Decorator
The decorator is essentially a Python function, which allows other functions to add additional functions without any code changes. The return value of the decorator is also a function object.
Let's start with a simple example:
def run(): time.sleep(1) print('run....')
There is a new requirement that we can record the running time of the function. We need to calculate the time in the code.
def run(): start_time = time.time() time.sleep(1) print('run....') end_time = time.time() print('run time', end_time - start_time)
login() and many other functions also have different types of requirements. What should we do? If you write a start and end time in each function, and then calculate the difference, the code will be redundant. You can define a function to calculate the execution time, and then execute the real business code, as follows:
def timer(func): #computing time start_time = time.time() func() end_time = time.time() print('run time', end_time - start_time) def run(): #Business code time.sleep(1) print('run....') timer(run)
The above code logic is incomprehensible, but in this case, each time a function is passed as a parameter to the timer() function, and this way has destroyed the original code logic structure. Before the execution of business logic, run() was executed, but now timer() has to be run. The above problems can be solved by using decorators.
Simple Decorator
def timer(func): #computing time def deco(*args, **kwargs): #It can be transmitted for reference. start_time = time.time() func(*args, **kwargs) #function call end_time = time.time() print('run time', end_time - start_time) return deco #return Function name, function is variable def run(): #Business code time.sleep(1) print('run....') run = timer(run) #run Amount to deco run() #run Call equivalent deco()
Function is a variable. The function in python is a variable and the function name is a variable. The function name stores the memory address of the function. It puts the function body in memory. When calling, it finds the function body from the memory address in the function name and runs the function. This function is called by adding parentheses after the function name. If you only write the function name, print out the memory address of the function.
Function timer is a decorator that wraps FuncS that perform real business methods in func tions and looks like run is decorated by timer. It continues to evolve as follows:
def timer(func): #computing time def deco(*args, **kwargs): #It can be transmitted for reference. start_time = time.time() func(*args, **kwargs) #function call end_time = time.time() print('run time', end_time - start_time) return deco #return Function name, function is variable @timer #Use @ This method is called when the form attaches the decorator to the function.timer(func) Returns the function name. deco，therefore run== deco，Function name is variable,here run Code updated,func() = run Previous code def run(): #Business code time.sleep(1) print('run....')
run()
The code after the run() function update is as follows: in fact, the code of run has not been changed directly, but when the decorator is called, the code of run is updated.
def run(): start_time = time.time() time.sleep(1) print('run....') end_time = time.time() print('run time', end_time - start_time)
python built-in function
print(all([1, 2, 3, 0, 11, -1])) #Judging whether all the values in an iterative object are true or not, one is false. False，Non-empty is true, non-zero is true. print(any([0, 1, 2])) #To determine whether a value in an iterative object is true, that is True print(bin(10)) #Converting decimal to binary print(bool('sdf')) #Converting an object to a Boolean type func = '' print(callable(func)) #Determine whether the incoming object is callable, func Not callable for variables, that is, returned False def adf(): pass print(callable(adf)) #Determine whether the incoming object is callable, adf Callable as a method, that is, returned True print(chr(98)) #Printed numerically corresponding ASCII Code, 98=b print(ord('a')) #Print String Corresponding ASCII Code, a=97 print(dict(a=1, b=2)) #Converting to a dictionary,{'b': 2, 'a': 1} #print(eval('[a=1]')) print(exec('def a():pass')) #implement python Code, which can only perform simple, defined data types and operations def func(num): name = '88' print(locals()) print(globals()) return num print(list(filter(func, [0, 1, 2, 3, 4]))) #stay python3 It's okay to use it like this. filter(func, [1, 2, 3, 4]) #According to the previous function processing logic, each element in the following iteratable object is processed in turn and returned. true Preservation print(list(map(func, [0, 1, 2, 3, 4]))) #According to the previous function processing logic, each element in the following iteratable object is processed in turn, and all the results returned by the previous function are saved. </span> print(globals()) #Returns all variables in the program, returning a dictionary,Local variables in functions do not return print(locals()) #Return local variables print(hex(111)) #Conversion of digits to hexadecimal print(max(111, 12, 13, 14, 16, 19)) #Maximum print(oct(111)) #Converting digits to octal print(round(11.1198, 2)) #Take a few decimal places.,Round off print(sorted([2, 31, 34, 6, 1, 23, 4], reverse=False))#sort
dic={1:2,3:4,5:6,7:8}
print(sorted(dic.items())) #According to the dictionary key sort,[(1, 2), (3, 4), (5, 6), (7, 8)]
print(sorted(dic.items(), key=lambda x:x[1])) #According to the dictionary value sort
import time #Import a module
import sys
print(sys.path) #See what directories the system environment variables have
sys.path.append(r'E:\python_workspace\base-code') #take base-code The following code is added to the environment variable, allowing python xxx.py Don't make a mistake
from day4.day5_test import hhh
hhh() #Direct right-click allows no error reporting, using python model2.py Allow Times to Error, Not Found day4 Modular No module named 'day4'
random module
import random print(random.randint(1, 20)) #At 1-19 Random generation of an integer, random print(random.choice('abs123')) #Random selection of an element, random iterative objects: string, dictionary, etc. list,tuple print(random.sample('abcdfgrtw12', 3)) #Randomly take a few elements, 3 is the length.['2', 'a', 'b']，The return result is list type print(random.uniform(1, 9)) #Random Floating Points, Random 1-9 Floating point number between, can specify range, 5.8791750348305625 print(random.random()) #Random 0-1 The floating point number of 0..9465901444615425 random.shuffle([1, 2, 3, 4, 5, 6]) #Random disruption list The value of 0, can only be __________. list
JSON function
Using JSON functions requires importing the JSON library: import json.
| function | describe |
| json.dumps | Converting a dictionary to a json string |
| json.dump | Write the json string converted by the dictionary to the file |
| json.loads | Converting json strings to dictionaries |
| json.load | Read json data from a file and convert it to a dictionary |
Examples are as follows:
a.json content format:
{"car":{"price":1100,"color":"red"},"mac":{"price":7999,"color":"black"},"abc":{"price":122,"color":"green"}}
json.load()
import json with open('a.json') as fp: shop_dic = json.load(fp) #from a.json Read the data in the file and return the result as a dictionary:{'abc': {'price': 122, 'color': 'green'}, 'mac': {'price': 7999, 'color': 'black'}, 'car': {'price': 1100, 'color': 'red'}} print(shop_dic)
json.loads()
s_json = '{"name":"niuniu","age":20,"status":true}' print(json.loads(s_json)) #take json String to dictionary:{'age': 20, 'status': True, 'name': 'niuniu'}
json.dump()
import json with open('a.json', 'a+') as fp: dic = {'name': 'niuniu', 'age': 18} fp.seek(0) fp.truncate() json.dump(dic, fp) #Converting a dictionary to json String write file
Write a.json as follows:
{"age": 18, "name": "niuniu"}
json.dumps()
import json dic = {'name': 'niuniu', 'age': 18} print(json.dumps(dic)) #Converting a dictionary to json String:{"name": "niuniu", "age"