Format it to 6 decimal places:

format(value, '.6f')

Demo:

>>> format(2.0, '.6f')
'2.000000'

The format() function turns values to strings following the formatting instructions given.

When it comes to floating numbers, there is "precision" involved and what you see is not exactly what is in the memory.

For example, you can have trailing zeros in the float, but it is not mathematically precise:

Example

import decimal

floating_values = [2.5000, 2.500100, 2.5010000, 2.500011, 2.50011100, 2.50011100000110000]

nums = [f'{val:.64f}' for val in floating_values]
deci = [decimal.Decimal(val) for val in floating_values]

for num, dec in zip(nums, deci):
    print(num)
    print(dec)

Prints

2.5000000000000000000000000000000000000000000000000000000000000000
2.5
2.5001000000000002110311925207497552037239074707031250000000000000
2.500100000000000211031192520749755203723907470703125
2.5009999999999998898658759571844711899757385253906250000000000000
2.500999999999999889865875957184471189975738525390625
2.5000110000000002052900072158081457018852233886718750000000000000
2.500011000000000205290007215808145701885223388671875
2.5001109999999999722319898864952847361564636230468750000000000000
2.500110999999999972231989886495284736156463623046875
2.5001110000010999812047884915955364704132080078125000000000000000
2.5001110000010999812047884915955364704132080078125

Note

• Decimals makes calculations a bit more precise, if you set precision. But, still that's not mathematically precise.

• For instance, for 2.500100, we have 2.5001000000000002110311925207497552037239074707031250000000000000 and this may even differ in your machine from my machine.

Float doesn't support precision configuration, only rounding and formating. You should use decimal instead:

>>> from decimal import *
>>> getcontext().prec = 2
>>> Decimal(1) / Decimal(7)
Decimal('0.14')

Python decimal: https://docs.python.org/2/library/decimal.html

You can use the format method on strings to specify how many decimal places you want to represent:

>>> "{:.2f}".format(1.5)
'1.50'

But even better would be to use the decimal module for representing money, since representation issues with binary floats can give you slightly off results if you're doing arithmetic. The documentation for that module mentions some of those issues specifically - one of the most interesting ones for money applications is:

>>> 0.1+0.1+0.1-0.3
5.551115123125783e-17
>>> from decimal import Decimal
>>> Decimal('.1') + Decimal('.1') + Decimal('.1') - Decimal('.3')
Decimal('0.0')

For Python versions in 2.6+ and 3.x

You can use the str.format method. Examples:

>>> print('{0:.16f}'.format(1.6))
1.6000000000000001

>>> print('{0:.15f}'.format(1.6))
1.600000000000000

Note the 1 at the end of the first example is rounding error; it happens because exact representation of the decimal number 1.6 requires an infinite number binary digits. Since floating-point numbers have a finite number of bits, the number is rounded to a nearby, but not equal, value.

For Python versions prior to 2.6 (at least back to 2.0)

You can use the "modulo-formatting" syntax (this works for Python 2.6 and 2.7 too):

>>> print '%.16f' % 1.6
1.6000000000000001

>>> print '%.15f' % 1.6
1.600000000000000

Multiply by 10 every time you want to add another 0.

This is the same as saying 10 to the power of how many zeroes you want. In python, that would be number * (10**extraZeroCount)