On the other hand, with behavior B, getting the effect of behavior A is significantly more complicated:

```
def parse_pure_int(s):
if "." in s:
raise ValueError("invalid literal for integer with base 10: " + s)
return int(s)
```

One can cast float objects to int objects by discarding the fraction part using the int() function. This function demonstrates so called rounding towards zero behavior:,We already know the following operators which may be applied to numbers: +, -, * and **. The division operator / for integers gives a floating-point real number (an object of type float). The exponentiation ** also returns a float when the power is negative:,Floating-point real numbers can't be represented with exact precision due to hardware limitations. This can lead to cumbersome effects. See the Python docs for the details.,There's a special operation for integer division where the remainder is discarded: //. The operation that yields a remainder of such a division looks like %. Both operation always yield an object of type int.

`None`

None

print(17 / 3) # gives 5.66666666667 print(2 ** 4) # gives 16 print(2 ** -2) # gives 0.25

`None`

None

print(17 / 3) # gives 5.66666666667 print(17 // 3) # gives 5 print(17 % 3) # gives 2

1.492

1.492

x = float(input()) print(x)

`None`

None

print(int(1.3)) # gives 1 print(int(1.7)) # gives 1 print(int(-1.3)) # gives - 1 print(int(-1.7)) # gives - 1

`None`

None

print(round(1.3)) # gives 1 print(round(1.7)) # gives 2 print(round(-1.3)) # gives - 1 print(round(-1.7)) # gives - 2

`None`

None

print(0.1 + 0.2) # gives 0.30000000000000004

Last Updated : 16 Jul, 2022

```
Input: 3.3
Output: 3
Input: 5.99
Output: 5
```

type: float converted value: 9, type: int

type: float converted value: 9, type: int

5 6

```
the result using floor(): 5, type: int
the result using ceil(): 6, type: int
```

Type: float Original number is: 5.6 Type: int the result using round: 6

This issue tracker has been migrated to GitHub, and is currently read-only. For more information, see the GitHub FAQs in the Python's Developer Guide., This issue has been migrated to GitHub: https://github.com/python/cpython/issues/83617

When python compares float and int created from the same int number should be equal like int(1) == float(1) but from 9007199254740993 this is not true. int(9007199254740993) == float(9007199254740993) is not true.The same behavior is for bigger odd numbers.The even numbers are still equal.So it looks like: int(9007199254740989) == float(9007199254740989) # True int(9007199254740990) == float(9007199254740990) # True int(9007199254740991) == float(9007199254740991) # True int(9007199254740992) == float(9007199254740992) # True int(9007199254740993) == float(9007199254740993) # False int(9007199254740994) == float(9007199254740994) # True int(9007199254740995) == float(9007199254740995) # False int(9007199254740996) == float(9007199254740996) # True int(9007199254740997) == float(9007199254740997) # False int(9007199254740998) == float(9007199254740998) # True

`Python floats have 53 bits of precision, so ints larger than 2 ** 53 will lose their lower bits(assumed to be 0) when converted.`

```
Further to what Matthew said, this is not just a Python oddity.It applies to just about all programming languages, including C, C++, Java, Javascript, Ruby, etc.Some of them have even less precision by
default.
Floats are not the same as the real numbers you learned about in school.There is a huge amount of resources about the limitations of floating point arithmetic on Stackoverflow etc which can be found by googling.A good place to start is the Python FAQs and tutorial:
https: //docs.python.org/3/faq/design.html#why-are-floating-point-calculations-so-inaccurate
https: //docs.python.org/3/tutorial/floatingpoint.html#tut-fp-issues
```

The constructors int(), float(), and complex() can be used to produce numbers of a specific type.,All numeric types (except complex) support the following operations (for priorities of the operations, see Operator precedence):,Not for complex numbers. Instead convert to floats using abs() if appropriate.,The range type represents an immutable sequence of numbers and is commonly used for looping a specific number of times in for loops.

```
>>> n = -37 >>>
bin(n)
'-0b100101' >>>
n.bit_length()
6
```

```
def bit_length(self):
s = bin(self) # binary representation: bin(-37) -- > '-0b100101'
s = s.lstrip('-0b') # remove leading zeros and minus sign
return len(s) # len('100101') -- > 6
```

```
>>> n = 19 >>>
bin(n)
'0b10011' >>>
n.bit_count()
3
>>>
(-n).bit_count()
3
```

```
def bit_count(self):
return bin(self).count("1")
```

```
>>> (1024).to_bytes(2, byteorder = 'big')
b '\x04\x00' >>>
(1024).to_bytes(10, byteorder = 'big')
b '\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00' >>>
(-1024).to_bytes(10, byteorder = 'big', signed = True)
b '\xff\xff\xff\xff\xff\xff\xff\xff\xfc\x00' >>>
x = 1000 >>>
x.to_bytes((x.bit_length() + 7) // 8, byteorder='little')
b '\xe8\x03'
```

```
>>> int.from_bytes(b '\x00\x10', byteorder = 'big')
16
>>>
int.from_bytes(b '\x00\x10', byteorder = 'little')
4096
>>>
int.from_bytes(b '\xfc\x00', byteorder = 'big', signed = True) -
1024 >>>
int.from_bytes(b '\xfc\x00', byteorder = 'big', signed = False)
64512
>>>
int.from_bytes([255, 0, 0], byteorder = 'big')
16711680
```

Every value in a program has a specific type.,Every value has a type.,Every value has a type. ,A value’s type determines what the program can do to it.

print(type(52))

`<class 'int'>`

```
fitness = 'average'
print(type(fitness))
```

`<class 'str'>`

print(5 - 3)

2