Related
How can I convert a str to float?
"545.2222" → 545.2222
How can I convert a str to int?
"31" → 31
For the reverse, see Convert integer to string in Python and Converting a float to a string without rounding it.
Please instead use How can I read inputs as numbers? to close duplicate questions where OP received a string from user input and immediately wants to convert it, or was hoping for input (in 3.x) to convert the type automatically.
>>> a = "545.2222"
>>> float(a)
545.22220000000004
>>> int(float(a))
545
Python2 method to check if a string is a float:
def is_float(value):
if value is None:
return False
try:
float(value)
return True
except:
return False
For the Python3 version of is_float see: Checking if a string can be converted to float in Python
A longer and more accurate name for this function could be: is_convertible_to_float(value)
What is, and is not a float in Python may surprise you:
The below unit tests were done using python2. Check it that Python3 has different behavior for what strings are convertable to float. One confounding difference is that any number of interior underscores are now allowed: (float("1_3.4") == float(13.4)) is True
val is_float(val) Note
-------------------- ---------- --------------------------------
"" False Blank string
"127" True Passed string
True True Pure sweet Truth
"True" False Vile contemptible lie
False True So false it becomes true
"123.456" True Decimal
" -127 " True Spaces trimmed
"\t\n12\r\n" True whitespace ignored
"NaN" True Not a number
"NaNanananaBATMAN" False I am Batman
"-iNF" True Negative infinity
"123.E4" True Exponential notation
".1" True mantissa only
"1_2_3.4" False Underscores not allowed
"12 34" False Spaces not allowed on interior
"1,234" False Commas gtfo
u'\x30' True Unicode is fine.
"NULL" False Null is not special
0x3fade True Hexadecimal
"6e7777777777777" True Shrunk to infinity
"1.797693e+308" True This is max value
"infinity" True Same as inf
"infinityandBEYOND" False Extra characters wreck it
"12.34.56" False Only one dot allowed
u'四' False Japanese '4' is not a float.
"#56" False Pound sign
"56%" False Percent of what?
"0E0" True Exponential, move dot 0 places
0**0 True 0___0 Exponentiation
"-5e-5" True Raise to a negative number
"+1e1" True Plus is OK with exponent
"+1e1^5" False Fancy exponent not interpreted
"+1e1.3" False No decimals in exponent
"-+1" False Make up your mind
"(1)" False Parenthesis is bad
You think you know what numbers are? You are not so good as you think! Not big surprise.
Don't use this code on life-critical software!
Catching broad exceptions this way, killing canaries and gobbling the exception creates a tiny chance that a valid float as string will return false. The float(...) line of code can failed for any of a thousand reasons that have nothing to do with the contents of the string. But if you're writing life-critical software in a duck-typing prototype language like Python, then you've got much larger problems.
def num(s):
try:
return int(s)
except ValueError:
return float(s)
This is another method which deserves to be mentioned here, ast.literal_eval:
This can be used for safely evaluating strings containing Python expressions from untrusted sources without the need to parse the values oneself.
That is, a safe 'eval'
>>> import ast
>>> ast.literal_eval("545.2222")
545.2222
>>> ast.literal_eval("31")
31
Localization and commas
You should consider the possibility of commas in the string representation of a number, for cases like float("545,545.2222") which throws an exception. Instead, use methods in locale to convert the strings to numbers and interpret commas correctly. The locale.atof method converts to a float in one step once the locale has been set for the desired number convention.
Example 1 -- United States number conventions
In the United States and the UK, commas can be used as a thousands separator. In this example with American locale, the comma is handled properly as a separator:
>>> import locale
>>> a = u'545,545.2222'
>>> locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')
'en_US.UTF-8'
>>> locale.atof(a)
545545.2222
>>> int(locale.atof(a))
545545
>>>
Example 2 -- European number conventions
In the majority of countries of the world, commas are used for decimal marks instead of periods. In this example with French locale, the comma is correctly handled as a decimal mark:
>>> import locale
>>> b = u'545,2222'
>>> locale.setlocale(locale.LC_ALL, 'fr_FR')
'fr_FR'
>>> locale.atof(b)
545.2222
The method locale.atoi is also available, but the argument should be an integer.
float(x) if '.' in x else int(x)
If you aren't averse to third-party modules, you could check out the fastnumbers module. It provides a function called fast_real that does exactly what this question is asking for and does it faster than a pure-Python implementation:
>>> from fastnumbers import fast_real
>>> fast_real("545.2222")
545.2222
>>> type(fast_real("545.2222"))
float
>>> fast_real("31")
31
>>> type(fast_real("31"))
int
Users codelogic and harley are correct, but keep in mind if you know the string is an integer (for example, 545) you can call int("545") without first casting to float.
If your strings are in a list, you could use the map function as well.
>>> x = ["545.0", "545.6", "999.2"]
>>> map(float, x)
[545.0, 545.60000000000002, 999.20000000000005]
>>>
It is only good if they're all the same type.
In Python, how can I parse a numeric string like "545.2222" to its corresponding float value, 542.2222? Or parse the string "31" to an integer, 31?
I just want to know how to parse a float string to a float, and (separately) an int string to an int.
