1.1. How to filter data according to conditions in lists

# 1.1.How to filter data according to conditions in lists

data = [-1, 2, 3, -4, 5]

#Screen out data Data larger than or equal to zero in the list
#The first method is not recommended.
res1 = []
for x in data:
    if x >= 0:
        res1.append(x)

print(res1)

#The second is list parsing, which is recommended.
res2 = [ x for x in data if x >= 0]
print(res2)

#Third uses filter function
res3 = list(filter(lambda x : x>= 0,data))
print(res3)

1.2. How to filter data according to conditions in dictionaries

# 1.2.How to filter data according to conditions in dictionaries

from random import randint

#Creating Students'Dictionary,The student number is 1.~20，The score is 50.~100 random
d = {'student%d'% i: randint(50,100) for i in range(1,21)}
print(d)

#Filter out the student dictionary with a score of 90
#The first method
d1 = {k:v for k,v in d.items() if v >= 90}
print(d1)

#The second method
d2 = dict(filter(lambda item:item[1] >= 90, d.items()))
print(d2)

1.3. How to filter data according to conditions in a set

# 1.3.How to filter data according to conditions in a set

from random import randint

s = {randint(0,20) for _ in range(20)}
print(s)

#Screen out the number that can be divided by three
s1 = {x for x in s if x % 3 == 0}
print(s1)

1.4. How to name each element in the meta-ancestor to improve program readability

The following are the ancestors who use functions to determine age and sex, but the code is poor readability. Others do not know what student[1] and student[2] mean. How to solve it?

def func(student):
    if student[1] < 18 :
        pass

    if student[2] == 'male':
        pass

student = ('derek',22,'male','111@qq.com')

func(student)

Solution 1: Define enumeration types

#1.4..How to Name Every Element in Yuanzu to Improve Program Readability

def func(student):
    if student[1] < 18 :
        pass

    if student[2] == 'male':
        pass

s1 = ('derek',22,'male','111@qq.com')

#First: Use enumerations
from enum import IntEnum

class StudentEnum(IntEnum):
    NAME = 0
    AGE = 1
    SEX = 2
    EMAIL = 3

print(s1[StudentEnum.NAME])
print(s1[StudentEnum.AGE])

Solution 2: Replace the built-in tuple with collections.namedtuple in the standard library

#1.4..How to Name Every Element in Yuanzu to Improve Program Readability

def func(student):
    if student[1] < 18 :
        pass

    if student[2] == 'male':
        pass

s1 = ('derek',22,'male','111@qq.com')

#First: Use enumerations
from enum import IntEnum

class StudentEnum(IntEnum):
    NAME = 0
    AGE = 1
    SEX = 2
    EMAIL = 3

print(s1[StudentEnum.NAME])
print(s1[StudentEnum.AGE])

#The second is using standard libraries collections.namedtuple Substitute built in tuple
from collections import namedtuple

Student = namedtuple('student',['name','age','sex','email'])
s2 = Student('derek',22,'male','222@qq.com')
print(s2[0])               #derek
# Can pass s2.name Get name
print(s2.name)             #derek

1.5. How to sort the items in the dictionary according to the size of the median value in the dictionary

The first method: list parsing

# 1.5.How to sort the items in a dictionary according to the size of the median value in the dictionary

from random import randint

d = {k: randint(60, 100) for k in 'abcdefg'}
print(d)
#The first method: use list parsing or zip()function,Dictionary keys and values Reverse
list1 = [(v,k) for k,v in d.items()]
#Or use zip()function
# list2 = list(zip(d.values(),d.keys()))
print(list1)
list1 = sorted(list1,reverse=True)
print(list1)

The second uses sorted

# 1.5.How to sort the items in a dictionary according to the size of the median value in the dictionary

from random import randint

d = {k: randint(60, 100) for k in 'abcdefg'}
print(d)
#The first method: use list parsing or zip()function,Dictionary keys and values Reverse
list1 = [(v,k) for k,v in d.items()]
#Or use zip()function
# list2 = list(zip(d.values(),d.keys()))

list1 = sorted(list1,reverse=True)


