Maison développement back-end Tutoriel Python PythonCookbook——数据结构和算法

PythonCookbook——数据结构和算法

Nov 26, 2016 am 10:13 AM
python

第一章    数据结构和算法 

1.1    将序列分解为单独的变量

p = (4, 5)
x, y = p
print x 
print y 
data = [ 'ACME', 50, 91.1, (2012, 12, 21) ]
name, shares, price, date = data
print name
print shares 
print price 
print date 
name, shares, price, (year, mon, day ) = data
print year 
p = (4, 5)
#x, y, z = p 错误!!!
s = 'hello!'
a, b, c, d, e, f = s
print a
print f
data = [ 'ACME', 50, 91.1, (2012, 12, 21) ]
_, shares, price, _ = data 
print shares
print price
#其他数据可以丢弃了
Copier après la connexion

1.2 从任意长度的可迭代对象中分解元素

from audioop import avg
def drop_first_last(grades):
    first, *middle, last = grades
    return avg(middle)
record = ('Dave', 'dave@example.com', '777-333-2323', '234-234-2345')
name, email, *phone_numbers = record
print name 
print email
print phone_numbers
*trailing, current = [10, 8, 7, 2, 5]
print trailing  #[10, 8, 7, 2, ]
print current #5
records = [
           ('foo', 1, 2),
           ('bar', 'hello'),
           ('foo', 5, 3)
           ]
def do_foo(x, y):
    print ('foo', x, y)
def do_bar(s):
    print ('bar', s)
for tag, *args in records:
    if tag == 'foo':
        do_foo(*args)
    elif tag == 'bar':
        do_bar(*args)
        
line = 'asdf:fedfr234://wef:678d:asdf'
uname, *fields, homedir, sh = line.split(':')
print uname 
print homedir
record = ('ACME', 50, 123.45, (12, 18, 2012))
name, *_, (*_, year) = record
print name
print year
items = [1, 10, 7, 4, 5, 9]
head, *tail = items
print head #1
print tail #[10, 7, 4, 5, 9]
def sum(items):
    head, *tail = items
    return head + sum(tail) if tail else head
sum(items)
Copier après la connexion

1.3 保存最后N个元素

from _collections import deque
def search(lines, pattern, history=5):
    previous_lines = deque(maxlen = history)
    for line in lines:
        if pattern in line:
            yield line, previous_lines
        previous_lines.append(line)
# Example use on a file
if __name__ == '__main__':
    with open('somefile.txt') as f:
        for line, prevlines in search(f, 'python', 5):
            for pline in prevlines:
                print (pline) #print (pline, end='')
            print (line) #print (pline, end='')
            print ('-'*20)
            
q = deque(maxlen=3)
q.append(1)
q.append(2)
q.append(3)
print q
q.append(4)
print q
q = deque()
q.append(1)
q.append(2)
q.append(3)
print q
q.appendleft(4)
print q
q_pop = q.pop()
print q_pop
print q
q_popleft = q.popleft()
print q_popleft
print q
Copier après la connexion

1.4 找到最大或最小的N个元素

import heapq
nums = [1,30,6,2,36,33,46,3,23,43]
print (heapq.nlargest(3, nums))
print (heapq.nsmallest(3, nums))
portfolio = [
                 {'name':'IBM', 'shares':100, 'price':2.4},
                 {'name':'A', 'shares':1040, 'price':12.4},
                 {'name':'S', 'shares':40, 'price':23.4},
                 {'name':'D', 'shares':1, 'price':2.49},
                 {'name':'F', 'shares':9, 'price':24}
             ]
cheap = heapq.nsmallest(3, portfolio, key=lambda s: s['price'])
expensive = heapq.nlargest(3, portfolio, key=lambda s: s['price'])
print cheap
print expensive
nums = [1,8,2,23,7,-4,18,23,42,37,2]
heap = list(nums)
print heap
heapq.heapify(heap)
print heap
print heapq.heappop(heap)
print heapq.heappop(heap)
print heapq.heappop(heap)
Copier après la connexion