It's good that you ask to do these separately. If you're mixing them, you may be setting yourself up for problems later. The simple answer is:
"545.2222" to float:
>>> float("545.2222")
545.2222
"31" to an integer:
>>> int("31")
31
Other conversions, ints to and from strings and literals:
Conversions from various bases, and you should know the base in advance (10 is the default). Note you can prefix them with what Python expects for its literals (see below) or remove the prefix:
>>> int("0b11111", 2)
31
>>> int("11111", 2)
31
>>> int('0o37', 8)
31
>>> int('37', 8)
31
>>> int('0x1f', 16)
31
>>> int('1f', 16)
31
If you don't know the base in advance, but you do know they will have the correct prefix, Python can infer this for you if you pass 0 as the base:
>>> int("0b11111", 0)
31
>>> int('0o37', 0)
31
>>> int('0x1f', 0)
31
Non-Decimal (i.e. Integer) Literals from other Bases
If your motivation is to have your own code clearly represent hard-coded specific values, however, you may not need to convert from the bases - you can let Python do it for you automatically with the correct syntax.
You can use the apropos prefixes to get automatic conversion to integers with the following literals. These are valid for Python 2 and 3:
Binary, prefix 0b
>>> 0b11111
31
Octal, prefix 0o
>>> 0o37
31
Hexadecimal, prefix 0x
>>> 0x1f
31
This can be useful when describing binary flags, file permissions in code, or hex values for colors - for example, note no quotes:
>>> 0b10101 # binary flags
21
>>> 0o755 # read, write, execute perms for owner, read & ex for group & others
493
>>> 0xffffff # the color, white, max values for red, green, and blue
16777215
Making ambiguous Python 2 octals compatible with Python 3
If you see an integer that starts with a 0, in Python 2, this is (deprecated) octal syntax.
>>> 037
31
It is bad because it looks like the value should be 37. So in Python 3, it now raises a SyntaxError:
>>> 037
File "<stdin>", line 1
037
^
SyntaxError: invalid token
Convert your Python 2 octals to octals that work in both 2 and 3 with the 0o prefix:
>>> 0o37
31
The question seems a little bit old. But let me suggest a function, parseStr, which makes something similar, that is, returns integer or float and if a given ASCII string cannot be converted to none of them it returns it untouched. The code of course might be adjusted to do only what you want:
>>> import string
>>> parseStr = lambda x: x.isalpha() and x or x.isdigit() and \
... int(x) or x.isalnum() and x or \
... len(set(string.punctuation).intersection(x)) == 1 and \
... x.count('.') == 1 and float(x) or x
>>> parseStr('123')
123
>>> parseStr('123.3')
123.3
>>> parseStr('3HC1')
'3HC1'
>>> parseStr('12.e5')
1200000.0
>>> parseStr('12$5')
'12$5'
>>> parseStr('12.2.2')
'12.2.2'
float("545.2222") and int(float("545.2222"))
The YAML parser can help you figure out what datatype your string is. Use yaml.load(), and then you can use type(result) to test for type:
>>> import yaml
>>> a = "545.2222"
>>> result = yaml.load(a)
>>> result
545.22220000000004
>>> type(result)
<type 'float'>
>>> b = "31"
>>> result = yaml.load(b)
>>> result
31
>>> type(result)
<type 'int'>
>>> c = "HI"
>>> result = yaml.load(c)
>>> result
'HI'
>>> type(result)
<type 'str'>
I use this function for that
import ast
def parse_str(s):
try:
return ast.literal_eval(str(s))
except:
return
It will convert the string to its type
value = parse_str('1') # Returns Integer
value = parse_str('1.5') # Returns Float
def get_int_or_float(v):
number_as_float = float(v)
number_as_int = int(number_as_float)
return number_as_int if number_as_float == number_as_int else number_as_float
def num(s):
"""num(s)
num(3),num(3.7)-->3
num('3')-->3, num('3.7')-->3.7
num('3,700')-->ValueError
num('3a'),num('a3'),-->ValueError
num('3e4') --> 30000.0
"""
try:
return int(s)
except ValueError:
try:
return float(s)
except ValueError:
raise ValueError('argument is not a string of number')
You could use json.loads:
>>> import json
>>> json.loads('123.456')
123.456
>>> type(_)
<class 'float'>
>>>
As you can see it becomes a type of float.
You need to take into account rounding to do this properly.
i.e. - int(5.1) => 5
int(5.6) => 5 -- wrong, should be 6 so we do int(5.6 + 0.5) => 6
def convert(n):
try:
return int(n)
except ValueError:
return float(n + 0.5)
To typecast in Python use the constructor functions of the type, passing the string (or whatever value you are trying to cast) as a parameter.
For example:
>>>float("23.333")
23.333
Behind the scenes, Python is calling the objects __float__ method, which should return a float representation of the parameter. This is especially powerful, as you can define your own types (using classes) with a __float__ method so that it can be casted into a float using float(myobject).
Handles hex, octal, binary, decimal, and float
This solution will handle all of the string conventions for numbers (all that I know about).
def to_number(n):
''' Convert any number representation to a number
This covers: float, decimal, hex, and octal numbers.
'''
try:
return int(str(n), 0)
except:
try:
# Python 3 doesn't accept "010" as a valid octal. You must use the
# '0o' prefix
return int('0o' + n, 0)
except:
return float(n)
This test case output illustrates what I'm talking about.