#The second method is to use sorted sort
p = sorted(d.items(),key=lambda item:item[1],reverse=True)
print(p)     #[('a', 97), ('b', 93), ('d', 93), ('e', 92), ('f', 76), ('c', 66), ('g', 61)]

#Add a ranking to the score
d = {k:(i,v) for i, (k,v) in enumerate(p,1)}
print(d)    #{'g': (1, 97), 'd': (2, 92), 'f': (3, 91), 'c': (4, 79), 'a': (5, 78), 'e': (6, 67), 'b': (7, 64)}

1.6. How to Statistics the Frequency of Elements in Sequences

# 1.6 How to Statistics the Frequency of Elements in Sequences
from random import randint
from collections import Counter

data = [randint(1,5) for _ in range(1,20)]
print(data)   #[5, 2, 1, 2, 5, 3, 1, 1, 1, 4, 2, 5, 3, 2, 3, 5, 1, 2, 5]

#The highest frequency of calculation is three numbers.
c = Counter(data)
print(c.most_common(3))    #[(1, 5), (3, 4), (2, 4)]

1.7. How to quickly find common keys in multiple dictionaries

# 1.7.How to quickly find common keys in multiple dictionaries

from random import randint,sample
from functools import reduce

d1 = {k:randint(1,4) for k in sample('abcdefgh',randint(3,6))}
d2 = {k:randint(1,4) for k in sample('abcdefgh',randint(3,6))}
d3 = {k:randint(1,4) for k in sample('abcdefgh',randint(3,6))}

#1.Dictionary-using keys()Method, get a dictionary keys Set
#2.Use map Function, get each dictionary keys Set
#3.Use reduce，Take all dictionaries keys Intersection of sets

dl = [d1,d2,d3]
#Find the same in three dictionaries keys
result = reduce(lambda a,b: a & b, map(dict.keys, dl))
print(result)

1.8. How to keep dictionaries in order

# 1.8.How to keep dictionaries in order

from collections import OrderedDict
from itertools import islice

d = OrderedDict()
d['e'] = 5
d['d'] = 4
d['c'] = 3
d['b'] = 2
d['a'] = 1

print(d)    #OrderedDict([('e', 5), ('d', 4), ('c', 3), ('b', 2), ('a', 1)])

#OrderedDict Dictionary, which maintains the order in which elements are inserted during iteration

def query_by_order(d, a, b =None):
    if b is None:
        b = a + 1
    return list(islice(d,a,b))

#Fifth key
res1 = query_by_order(d,4)
print(res1)     #['a']

#Second and third key
res2 = query_by_order(d,1,3)
print(res2)     #['d', 'c']

1.9. How to Realize User's History Recording Function

Use queues with capacity n to store history

• Use deque double-ended circular queue to store history (deque is saved in memory, and the next boot history will disappear)
• If you want to save it to your hard disk, use the pickle module so that you can start using it next time.

# 1.9 How to Realize User's History Recording Function

from random import randint
from collections import deque
import pickle


def guess(n, k):
    if n == k:
        print('Guess right. That's the number.%d' % k)
        return True
    if n < k:
        print('Guess big, than%d Small' % k)
    elif n > k:
        print('Guess it's smaller than that.%d large' % k)
    return False


def main():
    n = randint(1, 100)
    i = 1
    hq = deque([], 5)
    while True:
        line = input('[%d]Please enter a number:' % i)
        if line.isdigit():
            k = int(line)
            hq.append(k)
            i += 1
            if guess(n, k):
                break
        elif line == 'quit':
            break
        elif line == 'history':
            print(hq)


if __name__ == '__main__':
    main()

#Result
[1]Please enter a number: 1
//Guess smaller, bigger than 1
[2]Please enter a number: 2
//Guess smaller, bigger than 2
[3]Please enter a number: 3
//Guess smaller, bigger than three.
[4]Please enter a number: history
deque([1, 2, 3], maxlen=5)
[4]Please enter a number: