Python Basics 5 (collections, advanced features, higher-order functions)

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* * Remove duplicate elements from the list: L = [1,2,3,1,2,3]

-Mandatory conversion list for collection type: List (set (L))

-Convert the list to a dictionary and take out all the key values inside: Dict.fromkeys (L). Keys ()

* * Two ways to implement switch:

-If...elif...else ...

-Implemented by dictionary: d= {"Key", Func}

If Oper in D.keys ():

D[oper] ()

Else

Print "Error"

# Collection

# # Introduction of the collection:

Community

Linux Interest Group LINUXL = ["Wang Weber", "Wang Jianqiang"]

Python interest Group pythonl = ["Wang Weber", "Huangxin"]

。。。。

-Statistics of all associations L = []

-student = "Wang Weber"

-List: LINUXL + pythonl = ["Wang Weber", "Wang Jianqiang", "Wang Weber", "Huangxin"]

-Collection: {"Wang Jianqiang", "Wang Weber", "Huangxin"}

-ACM Competition:

# # Definition of the collection

* * Immutable data types must be hashed; a hash () built-in function can determine whether a type can be hashed;

# # Set of relationship tests

```

S1 = {1, 2, 3}

S2 = {2, 3, 4}

S3 = {1, 2}

S4 = {5}

Print "Intersection of S1,S2,S3:", s1.intersection (S2, S3)

Print "S1,s2,s3 intersection:", S1 & S2 & S3

Print "S1,S2,S3:", s1.union (S2, S3)

"S1,s2,s3 of print": ", S1 | S2 | S3

Print "S1-s2 of Difference:", s1.difference (S2)

Print "S1-s2 of Difference:", s1-s2

Print "S1-s2-s3 of Difference:", s1.difference (S2, S3)

Print "S1-s2-s3 of Difference:", S1-S2-S3

Print "S2-s1 of Difference:", s2.difference (S1)

print "S1 and S2 equivalent differential:", s1.symmetric_difference (S2)

print "S1 and S2 equivalent differential:", S1 ^ s2

print "S2 and S1 equivalent differential:", S2.symmetric_difference (S1)

# s.isdisjoint (S2) If there is an intersection, return false; otherwise, return true;

Print "S1 and S4 No intersection:", S1.isdisjoint (S4)

Print "S3 is a subset of S1:", S3.issubset (S1)

Print "S1 is the parent set of S3:", S1.issuperset (S3)

```

# # Collection of additions and deletions to search:

-Added: S.add (1), s.update (S1)

Delete

S.remove (1), # Delete existing element, if not present, direct error;

S.discard (1) # Delete the existing element if it does not exist, do nothing;

S.pop (), # Deletes the collection element without adding any parameters;

-copy: S1 = s.copy () #s和s1的id不同

-Empty: S.clear ()

# Frozen Set (Frozenset)

-Freeze the set, can not be deleted or modified;

-Frozenset (SET)

-Set (Frozenset)

# Advanced Features

# # Slice

# # Iterations

-any object that can be iterated can be traversed with a for loop;

-Iteration of the dictionary: The default is to iterate through key;

For I in D:

Print I

-Enumeration of dictionaries: enumerations can only return two values, one is index subscript, and the other is an iterative element;

D = {1: "A", 2: "B"}

For i,j in Enumerate (d):

Print I,j,d[j]

-How to determine if it is possible to iterate

From collections Import iterable

Isinstance ("Hello", iterable)

# # List-generated

List generation, in fact, is a way to generate a list, is Python built-in;

-Simple List-generation

[I*i for I in range (10)]# returns a list of 1-10 squares;

[Fun (i) for I in l]# performs a function operation on each element of the list;

-Nesting of For...if

[I*i for I in range (1,10) if i%2==0]# returns all the even numbers between 1-10

[I for I in range (1,10) if IsPrime (i)]# returns all prime numbers between 1-10, the function that determines prime numbers is custom;

-For...for ... The nested

[I+j for I in ' ABC ' for j in "123"]# returns all combinations of "abc" and "123";

# # Generator

-List generation can create a list directly, but the list capacity is limited by memory;

-The mechanism of looping one side in Python, called the Generator (Generator), is how much you need and how much it generates;

# # # Methods for creating generators:

-Change the list-generated [] to ();

-Add the yield keyword to the defined function;

# # # How to view builder elements:

-Use the next method of the generator; (infrequently used)

-The generator is an iterative object that is viewed directly through a for loop;

1, 1,

max = 6

def fib (max):

N,a,b = 0,1,1

While n < 6:

Print a

A, B = C, a + b

n = n + 1

# higher-order functions

# # Built-in high-order functions

-Map

-Reduce

Reduce (f,[1,2,3,4]) = = = > Add (add), 3, 4)

Reduce (Cheng,range (1,11))

* * for factorial of 10:

-Filter

in [+]: def is_oushu (n):

....: if n%2 = = 0:

....: Return True

.....: Else:

....: Return False

....:

in [+]: Filter (Is_oushu,range (1,11))

OUT[16]: [2, 4, 6, 8, 10]

-Sorted ()

```

n []: L = ["A", "Ab", "CD", "C"]

in [+]: sorted (L)

OUT[21]: [' Ab ', ' C ', ' A ', ' CD ']

In []: def cmp_ignore_case (S1,S2):

.....: S1 = S1.lower ()

.....: S2 = s2.lower ()

....: If S1 < s2:

.....: return-1

....: elif S1 > S2:

....: return 1

.....: Else:

....: return 0

....:

In [23°c]: sorted (l,cmp_ignore_case)

OUT[23]: [' A ', ' Ab ', ' C ', ' CD ']

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Python Basics 5 (collections, advanced features, higher-order functions)