======================== CAPTURED OUTPUT =========================
to_number(3735928559) = 3735928559 == 3735928559
to_number("0xFEEDFACE") = 4277009102 == 4277009102
to_number("0x0") = 0 == 0
to_number(100) = 100 == 100
to_number("42") = 42 == 42
to_number(8) = 8 == 8
to_number("0o20") = 16 == 16
to_number("020") = 16 == 16
to_number(3.14) = 3.14 == 3.14
to_number("2.72") = 2.72 == 2.72
to_number("1e3") = 1000.0 == 1000
to_number(0.001) = 0.001 == 0.001
to_number("0xA") = 10 == 10
to_number("012") = 10 == 10
to_number("0o12") = 10 == 10
to_number("0b01010") = 10 == 10
to_number("10") = 10 == 10
to_number("10.0") = 10.0 == 10
to_number("1e1") = 10.0 == 10
Here is the test:
class test_to_number(unittest.TestCase):
def test_hex(self):
# All of the following should be converted to an integer
#
values = [
# HEX
# ----------------------
# Input | Expected
# ----------------------
(0xDEADBEEF , 3735928559), # Hex
("0xFEEDFACE", 4277009102), # Hex
("0x0" , 0), # Hex
# Decimals
# ----------------------
# Input | Expected
# ----------------------
(100 , 100), # Decimal
("42" , 42), # Decimal
]
values += [
# Octals
# ----------------------
# Input | Expected
# ----------------------
(0o10 , 8), # Octal
("0o20" , 16), # Octal
("020" , 16), # Octal
]
values += [
# Floats
# ----------------------
# Input | Expected
# ----------------------
(3.14 , 3.14), # Float
("2.72" , 2.72), # Float
("1e3" , 1000), # Float
(1e-3 , 0.001), # Float
]
values += [
# All ints
# ----------------------
# Input | Expected
# ----------------------
("0xA" , 10),
("012" , 10),
("0o12" , 10),
("0b01010" , 10),
("10" , 10),
("10.0" , 10),
("1e1" , 10),
]
for _input, expected in values:
value = to_number(_input)
if isinstance(_input, str):
cmd = 'to_number("{}")'.format(_input)
else:
cmd = 'to_number({})'.format(_input)
print("{:23} = {:10} == {:10}".format(cmd, value, expected))
self.assertEqual(value, expected)
Pass your string to this function:
def string_to_number(str):
if("." in str):
try:
res = float(str)
except:
res = str
elif(str.isdigit()):
res = int(str)
else:
res = str
return(res)
It will return int, float or string depending on what was passed.
String that is an int
print(type(string_to_number("124")))
<class 'int'>
String that is a float
print(type(string_to_number("12.4")))
<class 'float'>
String that is a string
print(type(string_to_number("hello")))
<class 'str'>
String that looks like a float
print(type(string_to_number("hel.lo")))
<class 'str'>
There is also regex, because sometimes string must be prepared and normalized before casting to a number:
import re
def parseNumber(value, as_int=False):
try:
number = float(re.sub('[^.\-\d]', '', value))
if as_int:
return int(number + 0.5)
else:
return number
except ValueError:
return float('nan') # or None if you wish
Usage:
parseNumber('13,345')
> 13345.0
parseNumber('- 123 000')
> -123000.0
parseNumber('99999\n')
> 99999.0
And by the way, something to verify you have a number:
import numbers
def is_number(value):
return isinstance(value, numbers.Number)
# Will work with int, float, long, Decimal
a = int(float(a)) if int(float(a)) == float(a) else float(a)
This is a corrected version of Totoro's answer.
This will try to parse a string and return either int or float depending on what the string represents. It might rise parsing exceptions or have some unexpected behaviour.
def get_int_or_float(v):
number_as_float = float(v)
number_as_int = int(number_as_float)
return number_as_int if number_as_float == number_as_int else
number_as_float
If you are dealing with mixed integers and floats and want a consistent way to deal with your mixed data, here is my solution with the proper docstring:
def parse_num(candidate):
"""Parse string to number if possible
It work equally well with negative and positive numbers, integers and floats.
Args:
candidate (str): string to convert
Returns:
float | int | None: float or int if possible otherwise None
"""
try:
float_value = float(candidate)
except ValueError:
return None
# Optional part if you prefer int to float when decimal part is 0
if float_value.is_integer():
return int(float_value)
# end of the optional part
return float_value
# Test
candidates = ['34.77', '-13', 'jh', '8990', '76_3234_54']
res_list = list(map(parse_num, candidates))
print('Before:')
print(candidates)
print('After:')
print(res_list)
Output:
Before:
['34.77', '-13', 'jh', '8990', '76_3234_54']
After:
[34.77, -13, None, 8990, 76323454]
Use:
def num(s):
try:
for each in s:
yield int(each)
except ValueError:
yield float(each)
a = num(["123.55","345","44"])
print a.next()
print a.next()
This is the most Pythonic way I could come up with.
If you don't want to use third party modules the following might be the most robust solution:
def string_to_int_or_float(s):
try:
f = float(s) # replace s with str(s) if you are not sure that s is a string
except ValueError:
print("Provided string '" + s + "' is not interpretable as a literal number.")
raise
try:
i = int(str(f).rstrip('0').rstrip('.'))
except:
return f
return i
It might not be the fastest, but it handles correctly literal numbers where many other solutions fail, such as:
>>> string_to_int_or_float('789.')
