1.1 拆箱
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
>>>
a
,
b
,
c
=
1
,
2
,
3
>>>
a
,
b
,
c
(
1
,
2
,
3
)
>>>
a
,
b
,
c
=
[
1
,
2
,
3
]
>>>
a
,
b
,
c
(
1
,
2
,
3
)
>>>
a
,
b
,
c
=
(
2
*
i
+
1
for
i
in
range
(
3
)
)
>>>
a
,
b
,
c
(
1
,
3
,
5
)
>>>
a
,
(
b
,
c
)
,
d
=
[
1
,
(
2
,
3
)
,
4
]
>>>
a
1
>>>
b
2
>>>
c
3
>>>
d
4
|
1.2 拆箱变量交换
|
1
2
3
4
|
>>>
a
,
b
=
1
,
2
>>>
a
,
b
=
b
,
a
>>>
a
,
b
(
2
,
1
)
|
1.3 扩展拆箱（只兼容python3）
|
1
2
3
4
5
6
7
|
>>>
a
,
*
b
,
c
=
[
1
,
2
,
3
,
4
,
5
]
>>>
a
1
>>>
b
[
2
,
3
,
4
]
>>>
c
5
|
1.4 负数索引
|
1
2
3
4
5
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
>>>
a
[
-
1
]
10
>>>
a
[
-
3
]
8
|
1.5 切割列表
|
1
2
3
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
>>>
a
[
2
:
8
]
[
2
,
3
,
4
,
5
,
6
,
7
]
|
1.6 负数索引切割列表
|
1
2
3
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
>>>
a
[
-
4
:
-
2
]
[
7
,
8
]
|
1.7指定步长切割列表
|
1
2
3
4
5
6
7
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
>>>
a
[
::
2
]
[
0
,
2
,
4
,
6
,
8
,
10
]
>>>
a
[
::
3
]
[
0
,
3
,
6
,
9
]
>>>
a
[
2
:
8
:
2
]
[
2
,
4
,
6
]
|
1.8 负数步长切割列表
|
1
2
3
4
5
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
]
>>>
a
[
::
-
1
]
[
10
,
9
,
8
,
7
,
6
,
5
,
4
,
3
,
2
,
1
,
0
]
>>>
a
[
::
-
2
]
[
10
,
8
,
6
,
4
,
2
,
0
]
|
1.9 列表切割赋值
|
1
2
3
4
5
6
7
8
9
10
|
>>>
a
=
[
1
,
2
,
3
,
4
,
5
]
>>>
a
[
2
:
3
]
=
[
0
,
0
]
>>>
a
[
1
,
2
,
0
,
0
,
4
,
5
]
>>>
a
[
1
:
1
]
=
[
8
,
9
]
>>>
a
[
1
,
8
,
9
,
2
,
0
,
0
,
4
,
5
]
>>>
a
[
1
:
-
1
]
=
[
]
>>>
a
[
1
,
5
]
|
1.10 命名列表切割方式
|
1
2
3
4
5
6
|
>>>
a
=
[
0
,
1
,
2
,
3
,
4
,
5
]
>>>
LASTTHREE
=
slice
(
-
3
,
None
)
>>>
LASTTHREE
slice
(
-
3
,
None
,
None
)
>>>
a
[
LASTTHREE
]
[
3
,
4
,
5
]
|
1.11 列表以及迭代器的压缩和解压缩
|
1
2
3
4
5
6
7
|
>>>
a
=
[
1
,
2
,
3
]
>>>
b
=
[
'a'
,
'b'
,
'c'
]
>>>
z
=
zip
(
a
,
b
)
>>>
z
[
(
1
,
'a'
)
,
(
2
,
'b'
)
,
(
3
,
'c'
)
]
>>>
zip
(
*
z
)
[
(
1
,
2
,
3
)
,
(
'a'
,
'b'
,
'c'
)
]
|
1.12 列表相邻元素压缩器
