Skip to main content

Quickly convert strings to number types.

Project description

Convert strings to numbers quickly.

This module is a Python C extension that will convert strings to numbers much faster than can be done using pure Python; numeric types can also be converted to other numeric types.

Additionally, the user has control over what happens in the event that the input string cannot be converted to a number:

  • the input can be returned as-is (this is the default behavior)
  • the input can be passed to a user-given key function then returned
  • a ValueError can be raised (like the built-in float or int)
  • a default value can be returned


fastnumbers contains functions that are fast C implementations similar to the following Pure Python function:

def fast_float(input, default=None, raise_on_invalid=False, key=None, inf=None, nan=None):
    import math
        x = float(input)
    except ValueError:
        if raise_on_invalid:
        elif key is not None:
            return key(input)
        return default if default is not None else input
        if inf is not None and math.isinf(x):
            return inf
        elif nan is not None and math.isnan(x):
            return nan
            return x

In addition to fast_float, there are also fast_real, fast_int, fast_forceint, isreal, isfloat, isint, and isintlike - please see the API Documentation for full details.

Some example usage:

>>> from fastnumbers import fast_float
>>> # Convert string to a float
>>> fast_float('56.07')
>>> # Unconvertable string returned as-is by default
>>> fast_float('bad input')
'bad input'
>>> # Unconvertable strings can trigger a default value
>>> fast_float('bad input', default=0)
>>> # 'default' is also the first optional positional arg
>>> fast_float('bad input', 0)
>>> # Integers are converted to floats
>>> fast_float(54)
>>> # One can ask inf or nan to be substituted with another value
>>> fast_float('nan')
>>> fast_float('nan', nan=0.0)
>>> fast_float(float('nan'), nan=0.0)
>>> fast_float('56.07', nan=0.0)
>>> # The default built-in float behavior can be triggered with
>>> # "raise_on_invalid" set to True.
>>> fast_float('bad input', raise_on_invalid=True) #doctest: +IGNORE_EXCEPTION_DETAIL
Traceback (most recent call last):
ValueError: invalid literal for float(): bad input
>>> # A key function can be used to return an alternate value for invalid input
>>> fast_float('bad input', key=len)
>>> fast_float(54, key=len)
>>> # Single unicode characters can be converted.
>>> fast_float(u'\u2164')  # Roman numeral 5 (V)
>>> fast_float(u'\u2466')  # 7 enclosed in a circle

NOTE: If you need locale-dependent conversions, supply the fastnumbers function of your choice to locale.atof.

import locale
locale.setlocale(locale.LC_ALL, 'de_DE.UTF-8')
print(atof('468,5', func=fast_float))  # Prints 468.5


Just how much faster is fastnumbers than a pure python implementation? Below are the timing results for the *_float functions; please see the Timing Documentation for details into all timing results.

from timeit import timeit
float_try = '''\
def float_try(input):
    """Typical approach to this problem."""
        return float(input)
    except ValueError:
        return input

float_re = '''\
import re
float_match = re.compile(r'[-+]?\d*\.?\d+(?:[eE][-+]?\d+)?$').match
def float_re(input):
    """Alternate approach to this problem."""
        if float_match(input):
            return float(input)
            return input
    except TypeError:
        return float(input)

print('Invalid input:')
print("Try:", timeit('float_try("invalid")', float_try))
print("re:", timeit('float_re("invalid")', float_re))
print("fast", timeit('fast_float("invalid")', 'from fastnumbers import fast_float'))
print('Valid input:')
print("try:", timeit('float_try("56.07")', float_try))
print("re:", timeit('float_re("56.07")', float_re))
print("fast", timeit('fast_float("56.07")', 'from fastnumbers import fast_float'))

The results will be similar to below, but vary based on your system:

Invalid input:
Try: 2.27156710625
re: 0.570491075516
fast 0.173984050751

Valid input:
try: 0.378665924072
re: 1.08740401268
fast 0.204708099365

As you can see, in all cases fastnumbers beats the pure python implementations.


Seth M. Morton


These are the last three entries of the changelog. See the package documentation for the complete changelog.

03-19-2016 v. 0.7.4

  • Added the “coerce” option to fast_real.

03-08-2016 v. 0.7.3

  • Newline is now considered to be whitespace (for consistency with the builtin float and int).

03-07-2016 v. 0.7.2

  • Fixed overflow bug in exponential parts of floats.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
fastnumbers-0.7.4.tar.gz (46.9 kB) Copy SHA256 hash SHA256 Source None (63.2 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page