命名統計 collections
提取公共鍵 map reduce
佇列pickle
filter(lambda x: x>0 , list)
[ x for x in data if x >= 0]
from random import randint
data = [ randint(-10,10) for _ in range(10)]
res = filter(lambda x : x>=0 , data)
aa = [ x for x in
data if x >= 0]
from random import randint
d =
res =
print(res)
data = [-5, -7, -6, 7, 4, -3, -8, -9, 7, 0]
se = set(data)
res =
aa = filter(lambda x:x%3==0 , se)
# 測一下時間消耗
# （進入 ipython）
data = [-5, -7, -6, 7, 4, -3, -8, -9, 7, 0]
timeit filter(lambda x : x>=0 , data)
timeit [ x for x in
data if x >= 0]
# 元組查詢極快，元素不可修改。
name,age,***,email = range(4)
student = ('jim',16,'male','[email protected]')
print(student[email])
from collections import namedtuple
student = namedtuple('student',['name','age','***','email'])
s=student('jim',16,'male','[email protected]')
print(s.name)
data = [6, 1, 8, 1, 8, 2, 8, 4, 8, 6, 3, 4, 6, 3, 4, 5, 2, 9, 8, 3]
c = dict.fromkeys(data,0)
for x in
data:
c[x]+=1
print(c)
# 加強版
from collections import counter
data = [6, 1, 8, 1, 8, 2, 8, 4, 8, 6, 3, 4, 6, 3, 4, 5, 2, 9, 8, 3]
c2 = counter(data)
print(c2)
print(c2[1],c2[8])
# most_common 找出出現頻率最高的三個元素
print(c2.most_common(3))
import re
from collections import counter
with
open('secret.txt') as f:
text = f.read()
textlist = re.split('\w+',text)
print(len(textlist))
c3 = counter(re.split('\w+',text))
# print(c3)
print(c3.most_common(6))
from
random import randint,sample
from functools import reduce
left = 2
right = 6
s1 =
s2 =
s3 =
# 1.4 µs ± 55.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
print(s1.keys() & s2.keys() & s3.keys())
# 2.14 µs ± 36.3 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
reduce(lambda a,b:a&b , map(dict.keys,[s1,s2,s3]))
from random import randint,sample
aa = sample('abcdefg',randint(1,5))
print(aa)
from
random import randint,sample
left = 2
right = 6
s1 =
s2 =
s3 =
m = map(dict.keys,[s1,s2,s3])
print(list(m))
from functools import reduce
deff
(x, y):
return x + y
# reduce第乙個引數是 函式 ， 第二個引數是 列表、集合、元組或者map 之類可迭代的物件
reduce(f,[1,3,5,7,9],100) #第三個引數不要也行，意義是 設定初始值
from random import randint
from collections import deque
import pickle
history = deque(maxlen=5)
n=randint(0,100)
defguess
(k):
if k == n:
print('*****(`_`)*****')
return
true
elif k > n:
print("too big")
else:
print('too small')
while
true:
line = input("guess it ! :")
if line.isdigit():
k = int(line)
guess(k)
with open('history.txt','wb') as f:
pickle.dump(history,f)
elif line == "h":
with open('history.txt','rb') as f:
his = pickle.load(f)
print(his)
import pickle
from
random import randint
alist = [randint(0,100) for _ in range(10)]
with
open('testnote','wb') as f:
pickle.dump(alist,f)
with
open('testnote','rb') as f:
alist = pickle.load(f)
print(alist)
json被各種語言支援 ， pickle只用來python程式之間使用。
json在python裡面只支援列表和字典， pickle支援python的所有資料型別。
import pickle
from random import randint
import json
aa = [randint(0,100) for _ in range(10)]
atuple = tuple(aa)
aset = set(aa)
adic =
defppickle
(obj):
filename = 'picklenote'
with open(filename,'wb') as f:
pickle.dump(obj,f)
with open(filename,'rb') as f:
res = pickle.load(f)
print(res)
defjjson
(obj):
filename = 'jsonnote'
with open(filename,'w') as f:
json.dump(obj,f)
with open(filename,'r') as f:
res = json.load(f)
print(res)
print("\n+pickle:")
ppickle(aa)
ppickle(atuple)
ppickle(adic)
ppickle(aset)
print("\n+json:")
jjson(aa)
jjson(atuple)
jjson(adic)
# jjson(aset) # typeerror: object of type 'set' is not json serializable
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