(key, thisdict[key])) ＂＂＂ key: brand, value: Ford key: model, value: Mustang key: year, value: 1964 ＂＂＂3. range# range 会生成一个迭代器，(start,end,sep) ， 左闭右开 for x in range(6):  # [0,1,2,3,4,5]     print(＂x is %d＂ % x) ＂＂＂ x is 0 x is 1 x is 2 x is 3 x is 4 x is 5 ＂＂＂  for x in range(2, 6):     print(＂x is %d＂ % x)  ＂＂＂ x is 2 x is 3 x is 4 x is 5 ＂＂＂  for x in range(1, 6, 2):     print(＂x is %d＂ % x) ＂＂＂ x is 1 x is 3 x is 5 ＂＂＂方法1. 定义一个空方法def func_1():     pass  # 空方法必须申明pass   func_1()2. 参数# name 为必须添的参数，不然为空会报错 # age 为默认参数 # agrs 为可变参数 # kwargs 为 k v 参数 def func_1(name, age=1, *args, **kwargs):     print(＂name: %s＂ % name)     print(＂age: %d＂ % age)     print(＂len(args): {}, type: {}＂.format(len(args), type(args)))     for value in args:         print(＂args value: {}＂.format(value))      print(＂len(kwargs): {}, type: {}＂.format(len(kwargs), type(kwargs)))     for key, value in kwargs.items():         print(＂kwargs key: {}, value: {}＂.format(key, value))   func_1(name=＂tom＂, age=10, args=＂1＂, kwargs=＂2＂) ＂＂＂ name: tom age: 10 len(args): 0 len(kwargs): 0, type:  len(kwargs): 2, type:  kwargs key: args, value: 1 kwargs key: kwargs, value: 2 ＂＂＂  # 这里注意由于dict所以不能申明kv func_1(＂tom＂, 10, ＂1＂, ＂2＂, args=＂1＂, kwargs=＂2＂) ＂＂＂ name: tom age: 10 len(args): 2, type:  args value: 1 args value: 2 len(kwargs): 2, type:  kwargs key: args, value: 1 kwargs key: kwargs, value: 2 ＂＂＂3. 类型
　　申明输入输出类型  from typing import List, Union def decode_raw_args(     args: List[Union[str, bytes]],     stdin_encoding: str ) -> List[str]:     ＂＂＂     Convert all bytes args to str     by decoding them using stdin encoding.      ＂＂＂     return [         arg.decode(stdin_encoding)         if type(arg) is bytes else arg         for arg in args     ]类1. 定义类和方法# 如果没有父类继承，这里选择 object，比较规范 class Person(object):     # gender none, male or female     gender = ＂none＂      # 构造器     def __init__(self, name, age):         self.name = name         self.age = age      def my_name(self):         return self.name   p = Person(name=＂tome＂, age=1) print(p.my_name())2. 类型的继承import json   class Person(object):     # gender none, male or female     gender = ＂none＂      # 构造器     def __init__(self, name, age):         self.name = name         self.age = age      def my_name(self):         return self.name   p = Person(name=＂tome＂, age=1) print(p.my_name())   class Mail(Person):     def __init__(self, name, age):         super(Mail, self).__init__(name, age)         self.gender = ＂mail＂      def my_name(self):         return self.name + ＂_mail＂   p = Mail(name=＂tome＂, age=1) print(json.dumps(p, default=lambda obj: obj.__dict__)) print(p.my_name())3. 类__new__函数
　　主要是  __init__  执行前会调用#!/usr/bin/python  import json   class Person(object):     def __new__(cls, *args, **kwargs):         instance = object.__new__(cls)         instance.job = ＂it＂         return instance      # construct     def __init__(self, name, age):         self.name = name         self.age = age      def to_json(self):         return json.dumps(self, default=lambda obj: obj.__dict__)   p = Person(name=＂tome＂, age=1) print(p.to_json()) # {＂age＂: 1, ＂job＂: ＂it＂, ＂name＂: ＂tome＂}其他用法技巧1. 断言if type(1) is int:     print(＂args is int＂)     ...  # 等效 pass ＂＂＂ args is int ＂＂＂2. 测试<<<
