python Character subtraction is not allowed , When subtraction between characters is required , We can use ord() function ,ord() The function is python Self contained function , No need to import .
print(ord('b')-ord('a'))
#result:1
string = 'leetcode'
print(string[::-1])
#result:edocteel
import collections
li = [1,2,2,4,5,5]
cnt = collections.Counter(li)
print(cnt)
#result:Counter({
2: 2, 5: 2, 1: 1, 4: 1})
cnt = {
1:4,2:3}
# Traversal key value pairs
for item in cnt.items():
print(item)
# Traversal keys
for item in cnt.keys():
print(item)
# Traversal value
for item in cnt.values():
print(item)
result:
(1, 4)
(2, 3)
1
2
4
3
li = [0]*length # The first one is
li = [0 for i in range(length)] # The second kind
li = [[0]*3 for i in range(4)] # Two dimensional array
from collections import Counter
colors = ['red','blue','red','green','blue','blue']
c = Counter(colors)
print(c)
print(dict(c))
result:
Counter({
'blue': 3, 'red': 2, 'green': 1})
{
'red': 2, 'blue': 3, 'green': 1}
bisect yes python The built-in modules , For insertion and lookup of ordered sequences
lookup ：bisect(array,item)
Insert ：bisect(array,item)
import bisect
a = [1,2,2,5,8]
position = bisect.bisect(a,7)
print(position)
#4
bisect.insort(a,4) # Find the location to insert
print(a)
#[1,2,2,4,5,8]
bisect.bisect_left(a,2) # Insert to left
#1
bisect.bisect_right(a,2) # Insert to the right
#3
l1 = [1,4,4,2,3,4,5,6,1]
l2 = list(set(l1))
print(l2)
#result:[1, 2, 3, 4, 5, 6]
li = ['a','b','c']
print(' '.join(str(i) for i in li))
def square(x):
return x**2
a = list(map(square,[1,2,3,4,5])) # Calculate the square of each element of the list
b = list(map(lambda x:x**2,[1,2,3,4,5,])) # use lambda Anonymous functions
print(a,b)
#result:[1, 4, 9, 16, 25] [1, 4, 9, 16, 25]
deque It's a two terminal queue (double-ended queue) Abbreviation , Because both ends can be edited ,deque It can realize stack (stack), Queues can also be implemented (queue)
from collections import deque
# que = collections.deque()
a=deque([1,2,3])
a.pop()
# [1,2]
a.append(4)
# [1,2,4]
a.popleft()
# [2,4]
a.appendleft(0)
# [0,2,4]
comparison list Implemented queue ,deque The implementation has lower time and space complexity .list Get out of the team (pop) And insert (insert) The space of time
The complexity is about O(n),deque Out of the team (pop) And join the team (append) The time complexity is O(1).
