What Is the Reason for Having '//' in Python

What does In [*] in IPython Notebook mean and how to turn it off?

The kernel is busy. Go to the menu Kernel and click Interrupt. If this does not work click Restart. You need to go in a new cell and press Shift + Enter to see if it worked.

What is the difference between '/' and '//' when used for division?

In Python 3.x, 5 / 2 will return 2.5 and 5 // 2 will return 2. The former is floating point division, and the latter is floor division, sometimes also called integer division.

In Python 2.2 or later in the 2.x line, there is no difference for integers unless you perform a from __future__ import division, which causes Python 2.x to adopt the 3.x behavior.

Regardless of the future import, 5.0 // 2 will return 2.0 since that's the floor division result of the operation.

You can find a detailed description at PEP 238: Changing the Division Operator.

What is the purpose of the `//` operator in python?

Integer division vs. float division:

>>> 5.0/3
3: 1.6666666666666667
>>> 5.0//3
4: 1.0

Or as they put it in the Python docs, // is "(floored) quotient of x and y". The above example was run in Python 2.7.2, which only behaves that way for floating point numbers. If you were to use integers in 2.7.2 you'd get:

>>> 5/3
9: 1
>>> 5//3
10: 1

In Python 3.x you get different results, so if you really want the floored version, get into the habit of using // as some day it'll matter:

Python 3.2.2 (default, Sep  4 2011, 09:51:08) [MSC v.1500 32 bit (Intel)] on win32
Type "copyright", "credits" or "license()" for more information.
>>> 5/3
1.6666666666666667
>>> 5//3
1
>>> 5.0/3
1.6666666666666667
>>> 5.0//3
1.0

What is the purpose of the single underscore _ variable in Python?

_ has 3 main conventional uses in Python:

To hold the result of the last executed expression in an interactive
interpreter session (see docs). This precedent was set by the standard CPython
interpreter, and other interpreters have followed suit
For translation lookup in i18n (see the
gettext
documentation for example), as in code like
```
raise forms.ValidationError(_("Please enter a correct username"))
```
As a general purpose "throwaway" variable name:
1. To indicate that part
  of a function result is being deliberately ignored (Conceptually, it is being discarded.), as in code like:
```
label, has_label, _ = text.partition(':')
```
2. As part of a function definition (using either def or lambda), where
  the signature is fixed (e.g. by a callback or parent class API), but
  this particular function implementation doesn't need all of the
  parameters, as in code like:
```
def callback(_):
    return True
```
  [For a long time this answer didn't list this use case, but it came up often enough, as noted here, to be worth listing explicitly.]
This use case can conflict with the translation lookup use case, so it is necessary to avoid using _ as a throwaway variable in any code block that also uses it for i18n translation (many folks prefer a double-underscore, __, as their throwaway variable for exactly this reason).
Linters often recognize this use case. For example year, month, day = date() will raise a lint warning if day is not used later in the code. The fix, if day is truly not needed, is to write year, month, _ = date(). Same with lambda functions, lambda arg: 1.0 creates a function requiring one argument but not using it, which will be caught by lint. The fix is to write lambda _: 1.0. An unused variable is often hiding a bug/typo (e.g. set day but use dya in the next line).
The pattern matching feature added in Python 3.10 elevated this usage from "convention" to "language syntax" where match statements are concerned: in match cases, _ is a wildcard pattern, and the runtime doesn't even bind a value to the symbol in that case.
For other use cases, remember that _ is still a valid variable name, and hence will still keep objects alive. In cases where this is undesirable (e.g. to release memory or external resources) an explicit del name call will both satisfy linters that the name is being used, and promptly clear the reference to the object.

When should I be using classes in Python?

Classes are the pillar of Object Oriented Programming. OOP is highly concerned with code organization, reusability, and encapsulation.

First, a disclaimer: OOP is partially in contrast to Functional Programming, which is a different paradigm used a lot in Python. Not everyone who programs in Python (or surely most languages) uses OOP. You can do a lot in Java 8 that isn't very Object Oriented. If you don't want to use OOP, then don't. If you're just writing one-off scripts to process data that you'll never use again, then keep writing the way you are.

However, there are a lot of reasons to use OOP.

