1. What are iterators and generators.
Iterator is one of the most powerful functions in python. It is a collection of stored data.
The iterator can iterate over and access each element.
Each iterator contains an iter() and next() method.
iter() creates an iterator and next() gets the next value.
#Instantiate an iterator list = [1, 2, 3, 4] it = iter(list) print(next(it)) #Traversal to get the value in it print(next(it)) print(next(it)) print(next(it)) --- #The value obtained is 1 2 3 4 #Iterators can also use a for loop to iterate.
Create an iterator object. The iterator must contain the iter() method and the next() method
class Number(): def __iter__(self): #Create iter() method self.x = 1 return self def __next__(self):#Create next() method a = self.x self.x += 1 return a n1 = Number() n2 = iter(n1) print(next(n2)) print(next(n2)) print(next(n2)) print(next(n2)) ---- #The obtained value is 1 2 3 4
In python, the generator that uses the yield function is called. The generator is a function used to generate iterators. In short, yield is an iterator. In the generator, if the function is not called once, yield will pause and save the value of the current function, and continue to run from the current position the next time the next() method is executed
Take a Fibonacci sequence as an example
import sys def fibonacci(n): a, b, container = 0, 1, 0 while True: if container > n: return yield a a, b = b, a+b container += 1 fn = fibonacci(10) while True: try: print(next(fn), end=" ") except: sys.exit()
2. The difference between deep copy and shallow copy
When it comes to shallow copy and deep copy, we have to talk about variable objects and immutable objects.
1.1 variable object
Variable object means that the value pointed to by the object address can be modified without changing the address pointed to by the object
1.2 immutable object
Immutable object means that the value pointed to by an object address cannot be modified. If this value is modified, the address pointed to by this object will be modified.
1.3 the difference between deep copy and shallow copy is mainly reflected in variable objects
In shallow copy, the value pointed to by the modified object is the same as the original value, but the address pointed to is different, but the address pointed to by the elements in the variable object is the same.
In shallow copy, the value pointed to by the modified object is the same as the original value, but the address pointed to and the address pointed to by the elements in the variable object are different.
import copy a=[1,2,3,4,5,['a','b']] b = copy.copy(a) #Shallow copy c = copy.deepcopy(a) #Deep copy print('a',id(a), id(a)) print('b:',b, id(b), id(b)) print('c:',c, id(c), id(c)) ---- #Gets the value of the a 140351872525768 140351872525832 b: [1, 2, 3, 4, 5, ['a', 'b']] 140351872525768 140351872525960 c: [1, 2, 3, 4, 5, ['a', 'b']] 140351872575432 140351872528072
3. Explain what is a decorator and its function
Decorator is to add its function without modifying the function. Simple and easy to use Zhang Shiqi.
Decorators are mainly used in:
Configure domain name
4. How to read files in Python
In python, you need to use the open method to read files or the with open... as method. The first is to call the close() method to close the cursor object after calling open.
Using with open as will automatically call the close() method, so we don't need to call the close() method ourselves.
5. How to execute (operate) database in Python
Link database in python, such as mysql database
import pymysql #Create cursor object conn = pymysql.connect(host='localhost', port=3306, user='root', password='mysql', database='books', charset='utf8') cursor = conn.cursor() sql = 'select * from books;' cursor.execute(sql) items = cursor.fetchall() for item in items: print(item) cursor.close()
The specific steps are Step 1: create a link mysql Database objects The second step is to create a cursor object conn The third step is to implement sql sentence The fourth step is to close the cursor object The fifth step is to close the linked object