基础部分

map,reduce,filter,sort,推导式，匿名函数lambda , 协程，异步io，上下文管理

自定义字符串转数字方法一不使用reduce

import re

def str2int(s):

    if not re.match(r'^\d+$',s):

        raise ValueError('请检查数字格式是否正确')

    else:

        digital={'0':0,"1":1,"2":2,"3":3,"4":4,"5":5,"6":6,"7":7,"8":8,"9":9}

        int_list = list(map(lambda k:digital[k] or 0,s))

        sum=0

        for i,v in enumerate(int_list):

            sum+=v*(10**(len(int_list)-i-1))

    return sum

print(str2int('456'))

自定义字符串转数字方法二使用reduce

from functools import reduce

import re

def str2int(s):

    if not re.match(r'^\d+$',s):

        raise ValueError('请检查数字格式是否正确')

    else:

        digital={'0':0,"1":1,"2":2,"3":3,"4":4,"5":5,"6":6,"7":7,"8":8,"9":9}

        int_list = list(map(lambda k:digital[k] or 0,s))

        return reduce(lambda a,b:a+b,[v*(10**(len(int_list)-i-1))for i,v in enumerate(int_list)])

print(str2int('456'))

import re

from functools import reduce

def digital(c):

    return {'0':0,'1':1,'2':2,'3':3,'4':4,'5':5,'6':6,'7':7,'8':8,'9':9}.get(c,0)

def str2int(s):

    if not re.match(r'^\d+$',s):

        raise TypeError('类型不是数字!')

    return reduce(lambda x,y:x+y,[v*(10**i) for i,v in enumerate(list(map(lambda c:digital(c),s))[::-1])])

print('%s-->%d' %(type(str2int('123')),str2int('123')))

assert isinstance(str2int('123'),int)

<class 'int'>-->123

让人眼前一亮的匿名函数

>>> for i in range(10):

...     print(list(map(lambda x:x(i),[lambda x:x+x,lambda x:x**2])))

列表推导式与 filter 相互等价

[i for i in range(30) if i%2==0]

list(filter(lambda x:x%2==0,range(30)))

# 0,1,2,3,4,5...

# 累加

accumulate = lambda x:x+fib(x-1) if x!=0 else 0

accumulate(3)

# 0,1,2,3,4,5...

# 阶乘

factorical = lambda x:x*factorical(x-1) if x!=1 else 1

factorical(6)

# 斐波拉契数列

# 0,1,1,2,3,5...

fib = lambda x: 1 if x==1 or x==2 else fib(x-1)+fib(x-2)

fib(6)

#生成器斐波拉契

def fib(x):

    n=0

    a,b = 0,1

    while n<x:

        b,a = a,a+b

        yield a

        n+=1

for i in fib(6):

    print(i,end=',')

#协程写斐波拉契

>>> def fib():

...     a,b = 0,1

...     r = 'start...'

...     yield r

...     while True:

...         yield b

...         a,b = b,a+b

...

>>> f = fib()

>>> f.send(None)

'start...'

>>> for i in range(1,10):

...     print('index {}-->{}'.format(i,f.send(i)))

...

index 1-->1

index 2-->1

index 3-->2

index 4-->3

index 5-->5

index 6-->8

index 7-->13

index 8-->21

index 9-->34

>>> f.close()

异步 io

>>> import asyncio

>>> @asyncio.coroutine

... def say(greet_str):

...     print(greet_str)

...     r = yield from asyncio.sleep(1)

...     print(greet_str,'again')

...     print('r:{}'.format(r))

...

>>> loop = asyncio.get_event_loop()

>>> tasks = [say('hello world!'),say('hello frank')]

>>> loop.run_until_complete(asyncio.wait(tasks))

hello frank

hello world!

hello frank again

r:None

hello world! again

r:None

({<Task finished coro=<say() done, defined at <stdin>:1> result=None>, <Task finished coro=<say() done, defined at <stdin>:1> result=None>}, set())

>>> loop.close()