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
|
>>>
a
=
[
1
,
2
,
3
,
4
,
5
,
6
]
>>>
zip
(
*
(
[
iter
(
a
)
]
*
2
)
)
[
(
1
,
2
)
,
(
3
,
4
)
,
(
5
,
6
)
]
>>>
group_adjacent
=
lambda
a
,
k
:
zip
(
*
(
[
iter
(
a
)
]
*
k
)
)
>>>
group_adjacent
(
a
,
3
)
[
(
1
,
2
,
3
)
,
(
4
,
5
,
6
)
]
>>>
group_adjacent
(
a
,
2
)
[
(
1
,
2
)
,
(
3
,
4
)
,
(
5
,
6
)
]
>>>
group_adjacent
(
a
,
1
)
[
(
1
,
)
,
(
2
,
)
,
(
3
,
)
,
(
4
,
)
,
(
5
,
)
,
(
6
,
)
]
>>>
zip
(
a
[
::
2
]
,
a
[
1
::
2
]
)
[
(
1
,
2
)
,
(
3
,
4
)
,
(
5
,
6
)
]
>>>
zip
(
a
[
::
3
]
,
a
[
1
::
3
]
,
a
[
2
::
3
]
)
[
(
1
,
2
,
3
)
,
(
4
,
5
,
6
)
]
>>>
group_adjacent
=
lambda
a
,
k
:
zip
(
*
(
a
[
i
::
k
]
for
i
in
range
(
k
)
)
)
>>>
group_adjacent
(
a
,
3
)
[
(
1
,
2
,
3
)
,
(
4
,
5
,
6
)
]
>>>
group_adjacent
(
a
,
2
)
[
(
1
,
2
)
,
(
3
,
4
)
,
(
5
,
6
)
]
>>>
group_adjacent
(
a
,
1
)
[
(
1
,
)
,
(
2
,
)
,
(
3
,
)
,
(
4
,
)
,
(
5
,
)
,
(
6
,
)
]
|
1.13 在列表中用压缩器和迭代器滑动取值窗口
|
1
2
3
4
5
6
7
8
9
10
11
|
>>>
def
n_grams
(
a
,
n
)
:
.
.
.
z
=
[
iter
(
a
[
i
:
]
)
for
i
in
range
(
n
)
]
.
.
.
return
zip
(
*
z
)
.
.
.
>>>
a
=
[
1
,
2
,
3
,
4
,
5
,
6
]
>>>
n_grams
(
a
,
3
)
[
(
1
,
2
,
3
)
,
(
2
,
3
,
4
)
,
(
3
,
4
,
5
)
,
(
4
,
5
,
6
)
]
>>>
n_grams
(
a
,
2
)
[
(
1
,
2
)
,
(
2
,
3
)
,
(
3
,
4
)
,
(
4
,
5
)
,
(
5
,
6
)
]
>>>
n_grams
(
a
,
4
)
[
(
1
,
2
,
3
,
4
)
,
(
2
,
3
,
4
,
5
)
,
(
3
,
4
,
5
,
6
)
]
|
1.14 用压缩器反转字典
|
1
2
3
4
5
6
7
8
|
>>>
m
=
{
'a'
:
1
,
'b'
:
2
,
'c'
:
3
,
'd'
:
4
}
>>>
m
.
items
(
)
[
(
'a'
,
1
)
,
(
'c'
,
3
)
,
(
'b'
,
2
)
,
(
'd'
,
4
)
]
>>>
zip
(
m
.
values
(
)
,
m
.
keys
(
)
)
[
(
1
,
'a'
)
,
(
3
,
'c'
)
,
(
2
,
'b'
)
,
(
4
,
'd'
)
]
>>>
mi
=
dict
(
zip
(
m
.
values
(
)
,
m
.
keys
(
)
)
)
>>>
mi
{
1
:
'a'
,
2
:
'b'
,
3
:
'c'
,
4
:
'd'
}
|
1.15 列表展开
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
>>>
a
=
[
[
1
,
2
]
,
[
3
,
4
]
,
[
5
,
6
]
]
>>>
list
(
itertools
.
chain
.
