Develop Reference

formatting very large numbers in python 3

I am performing calculation in python that results in very large numbers. The smallest of them is 2^10^6, this number is extremely long so I attempted to use format() to convert it to scientific notation. I keep getting an error message stating that the number is too large to convert to a float.
this is the error I keep getting:
print(format(2**10**6, "E"))
OverflowError: int too large to convert to float
I would like to print the result of 2^10^6 in a way that is concise and readable

You calculated 2 raised to the 10th then raised to the 6th power. If your aim is "2 times 10 to the sixth", then 2*10**6 is what you want. In python that can also be expressed by 2E6 where E means "to the 10th power". This is confusing when you are thinking in terms of natural logs and Euler's Number e.
You can also use the decimal.Decimal package if you want to side step decimal to binary float problems. In python, floats expressed in decimal are rounded to the nearest binary float. If you really did want the huge number, Decimal can handle it.
>>> Decimal("2E6")
Decimal('2E+6')
>>> Decimal("2")*10**6
Decimal('2000000')
>>> Decimal("2")**10**6
Decimal('9.900656229295898250697923616E+301029')
For printing, use the "g" format
>>> d = Decimal('2')**10**6
>>> format(d,'g')
'9.900656229295898250697923616e+301029'
>>> format(d,'.6g')
'9.90066e+301029'
>>> "{:g}".format(d)
'9.900656229295898250697923616e+301029'
>>> "{:.6g}".format(d)
'9.90066e+301029'

How can I check the length of a long float? Python is truncating the length [duplicate]

I have some number 0.0000002345E^-60. I want to print the floating point value as it is.
What is the way to do it?
print %f truncates it to 6 digits. Also %n.nf gives fixed numbers. What is the way to print without truncation.

Like this?
>>> print('{:.100f}'.format(0.0000002345E-60))
0.0000000000000000000000000000000000000000000000000000000000000000002344999999999999860343602938602754
As you might notice from the output, it’s not really that clear how you want to do it. Due to the float representation you lose precision and can’t really represent the number precisely. As such it’s not really clear where you want the number to stop displaying.
Also note that the exponential representation is often used to more explicitly show the number of significant digits the number has.
You could also use decimal to not lose the precision due to binary float truncation:
>>> from decimal import Decimal
>>> d = Decimal('0.0000002345E-60')
>>> p = abs(d.as_tuple().exponent)
>>> print(('{:.%df}' % p).format(d))
0.0000000000000000000000000000000000000000000000000000000000000000002345

You can use decimal.Decimal:
>>> from decimal import Decimal
>>> str(Decimal(0.0000002345e-60))
'2.344999999999999860343602938602754401109865640550232148836753621775217856801120686600683401464097113374472942165409862789978024748827516129306833728589548440037314681709534891496105046826414763927459716796875E-67'
This is the actual value of float created by literal 0.0000002345e-60. Its value is a number representable as python float which is closest to actual 0.0000002345 * 10**-60.
float should be generally used for approximate calculations. If you want accurate results you should use something else, like mentioned Decimal.

If I understand, you want to print a float?
The problem is, you cannot print a float.
You can only print a string representation of a float. So, in short, you cannot print a float, that is your answer.
If you accept that you need to print a string representation of a float, and your question is how specify your preferred format for the string representations of your floats, then judging by the comments you have been very unclear in your question.
If you would like to print the string representations of your floats in exponent notation, then the format specification language allows this:
{:g} or {:G}, depending whether or not you want the E in the output to be capitalized). This gets around the default precision for e and E types, which leads to unwanted trailing 0s in the part before the exponent symbol.
Assuming your value is my_float, "{:G}".format(my_float) would print the output the way that the Python interpreter prints it. You could probably just print the number without any formatting and get the same exact result.
If your goal is to print the string representation of the float with its current precision, in non-exponentiated form, User poke describes a good way to do this by casting the float to a Decimal object.
If, for some reason, you do not want to do this, you can do something like is mentioned in this answer. However, you should set 'max_digits' to sys.float_info.max_10_exp, instead of 14 used in the answer. This requires you to import sys at some point prior in the code.
A full example of this would be:
import math
import sys
def precision_and_scale(x):
max_digits = sys.float_info.max_10_exp
int_part = int(abs(x))
magnitude = 1 if int_part == 0 else int(math.log10(int_part)) + 1
if magnitude >= max_digits:
return (magnitude, 0)
frac_part = abs(x) - int_part
multiplier = 10 ** (max_digits - magnitude)
frac_digits = multiplier + int(multiplier * frac_part + 0.5)
while frac_digits % 10 == 0:
frac_digits /= 10
scale = int(math.log10(frac_digits))
return (magnitude + scale, scale)
f = 0.0000002345E^-60
p, s = precision_and_scale(f)
print "{:.{p}f}".format(f, p=p)
But I think the method involving casting to Decimal is probably better, overall.

Can Decimal('5E+1') be simply converted to Decimal('50') in Python?

Context
We display percentage values to agents in our app without trailing zeros (50% is much easier to quickly scan than is 50.000%), and hitherto we've just used quantize to sort of brute force normalize the value to remove trailing zeros.
This morning I decided to look into using Decimal.normalize instead, but ran into this:
Given the decimal value:
>>> value = Decimal('50.000')
Normalizing that value:
>>> value = value.normalize()
Results in:
>>> value
Decimal('5E+1')
I understand the value is the same:
>>> Decimal('5E+1') == Decimal('50')
True
But from a non-technical user's perspective, 5E+1 is basically meaningless.
Question
Is there a way to convert Decimal('5E+1') to Decimal('50')?
Note
I'm not looking to do anything that would change the value of the Decimal (e.g., removing decimal places altogether), since the value could be e.g., Decimal('33.333'). IOW, don't confuse my 50.000 example as meaning that we're only dealing with whole numbers.

