fastnumbers 2.0.2

Super-fast and clean conversions to numbers.

Super-fast and clean conversions to numbers.

• Source Code: https://github.com/SethMMorton/fastnumbers

• Downloads: https://pypi.org/project/fastnumbers/

• Documentation: http://fastnumbers.readthedocs.io/

fastnumbers is a module with the following three objectives:

1. Provide drop-in replacements for the Python built-in int and float that on average are up to 2x faster. These functions should behave identically to the Python built-ins except for a few specific corner-cases as mentioned in the API documentation.

2. Provide a set of convenience functions that wrap the above int and float replacements and provides easy, concise, powerful, fast and flexible error handling.

3. Provide a set of functions that can be used to rapidly identify if an input could be converted to int or float.

Examples

The below examples showcase the fast_float function, which is a fast conversion function with error-handling. Please see the API Documentation for other functions that are available from fastnumbers.

>>> from fastnumbers import fast_float, float as fnfloat
>>> # Convert string to a float
>>> fast_float('56.07')
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)
0
>>> # 'default' is also the first optional positional arg
>>> fast_float('bad input', 0)
0
>>> # Integers are converted to floats
>>> fast_float(54)
54.0
>>> # One can ask inf or nan to be substituted with another value
>>> fast_float('nan')
nan
>>> fast_float('nan', nan=0.0)
0.0
>>> fast_float(float('nan'), nan=0.0)
0.0
>>> fast_float('56.07', nan=0.0)
56.07
>>> # 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)
9
>>> fast_float(54, key=len)
54.0
>>> # Single unicode characters can be converted.
>>> fast_float(u'\u2164')  # Roman numeral 5 (V)
5.0
>>> fast_float(u'\u2466')  # 7 enclosed in a circle
7.0

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

Timing

Just how much faster is fastnumbers than a pure python implementation? Please see the following Jupyter notebooks for timing information on various Python versions.

• https://github.com/SethMMorton/fastnumbers/blob/master/TIMING_27.ipynb

• https://github.com/SethMMorton/fastnumbers/blob/master/TIMING_35.ipynb

• https://github.com/SethMMorton/fastnumbers/blob/master/TIMING_36.ipynb

Author

Seth M. Morton

History

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

11-11-2017 v. 2.0.2

• Updated docstrings.

• Improved timing documentation.

• Added testing for Python 3.7.

04-30-2017 v. 2.0.1

• Fixed bug in decimal digit limit on GCC.

04-30-2017 v. 2.0.0

• Dropped support for Python 2.6.

• Added support for Python 3.6 underscores.

• Added drop-in replacements for the built-in int() and float() functions.

• Incorporated unit tests from Python’s testing library to ensure that any input that Python can handle will also be handled the same way by fastnumbers.

• Added Appveyor testing to ensure no surprises on Windows.

• Revamped documentation.

• Refactored internal mechanism for assessing overflow to be faster in the most common cases.