3.5 及以后

把@asyncio.coroutine替换为async；

把yield from替换为await。

通过async定义的协程被称为原生协程跟

通过@asyncio.coroutine定义的协程函数被称为基于生成器的协程

两者不是一个概念

查找文件名包含某字符串的文件并输出器文件名

import os

def findstr_in_file(path):

    for child in os.listdir(path):

        qualified_child = os.path.join(path,child)

        if os.path.isdir(qualified_child):

                tmp = findstr_in_file(qualified_child)

                for item in tmp:

                    yield item

        else:

            yield qualified_child

for name in findstr_in_file('.'):

    if 'diabetes' in name:

        print(name)

os os.path 学习

#

os.environ.get('PATH')

if 'Linux' in  os.name:

    os.system('clear')

elif 'nt' in os.name:

    os.system('cls')

# 查看当前目录的绝对路径:

os.path.abspath('.')

os.path.join('/Users/michael', 'testdir')

os.mkdir('/Users/michael/testdir')

# 删掉一个目录:

os.rmdir('/Users/michael/testdir')

os.path.split('/Users/michael/testdir/demo.txt')

os.path.splitext('/Users/michael/testdir/demo.txt')

os.rename('text.txt','test.py')

os.remove('test.py')

[x for x in os.listdir('.') if os.path.isdir(x)] # 查出当前目录下子目录

[x for x in os.listdir('.') if os.path.isfile(x) and os.path.splitext(x)[1]=='.py'] # 查出当前目录下 py 文件

序列化与反序列化

import json

class Student(object):

    def __init__(self,name,age,score):

        self._name = name

        self._age = age

        self._score = score

    def __repr__(self):

        return 'Student(name={},age={},score={})'.format(self._name,self._age,self._score)

    def __str__(self):

        return self.__repr__()

    def student2dict(self,std):

        return {'name':std._name

                ,'age':std._age

                ,'score':std._score}

s = Student('frank','18',100)

json.dumps(s,default=s.student2dict)

json.dumps(s,default=lambda obj:obj.__dict__)

print(eval(s.__repr__()))

json_str = '{"name":"frank","age":18,"score":100}'

def dict2student(d):

    return Student(d['name'],d['age'],d['score'])

print(json.loads(json_str,object_hook=dict2student))

另一种形式的 迭代器，注意字符串也是序列

a = 'baidu'

try:

    g = iter(a)

    while True:

        print(next(g))

except StopIteration as stopIter:

    print(stopIter)

    print('no more!')

map filter lambda 综合点运用

from functools import reduce

import re

exp = '99 + 88 + 7.6 ='

reduce(lambda x,y:x+y,list(map(int,filter(lambda x: x if x else None,map(lambda s:s.replace('.','').strip(),re.split(r'[\+|=]',exp))))))

sorted 排序

>>> sorted(d.items(),key=lambda t:t[1])

[('g', 20), ('f', 21), ('e', 22), ('d', 23), ('c', 24), ('b', 25), ('a', 26)]

>>> dict(sorted(d.items(),key=lambda t:t[1]))

{'g': 20, 'f': 21, 'e': 22, 'd': 23, 'c': 24, 'b': 25, 'a': 26}

>>> {}.fromkeys([1,2,2,3,1,4,5])

{1: None, 2: None, 3: None, 4: None, 5: None}

>>> set([1,2,3,1,2,1,4,5])

{1, 2, 3, 4, 5}

>>> import os

>>> with open(os.path.join(baseDir,'test.txt')) as f:

...     for line in f:

...         print(line)

自己写冒泡+快速排序

import time

from functools import wraps

def time_count(func):

    @wraps(func)

    def execute_func(*args,**kw):

        t1 = time.time()

        result = func(*args,**kw)

        t2 = time.time()

        print('共花费:{} 秒'.format(t2-t1))

        return result

    return execute_func

l = [9,8,7,6,5,4,3,2,1]

@time_count

def bubble_sort(l):

    for i in range(len(l)):

        for j in range(len(l)-i-1):

            if l[j]>l[j+1]:

                l[j],l[j+1] = l[j+1],l[j]

    return l

bubble_sort(l)

@time_count

def quick_sort(array,low=0,high=None):

    high = len(array)-1 if high is None else high

    if low>=high:

        return

    l,r = low,high

    base_value = array[l]

    while l<r:

        while l<r and array[r]>=base_value:

            r-=1

        array[l] = array[r]

        while l<r and array[r]<base_value:

            l+=1

        array[r] = array[l]

        array[l] = base_value

        quick_sort(array,low,l)

        quick_sort(array,l+1,high)

    return array

l = [9,8,7,6,5,4,3,2,1]

quick_sort(l)