789
>>> string_to_int_or_float('789.0')
789
>>> string_to_int_or_float('12.3e2')
1230
>>> string_to_int_or_float('12.3e-2')
0.123
>>> string_to_int_or_float('4560e-1')
456
>>> string_to_int_or_float('4560e-2')
45.6
You can simply do this by
s = '542.22'
f = float(s) # This converts string data to float data with a decimal point
print(f)
i = int(f) # This converts string data to integer data by just taking the whole number part of it
print(i)
For more information on parsing of data types check on python documentation!
This is a function which will convert any object (not just str) to int or float, based on if the actual string supplied looks like int or float. Further if it's an object which has both __float and __int__ methods, it defaults to using __float__
def conv_to_num(x, num_type='asis'):
'''Converts an object to a number if possible.
num_type: int, float, 'asis'
Defaults to floating point in case of ambiguity.
'''
import numbers
is_num, is_str, is_other = [False]*3
if isinstance(x, numbers.Number):
is_num = True
elif isinstance(x, str):
is_str = True
is_other = not any([is_num, is_str])
if is_num:
res = x
elif is_str:
is_float, is_int, is_char = [False]*3
try:
res = float(x)
if '.' in x:
is_float = True
else:
is_int = True
except ValueError:
res = x
is_char = True
else:
if num_type == 'asis':
funcs = [int, float]
else:
funcs = [num_type]
for func in funcs:
try:
res = func(x)
break
except TypeError:
continue
else:
res = x
By using int and float methods we can convert a string to integer and floats.
s="45.8"
print(float(s))
y='67'
print(int(y))
For numbers and characters together:
string_for_int = "498 results should get"
string_for_float = "498.45645765 results should get"
First import re:
import re
# For getting the integer part:
print(int(re.search(r'\d+', string_for_int).group())) #498
# For getting the float part:
print(float(re.search(r'\d+\.\d+', string_for_float).group())) #498.45645765
For easy model:
value1 = "10"
value2 = "10.2"
print(int(value1)) # 10
print(float(value2)) # 10.2
I'm new to python and am wondering if there are more efficient ways to complete this homework problem:
Write a function mytype(v) that performs the same action as type(), and can recognize integers, floats, strings, and lists. Do this by first using str(v), and then reading the string. Assume that lists can only contain numbers (not strings, other lists, etc...), and assume that strings can be anything that is not an integer, float or list.
The problem requires using Regular Expressions.
Here's what I have so far, and it works to my knowledge.
I'm wondering if there exists ways to do this WITHOUT so many if statements? ie more concise or more efficient?
import re
def mytype(v):
s = str(v)
# Check if list
list_regex = re.compile(r'[\[\]]')
l = re.findall(list_regex, s)
if l:
return "<type 'list'>"
# Check if float
float_regex = re.compile(r'[0-9]+\.')
f = re.findall(float_regex, s)
if f:
return "<type 'float'>"
# Check if int
int_regex = re.compile(r'[0-9]+')
i = re.findall(int_regex, s)
if i:
return "<type 'int'>"
# Check if string
str_regex = re.compile(r'[a-zA-Z]+')
t = re.findall(str_regex, s)
if t:
return "<type 'string'>"
x = 5
y = 5.5
z= .99
string = "hsjjsRHJSK"
li = [1.1,2,3.2,4,5]
print mytype(x) # <type 'int'>
print mytype(y) # <type 'float'>
print mytype(z) # <type 'float'>
print mytype(string) # <type 'string'>
print mytype(li) # <type 'list'>
Use group to match and get a captured group name and pipe | in regex.
Regex: (?P<list>\[\[^\]\]+\])|(?P<float>\d*\.\d+)|(?P<int>\d+)|(?P<string>\[a-zA-Z\]+)
Details:
| or
(?P<>) python named capturing group
Python code:
def mytype(v):
s = str(v)
regex = re.compile(r'(?P<list>\[[^]]+\])|(?P<float>\d*\.\d+)|(?P<int>\d+)|(?P<string>[a-zA-Z]+)')
return r"<type '%s'>" % regex.search(s).lastgroup
Input:
print(mytype(5))
print(mytype(5.5))
print(mytype(.99))
print(mytype("hsjjsRHJSK"))
print(mytype([1.1,2,3.2,4,5]))
Output:
<type 'int'>
<type 'float'>
<type 'float'>
<type 'string'>
<type 'list'>
Code demo
I'm wondering if there exists ways to do this WITHOUT so many if
statements? ie more concise or more efficient?
Without affecting your results, and more strictly following the rules, we can toss one if statement and half your code:
def mytype(v):
s = str(v)
# Check if list
if re.search(r'[\[\]]', s):
return "<type 'list'>"
# Check if float
if re.search(r'[\d]+\.', s):
return "<type 'float'>"
# Check if int
if re.search(r'[\d]+', s):
return "<type 'int'>"
# Assume strings are anything that's not an int, float or list
return "<type 'string'>"
This is even before considering your regular expressions. You don't need to call re.compile() for this usage. Your list test could easily catch a dict but dict wasn't in your requirements. The z = .99 only works because by the time it turns to string, it's "0.99". An actual string of ".99" would have failed your float test. There's an order dependency to your float and int tests -- that should be commented.
How can I convert a str to float?
"545.2222" → 545.2222
How can I convert a str to int?
