pythonic_code

pythonic.py

# 列表对象（list）是一个查询效率高于更新操作的数据结构，比如删除一个元素和插入一个元素时执行效率就非常低，因为还要对剩下的元素进行移动
names = ['raymond', 'rachel', 'matthew', 'roger',
         'betty', 'melissa', 'judith', 'charlie']
names.pop(0)
names.insert(0, 'mark')

## pythonic
from collections import deque
names = deque(['raymond', 'rachel', 'matthew', 'roger',
               'betty', 'melissa', 'judith', 'charlie'])
names.popleft()
names.appendleft('mark')

#序列解包
p = 'vttalk', 'female', 30, 'python@qq.com'

name = p[0]
gender = p[1]
age = p[2]
email = p[3]

## pythonic
name, gender, age, email = p

# 带有索引位置的集合遍历
colors = ['red', 'green', 'blue', 'yellow']

for i in range(len(colors)):
    print (i, '--->', colors[i])

## pythonic
for i, color in enumerate(colors):
    print (i, '--->', color)

# 链式比较操作
age = 18
if age > 18 and age < 60:
    print("young man")

## pythonic
if 18 < age < 60:
    print("young man")

#for/else语句 : for else 是 Python 中特有的语法格式，else 中的代码在 for 循环遍历完所有元素之后执行。
flagfound = False
for i in mylist:
    if i == theflag:
        flagfound = True
        break
    process(i)

if not flagfound:
    raise ValueError("List argument missing terminal flag.")

## pythonic
for i in mylist:
    if i == theflag:
        break
    process(i)
else:
    raise ValueError("List argument missing terminal flag.")

# 获取字典元素
d = {'name': 'foo'}
if d.has_key('name'):
    print(d['name'])
else:
    print('unkonw')

## pythonic
d.get("name", "unknow")

# 预设字典默认值: 通过 key 分组的时候，不得不每次检查 key 是否已经存在于字典中。
data = [('foo', 10), ('bar', 20), ('foo', 39), ('bar', 49)]
groups = {}
for (key, value) in data:
    if key in groups:
        groups[key].append(value)
    else:
        groups[key] = [value]

## pythonic
###　第一种方式
groups = {}
for (key, value) in data:
    groups.setdefault(key, []).append(value)

### 第二种方式
from collections import defaultdict
groups = defaultdict(list)
for (key, value) in data:
    groups[key].append(value)

# 字典推导式
numbers = [1, 2, 3]
my_dict = {number: number * 2 for number in numbers}
print(my_dict)  # {1: 2, 2: 4, 3: 6}

## 还可以指定过滤条件
my_dict = {number: number * 2 for number in numbers if number > 1}
print(my_dict)  # {2: 4, 3: 6}

##不推荐
if my_dict.has_key(key):
    ...do something with d[key]

##推荐
if key in my_dict:
    ...do something with d[key]

## 解压可迭代对象赋值给多个变量
>>> record = ('Dave', 'dave@example.com', '773-555-1212', '847-555-1212')
>>> name, email, *phone_numbers = record
>>> name
'Dave'
>>> email
'dave@example.com'
>>> phone_numbers
['773-555-1212', '847-555-1212']

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)