较为奢华版

from functools import wraps

from time import time

def time_count(func):

    @wraps(func)

    def wrapper_func(*args,**kw):

        start = time()

        result = func(*args,**kw)

        end = time()

        print('{} cost {} seconds in total...'.format(func.__name__,(end-start)))

        return result

    return wrapper_func

@time_count

def quick_sort(array,low=0,high=None):

    high = len(array)-1 if high is None else high

    if low>=high:

        return

    l,r = low,high

    base = array[l]

    while l<r:

        while all([l<r,base<=array[r]]):

            r-=1

        array[l] = array[r]

        while all([l<r,base>=array[l]]):

            l+=1

        array[r] = array[l]

        array[l] = base

        quick_sort(array,low,l-1)

        quick_sort(array,l+1,high)

    return array

array = [9,8,7,6,5,4,3,2,1]

quick_sort(array)

from functools import reduce

import re

out_str = """quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 2.384185791015625e-06 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 1.6689300537109375e-06 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 0.0007488727569580078 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 0.0014128684997558594 seconds in total...

quick_sort cost 0.002044200897216797 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 0.0027604103088378906 seconds in total...

quick_sort cost 0.003480195999145508 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 0.003975629806518555 seconds in total...

quick_sort cost 0.005151271820068359 seconds in total...

quick_sort cost 1.9073486328125e-06 seconds in total...

quick_sort cost 0.005714893341064453 seconds in total..."""

reduce(lambda x,y:float(x)+float(y),[item.strip() for item in re.findall(r'(\d.*)(?:second)',out_str)])

一句话简单版

quick_sort = lambda array: array if len(array) <= 1 else quick_sort([item for item in array[1:] if item <= array[0]]) + [array[0]] + quick_sort([item for item in array[1:] if item > array[0]])

l = [9,8,7,6,5,4,3,2,1]

quick_sort(l)

# 等价于：

def quick_sort2(arr):

    if len(arr) <= 1:

        return arr

    else:

        base = arr[0]

        left = [item for item in arr[1:] if item<base]

        right = [item for item in arr[1:] if item>=base]

        return quick_sort2(left)+[base]+quick_sort2(right)

l = [9,8,7,6,5,4,3,2,1]

quick_sort2(l)

比较精简版水仙花数(原创)

from functools import reduce

[x for x in range(100,1000) if reduce(lambda x,y:x+y,map(lambda i:int(i)**3,str(x))) == x]

杨辉三角之前准备，先打印一下99乘法表

>>> def g_mul():

...     for i in range(1,10):

...         l = []

...         for j in range(1,i+1):

...             l.extend('{}*{}={}\t'.format(j,i,j*i))

...         yield l

...

>>> for i in g_mul():

...     print(''.join(i))

一句话版99乘法表

print ('\n'.join([' '.join(['%s*%s=%-2s' % (y,x,x*y) for y in range(1,x+1)]) for x in range(1,10)]))

print('\n'.join([ '\t'.join([str(j)+'*'+str(i)+'='+str(j*i) for j in range(1,i+1)]) for i in range(1,10)]))

print('\n'.join([ '\t'.join(['{}*{}={}'.format(j,i,j*i) for j in range(1,i+1)]) for i in range(1,10)]))

杨辉三角

>>> def triangle(x):

...     l=[1]

...     while x>0:

...         yield l

...         l.append(0)

...         l = [l[i-1]+l[i] for i in range(len(l))]

...         x-=1

...