"31" → 31
For the reverse, see Convert integer to string in Python and Converting a float to a string without rounding it.
Please instead use How can I read inputs as numbers? to close duplicate questions where OP received a string from user input and immediately wants to convert it, or was hoping for input (in 3.x) to convert the type automatically.
>>> a = "545.2222"
>>> float(a)
545.22220000000004
>>> int(float(a))
545
Python2 method to check if a string is a float:
def is_float(value):
if value is None:
return False
try:
float(value)
return True
except:
return False
For the Python3 version of is_float see: Checking if a string can be converted to float in Python
A longer and more accurate name for this function could be: is_convertible_to_float(value)
What is, and is not a float in Python may surprise you:
The below unit tests were done using python2. Check it that Python3 has different behavior for what strings are convertable to float. One confounding difference is that any number of interior underscores are now allowed: (float("1_3.4") == float(13.4)) is True
val is_float(val) Note
-------------------- ---------- --------------------------------
"" False Blank string
"127" True Passed string
True True Pure sweet Truth
"True" False Vile contemptible lie
False True So false it becomes true
"123.456" True Decimal
" -127 " True Spaces trimmed
"\t\n12\r\n" True whitespace ignored
"NaN" True Not a number
"NaNanananaBATMAN" False I am Batman
"-iNF" True Negative infinity
"123.E4" True Exponential notation
".1" True mantissa only
"1_2_3.4" False Underscores not allowed
"12 34" False Spaces not allowed on interior
"1,234" False Commas gtfo
u'\x30' True Unicode is fine.
"NULL" False Null is not special
0x3fade True Hexadecimal
"6e7777777777777" True Shrunk to infinity
"1.797693e+308" True This is max value
"infinity" True Same as inf
"infinityandBEYOND" False Extra characters wreck it
"12.34.56" False Only one dot allowed
u'四' False Japanese '4' is not a float.
"#56" False Pound sign
"56%" False Percent of what?
"0E0" True Exponential, move dot 0 places
0**0 True 0___0 Exponentiation
"-5e-5" True Raise to a negative number
"+1e1" True Plus is OK with exponent
"+1e1^5" False Fancy exponent not interpreted
"+1e1.3" False No decimals in exponent
"-+1" False Make up your mind
"(1)" False Parenthesis is bad
You think you know what numbers are? You are not so good as you think! Not big surprise.
Don't use this code on life-critical software!
Catching broad exceptions this way, killing canaries and gobbling the exception creates a tiny chance that a valid float as string will return false. The float(...) line of code can failed for any of a thousand reasons that have nothing to do with the contents of the string. But if you're writing life-critical software in a duck-typing prototype language like Python, then you've got much larger problems.
def num(s):
try:
return int(s)
except ValueError:
return float(s)
This is another method which deserves to be mentioned here, ast.literal_eval:
This can be used for safely evaluating strings containing Python expressions from untrusted sources without the need to parse the values oneself.
That is, a safe 'eval'
>>> import ast
>>> ast.literal_eval("545.2222")
545.2222
>>> ast.literal_eval("31")
31
Localization and commas
You should consider the possibility of commas in the string representation of a number, for cases like float("545,545.2222") which throws an exception. Instead, use methods in locale to convert the strings to numbers and interpret commas correctly. The locale.atof method converts to a float in one step once the locale has been set for the desired number convention.
Example 1 -- United States number conventions
In the United States and the UK, commas can be used as a thousands separator. In this example with American locale, the comma is handled properly as a separator:
>>> import locale
>>> a = u'545,545.2222'
>>> locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')
'en_US.UTF-8'
>>> locale.atof(a)
545545.2222
>>> int(locale.atof(a))
545545
>>>
Example 2 -- European number conventions
In the majority of countries of the world, commas are used for decimal marks instead of periods. In this example with French locale, the comma is correctly handled as a decimal mark:
>>> import locale
>>> b = u'545,2222'
>>> locale.setlocale(locale.LC_ALL, 'fr_FR')
'fr_FR'
>>> locale.atof(b)
545.2222
The method locale.atoi is also available, but the argument should be an integer.
float(x) if '.' in x else int(x)
If you aren't averse to third-party modules, you could check out the fastnumbers module. It provides a function called fast_real that does exactly what this question is asking for and does it faster than a pure-Python implementation:
>>> from fastnumbers import fast_real
>>> fast_real("545.2222")
545.2222
>>> type(fast_real("545.2222"))
float
>>> fast_real("31")
31
>>> type(fast_real("31"))
int
Users codelogic and harley are correct, but keep in mind if you know the string is an integer (for example, 545) you can call int("545") without first casting to float.
If your strings are in a list, you could use the map function as well.
>>> x = ["545.0", "545.6", "999.2"]
>>> map(float, x)
[545.0, 545.60000000000002, 999.20000000000005]
>>>
It is only good if they're all the same type.
In Python, how can I parse a numeric string like "545.2222" to its corresponding float value, 542.2222? Or parse the string "31" to an integer, 31?
I just want to know how to parse a float string to a float, and (separately) an int string to an int.