from queue import PriorityQueue
Q = PriorityQueue()
Q.put(3)
Q.put(2)
Q.put(1)
Q.get()
Priority queue , The default is sorted from small to large
li = [[1,3],[8,10],[2,6],[15,18]]
li.sort(key=lambda x:x[0])
li
print(li)
#result:[[1, 3], [2, 6], [8, 10], [15, 18]]
name = 'python'
f'Hello {name}'
print(f'Hello {name}')
systems = ['windows','ubuntu','mac']
version = ['20.20','19.10','21.20']
countries = ['UK','Chinese','US']
for system,ver,country in zip(systems,version,countries):
print(f'{
system} plays in {
ver}.country:{
country}')
person = {
'name':'YQ','age':22}
print('Name:',person.get('name'))
print('Age:',person.get('age'))
print('Salary:',person.get('salary'))
result:
Name: YQ
Age: 22
Salary: None
from collections import OrderedDict
mydict = OrderedDict({
'a':2,'b':1,'c':0})
for key,value in mydict.items():
print(key,value)
result:
a 2
b 1
c 0
nums = [1,2,2,2,3,4,4]
from collections import Counter
cnt = Counter(nums)
print(max(cnt.keys(),key = cnt.get))
#result:2
NameError: name 'lru_cache' is not defined
from functools import lru_cache
A decorator that provides caching for functions , Directly used in a user-defined function , The next time you call with the same parameter, you will directly return the last result
lru_cache maxsize The default value of the parameter is 128. If it is set to None, The cache can grow indefinitely
from functools import lru_cache
@lru_cache(maxsize = None)
def fib(n):
if n < 2:
return n
return fib(n-1) + fib(n-2)
# Dictionary sort
a = {
'a':3,'c':89,'b':0,'d':34}
# Sort by dictionary value
a1 = sorted(a.items(),key = lambda x: x[1])
# Sort by dictionary key
a2 = sorted(a.items(),key = lambda x: x[0])
print(' Results sorted by value ',a1)
print(' Press the key to sort the results ',a2)
print(' The result is converted to dictionary format ',dict(a1))
print(' The result is converted to dictionary format ',dict(a2))
result：
Results sorted by value [('b', 0), ('a', 3), ('d', 34), ('c', 89)]
Press the key to sort the results [('a', 3), ('b', 0), ('c', 89), ('d', 34)]
The result is converted to dictionary format {
'b': 0, 'a': 3, 'd': 34, 'c': 89}
The result is converted to dictionary format {
'a': 3, 'b': 0, 'c': 89, 'd': 34}
my_str = 'python'
my_str.isalpha()
print(my_str.isalpha())
Multi step sorting , for example ： Sort by content first , If the content is the same, then follow ID Sort
my_test = ["b:7","a:7","c:4","d:3"]
def f(log):
id_,rest = log.split(":",1)
return (rest,id_)
print(sorted(my_test,key=f))
#result:['d:3', 'c:4', 'a:7', 'b:7']
Take the example above , First sort by string value , Then according to the string id Sort
Sometimes you need to use a dictionary to count the number of the same elements in a list , But maybe an element is also a list , You can't use it directly at this time
collections.Counter To statistics , You need to convert the elements of the original list to tuple
1、 Array operation
1.1. Traversal array , Enumerate indexes and values
for i,j in enumerate([1,2,34,5,56,4]):
#i Index
#j Value
1.2. An array of reverse
a = [1,2,3,4,5]
a[::-1]
a.reverse()
1.3. Array sorting
a = [1,2,6,8,0,3,4]
a.sort()
a = [[1,3],[2,4],[5,0]]
sort(key = lambda x:x[0]) # According to the first number is key Sort
1.4. Array merge
a = [1,2,6,8,0,3,4]
b = [2,5,9]
a.extend(b)
a.[len(a):]=b
1.5. Build stacks and queues
a = [1,2,6,8,0,3,4]
a.append() # Add... At the end of the array
a.insert(x,3) # The index is x Insert at 3
a.pop() # Delete the tail element
a.pop(0) # Delete index as 0 The elements of
a = [] # Build stack
a.append()
a.pop()
a = []
a.append()
a.pop(0)
1.6. Array weight removal
# Turn into set, Convert to list
a = [1,1,1,3,4,4]
a = list(set(a))
1.7. Find array
a.index(3)
2、 String manipulation
2.1. Remove the space
a = ' hello world '
a.strip() # Remove all spaces on both sides
a.lstrip() # Remove the space on the left
a.rstrip() # Remove the space on the right
2.2. Replace character
# take a Medium x Replace with yyy, You can put spaces ' ' Replace with '' Equal to removing spaces
a.replace('x','yyy')
2.3. Merge characters
a = 'hello'
b = 'world'
c = a + b
2.4. Judge the composition of characters
# If string Only Numbers are returned true, Otherwise return to False
a.isdigit()
# If string Returns at least one character and all characters are letters or Numbers True, Otherwise return to False
a.isalnum()
# If string Returns at least one character and all characters are letters True, Otherwise return to False
a.isalpha()
2.5. Convert array to characters
# With string As a separator , take seq All the elements in （ String representation of ） Merge into a new string
#string.join(seq)
a = [1,2,3,4]