>>> for i in triangle(10):

...     print(i)

三元运算符的另一种写法

>>> a = 1

>>> b = (2,3)[a==1]

>>> b

3

>>> b = (2,3)[a==13]

>>> b

2

注意

reload(sys)

sys.setdefaultencoding("utf-8")12

在Python 3.x中不好使了 提示 name ‘reload’ is not defined

在3.x中已经被毙掉了被替换为

import importlib

importlib.reload(sys)

上下文管理

#方式一：

# 第1个参数保存异常类型；

# 第2个参数保存异常对象的值；

# 第3个参数保存异常的traceback信息。

class OpenObj(object):

    def __init__(self,filename,model):

        self.fp = open(filename,model)

    def __enter__(self):

        return self.fp

    def __exit__(self,exc_type,exc_val,exc_traceback):

        self.fp.close()

with OpenObj('./test.py','r') as f:

    for line in f:

        print(line)

#方式二：

from contextlib import contextmanager

@contextmanager

def make_open_context(filename,model):

    fp = open(filename,model)

    try:

        yield fp

    finally:

        fp.close()

with make_open_context('./test.py','r') as f:

    for line in f:

        print(line)

# 扩展 mysql 数据库游标

from pymysql import connect

class DBHelper:

    def __init__(self):

        self.conn = connect(host='localhost', port=3306, user='user', password='password', database='database', charset='utf8')

        self.csr = self.conn.cursor()

    def __enter__(self):

        return self.csr

    def __exit__(self, exc_type, exc_val, exc_tb):

        self.csr.close()

        self.conn.close()

with DBHelper() as csr:

    sql = """select * from table;"""

    csr.execute(sql)

    all_datas = csr.fetchall()

for item in all_datas:

    print(item)

@contextmanager

def conn_db():

    conn = connect(host='localhost', port=3306, user='user', password='password', database='database', charset='utf8')

    csr = conn.cursor()

    yield csr

    csr.close()

    conn.close()

with conn_db() as csr:

    sql = """select * from table"""

    csr.execute(sql)

    all_datas = csr.fetchall()

for item in all_datas:

    print(item)

深度遍历与宽度遍历

class Node(object):

    def __init__(self,sName):

        self._lChildren = []

        self.sName = sName

    def __repr__(self):

        return "<Node '{}'>".format(self.sName)

    def append(self,*args,**kwargs):

        self._lChildren.append(*args,**kwargs)

    def print_all_1(self):

        print(self)

        for oChild in self._lChildren:

            oChild.print_all_1()

    def print_all_2(self):

        def gen(o):

            lAll = [o,]

            while lAll:

                oNext = lAll.pop(0)

                lAll.extend(oNext._lChildren)

                yield oNext

        for oNode in gen(self):

            print(oNode)

oRoot = Node("root")

oChild1 = Node("child1")

oChild2 = Node("child2")

oChild3 = Node("child3")

oChild4 = Node("child4")

oChild5 = Node("child5")

oChild6 = Node("child6")

oChild7 = Node("child7")

oChild8 = Node("child8")

oChild9 = Node("child9")

oChild10 = Node("child10")

oRoot.append(oChild1)

oRoot.append(oChild2)

oRoot.append(oChild3)

oChild1.append(oChild4)

oChild1.append(oChild5)

oChild2.append(oChild6)

oChild4.append(oChild7)

oChild3.append(oChild8)

oChild3.append(oChild9)

oChild6.append(oChild10)

# 说明下面代码的输出结果

oRoot.print_all_1()

oRoot.print_all_2()

验证下parquet 与 csv 读写效率

import psycopg2

from contextlib import contextmanager

import pandas as pd

import numpy as np

import time

from functools import wraps

@contextmanager

def get_cur(**kw):

        conn = psycopg2.connect(**kw)

        crs = conn.cursor()

        yield crs

        crs.close

        conn.close()

field_list = ['person_id',xxx

                      'survival_36m', 'survival_60m', 'survival_120m', 'survival_months', 'recurrence_months',

                      'recurrence_site']

kw = dict(dbname='demodb'

     , host='devxxxom'

     , port=5439

     , user='user'

     , password='password')

def get_frame():

    with get_cur(**kw) as crs:

        sql = 'select "'+'","'.join(field_list)+'" from ml_sample limit 10000'

        print(sql)

        crs.execute(sql)

        df = pd.DataFrame(list(crs.fetchall()))

        df.columns = field_list

    return df

def save_file(df,filename,file_ex):

    if file_ex.strip()=='parquet':

#         from os import path

#         if path.exits(filename):

#             os.remove(filename)

        df.to_parquet(filename, compression='gzip')

    elif file_ex.strip() == 'csv':

        df.to_csv(filename)

    else:

        print('not implement~...')