from_iterable
(
a
)
)
[
1
,
2
,
3
,
4
,
5
,
6
]
>>>
sum
(
a
,
[
]
)
[
1
,
2
,
3
,
4
,
5
,
6
]
>>>
[
x
for
l
in
a
for
x
in
l
]
[
1
,
2
,
3
,
4
,
5
,
6
]
>>>
a
=
[
[
[
1
,
2
]
,
[
3
,
4
]
]
,
[
[
5
,
6
]
,
[
7
,
8
]
]
]
>>>
[
x
for
l1
in
a
for
l2
in
l1
for
x
in
l2
]
[
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
]
>>>
a
=
[
1
,
2
,
[
3
,
4
]
,
[
[
5
,
6
]
,
[
7
,
8
]
]
]
>>>
flatten
=
lambda
x
:
[
y
for
l
in
x
for
y
in
flatten
(
l
)
]
if
type
(
x
)
is
list
else
[
x
]
>>>
flatten
(
a
)
[
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
]
|
1.16 生成器表达式
|
1
2
3
4
5
6
7
8
9
10
11
12
13
|
>>>
g
=
(
x
*
*
2
for
x
in
xrange
(
10
)
)
>>>
next
(
g
)
0
>>>
next
(
g
)
1
>>>
next
(
g
)
4
>>>
next
(
g
)
9
>>>
sum
(
x
*
*
3
for
x
in
xrange
(
10
)
)
2025
>>>
sum
(
x
*
*
3
for
x
in
xrange
(
10
)
if
x
%
3
==
1
)
408
|
1.17 字典推导
|
1
2
3
4
5
6
7
|
>>>
m
=
{
x
:
x
*
*
2
for
x
in
range
(
5
)
}
>>>
m
{
0
:
0
,
1
:
1
,
2
:
4
,
3
:
9
,
4
:
16
}
>>>
m
=
{
x
:
'A'
+
str
(
x
)
for
x
in
range
(
10
)
}
>>>
m
{
0
:
'A0'
,
1
:
'A1'
,
2
:
'A2'
,
3
:
'A3'
,
4
:
'A4'
,
5
:
'A5'
,
6
:
'A6'
,
7
:
'A7'
,
8
:
'A8'
,
9
:
'A9'
}
|
1.18 用字典推导反转字典
|
1
2
3
4
5
|
>>>
m
=
{
'a'
:
1
,
'b'
:
2
,
'c'
:
3
,
'd'
:
4
}
>>>
m
{
'd'
:
4
,
'a'
:
1
,
'b'
:
2
,
'c'
:
3
}
>>>
{
v
:
k
for
k
,
v
in
m
.
items
(
)
}
{
1
:
'a'
,
2
:
'b'
,
3
:
'c'
,
4
:
'd'
}
|
1.19 命名元组
|
1
2
3
4
5
6
7
8
|
>>>
Point
=
collections
.
namedtuple
(
'Point'
,
[
'x'
,
'y'
]
)
>>>
p
=
Point
(
x
=
1.0
,
y
=
2.0
)
>>>
p
Point
(
x
=
1.0
,
y
=
2.0
)
>>>
p
.
x
1.0
>>>
p
.
y
2.0
|
1.20 继承命名元组
|
1
2
3
4
5
6
7
8
9
|
>>>
class
Point
(
collections
.
namedtuple
(
'PointBase'
,
[
'x'
,
'y'
]
)
)
:
.
.
.
__slots__
=
(
)
.
.
.
def
__add__
(
self
,
other
)
:
.
.
.
return
Point
(
x
=
self
.
x
+
other
.
x
,
y
=
self
.
y
+
other
.
y
)
.
.
.
>>>
p
=
Point
(
x
=
1.0
,
y
=
2.0
)
>>>
q
=
Point
(
x
=
2.0
,
y
=
3.0
)
>>>
p
+
q
Point
(
x
=
3.0
,
y
=
5.0
)
|
1.21 操作集合
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
>>>
A
=
{
1
,
2
,
3
,
3
}
>>>
A
set
(
[
1
,
2
,
3
]
)
>>>
B
=
{
3
,
4
,
5
,
6
,
7
}
>>>
B
set
(
[
3
,
4
,
5
,
6
,
7
]
)
>>>
A
|
B
set
(
[
1
,
2
,
3
,
4
,
5
,
6
,
7
]
)
>>>
A
&
B
set
(
[
3
]
)
>>>
A
-
B
set
(
[
1
,
2
]
)
>>>
B
-
A
set
(
[
4
,
5
,
6
,
7
]
)
>>>
A
^
B
set
(
[
1
,
2
,
4
,
5
,
6
,
7
]
)
>>>
(
A
^
B
)
==
(
(
A
-
B
)
|
(
B
-
A
)
)
True
|
1.22 操作多重集合
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
|
>>>
A
=
collections
.
Counter
(
[
1
,
2
,
2
]
)
>>>
B
=
collections
.
