How do I check if a string is a number (float)?

Question

What is the best possible way to check if a string can be represented as a number in Python?

The function I currently have right now is:

def is_numb         


        

Answer 1

You can generalize the exception technique in a useful way by returning more useful values than True and False. For example this function puts quotes round strings but leaves numbers alone. Which is just what I needed for a quick and dirty filter to make some variable definitions for R.

import sys

def fix_quotes(s):
    try:
        float(s)
        return s
    except ValueError:
        return '"{0}"'.format(s)

for line in sys.stdin:
    input = line.split()
    print input[0], '<- c(', ','.join(fix_quotes(c) for c in input[1:]), ')'

Answer 2

I wanted to see which method is fastest. Overall the best and most consistent results were given by the check_replace function. The fastest results were given by the check_exception function, but only if there was no exception fired - meaning its code is the most efficient, but the overhead of throwing an exception is quite large.

Please note that checking for a successful cast is the only method which is accurate, for example, this works with check_exception but the other two test functions will return False for a valid float:

huge_number = float('1e+100')

Here is the benchmark code:

import time, re, random, string

ITERATIONS = 10000000

class Timer:    
    def __enter__(self):
        self.start = time.clock()
        return self
    def __exit__(self, *args):
        self.end = time.clock()
        self.interval = self.end - self.start

def check_regexp(x):
    return re.compile("^\d*\.?\d*$").match(x) is not None

def check_replace(x):
    return x.replace('.','',1).isdigit()

def check_exception(s):
    try:
        float(s)
        return True
    except ValueError:
        return False

to_check = [check_regexp, check_replace, check_exception]

print('preparing data...')
good_numbers = [
    str(random.random() / random.random()) 
    for x in range(ITERATIONS)]

bad_numbers = ['.' + x for x in good_numbers]

strings = [
    ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(random.randint(1,10)))
    for x in range(ITERATIONS)]

print('running test...')
for func in to_check:
    with Timer() as t:
        for x in good_numbers:
            res = func(x)
    print('%s with good floats: %s' % (func.__name__, t.interval))
    with Timer() as t:
        for x in bad_numbers:
            res = func(x)
    print('%s with bad floats: %s' % (func.__name__, t.interval))
    with Timer() as t:
        for x in strings:
            res = func(x)
    print('%s with strings: %s' % (func.__name__, t.interval))

Here are the results with Python 2.7.10 on a 2017 MacBook Pro 13:

check_regexp with good floats: 12.688639
check_regexp with bad floats: 11.624862
check_regexp with strings: 11.349414
check_replace with good floats: 4.419841
check_replace with bad floats: 4.294909
check_replace with strings: 4.086358
check_exception with good floats: 3.276668
check_exception with bad floats: 13.843092
check_exception with strings: 15.786169

Here are the results with Python 3.6.5 on a 2017 MacBook Pro 13:

check_regexp with good floats: 13.472906000000009
check_regexp with bad floats: 12.977665000000016
check_regexp with strings: 12.417542999999995
check_replace with good floats: 6.011045999999993
check_replace with bad floats: 4.849356
check_replace with strings: 4.282754000000011
check_exception with good floats: 6.039081999999979
check_exception with bad floats: 9.322753000000006
check_exception with strings: 9.952595000000002

Here are the results with PyPy 2.7.13 on a 2017 MacBook Pro 13:

check_regexp with good floats: 2.693217
check_regexp with bad floats: 2.744819
check_regexp with strings: 2.532414
check_replace with good floats: 0.604367
check_replace with bad floats: 0.538169
check_replace with strings: 0.598664
check_exception with good floats: 1.944103
check_exception with bad floats: 2.449182
check_exception with strings: 2.200056

Answer 3

I needed to determine if a string cast into basic types (float,int,str,bool). After not finding anything on the internet I created this:

def str_to_type (s):
    """ Get possible cast type for a string

    Parameters
    ----------
    s : string

    Returns
    -------
    float,int,str,bool : type
        Depending on what it can be cast to

    """    
    try:                
        f = float(s)        
        if "." not in s:
            return int
        return float
    except ValueError:
        value = s.upper()
        if value == "TRUE" or value == "FALSE":
            return bool
        return type(s)

Example

str_to_type("true") # bool
str_to_type("6.0") # float
str_to_type("6") # int
str_to_type("6abc") # str
str_to_type(u"6abc") # unicode       

You can capture the type and use it

s = "6.0"
type_ = str_to_type(s) # float
f = type_(s) 

Answer 4

User helper function:

def if_ok(fn, string):
  try:
    return fn(string)
  except Exception as e:
    return None

then

if_ok(int, my_str) or if_ok(float, my_str) or if_ok(complex, my_str)
is_number = lambda s: any([if_ok(fn, s) for fn in (int, float, complex)])

Answer 5

This answer provides step by step guide having function with examples to find the string is:

• Positive integer
• Positive/negative - integer/float
• How to discard "NaN" (not a number) strings while checking for number?

Check if string is positive integer

You may use str.isdigit() to check whether given string is positive integer.

Sample Results:

# For digit
>>> '1'.isdigit()
True
>>> '1'.isalpha()
False

Check for string as positive/negative - integer/float

str.isdigit() returns False if the string is a negative number or a float number. For example:

# returns `False` for float
>>> '123.3'.isdigit()
False
# returns `False` for negative number
>>> '-123'.isdigit()
False

If you want to also check for the negative integers and float, then you may write a custom function to check for it as:

def is_number(n):
    try:
        float(n)   # Type-casting the string to `float`.
                   # If string is not a valid `float`, 
                   # it'll raise `ValueError` exception
    except ValueError:
        return False
    return True

Sample Run:

>>> is_number('123')    # positive integer number
True

>>> is_number('123.4')  # positive float number
True

>>> is_number('-123')   # negative integer number
True

>>> is_number('-123.4') # negative `float` number
True

>>> is_number('abc')    # `False` for "some random" string
False

Discard "NaN" (not a number) strings while checking for number

The above functions will return True for the "NAN" (Not a number) string because for Python it is valid float representing it is not a number. For example:

>>> is_number('NaN')
True

In order to check whether the number is "NaN", you may use math.isnan() as:

>>> import math
>>> nan_num = float('nan')

>>> math.isnan(nan_num)
True

Or if you don't want to import additional library to check this, then you may simply check it via comparing it with itself using ==. Python returns False when nan float is compared with itself. For example:

# `nan_num` variable is taken from above example
>>> nan_num == nan_num
False

Hence, above function is_number can be updated to return False for "NaN" as:

def is_number(n):
    is_number = True
    try:
        num = float(n)
        # check for "nan" floats
        is_number = num == num   # or use `math.isnan(num)`
    except ValueError:
        is_number = False
    return is_number

Sample Run:

>>> is_number('Nan')   # not a number "Nan" string
False

>>> is_number('nan')   # not a number string "nan" with all lower cased
False

>>> is_number('123')   # positive integer
True

>>> is_number('-123')  # negative integer
True

>>> is_number('-1.12') # negative `float`
True

>>> is_number('abc')   # "some random" string
False

PS: Each operation for each check depending on the type of number comes with additional overhead. Choose the version of is_number function which fits your requirement.

Answer 6

So to put it all together, checking for Nan, infinity and complex numbers (it would seem they are specified with j, not i, i.e. 1+2j) it results in:

def is_number(s):
    try:
        n=str(float(s))
        if n == "nan" or n=="inf" or n=="-inf" : return False
    except ValueError:
        try:
            complex(s) # for complex
        except ValueError:
            return False
    return True