#

#     pd.read_parquet('df.parquet.gzip')

def magnify_file(src,target,tn):

    for i in range(tn):

        print(src)

        with open(src,'rb') as fr:

            with open(target,'ab') as fw:

                for blk in fr:

                    fw.write(blk)

def time_count(func):

    @wraps(func)

    def func_wrapper(*args,**kw):

        start = time.time()

        result = func(*args,**kw)

        end = time.time()

        print('{} cost {} seconds...'.format(func.__name__,(end-start)))

        return result

    return func_wrapper

@time_count

def parquet_test(tn):

    df = get_frame()

    parquet_file = 'dataset.gzip'

    save_file(df,parquet_file,'parquet')

    from os import path

    parquet_file_magnif,_= path.splitext(parquet_file)

    magnify_file(parquet_file,parquet_file_magnif+'_magnif.gzip',tn)

    df = pd.read_parquet(parquet_file_magnif+'_magnif.gzip')

    df.head()

@time_count

def csv_test(tn):

    df = get_frame()

    csv_file = 'dataset.csv'

    save_file(df,csv_file,'csv')

    from os import path

    csv_file_magnif,_ = path.splitext(csv_file)

    print(csv_file_magnif)

    magnify_file(csv_file,csv_file_magnif+'_magnif.csv',tn)

    print('.....herer ....')

    df = pd.read_csv(csv_file_magnif+'_magnif.csv')

    df.head()

csv_test(10)

parquet_test(10)

csv_test(100)

parquet_test(100)

回文数的n种写法

def palindrome(s):

    return s == s[::-1]

def palindrome2(s):

    flag = True

    l,r = 0,len(s)-1

    while l<=r:

        if s[l] != s[r]:

            flag = False

        l+=1

        r-=1

    return flag

# 存在闭包问题，下面这种是错误的

def palindrome3(s,low=0,high=None):

    flag = True

    high = len(s)-1 if high is None else high

    l,r  = low, high

    if l<r:

        if s[l] == s[r]:

            palindrome3(s,l+1,r-1)

        else:

            flag = False

    return flag

palindrome3('aba')

True

# 解决了闭包问题

def palindrome3(s,low=0,high=None):

    global flag

    high = len(s)-1 if high is None else high

    l,r  = low, high

    print(l,'--',r)

    if l<r:

        if s[l] == s[r]:

            flag = True

            palindrome3(s,l+1,r-1)

        else:

            flag = False

            print(flag)

    return flag

argparse 模块用来做命令行工具挺方便

import argparse

import time

if __name__ == '__main__':

    start_time = time.time()

    #PATIENT SIMILARITY REQUEST INPUT

    parser = argparse.ArgumentParser(description="input to experiments")

    parser.add_argument('--organization_id', type=int, help='org id for filter')

    parser.add_argument('--save_cluster', type=int, help='if save cluster, please provide org_model_id')

    parser.add_argument('--threshold', type=float, help='initial threshold ')

    parser.add_argument('--bin', type=float, help='degree of freedom to do chi-squared test')

    parser.add_argument('--list_of_features', type=str, nargs='*',help='features could be demographic, tumor-related and gene related')

    parser.add_argument('--organization_model_id', type=int, help='organization_model_id from ml_organization_model table')

    args = parser.parse_args()

    print(args.list_of_features)

    end_time = time.time()

    print('cost {} s in total...'.format(end_time-start_time))

实用代码片段

# 屏蔽标准输出流标准错误流

def shield_print(func):

    @wraps(func)

    def main_func(*args,**kw):

        with open('outprint.log','w') as fw:

            old_stdout = sys.stdout

            old_stderr = sys.stderr

            sys.stdout = sys.stderr = fw

            result = func(*args,**kw)

            sys.stdout = old_stdout

            sys.stderr = old_stderr

            return result

    return main_func

自定义 精度条显示

import sys,time

def progress_bar(num,total):

    rate = float(num)/total

    rate_num = int(rate*100)

    out = '\r[{}{}] 已完成 {} %'.format('*'*rate_num,' '*(100-rate_num),rate_num)

    stdout = sys.stdout

    stdout.write(out)

    stdout.flush()

def test_progress_bar(start,end):

    i = start

    for i in range(end):

        time.sleep(0.1)

        progress_bar(i+1,end)

if __name__ == '__main__':

    start = 0

    end = 200

    test_progress_bar(start,end)

