python float and int behavior

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)

Suggestion : 2

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.

1._

None

None

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

1._

None

None

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

1._

1.492

1.492

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

1._

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

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

1._

None

None

print(0.1 + 0.2) # gives 0.30000000000000004

Suggestion : 3

Last Updated : 16 Jul, 2022

1._

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

Suggestion : 4

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

Suggestion : 5

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

Suggestion : 6

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)