1.5 实现优先级队列

import heapq
class PriorityQueue:
    def __init__(self):
        self._queue = []
        self._index = 0
    def push(self, item, priority):
        heapq.heappush(self._queue, (-priority, self._index, item))
        self._index += 1
    def pop(self):
        return heapq.heappop(self._queue)[-1]
#Example
class Item:
    def __init__(self, name):
        self.name = name
    def __repr__(self):
        return 'Item({!r})'.format(self.name)
q = PriorityQueue()
q.push(Item('foo'), 1)
q.push(Item('spam'), 4)
q.push(Item('bar'), 5)
q.push(Item('grok'), 1)
print q.pop()
print q.pop()
print q.pop()
a = Item('foo')
b = Item('bar')
#a < b    error
a = (1, Item('foo'))
b = (5, Item('bar'))
print a < b
c = (1, Item('grok'))
#a < c  error
a = (1, 0, Item('foo'))
b = (5, 1, Item('bar'))
c = (1, 2, Item('grok'))
print a < b
print a < c
Copier après la connexion

1.6 在字典中将建映射到多个值上

d = {  
        'a' : [1, 2, 3],  
        'b' : [4, 5]  
     }  
e = {  
        'a' : {1, 2, 3},  
        'b' : {4, 5}  
     }  
  
from collections import defaultdict  
  
d = defaultdict(list)  
d['a'].append(1)  
d['a'].append(2)  
d['a'].append(3)  
print d  
  
d = defaultdict(set)  
d['a'].add(1)  
d['a'].add(2)  
d['a'].add(3)  
print d  
  
d = {}  
d.setdefault('a', []).append(1)  
d.setdefault('a', []).append(2)  
d.setdefault('b', []).append(3)  
print d   
  
d = {}  
for key, value in d:#pairs:  
    if key not in d:  
        d[key] = []  
    d[key].append(value)  
  
d = defaultdict(list)  
for key, value in d:#pairs:  
    d[key].append(value)
Copier après la connexion

1.7 让字典保持有序

from collections import OrderedDict  
  
d = OrderedDict()  
d['foo'] = 1  
d['bar'] = 2  
d['spam'] = 3  
d['grol'] = 4  
for key in d:  
    print (key, d[key])  
      
import json  
  
json.dumps(d)
Copier après la connexion

1.8 与字典有关的计算问题

price = {  
            'ACME':23.45,  
            'IBM':25.45,  
            'FB':13.45,  
            'IO':4.45,  
            'JAVA':45.45,  
            'AV':38.38,  
         }  
  
min_price = min( zip( price.values(), price.keys() ) )  
print min_price  
  
max_price = max( zip( price.values(), price.keys() ) )  
print max_price  
  
price_sorted = sorted( zip( price.values(), price.keys() ) )  
print price_sorted     
  
price_and_names = zip( price.values(), price.keys() )  
print (min(price_and_names))  
#print (max(price_and_names))  error  zip()创建了迭代器,内容只能被消费一次  
  
print min(price)  
print max(price)  
  
print min(price.values())  
print max(price.values())  
  
  
print min(price, key = lambda k : price[k])  
print max(price, key = lambda k : price[k])  
  
min_value = price[ min(price, key = lambda k : price[k]) ]  
print min_value  
  
price = {  
            'AAA': 23,  
            'ZZZ': 23,  
         }  
print min( zip( price.values(), price.keys() ) )  
print max( zip( price.values(), price.keys() ) )
Copier après la connexion

1.9 在两个字典中寻找相同点

a = {  
        'x':1,  
        'y':2,  
        'z':3  
     }  
b = {  
        'x':11,  
        'y':2,  
        'w':10  
     }  
  
print a.keys() & b.keys() #{'x','y'}  
print a.keys() - b.keys() #{'z'}  
print a.items() & b.items() #{('y', 2)}  
  
c = {key: a[key] for key in a.keys() - {'z', 'w'} }  
print c #{'x':1, 'y':2}
Copier après la connexion

1.10 从序列中移除重复项且保持元素间顺序不变

def dedupe(items):  
    seen = set()  
    for item in items:  
        if item not in seen:  
            yield item  
            seen.add(item)  
#example  
a = [1,5,2,1,9,1,5,10]  
print list(dedupe(a))  
  
def dedupe2(items, key = None):  
    seen = set()  
    for item in items:  
        val = item if key is None else key(item)  
        if val not in seen:  
            yield item  
            seen.add(val)   
#example  
a = [   
        {'x':1, 'y':2},   
        {'x':1, 'y':3},   
        {'x':1, 'y':2},   
        {'x':2, 'y':4},   
     ]  
print list( dedupe2(a, key=lambda d : (d['x'], d['y']) ) )  
print list( dedupe2(a, key=lambda d : (d['x']) ) )  
  