#''.join(a) # The result is '1234'
print(' '.join('%s' %id for id in a))
python Provides an intuitive way to assign and exchange values in a single line of code （ A variable's value ） Methods
x,y = 10,20
print(x,y)
x,y = y,x
print(x,y)
The right side of the assignment forms a new tuple , Parse now on the left （unpack） that （ Not quoted ） Tuples to variables and , Once the assignment is complete , The new tuple becomes unreferenced and marked for garbage collection , Finally, the exchange of variables is completed
Aggregation of comparison operators is another sometimes convenient technique ：
n = 10
result = 1<n<20
print(result) #True
result = 1>n<=9
print(result) #False
We can use lists to initialize multiple variables , When parsing the list , The number of variables should not exceed the number of elements in the list ：[ The number of elements and the length of the list should be exactly the same ]
testList =[1,2,3]
x,y,z = testList
print(x,y,z) #1 2 3
If you want to know the absolute path to the module referenced in the code, you can use
import threading
import socket
print(threading)
print(socket)
This is a useful feature that most of us don't know , stay python Console , Whenever we test an expression or call a method , The result is a temporary variable ：_
# Method 1 ：
#List = eval(input(' Enter several numbers , Separate with commas ：'))
# Method 2 ：
#List = List(map(int,input(' Input number , Space off ').split()))
#int It can be replaced by float etc. , The resulting data is of the corresponding type
# explain ：
#1. map()
#map() The function takes two arguments , One is a function , One is the sequence ,map Apply the incoming function to each element of the sequence in turn , And take the result as a new list return
#2. split()
# Split string , Slice a string by specifying a separator , And return the separated string list
#3. map(function,input(" Separate... By spaces ").split())
# because input() The output is a string separated by spaces ,split() The values are separated and placed in the list , At this point, the value in the list is string , If you want to calculate , Then it must be in map() In the use of int() or float() And then assign values after processing
List = [1,2,3,4,5,6]
for i,j in enumerate(List): #i Subscript ,j For the corresponding data
print("data:",end=' ')
print("index",i)
result:
data: index 0
data: index 1
data: index 2
data: index 3
data: index 4
data: index 5
a = 123
b = 'blue'
print(id(a)) # Different computers , Values should be different
print(id(b))
a = ['A','B','C','D','E']
b = [1,2,3,4,5]
# Method 1 ：
c1 = dict(zip(a,b))
# Method 2
c2 = {
key:value for key,value in zip(a,b)}
# Method 3
c3 = {
} # Initialize an empty dictionary
for k,v in zip(a,b):
if k not in c3.keys(): # Judge k Whether in c3 In the dictionary key
c3[k] = v
print(c1)
print(c2)
print(c3)
result:
{
'A': 1, 'B': 2, 'C': 3, 'D': 4, 'E': 5}
{
'A': 1, 'B': 2, 'C': 3, 'D': 4, 'E': 5}
{
'A': 1, 'B': 2, 'C': 3, 'D': 4, 'E': 5}
a = [1,2,3,1,2,4,6,5,6,6,7,9,10,10]
b = {
}
for i in a:
if i not in b.keys():
b[i] = 1
else:
b[i] =b[i] + 1
print(b)
#result:{
1: 2, 2: 2, 3: 1, 4: 1, 6: 3, 5: 1, 7: 1, 9: 1, 10: 2}
from sys import getsizeof
a = 100
b = 'green'
print(getsizeof(a)) #28
print(getsizeof(b)) #54
List1 = [1,2,3,4,56]
List2 = [1,1,3,4,5,5]
print(" There are repeating elements :",len(List1) != len(set(List1))) # There are repeating elements ：False
print(" There are repeating elements :",len(List2) != len(set(List2))) # There are repeating elements ：True
explain ：set(x) Function can be used for collection generation , The parameters can be any data type , The returned result is a set with no repetition and arbitrary sorting ,
in other words , If the input data is duplicated , The returned result will also make the duplicate data non duplicate
# Method 1 ：
List1 = [1,2,3,4,56,11,2,3,4,5,6,7,1,2,3,1,1,1,19]
print(max(set(List1),key = List1.count)) #1
# Method 2 ：
from collections import Counter #python Built in libraries for
ct = Counter(List1)
print(ct.most_common(1)) # The one with the highest output frequency #[(1,5)] 1 appear 5 Time
List1 = [1,2,5,4,7,6]
List2 = List1[::-1]
print(List2) #[6, 7, 4, 5, 2, 1]
list1=[1,2,5,4,7,6]
list2=['A','B','C','D']
list3=list1+list2# Direct addition
list4=list1.extend(list2)# Of the call list extend Method
print(list3) #[1, 2, 5, 4, 7, 6, 'A', 'B', 'C', 'D']
print(list4) #None
print(list1) #[1, 2, 5, 4, 7, 6, 'A', 'B', 'C', 'D']
explain ： Why? list4 by None？ Actually , This is very important , List append and extend Method will modify the original list , Will not return a new list , The return value is None.