It's good that you ask to do these separately. If you're mixing them, you may be setting yourself up for problems later. The simple answer is:
"545.2222" to float:
>>> float("545.2222")
545.2222
"31" to an integer:
>>> int("31")
31
Other conversions, ints to and from strings and literals:
Conversions from various bases, and you should know the base in advance (10 is the default). Note you can prefix them with what Python expects for its literals (see below) or remove the prefix:
>>> int("0b11111", 2)
31
>>> int("11111", 2)
31
>>> int('0o37', 8)
31
>>> int('37', 8)
31
>>> int('0x1f', 16)
31
>>> int('1f', 16)
31
If you don't know the base in advance, but you do know they will have the correct prefix, Python can infer this for you if you pass 0 as the base:
>>> int("0b11111", 0)
31
>>> int('0o37', 0)
31
>>> int('0x1f', 0)
31
Non-Decimal (i.e. Integer) Literals from other Bases
If your motivation is to have your own code clearly represent hard-coded specific values, however, you may not need to convert from the bases - you can let Python do it for you automatically with the correct syntax.
You can use the apropos prefixes to get automatic conversion to integers with the following literals. These are valid for Python 2 and 3:
Binary, prefix 0b
>>> 0b11111
31
Octal, prefix 0o
>>> 0o37
31
Hexadecimal, prefix 0x
>>> 0x1f
31
This can be useful when describing binary flags, file permissions in code, or hex values for colors - for example, note no quotes:
>>> 0b10101 # binary flags
21
>>> 0o755 # read, write, execute perms for owner, read & ex for group & others
493
>>> 0xffffff # the color, white, max values for red, green, and blue
16777215
Making ambiguous Python 2 octals compatible with Python 3
If you see an integer that starts with a 0, in Python 2, this is (deprecated) octal syntax.
>>> 037
31
It is bad because it looks like the value should be 37. So in Python 3, it now raises a SyntaxError:
>>> 037
File "<stdin>", line 1
037
^
SyntaxError: invalid token
Convert your Python 2 octals to octals that work in both 2 and 3 with the 0o prefix:
>>> 0o37
31
The question seems a little bit old. But let me suggest a function, parseStr, which makes something similar, that is, returns integer or float and if a given ASCII string cannot be converted to none of them it returns it untouched. The code of course might be adjusted to do only what you want:
>>> import string
>>> parseStr = lambda x: x.isalpha() and x or x.isdigit() and \
... int(x) or x.isalnum() and x or \
... len(set(string.punctuation).intersection(x)) == 1 and \
... x.count('.') == 1 and float(x) or x
>>> parseStr('123')
123
>>> parseStr('123.3')
123.3
>>> parseStr('3HC1')
'3HC1'
>>> parseStr('12.e5')
1200000.0
>>> parseStr('12$5')
'12$5'
>>> parseStr('12.2.2')
'12.2.2'
float("545.2222") and int(float("545.2222"))
The YAML parser can help you figure out what datatype your string is. Use yaml.load(), and then you can use type(result) to test for type:
>>> import yaml
>>> a = "545.2222"
>>> result = yaml.load(a)
>>> result
545.22220000000004
>>> type(result)
<type 'float'>
>>> b = "31"
>>> result = yaml.load(b)
>>> result
31
>>> type(result)
<type 'int'>
>>> c = "HI"
>>> result = yaml.load(c)
>>> result
'HI'
>>> type(result)
<type 'str'>
I use this function for that
import ast
def parse_str(s):
try:
return ast.literal_eval(str(s))
except:
return
It will convert the string to its type
value = parse_str('1') # Returns Integer
value = parse_str('1.5') # Returns Float
def get_int_or_float(v):
number_as_float = float(v)
number_as_int = int(number_as_float)
return number_as_int if number_as_float == number_as_int else number_as_float
def num(s):
"""num(s)
num(3),num(3.7)-->3
num('3')-->3, num('3.7')-->3.7
num('3,700')-->ValueError
num('3a'),num('a3'),-->ValueError
num('3e4') --> 30000.0
"""
try:
return int(s)
except ValueError:
try:
return float(s)
except ValueError:
raise ValueError('argument is not a string of number')
You could use json.loads:
>>> import json
>>> json.loads('123.456')
123.456
>>> type(_)
<class 'float'>
>>>
As you can see it becomes a type of float.
You need to take into account rounding to do this properly.
i.e. - int(5.1) => 5
int(5.6) => 5 -- wrong, should be 6 so we do int(5.6 + 0.5) => 6
def convert(n):
try:
return int(n)
except ValueError:
return float(n + 0.5)
To typecast in Python use the constructor functions of the type, passing the string (or whatever value you are trying to cast) as a parameter.
For example:
>>>float("23.333")
23.333
Behind the scenes, Python is calling the objects __float__ method, which should return a float representation of the parameter. This is especially powerful, as you can define your own types (using classes) with a __float__ method so that it can be casted into a float using float(myobject).
Handles hex, octal, binary, decimal, and float
This solution will handle all of the string conventions for numbers (all that I know about).
def to_number(n):
''' Convert any number representation to a number
This covers: float, decimal, hex, and octal numbers.
'''
try:
return int(str(n), 0)
except:
try:
# Python 3 doesn't accept "010" as a valid octal. You must use the
# '0o' prefix
return int('0o' + n, 0)
except:
return float(n)
This test case output illustrates what I'm talking about.