Counter
(
[
2
,
2
,
3
]
)
>>>
A
Counter
(
{
2
:
2
,
1
:
1
}
)
>>>
B
Counter
(
{
2
:
2
,
3
:
1
}
)
>>>
A
|
B
Counter
(
{
2
:
2
,
1
:
1
,
3
:
1
}
)
>>>
A
&
B
Counter
(
{
2
:
2
}
)
>>>
A
+
B
Counter
(
{
2
:
4
,
1
:
1
,
3
:
1
}
)
>>>
A
-
B
Counter
(
{
1
:
1
}
)
>>>
B
-
A
Counter
(
{
3
:
1
}
)
|
1.23 统计在可迭代器中最常出现的元素
|
1
2
3
4
5
6
7
|
>>>
A
=
collections
.
Counter
(
[
1
,
1
,
2
,
2
,
3
,
3
,
3
,
3
,
4
,
5
,
6
,
7
]
)
>>>
A
Counter
(
{
3
:
4
,
1
:
2
,
2
:
2
,
4
:
1
,
5
:
1
,
6
:
1
,
7
:
1
}
)
>>>
A
.
most_common
(
1
)
[
(
3
,
4
)
]
>>>
A
.
most_common
(
3
)
[
(
3
,
4
)
,
(
1
,
2
)
,
(
2
,
2
)
]
|
1.24 两端都可操作的队列
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
|
>>>
Q
=
collections
.
deque
(
)
>>>
Q
.
append
(
1
)
>>>
Q
.
appendleft
(
2
)
>>>
Q
.
extend
(
[
3
,
4
]
)
>>>
Q
.
extendleft
(
[
5
,
6
]
)
>>>
Q
deque
(
[
6
,
5
,
2
,
1
,
3
,
4
]
)
>>>
Q
.
pop
(
)
4
>>>
Q
.
popleft
(
)
6
>>>
Q
deque
(
[
5
,
2
,
1
,
3
]
)
>>>
Q
.
rotate
(
3
)
>>>
Q
deque
(
[
2
,
1
,
3
,
5
]
)
>>>
Q
.
rotate
(
-
3
)
>>>
Q
deque
(
[
5
,
2
,
1
,
3
]
)
|
1.25 有最大长度的双端队列
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
|
>>>
last_three
=
collections
.
deque
(
maxlen
=
3
)
>>>
for
i
in
xrange
(
10
)
:
.
.
.
last_three
.
append
(
i
)
.
.
.
print
', '
.
join
(
str
(
x
)
for
x
in
last_three
)
.
.
.
0
0
,
1
0
,
1
,
2
1
,
2
,
3
2
,
3
,
4
3
,
4
,
5
4
,
5
,
6
5
,
6
,
7
6
,
7
,
8
7
,
8
,
9
|
1.26 可排序词典
|
1
2
3
4
5
6
7
8
9
|
>>>
m
=
dict
(
(
str
(
x
)
,
x
)
for
x
in
range
(
10
)
)
>>>
print
', '
.
join
(
m
.
keys
(
)
)
1
,
0
,
3
,
2
,
5
,
4
,
7
,
6
,
9
,
8
>>>
m
=
collections
.
OrderedDict
(
(
str
(
x
)
,
x
)
for
x
in
range
(
10
)
)
>>>
print
', '
.
join
(
m
.
keys
(
)
)
0
,
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
>>>
m
=
collections
.
OrderedDict
(
(
str
(
x
)
,
x
)
for
x
in
range
(
10
,
0
,
-
1
)
)
>>>
print
', '
.
join
(
m
.
keys
(
)
)
10
,
9
,
8
,
7
,
6
,
5
,
4
,
3
,
2
,
1
|
1.27 默认词典
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
|
>>>
m
=
dict
(
)
>>>
m
[
'a'
]
Traceback
(
most
recent
call
last
)
:
File
"<stdin>"
,
line
1
,
in
<
module
>
KeyError
:
'a'
>>>
>>>
m
=
collections
.
defaultdict
(
int
)
>>>
m
[
'a'
]
0
>>>
m
[
'b'
]
0
>>>
m
=
collections
.
defaultdict
(
str
)
>>>
m
[
'a'
]
''
>>>
m
[
'b'
]
+=
'a'
>>>
m
[
'b'
]
'a'
>>>
m
=
collections
.
defaultdict
(
lambda
:
'[default value]'
)
>>>
m
[
'a'
]
'[default value]'
>>>
m
[
'b'
]
'[default value]'
|
1.28 默认字典的简单树状表达
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
|
>>>
import
json
>>>
tree
=
lambda
:
collections
.