a = [1,5,2,1,9,1,5,10]  
print set(a)
Copier après la connexion

1.11 对切片命名

items = [0,1,2,3,4,5,6]  
a = slice(2,4)  
print items[2:4]  
print items[a]  
items[a] = [10,11]  
print items  
  
print a.start  
print a.stop  
print a.step
Copier après la connexion

1.12 找出序列中出现次数最多的元素

words = [  
            'look', 'into', 'my', 'eyes', 'look', 'into', 'my', 'eyes',  
            'the', 'look'  
         ]  
  
from collections import Counter  
  
word_counts = Counter(words)  
top_three = word_counts.most_common(3)  
print top_three  
  
print word_counts['look']  
print word_counts['the']  
  
morewords = ['why', 'are', 'you', 'not', 'looking', 'in', 'my', 'eyes']  
for word in morewords:  
    word_counts[word] += 1  
print word_counts['eyes']  
print word_counts['why']  
  
word_counts.update(morewords)  
print word_counts['eyes']  
print word_counts['why']  
  
a = Counter(words)  
b = Counter(morewords)  
print a  
print b  
c = a + b  
print c  
d = a - b  
print b
Copier après la connexion

1.13 通过公共键对字典列表排序

rows = [  
            {'fname':'Brian', 'lname':'Jones', 'uid':1003},  
            {'fname':'David', 'lname':'Beazley', 'uid':1002},  
            {'fname':'John', 'lname':'Cleese', 'uid':1001},  
            {'fname':'Big', 'lname':'Jones', 'uid':1004}  
        ]  
  
from operator import itemgetter  
  
rows_by_fname = sorted(rows, key=itemgetter('fname'))  
rows_by_uid = sorted(rows, key=itemgetter('uid'))  
print rows_by_fname  
print rows_by_uid  
rows_by_lfname = sorted(rows, key=itemgetter('lname', 'fname'))  
print rows_by_lfname  
  
rows_by_fname = sorted(rows, key=lambda r: r['fname'])  
rows_by_lfname = sorted(rows, key=lambda r: (r['fname'], r['lname']))  
print rows_by_fname  
print rows_by_lfname  
  
print min(rows, key=itemgetter('uid'))  
print max(rows, key=itemgetter('uid'))
Copier après la connexion

1.14 对不原生支持比较操作的对象排序

class User:  
    def __init__(self, user_id):  
        self.user_id = user_id  
    def __repr__(self):  
        return 'User({})'.format(self.user_id)  
  
users = [User(23), User(3), User(99)]  
print users  
print sorted(users, key = lambda u: u.user_id)  
  
from operator import attrgetter  
print sorted(users, key=attrgetter('user_id'))  
  
print min(users, key=attrgetter('user_id'))  
print max(users, key=attrgetter('user_id'))
Copier après la connexion

1.15 根据字段将记录分组

rows = [  
            {'address':'5412 N CLARK', 'data':'07/01/2012'},  
            {'address':'5232 N CLARK', 'data':'07/04/2012'},  
            {'address':'5542 E 58ARK', 'data':'07/02/2012'},  
            {'address':'5152 N CLARK', 'data':'07/03/2012'},  
            {'address':'7412 N CLARK', 'data':'07/02/2012'},  
            {'address':'6789 w CLARK', 'data':'07/03/2012'},  
            {'address':'9008 N CLARK', 'data':'07/01/2012'},  
            {'address':'2227 W CLARK', 'data':'07/04/2012'}  
        ]  
  
from operator import itemgetter  
from itertools import groupby  
  
rows.sort(key=itemgetter('data'))  
for data, items in groupby(rows, key=itemgetter('data')):  
    print (data)  
    for i in items:  
        print (' ', i)  
          
from collections import defaultdict  
rows_by_date = defaultdict(list)  
for row in rows:  
    rows_by_date[row['data']].append(row)  
for r in rows_by_date['07/04/2012']:  
    print(r)
Copier après la connexion