======================== CAPTURED OUTPUT =========================
to_number(3735928559) = 3735928559 == 3735928559
to_number("0xFEEDFACE") = 4277009102 == 4277009102
to_number("0x0") = 0 == 0
to_number(100) = 100 == 100
to_number("42") = 42 == 42
to_number(8) = 8 == 8
to_number("0o20") = 16 == 16
to_number("020") = 16 == 16
to_number(3.14) = 3.14 == 3.14
to_number("2.72") = 2.72 == 2.72
to_number("1e3") = 1000.0 == 1000
to_number(0.001) = 0.001 == 0.001
to_number("0xA") = 10 == 10
to_number("012") = 10 == 10
to_number("0o12") = 10 == 10
to_number("0b01010") = 10 == 10
to_number("10") = 10 == 10
to_number("10.0") = 10.0 == 10
to_number("1e1") = 10.0 == 10
Here is the test:
class test_to_number(unittest.TestCase):
def test_hex(self):
# All of the following should be converted to an integer
#
values = [
# HEX
# ----------------------
# Input | Expected
# ----------------------
(0xDEADBEEF , 3735928559), # Hex
("0xFEEDFACE", 4277009102), # Hex
("0x0" , 0), # Hex
# Decimals
# ----------------------
# Input | Expected
# ----------------------
(100 , 100), # Decimal
("42" , 42), # Decimal
]
values += [
# Octals
# ----------------------
# Input | Expected
# ----------------------
(0o10 , 8), # Octal
("0o20" , 16), # Octal
("020" , 16), # Octal
]
values += [
# Floats
# ----------------------
# Input | Expected
# ----------------------
(3.14 , 3.14), # Float
("2.72" , 2.72), # Float
("1e3" , 1000), # Float
(1e-3 , 0.001), # Float
]
values += [
# All ints
# ----------------------
# Input | Expected
# ----------------------
("0xA" , 10),
("012" , 10),
("0o12" , 10),
("0b01010" , 10),
("10" , 10),
("10.0" , 10),
("1e1" , 10),
]
for _input, expected in values:
value = to_number(_input)
if isinstance(_input, str):
cmd = 'to_number("{}")'.format(_input)
else:
cmd = 'to_number({})'.format(_input)
print("{:23} = {:10} == {:10}".format(cmd, value, expected))
self.assertEqual(value, expected)
Pass your string to this function:
def string_to_number(str):
if("." in str):
try:
res = float(str)
except:
res = str
elif(str.isdigit()):
res = int(str)
else:
res = str
return(res)
It will return int, float or string depending on what was passed.
String that is an int
print(type(string_to_number("124")))
<class 'int'>
String that is a float
print(type(string_to_number("12.4")))
<class 'float'>
String that is a string
print(type(string_to_number("hello")))
<class 'str'>
String that looks like a float
print(type(string_to_number("hel.lo")))
<class 'str'>
There is also regex, because sometimes string must be prepared and normalized before casting to a number:
import re
def parseNumber(value, as_int=False):
try:
number = float(re.sub('[^.\-\d]', '', value))
if as_int:
return int(number + 0.5)
else:
return number
except ValueError:
return float('nan') # or None if you wish
Usage:
parseNumber('13,345')
> 13345.0
parseNumber('- 123 000')
> -123000.0
parseNumber('99999\n')
> 99999.0
And by the way, something to verify you have a number:
import numbers
def is_number(value):
return isinstance(value, numbers.Number)
# Will work with int, float, long, Decimal
a = int(float(a)) if int(float(a)) == float(a) else float(a)
This is a corrected version of Totoro's answer.
This will try to parse a string and return either int or float depending on what the string represents. It might rise parsing exceptions or have some unexpected behaviour.
def get_int_or_float(v):
number_as_float = float(v)
number_as_int = int(number_as_float)
return number_as_int if number_as_float == number_as_int else
number_as_float
If you are dealing with mixed integers and floats and want a consistent way to deal with your mixed data, here is my solution with the proper docstring:
def parse_num(candidate):
"""Parse string to number if possible
It work equally well with negative and positive numbers, integers and floats.
Args:
candidate (str): string to convert
Returns:
float | int | None: float or int if possible otherwise None
"""
try:
float_value = float(candidate)
except ValueError:
return None
# Optional part if you prefer int to float when decimal part is 0
if float_value.is_integer():
return int(float_value)
# end of the optional part
return float_value
# Test
candidates = ['34.77', '-13', 'jh', '8990', '76_3234_54']
res_list = list(map(parse_num, candidates))
print('Before:')
print(candidates)
print('After:')
print(res_list)
Output:
Before:
['34.77', '-13', 'jh', '8990', '76_3234_54']
After:
[34.77, -13, None, 8990, 76323454]
Use:
def num(s):
try:
for each in s:
yield int(each)
except ValueError:
yield float(each)
a = num(["123.55","345","44"])
print a.next()
print a.next()
This is the most Pythonic way I could come up with.
If you don't want to use third party modules the following might be the most robust solution:
def string_to_int_or_float(s):
try:
f = float(s) # replace s with str(s) if you are not sure that s is a string
except ValueError:
print("Provided string '" + s + "' is not interpretable as a literal number.")
raise
try:
i = int(str(f).rstrip('0').rstrip('.'))
except:
return f
return i
It might not be the fastest, but it handles correctly literal numbers where many other solutions fail, such as:
>>> string_to_int_or_float('789.')