defaultdict
(
tree
)
>>>
root
=
tree
(
)
>>>
root
[
'menu'
]
[
'id'
]
=
'file'
>>>
root
[
'menu'
]
[
'value'
]
=
'File'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'new'
]
[
'value'
]
=
'New'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'new'
]
[
'onclick'
]
=
'new();'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'open'
]
[
'value'
]
=
'Open'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'open'
]
[
'onclick'
]
=
'open();'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'close'
]
[
'value'
]
=
'Close'
>>>
root
[
'menu'
]
[
'menuitems'
]
[
'close'
]
[
'onclick'
]
=
'close();'
>>>
print
json
.
dumps
(
root
,
sort_keys
=
True
,
indent
=
4
,
separators
=
(
','
,
': '
)
)
{
"menu"
:
{
"id"
:
"file"
,
"menuitems"
:
{
"close"
:
{
"onclick"
:
"close();"
,
"value"
:
"Close"
}
,
"new"
:
{
"onclick"
:
"new();"
,
"value"
:
"New"
}
,
"open"
:
{
"onclick"
:
"open();"
,
"value"
:
"Open"
}
}
,
"value"
:
"File"
}
}
|
1.29 对象到唯一计数的映射
|
1
2
3
4
5
6
7
8
9
10
11
12
|
>>>
import
itertools
,
collections
>>>
value_to_numeric_map
=
collections
.
defaultdict
(
itertools
.
count
(
)
.
next
)
>>>
value_to_numeric_map
[
'a'
]
0
>>>
value_to_numeric_map
[
'b'
]
1
>>>
value_to_numeric_map
[
'c'
]
2
>>>
value_to_numeric_map
[
'a'
]
0
>>>
value_to_numeric_map
[
'b'
]
1
|
1.30 最大和最小的几个列表元素
|
1
2
3
4
5
|
>>>
a
=
[
random
.
randint
(
0
,
100
)
for
__
in
xrange
(
100
)
]
>>>
heapq
.
nsmallest
(
5
,
a
)
[
3
,
3
,
5
,
6
,
8
]
>>>
heapq
.
nlargest
(
5
,
a
)
[
100
,
100
,
99
,
98
,
98
]
|
1.31 两个列表的笛卡尔积
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
|
>>>
for
p
in
itertools
.
product
(
[
1
,
2
,
3
]
,
[
4
,
5
]
)
:
(
1
,
4
)
(
1
,
5
)
(
2
,
4
)
(
2
,
5
)
(
3
,
4
)
(
3
,
5
)
>>>
for
p
in
itertools
.
product
(
[
0
,
1
]
,
repeat
=
4
)
:
.
.
.
print
''
.
join
(
str
(
x
)
for
x
in
p
)
.
.
.
0000
0001
0010
0011
0100
0101
0110
0111
1000
1001
1010
1011
1100
1101
1110
1111
|
1.32 列表组合和列表元素替代组合
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
|
>>>
for
c
in
itertools
.
combinations
(
[
1
,
2
,
3
,
4
,
5
]
,
3
)
:
.
.
.
print
''
.
join
(
str
(
x
)
for
x
in
c
)
.
.
.
123
124
125
134
135
145
234
235
245
345
>>>
for
c
in
itertools
.
combinations_with_replacement
(
[
1
,
2
,
3
]
,
2
)
:
.
.
.
print
''
.
join
(
str
(
x
)
for
x
in
c
)
.
.
.
11
12
13
22
23
33
|
1.33 列表元素排列组合
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
|
>>>
for
p
in
itertools
.
permutations
(
[
1
,
2
,
3
,
4
]
)
:
.
.
.
print
''
.
join
(
str
(
x
)
for
x
in
p
)
.
.
.
1234
1243
1324
1342
1423
1432
2134
2143
2314
2341
2413
2431
3124
3142
3214
3241
3412
3421
4123
4132
4213
4231
4312
4321
|
1.34 可链接迭代器
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
|
>>>
a
=
[
1
,
2
,
3
,
4
]
>>>
for
p
in
itertools
.
chain
(
itertools
.
combinations
(
a
,
2
)
,
itertools
.
combinations
(
a
,
3
)
)
:
.
.
.
print
p
.
.
.