1.16 筛选序列中的元素

mylist = [1,4,-5,10,-7,2,3,-1]  
print [n for n in mylist if n > 0]#列表推导式  
print [n for n in mylist if n < 0]  
  
pos = (n for n in mylist if n > 0)#生成器表达式  
print pos  
for x in pos:  
    print(x)  
  
values = ['1', '2', '-3', '-', '4', 'N/A', '5']  
def is_int(val):  
    try:  
        x = int(val)  
        return True  
    except ValueError:  
        return False  
ivals = list(filter(is_int, values))  
print(ivals)  
  
mylist = [1,4,-5,10,-7,2,3,-1]  
import math  
print [math.sqrt(n) for n in mylist if n > 0]  
  
clip_neg = [n if n > 0 else 0 for n in mylist]  
print clip_neg  
  
clip_pos = [n if n < 0 else 0 for n in mylist]  
print clip_pos  
  
addresses = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']  
counts = [0, 3, 10, 4, 1, 7, 6, 1]  
from itertools import compress  
more5 = [n > 5 for n in counts]  
print more5  
print list(compress(addresses, more5))
Copier après la connexion

1.17 从字典中提取子集

prices = {'ACNE':45.23, 'AAPL':612.78, 'IBM':205.55, 'HPQ':37.20, 'FB':10.75}  
p1 = { key:value for key, value in prices.items() if value > 200 }  
print p1  
  
tech_names = {'AAPL', 'IBM', 'HPQ'}  
p2 = { key:value for key, value in prices.items() if key in tech_names }  
print p2  
  
p3 = dict( (key, value) for key, value in prices.items() if value > 200 ) #慢  
print p3  
  
tech_names = {'AAPL', 'IBM', 'HPQ'}  
p4 = { key:prices[key] for key in prices.keys() if key in tech_names } #慢  
print p4
Copier après la connexion

1.18 将名称映射到序列的元素中

from collections import namedtuple  
  
Subscriber = namedtuple('Subscriber', ['addr', 'joined'])  
sub = Subscriber('wang@qq.com', '2020-10-10')  
print sub  
print sub.joined  
print sub.addr  
  
print len(sub)  
addr, joined = sub  
print addr  
print joined  
  
def compute_cost(records):  
    total = 0.0  
    for rec in records:  
        total += rec[1]*rec[2]  
    return total  
  
Stock = namedtuple('Stock', ['name', 'shares', 'price'])  
def compute_cost2(records):  
    total = 0.0  
    for rec in records:  
        s = Stock(*rec)  
        total += s.shares * s.price  
    return total  
  
s = Stock('ACME', 100, 123.45)  
print s  
#s.shares = 75    #error  
s = s._replace(shares=75)  
print s  
  
Stock = namedtuple('Stock', ['name', 'shares', 'price', 'date', 'time'])  
stock_prototype = Stock('',0, 0.0, None, None)  
def dict_to_stock(s):  
    return stock_prototype._replace(**s)  
a = {'name':'ACME', 'shares':100, 'price':123.45}  
print dict_to_stock(a)  
b = {'name':'ACME', 'shares':100, 'price':123.45, 'date':'12/12/2012'}  
print dict_to_stock(b)
Copier après la connexion

1.19 同时对数据做转换和换算

nums = [1, 2, 3, 4, 5]  
s = sum( x*x for x in nums )  
print s  
  
import os  
files = os.listdir('dirname')  
if any(name.endswith('.py') for name in files):  
    print('There be Python!')  
else:  
    print('sorry, no Python!')  
      
s = ('ACME', 50, 123.45)  
print(','.join(str(x) for x in s))  
  
portfolio = [  
                {'name':'GOOG', 'shares':50},  
                {'name':'YHOO', 'shares':75},  
                {'name':'AOL', 'shares':20},  
                {'name':'SCOX', 'shares':65}  
             ]  
min_shares = min(s['shares'] for s in portfolio)  
print min_shares      
  
min_shares = min(portfolio, key=lambda s: s['shares'])  
print min_shares  
 1.20    将多个映射合并为单个映射
Java代码  
a = {'x':1, 'z':3}  
b = {'y':2, 'z':4}  
  