Some reasons:

Organization:
OOP defines well known and standard ways of describing and defining both data and procedure in code. Both data and procedure can be stored at varying levels of definition (in different classes), and there are standard ways about talking about these definitions. That is, if you use OOP in a standard way, it will help your later self and others understand, edit, and use your code. Also, instead of using a complex, arbitrary data storage mechanism (dicts of dicts or lists or dicts or lists of dicts of sets, or whatever), you can name pieces of data structures and conveniently refer to them.
State: OOP helps you define and keep track of state. For instance, in a classic example, if you're creating a program that processes students (for instance, a grade program), you can keep all the info you need about them in one spot (name, age, gender, grade level, courses, grades, teachers, peers, diet, special needs, etc.), and this data is persisted as long as the object is alive, and is easily accessible. In contrast, in pure functional programming, state is never mutated in place.
Encapsulation:
With encapsulation, procedure and data are stored together. Methods (an OOP term for functions) are defined right alongside the data that they operate on and produce. In a language like Java that allows for access control, or in Python, depending upon how you describe your public API, this means that methods and data can be hidden from the user. What this means is that if you need or want to change code, you can do whatever you want to the implementation of the code, but keep the public APIs the same.
Inheritance:
Inheritance allows you to define data and procedure in one place (in one class), and then override or extend that functionality later. For instance, in Python, I often see people creating subclasses of the dict class in order to add additional functionality. A common change is overriding the method that throws an exception when a key is requested from a dictionary that doesn't exist to give a default value based on an unknown key. This allows you to extend your own code now or later, allow others to extend your code, and allows you to extend other people's code.
Reusability: All of these reasons and others allow for greater reusability of code. Object oriented code allows you to write solid (tested) code once, and then reuse over and over. If you need to tweak something for your specific use case, you can inherit from an existing class and overwrite the existing behavior. If you need to change something, you can change it all while maintaining the existing public method signatures, and no one is the wiser (hopefully).

Again, there are several reasons not to use OOP, and you don't need to. But luckily with a language like Python, you can use just a little bit or a lot, it's up to you.

An example of the student use case (no guarantee on code quality, just an example):

Object Oriented

class Student(object):
    def __init__(self, name, age, gender, level, grades=None):
        self.name = name
        self.age = age
        self.gender = gender
        self.level = level
        self.grades = grades or {}

    def setGrade(self, course, grade):
        self.grades[course] = grade

    def getGrade(self, course):
        return self.grades[course]

    def getGPA(self):
        return sum(self.grades.values())/len(self.grades)

# Define some students
john = Student("John", 12, "male", 6, {"math":3.3})
jane = Student("Jane", 12, "female", 6, {"math":3.5})

# Now we can get to the grades easily
print(john.getGPA())
print(jane.getGPA())

Standard Dict

def calculateGPA(gradeDict):
    return sum(gradeDict.values())/len(gradeDict)

students = {}
# We can set the keys to variables so we might minimize typos
name, age, gender, level, grades = "name", "age", "gender", "level", "grades"
john, jane = "john", "jane"
math = "math"
students[john] = {}
students[john][age] = 12
students[john][gender] = "male"
students[john][level] = 6
students[john][grades] = {math:3.3}

students[jane] = {}
students[jane][age] = 12
students[jane][gender] = "female"
students[jane][level] = 6
students[jane][grades] = {math:3.5}

# At this point, we need to remember who the students are and where the grades are stored. Not a huge deal, but avoided by OOP.
print(calculateGPA(students[john][grades]))
print(calculateGPA(students[jane][grades]))

What is the purpose of the colon before a block in Python?

The colon is there to declare the start of an indented block.

Technically, it's not necessary; you could just indent and de-indent when the block is done. However, based on the Python koan “explicit is better than implicit” (EIBTI), I believe that Guido deliberately made the colon obligatory, so any statement that should be followed by indented code ends in a colon. (It also allows one-liners if you continue after the colon, but this style is not in wide use.)

It also makes the work of syntax-aware auto-indenting editors easier, which also counted in the decision.

This question turns out to be a Python FAQ, and I found one of its answers by Guido here:

Why are colons required for the if/while/def/class statements?

The colon is required primarily to enhance readability (one of the results of the experimental ABC language). Consider this:
if a == b 
    print a
versus
if a == b: 
    print a
Notice how the second one is slightly easier to read. Notice further how a colon sets off the example in this FAQ answer; it’s a standard usage in English.

Another minor reason is that the colon makes it easier for editors with syntax highlighting; they can look for colons to decide when indentation needs to be increased instead of having to do a more elaborate parsing of the program text.