Most of the python Programmers know and use list derivation list comprehensions, If you are right about list comprehensions Not familiar with , Shorter ：
some_list = [1,2,3,4,5]
another_list = [x + 1 for x in some_list]
print(another_list) #[2, 3, 4, 5, 6]
some_list = [1,2,3,4,5,2,5,1,4,8]
even_set = {
x for x in some_list if x %2 == 0}
print(even_set) #{
8, 2, 4}
set([8,2,4])
d = {
x: x%2 == 0 for x in range(1,11)}
print(d) #{
1: False, 2: True, 3: False, 4: True, 5: False, 6: True, 7: False, 8: True, 9: False, 10: True}
In the first example , We use some_list Based on , Create a collection with non repeating elements , And the set contains only even numbers , And in the dictionary table , We created
One key Is not repeated 1 To 10 Integer between ,value It's Boolean , Used to indicate key Is it an even number
Another important thing to note here is the literal representation of sets , We can simply create a collection in this way
my_set = {
1,2,1,2,3,4}
print(my_set) #{
1, 2, 3, 4}
and collections Like the library , There is also a library that is more itertools, It can effectively solve some problems , One of the use cases is to find all the combinations
from itertools import combinations
teams = ["Packers","49ers","Ravens","Patriots"]
for game in combinations(teams,2):
print(game)
result:
('Packers', '49ers')
('Packers', 'Ravens')
('Packers', 'Patriots')
('49ers', 'Ravens')
('49ers', 'Patriots')
('Ravens', 'Patriots')
With the help of the module, we can python Set breakpoints in the script
import pdb
pdb.set_trace()
# Method 1 ：
#List = eval(input(' Enter several numbers , Separated by commas ：')) # Enter any number , All saved to list in
# Method 2 ：
#List = list(map(int(input(' Input number , Space off ').split())))
#int Can be replaced by float etc. , The resulting data is of the corresponding type
# explain ：
1.map()
map Function takes two parameters , One is a function , One is the sequence ,map Apply the incoming function to each element of the sequence in turn , And take the result as a new list return
2.split()
split Split string , Slice a string by specifying a separator , And returns a list of split strings
3.map(function,input(" Separate... By spaces ").split())
because input() The output is a string separated by spaces ,split() The values are split and placed in the list , At this point, the value in the list is string \
If you want to use it in an operation , Then it must be in map() In the use of int() or float() Wait for the treatment , To assign a value
Share ：
Experience is a potential condition for our innovation . Strictly speaking , Experience without experience , Experience is a condition for innovation , otherwise , Experience will become an obstacle to innovation . There are different levels of experience . To sublimate wisdom , We should learn from high-level experience as much as possible —
This not only provides us with a way forward , It also provides ideas for selection , Make it the starting point for triggering new success .