(
1
,
2
)
(
1
,
3
)
(
1
,
4
)
(
2
,
3
)
(
2
,
4
)
(
3
,
4
)
(
1
,
2
,
3
)
(
1
,
2
,
4
)
(
1
,
3
,
4
)
(
2
,
3
,
4
)
>>>
for
subset
in
itertools
.
chain
.
from_iterable
(
itertools
.
combinations
(
a
,
n
)
for
n
in
range
(
len
(
a
)
+
1
)
)
.
.
.
print
subset
.
.
.
(
)
(
1
,
)
(
2
,
)
(
3
,
)
(
4
,
)
(
1
,
2
)
(
1
,
3
)
(
1
,
4
)
(
2
,
3
)
(
2
,
4
)
(
3
,
4
)
(
1
,
2
,
3
)
(
1
,
2
,
4
)
(
1
,
3
,
4
)
(
2
,
3
,
4
)
(
1
,
2
,
3
,
4
)
|
1.35 根据文件指定列类聚
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
|
>>>
import
itertools
>>>
with
open
(
'contactlenses.csv'
,
'r'
)
as
infile
:
.
.
.
data
=
[
line
.
strip
(
)
.
split
(
','
)
for
line
in
infile
]
.
.
.
>>>
data
=
data
[
1
:
]
>>>
def
print_data
(
rows
)
:
.
.
.
print
'\n'
.
join
(
'\t'
.
join
(
'{: <16}'
.
format
(
s
)
for
s
in
row
)
for
row
in
rows
)
.
.
.
>>>
print_data
(
data
)
young
myope
no
reduced
none
young
myope
no
normal
soft
young
myope
yes
reduced
none
young
myope
yes
normal
hard
young
hypermetrope
no
reduced
none
young
hypermetrope
no
normal
soft
young
hypermetrope
yes
reduced
none
young
hypermetrope
yes
normal
hard
pre
-
presbyopic
myope
no
reduced
none
pre
-
presbyopic
myope
no
normal
soft
pre
-
presbyopic
myope
yes
reduced
none
pre
-
presbyopic
myope
yes
normal
hard
pre
-
presbyopic
hypermetrope
no
reduced
none
pre
-
presbyopic
hypermetrope
no
normal
soft
pre
-
presbyopic
hypermetrope
yes
reduced
none
pre
-
presbyopic
hypermetrope
yes
normal
none
presbyopic
myope
no
reduced
none
presbyopic
myope
no
normal
none
presbyopic
myope
yes
reduced
none
presbyopic
myope
yes
normal
hard
presbyopic
hypermetrope
no
reduced
none
presbyopic
hypermetrope
no
normal
soft
presbyopic
hypermetrope
yes
reduced
none
presbyopic
hypermetrope
yes
normal
none
>>>
data
.
sort
(
key
=
lambda
r
:
r
[
-
1
]
)
>>>
for
value
,
group
in
itertools
.
groupby
(
data
,
lambda
r
:
r
[
-
1
]
)
:
.
.
.
print
'-----------'
.
.
.
print
'Group: '
+
value
.
.
.
print_data
(
group
)
.
.
.
--
--
--
--
--
-
Group
:
hard
young
myope
yes
normal
hard
young
hypermetrope
yes
normal
hard
pre
-
presbyopic
myope
yes
normal
hard
presbyopic
myope
yes
normal
hard
--
--
--
--
--
-
Group
:
none
young
myope
no
reduced
none
young
myope
yes
reduced
none
young
hypermetrope
no
reduced
none
young
hypermetrope
yes
reduced
none
pre
-
presbyopic
myope
no
reduced
none
pre
-
presbyopic
myope
yes
reduced
none
pre
-
presbyopic
hypermetrope
no
reduced
none
pre
-
presbyopic
hypermetrope
yes
reduced
none
pre
-
presbyopic
hypermetrope
yes
normal
none
presbyopic
myope
no
reduced
none
presbyopic
myope
no
normal
none
presbyopic
myope
yes
reduced
none
presbyopic
hypermetrope
no
reduced
none
presbyopic
hypermetrope
yes
reduced
none
presbyopic
hypermetrope
yes
normal
none
--
--
--
--
--
-
Group
:
soft
young
myope
no
normal
soft
young
hypermetrope
no
normal
soft
pre
-
presbyopic
myope
no
normal
soft
pre
-
presbyopic
hypermetrope
no
normal
soft
presbyopic
hypermetrope
no
normal
|