Python Learning record-1

Change in place, fast:

The first way:

>>> a=[1,2,3]

>>> B=a

>>> a.extend ([4,5])

>>> A

[1, 2, 3, 4, 5]

>>> b

[1, 2, 3, 4, 5]

The second way:

>>> a=[1,2,3]

>>> B=a

>>> a+=[4,5]

>>> A

[1, 2, 3, 4, 5]

>>> b

[1, 2, 3, 4, 5]

Merge:

>>> A

[1, 2, 3]

>>> B=a

>>> A=a+[4]

>>> A

[1, 2, 3, 4]

>>> b

[1, 2, 3]

For the two ways to traverse the dictionary:

>>> d={' A ': 1, ' B ': 2, ' C ': 3}

>>> for key in D:

... print (key, ' = = ', D[key])

...

b = 2

A = 1

c = 3

>>> list (D.items ())

[(' B ', 2), (' A ', 1), (' C ', 3)]

>>> for (Key,value) in D.items ():

... print (key, ' = = ', value)

...

b = 2

A = 1

c = 3

The For loop generally runs faster than the while counter. Because iterators run at the speed of the C language in Python, while the while loop version runs Python bytecode through a Python virtual machine.

ReadLines will read the file in memory at once, not suitable for large files.

Lists, as well as many other built-in objects, are not their own iterators, because they support opening iterators multiple times. For such an object, we must call ITER to start the iteration:

>>> l=[1,2,3]

>>> ITER (L) is L

False

>>> l.__next__ ()

Traceback (most recent):

File "<stdin>", line 1, in <module>

Attributeerror: ' List ' object has no attribute ' __next__ '

>>> A=iter (L)

>>> a.__next__ ()

1

>>> Next (a)

2

Two types of inverse of list parsing:

Slow:

>>> l=[1,2,3,4,5]

>>> for I in range (len (L)):

... l[i]+=10

...

>>> L

[11, 12, 13, 14, 15]

Fast:

>>> l=[x+10 for x in L]

>>> L

[21, 22, 23, 24, 25]

Python Learning record-1