Python Grammar Tips

1, three-dimensional expression:

Value= true-expr If condition else false-expr

Example: a= ' positive ' if 3>0 else ' negative '

2. Use list derivation to replace map and filter

a=[1,2,3,4,5]squares=list (Map (LambdaX:x**2, a))Print(squares)#[1, 4, 9, +,]Squares=[x**2 forXinchA]Print(squares)#[1, 4, 9, +,]Data=list (Map (LambdaX:x**2, Filter (Lambdax:x%2==0,a )))Print(data)#[4, +]Data_one=[x**2 forXinchAifx%2==0] equivalent todata_one=[x**2 for X in A and x%2==0]

Print(Data_one)#[4, +] #dictionaries and collections have similar derivation mechanisms.chile_ranks={'Ghost': 1,'Habanero': 2,'Cayenne': 3} rank_dict={rank:name forName,rankinchchile_ranks.items ()} Chile_len_set={len (name) forNameinchrank_dict.values ()}Print(rank_dict)#{1: ' Ghost ', 2: ' Habanero ', 3: ' Cayenne '} Print(Chile_len_set)#{8, 5, 7}

3. Function-Type programming

Functions that can receive other functions as arguments are called higher order functions (High-order function).

Representative higher-order functions: Map () filter () and reduce ()

The map () function receives two parameters, one is the function, and the other is the ITERABLE,MAP functions the incoming function to each element of the sequence sequentially.

and return the result as a new iterable.

 lambda_sum=lambda  x,y:x+y  print  (Lambda_sum (3,4))  #  7  data_list=[1,3,5,6]result  =map (lambda  x:x+3,data_list)  print  (list (result)) #  [4, 6, 8, 9]  def   f (x):  return  x+3result_one  =list (map (f,data_list))  print    (Result_one) #  [4, 6, 8, 9]   

Reduce (): Action of a function in a sequence [x1,x2,x3,...] , the function must receive two parameters, reduce results

Continue with the next element of the sequence to do the cumulative calculation. It doesn't feel very useful! Can write yourself, will be troublesome, if necessary, still available.

 fromFunctoolsImportreducedata_list=[1,3,5]Print(Reduce (LambdaX,y:2*x+y,data_list))# thedeff_reduce (x, y):return2*x+yPrint(Reduce (f_reduce,data_list))# theNew_list=data_list[:1] forIinchRange (1, Len (data_list)): New_list.append (2*new_list[i-1]+Data_list[i])Print(new_list)#[1, 5, the]Print(New_list[-1])# thedefprod (L): New_list=l[:1]     forIinchRange (1, Len (L)): New_list.append (New_list[i-1]*L[i])returnNew_list[-1]Print(Prod ([3, 5, 7, 9]))#945defprod (L):returnReduceLambdax,y:x*y,l)Print(Prod ([3, 5, 7, 9]))#945

3, filter (), and map () similar, also receive a function and a sequence. Unlike map (), filter () applies the incoming function to each element sequentially,

The element is then persisted or discarded based on whether the return value is TRUE or False

List (filter (lambda x:x%2==0,[3,4,5))  #[4]list (filter (lambda x:x%2==1, [3,4,5]))  # [3,5]

Lst=[x**2 forXinchRange (10)]#[0, 1, 4, 9, +,-x1=[1,3,5]y1=[9,12,13]lst1=[x**2 for(x, Y)inchZip (x1,y1)ifY>10]Print(LST1)#[9]Dict={k:v forKvinchEnumerate ('Vamei')ifV not inch 'VI'}Print(dict)#{1: ' A ', 2: ' m ', 3: ' E '}

Python Grammar Tips