For the purposes of output formatting, you can print your normalized Decimal objects with the f format specifier. (While the format string docs say this defaults to a precision of 6, this does not appear to be the case for Decimal objects.)
>>> print('{:f}%'.format(decimal.Decimal('50.000').normalize()))
50%
>>> print('{:f}%'.format(decimal.Decimal('50.003').normalize()))
50.003%
>>> print('{:f}%'.format(decimal.Decimal('1.23456789').normalize()))
1.23456789%
If for some reason, you really want to make a new Decimal object with different precision, you can do that by just calling Decimal on the f format output, but it sounds like you're dealing with an output format problem, not something you should change the internal representation for.
>>> Decimal('{:f}'.format(Decimal('5E+1')))
Decimal('50')
>>>
>>> Decimal('{:f}'.format(Decimal('50.000').normalize()))
Decimal('50')
>>> Decimal('{:f}'.format(Decimal('50.003').normalize()))
Decimal('50.003')
>>> Decimal('{:f}'.format(Decimal('1.23456789').normalize()))
Decimal('1.23456789')

according to the python 3.9 docs the below is how to do it - https://docs.python.org/3.9/library/decimal.html#decimal-faq
def remove_exponent(d):
return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()

Add Decimal(0) to your result.
Decimal('50.000').normalize()
# Decimal('5E+1')
Decimal('50.000').normalize() + Decimal(0)
# Decimal('50')

Floor function is eliminating Integer scientific notation, Python

I will explain my problem by example:
>>> #In this case, I get unwanted result
>>> k = 20685671025767659927959422028 / 2580360422
>>> k
8.016582043889239e+18
>>> math.floor(k)
8016582043889239040
>>> #I dont want this to happen ^^, let it remain 8.016582043889239e+18
>>> #The following case though, is fine
>>> k2 = 5/6
>>> k2
0.8333333333333334
>>> math.floor(k2)
0
How do I make math.floor not flooring the scientific notated numbers? Is there a rule for which numbers are represented in a scientific notation (I guess it would be a certain boundry).
EDIT:
I first thought that the math.floor function was causing an accuracy loss, but it turns out that the first calculation itself lost the calculation's accuracy, which had me really confused, it can be easily seen here:
>>> 20685671025767659927959422028 / 2580360422
8016582043889239040
>>> 8016582043889239040 * 2580360422
20685671025767659370513274880
>>> 20685671025767659927959422028 - 20685671025767659370513274880
557446147148
>>> 557446147148 / 2580360422
216.0342184739958
>>> ##this is >1, meaning I lost quite a bit of information, and it was not due to the flooring
So now my problem is how to get the actual result of the division. I looked at the following thread:
How to print all digits of a large number in python?
But for some reason I didn't get the same result.
EDIT:
I found a simple solution for the division accuracy problem in here:
How to manage division of huge numbers in Python?
Apparently the // operator returns an int rather then float, which has no size limit apart to the machine's memory.

In Python 3, math.floor returns an integer. Integers are not displayed using scientific notation. Some floats are represented using scientific notation. If you want scientific notation, try converting back to float.
>>> float(math.floor(20685671025767659927959422028 / 2580360422))
8.016582043889239e+18
As Tadhg McDonald-Jensen indicates, you can also use str.format to get a string representation of your integer in scientific notation:
>>> k = 20685671025767659927959422028 / 2580360422
>>> "{:e}".format(k)
'8.016582e+18'
This may, in fact, be more practical than converting to float. As a general rule of thumb, you should choose a numeric data type based on the precision and range you require, without worrying about what it looks like when printed.

Is there a more readable or Pythonic way to format a Decimal to 2 places?

What the heck is going on with the syntax to fix a Decimal to two places?
>>> from decimal import Decimal
>>> num = Decimal('1.0')
>>> num.quantize(Decimal(10) ** -2) # seriously?!
Decimal('1.00')
Is there a better way that doesn't look so esoteric at a glance? 'Quantizing a decimal' sounds like technobabble from an episode of Star Trek!

Use string formatting:
>>> from decimal import Decimal
>>> num = Decimal('1.0')
>>> format(num, '.2f')
'1.00'
The format() function applies string formatting to values. Decimal() objects can be formatted like floating point values.
You can also use this to interpolate the formatted decimal value is a larger string:
>>> 'Value of num: {:.2f}'.format(num)
'Value of num: 1.00'
See the format string syntax documentation.
Unless you know exactly what you are doing, expanding the number of significant digits through quantisation is not the way to go; quantisation is the privy of accountancy packages and normally has the aim to round results to fewer significant digits instead.

Quantize is used to set the number of places that are actually held internally within the value, before it is converted to a string. As Martijn points out this is usually done to reduce the number of digits via rounding, but it works just as well going the other way. By specifying the target as a decimal number rather than a number of places, you can make two values match without knowing specifically how many places are in them.
It looks a little less esoteric if you use a decimal value directly instead of trying to calculate it:
num.quantize(Decimal('0.01'))
You can set up some constants to hide the complexity:
places = [Decimal('0.1') ** n for n in range(16)]
num.quantize(places[2])