类似于 log4j

# -*- coding: utf-8 -*-

"""

 %(levelno)s:         打印日志级别的数值

 %(levelname)s:    打印日志级别名称

 %(pathname)s:    打印当前执行程序的路径，其实就是sys.argv[0]

 %(filename)s:      打印当前执行程序名

 %(funcName)s:    打印日志的当前函数

 %(lineno)d:         打印日志的当前行号

 %(asctime)s:      打印日志的时间

 %(thread)d:        打印线程ID

 %(threadName)s: 打印线程名称

 %(process)d:      打印进程ID

 %(message)s:    打印日志信息 

%y 两位数的年份表示（00-99）

%Y 四位数的年份表示（000-9999）

%m 月份（01-12）

%d 月内中的一天（0-31）

%H 24小时制小时数（0-23）

%I 12小时制小时数（01-12）

%M 分钟数（00=59）

%S 秒（00-59）

%a 本地简化星期名称

%A 本地完整星期名称

%b 本地简化的月份名称

%B 本地完整的月份名称

%c 本地相应的日期表示和时间表示

%j 年内的一天（001-366）

%p 本地A.M.或P.M.的等价符

%U 一年中的星期数（00-53）星期天为星期的开始

%w 星期（0-6），星期天为星期的开始

%W 一年中的星期数（00-53）星期一为星期的开始

%x 本地相应的日期表示

%X 本地相应的时间表示

%Z 当前时区的名称

%% %号本身

"""

import logging

import datetime

def getLog(path='.'):  

    dt=datetime.datetime.now()

    dtstr=dt.strftime('%Y-%m-%d')

    #dtstr=dt.strftime('%Y-%m-%d_%H_%M_%S')

    #创建一个logger实例

    logger = logging.getLogger("mllogger")

    logging.basicConfig(filemode='wa')

    hds=logger.handlers

    for h in hds:

        logger.removeHandler(h)

    logger.setLevel(logging.INFO)

    #创  建一个handler,用于写入日志文件，handler可以把日志内容写到不同的地方

    logName ="%s/%s.ml.log"%(path,dtstr)

    fh = logging.FileHandler(logName)

    fh.setLevel(logging.ERROR)

    #再  创建一个handler，用于输出控制台

    ch = logging.StreamHandler()

    ch.setLevel(logging.INFO)

    log_format=logging.Formatter("[%(asctime)s-%(filename)s:%(lineno)d]\n%(message)s",datefmt='%d %H:%M:%S')

    fh.setFormatter(log_format) #setFormatter() selects a Formatter object for this handler to use

    ch.setFormatter(log_format)

    logger.addHandler(fh)

    logger.addHandler(ch)  

    return logger

if __name__=='__main__':

    log=getLog()

    try:

        with open('./test.txt') as f:

            pass

    except (FileNotFoundError,EOFError) as e:

        log.error(e)

    log.info(a)

    log.info('test1')

    log.info('test2')

    log.info('test3')

自己写好的 工具 py 脚本 放到对应目录下去

有时候我们在liunx上想修改查看python的包路径可以试试以下命令

from distutils.sysconfig import get_python_lib

print(get_python_lib())

1024 == 2**10

65535 == 2**16-1

4294967295 == 2**32-1

[chr(i) for i in range(65,91)]+[chr(i) for i in range(97,123)]

b'\xe4\xb8\xad\xff'.decode('utf-8',errors='ignore')

不可变的tuple有什么意义？因为tuple不可变，所以代码更安全。如果可能，能用tuple代替list就尽量用tuple。

思考

eval   exec zip 的应用场景

不可变参数通过值传递，可变参数通过引用传递 list=[] 与 list =None 做参数的例子

上下文管理器+各种编码问题+异常处理深入

第三方模块

谷歌的 fire 模块

import dis 分析函数过程等...

from __future__ import printfunction 等 用来兼容 py2 与 py3

代码统计 cloc

excel 读写 pandas + xlrd , xlsxwriter

lxml

shutil

f-string

框架部分

相见恨晚

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