　　可以参考文件: https://segmentfault.com/q/1010000010389542 , 属于 doctest  def humanize_bytes(n, precision=2):     # Author: Doug Latornell     # Licence: MIT     # URL: https://code.activestate.com/recipes/577081/     ＂＂＂Return a humanized string representation of a number of bytes.      >>> humanize_bytes(1)     ＂1 B＂     >>> humanize_bytes(1024, precision=1)     ＂1.0 kB＂     >>> humanize_bytes(1024 * 123, precision=1)     ＂123.0 kB＂     >>> humanize_bytes(1024 * 12342, precision=1)     ＂12.1 MB＂     >>> humanize_bytes(1024 * 12342, precision=2)     ＂12.05 MB＂     >>> humanize_bytes(1024 * 1234, precision=2)     ＂1.21 MB＂     >>> humanize_bytes(1024 * 1234 * 1111, precision=2)     ＂1.31 GB＂     >>> humanize_bytes(1024 * 1234 * 1111, precision=1)     ＂1.3 GB＂      ＂＂＂     abbrevs = [         (1 << 50, ＂PB＂),         (1 << 40, ＂TB＂),         (1 << 30, ＂GB＂),         (1 << 20, ＂MB＂),         (1 << 10, ＂kB＂),         (1, ＂B＂)     ]      if n == 1:         return ＂1 B＂      for factor, suffix in abbrevs:         if n >= factor:             break      # noinspection PyUnboundLocalVariable     return f＂{n / factor:.{precision}f} {suffix}＂3. yield参考: https://zhuanlan.zhihu.com/p/268605982
　　其实类似于程序的断电，比如程序运行到那里其实是返回一个生成器，然后当你下一步是才会执行，比较节省内存 from typing import List   def new(size: int = 1024 * 1024):     yield new_data(size)   def new_data(size: int) -> List[int]:     return [0] * size   data = new() print(type(data)) print(len(next(data)))  # 只能执行一次 next不然报错 ＂＂＂  1048576 ＂＂＂脚本base64输出echo ＂aGVsbG8gcHl0aG9uCg==＂ | python -c ＂import sys,base64; print(sys.stdin.read())＂  ->  echo ＂aGVsbG8gcHl0aG9uCg==＂ | python -c ＂import sys,base64; print(base64.b64decode(sys.stdin.read()))＂ -> stdout: b＂hello python ＂文件操作r   ,w  ,x   ,a  四种类型(a: append, w=truncate+create, x=truncate+create if not exit)b  ,t   文件类型
　　第一列可以和第二列文件类型组合，第一列不允许并存 import os   with open(＂file.log＂, ＂w＂) as file:     for x in range(0, 100):         file.write(＂hello world＂+os.linesep)   with open(＂file.log＂,＂r＂) as file:     for line in file.readlines():         print(line)jsonimport json  print(json.dumps({＂k1＂: ＂v1＂, ＂k2＂: [1, 2, 3]})) print(json.loads(＂{＂k1＂: ＂v1＂, ＂k2＂: [1, 2, 3]}＂))
　　如果是class，需要继承 JSONEncoder和JSONDecoder实现子类   ，或者import json, datetime  class Demo(object):     def __init__(self, name: str, age: int, birthday: datetime.date):         self.name = name         self.agw = age         self.birthday = birthday      def to_json(self, _):         return {＂name＂: self.name, ＂age＂: self.agw, ＂birthday＂: self.birthday.strftime(＂%Y-%m-%d＂)}   data = Demo(＂tom＂, 18, datetime.date(2001, 1, 1)) print(json.dumps(data, default=data.to_json))typing (申明类型)
　　官方文档： https://docs.python.org/zh-cn/3/library/typing.html
　　可以参考这篇文章： https://sikasjc.github.io/2018/07/14/type-hint-in-python/
　　对于喜欢静态类型的语言，我觉得是非常nice的 from typing import Dict, List   def test(data: Dict[str, str]) -> List[str]:     return [x for x in data]   print(test({＂k1＂: ＂v1＂, ＂k2＂: ＂v2＂}))