789
>>> string_to_int_or_float('789.0')
789
>>> string_to_int_or_float('12.3e2')
1230
>>> string_to_int_or_float('12.3e-2')
0.123
>>> string_to_int_or_float('4560e-1')
456
>>> string_to_int_or_float('4560e-2')
45.6
You can simply do this by
s = '542.22'
f = float(s) # This converts string data to float data with a decimal point
print(f)
i = int(f) # This converts string data to integer data by just taking the whole number part of it
print(i)
For more information on parsing of data types check on python documentation!
This is a function which will convert any object (not just str) to int or float, based on if the actual string supplied looks like int or float. Further if it's an object which has both __float and __int__ methods, it defaults to using __float__
def conv_to_num(x, num_type='asis'):
'''Converts an object to a number if possible.
num_type: int, float, 'asis'
Defaults to floating point in case of ambiguity.
'''
import numbers
is_num, is_str, is_other = [False]*3
if isinstance(x, numbers.Number):
is_num = True
elif isinstance(x, str):
is_str = True
is_other = not any([is_num, is_str])
if is_num:
res = x
elif is_str:
is_float, is_int, is_char = [False]*3
try:
res = float(x)
if '.' in x:
is_float = True
else:
is_int = True
except ValueError:
res = x
is_char = True
else:
if num_type == 'asis':
funcs = [int, float]
else:
funcs = [num_type]
for func in funcs:
try:
res = func(x)
break
except TypeError:
continue
else:
res = x
By using int and float methods we can convert a string to integer and floats.
s="45.8"
print(float(s))
y='67'
print(int(y))
For numbers and characters together:
string_for_int = "498 results should get"
string_for_float = "498.45645765 results should get"
First import re:
import re
# For getting the integer part:
print(int(re.search(r'\d+', string_for_int).group())) #498
# For getting the float part:
print(float(re.search(r'\d+\.\d+', string_for_float).group())) #498.45645765
For easy model:
value1 = "10"
value2 = "10.2"
print(int(value1)) # 10
print(float(value2)) # 10.2
Given:
if parse_rec[i] != col_data:
parse_rec[i] = col_data
data_changed = True
print str(i)
print str(parse_rec[i])
print str(col_data)
print type(parse_rec[i])
print type(col_data)
print len(parse_rec[i])
print len(col_data)
print parse_rec[i] != col_data
I get:
10
1037864
1037864
<type 'str'>
<type 'str'>
7
7
False
If I change the test to:
if str(parse_rec[i]) != str(col_data):
It works as expected and the 'if' condition fails (they are equal) and nothing prints. What is the str() doing? Why do I need it? Can I not trust any string comparisons in Python?
I have verified it. There are no tabs in my file.
This would happen if e.g. parse_rec[i] originally contained the number 10 while col_data contained the string '10'. str converts any Python object to a string representation; converting both of them (with one already being a string) would make them equal.
Your two data are strings and can be safely compared with the == operator.
What str() does:
Return a string containing a nicely printable representation of an object. For strings, this returns the string itself.
If you had an integer and a string, str() becomes necessary:
print 123 == '123' # false
print 123 is '123' # false
print str(123) == '123' # true
print '123' == '123' # true
print '123' is '123' # false
varA = 1
varB = 2
Code w/ Correct Result:
if type(varA) == type('a') or type(varB) == type('a'):
print "string involved (either varA or varB is a string)"
else:
print "varA and varB are not strings"
Code w/ Incorrect Result:
if type(varA) or type(varB) == type('a'):
print "string involved (either varA or varB is a string)"
else:
print "varA and varB are not strings"
Why exactly does the 2nd set of code not return the expected result (i.e. "varA and varB are not strings")? What is the step-by-step breakdown of what Python is doing with the 2nd set of code? I found a similar question had already been answered but did not entirely understand the explanation. Python: If-else statements.
In the second code snippet, the condition of the if-statement is being interpreted by Python like this:
if (type(varA)) or (type(varB) == type('a')):
Moreover, it will always evaluate to True.
This is because, no matter what the value of varA is, type(varA) evaluates to True:
>>> varA = 'a'
>>> bool(type(varA))
True
>>> varA = False
>>> bool(type(varA))
True
>>>
In fact, since Python's logical operators short-circuit (stop evaluating as soon as possible), the type(varB) == type('a') part of the condition will never even be evaluated.
On a separate note, you should be using is to compare types:
if type(varA) is str or type(varB) is str:
or, you can use isinstance:
if isinstance(varA, str) or isinstance(varB, str):
Your second example does not work because it parses as
if (type(varA)) or (type(varB) == type('a')):
and type(varA) will always be a class type which is considered True, so the whole expression will be True
There are better ways to do this
if any(isinstance(v, str) for v in (varA, varB)):
any takes an iterable and evaluates to True if anything in the iterable is true.
isinstance checks to see if the first argument "is a" second argument. Placing the generator expression inside of any reads as "if any v in (varA, varB) is a string): ... "
>>> var = 1
>>> isinstance(var, str) # var is an int, not a str
False
>>> isinstance(var, int)
True
>>> isinstance('a', int)
False
>>> isinstance('a', str) # 'a' is a str
True
iCodez is absolutely correct, but if you really want to do something along the lines of "list all elements and check if one of them is a string":
if str in map(type, [varA, varB]):
print "string involved"
Because in the second case you are not comparing both variables. Any integer above 0 would return True so you are not comparing types here.
if type(varA):
will always be True, because varA is equal to 1. You never even get to the second part of the condition.