#from collections import ChainMap  
from pip._vendor.distlib.compat import ChainMap  
  
c = ChainMap(a, b)  
print(c['x'])  
print(c['y'])  
print(c['z']) #from a    第一个映射中的值  
  
print len(c)  
print list(c.values())  
  
c['z'] = 10  
c['w'] = 40  
del c['x']  
print a  
#del c['y']    #error    修改映射的操作总是会作用在列表的第一个映射结构上  
  
values = ChainMap()  
values['x'] = 1  
values = values.new_child()#add a new map  
values['x'] = 2  
values = values.new_child()  
values['x'] = 3  
#print values  
print values['x']  
values = values.parents  
print values['x']  
values = values.parents  
print values['x']  
  
a = {'x':1, 'z':3}  
b = {'y':2, 'z':4}  
merged = dict(b)  
merged.update(a)  
print merged['x']  
print merged['y']  
print merged['z']  
a['x'] = 13  
print merged['x']   #不会反应到合并后的字典中  
  
a = {'x':1, 'z':3}  
b = {'y':2, 'z':4}  
merged = ChainMap(a, b)  
print merged['x']  
a['x'] = 42  
print merged['x']   #会反应到合并后的字典中
Copier après la connexion

 


Déclaration de ce site Web
Le contenu de cet article est volontairement contribué par les internautes et les droits d'auteur appartiennent à l'auteur original. Ce site n'assume aucune responsabilité légale correspondante. Si vous trouvez un contenu suspecté de plagiat ou de contrefaçon, veuillez contacter admin@php.cn

Article chaud

Repo: Comment relancer ses coéquipiers
3 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌
Combien de temps faut-il pour battre Split Fiction?
3 Il y a quelques semaines By DDD
R.E.P.O. Crystals d'énergie expliqués et ce qu'ils font (cristal jaune)
1 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: Comment obtenir des graines géantes
3 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌

Article chaud

Repo: Comment relancer ses coéquipiers
3 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌
Combien de temps faut-il pour battre Split Fiction?
3 Il y a quelques semaines By DDD
R.E.P.O. Crystals d'énergie expliqués et ce qu'ils font (cristal jaune)
1 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: Comment obtenir des graines géantes
3 Il y a quelques semaines By 尊渡假赌尊渡假赌尊渡假赌

Tags d'article chaud

Bloc-notes++7.3.1

Bloc-notes++7.3.1

Éditeur de code facile à utiliser et gratuit

SublimeText3 version chinoise

SublimeText3 version chinoise

Version chinoise, très simple à utiliser

Envoyer Studio 13.0.1

Envoyer Studio 13.0.1

Puissant environnement de développement intégré PHP

Dreamweaver CS6

Dreamweaver CS6

Outils de développement Web visuel

SublimeText3 version Mac

SublimeText3 version Mac

Logiciel d'édition de code au niveau de Dieu (SublimeText3)

Comment télécharger Deepseek Xiaomi Comment télécharger Deepseek Xiaomi Feb 19, 2025 pm 05:27 PM

Comment télécharger Deepseek Xiaomi

Quels sont les avantages et les inconvénients des modèles ? Quels sont les avantages et les inconvénients des modèles ? May 08, 2024 pm 03:51 PM

Quels sont les avantages et les inconvénients des modèles ?

Google AI annonce Gemini 1.5 Pro et Gemma 2 pour les développeurs Google AI annonce Gemini 1.5 Pro et Gemma 2 pour les développeurs Jul 01, 2024 am 07:22 AM

Google AI annonce Gemini 1.5 Pro et Gemma 2 pour les développeurs

Pour seulement 250$, le directeur technique de Hugging Face vous apprend étape par étape comment peaufiner Llama 3 Pour seulement 250$, le directeur technique de Hugging Face vous apprend étape par étape comment peaufiner Llama 3 May 06, 2024 pm 03:52 PM

Pour seulement 250$, le directeur technique de Hugging Face vous apprend étape par étape comment peaufiner Llama 3

Partagez plusieurs frameworks de projets open source .NET liés à l'IA et au LLM Partagez plusieurs frameworks de projets open source .NET liés à l'IA et au LLM May 06, 2024 pm 04:43 PM

Partagez plusieurs frameworks de projets open source .NET liés à l'IA et au LLM

Un guide complet sur le débogage et l'analyse des fonctions Golang Un guide complet sur le débogage et l'analyse des fonctions Golang May 06, 2024 pm 02:00 PM

Un guide complet sur le débogage et l'analyse des fonctions Golang

Comment lui demandez-vous Deepseek Comment lui demandez-vous Deepseek Feb 19, 2025 pm 04:42 PM

Comment lui demandez-vous Deepseek

Comment enregistrer la fonction d'évaluation Comment enregistrer la fonction d'évaluation May 07, 2024 am 01:09 AM

Comment enregistrer la fonction d'évaluation

See all articles