repr(): evaluatable string representation of an object (can "eval()"
it, meaning it is a string representation that evaluates to a Python
object)
In other words:
>>> x = 'foo'
>>> repr(x)
"'foo'"
Questions:
Why do I get the double quotes when I do repr(x)? (I don't get them
when I do str(x))
Why do I get 'foo' when I do eval("'foo'") and not x which is the
object?
>>> x = 'foo'
>>> x
'foo'
So the name x is attached to 'foo' string. When you call for example repr(x) the interpreter puts 'foo' instead of x and then calls repr('foo').
>>> repr(x)
"'foo'"
>>> x.__repr__()
"'foo'"
repr actually calls a magic method __repr__ of x, which gives the string containing the representation of the value 'foo' assigned to x. So it returns 'foo' inside the string "" resulting in "'foo'". The idea of repr is to give a string which contains a series of symbols which we can type in the interpreter and get the same value which was sent as an argument to repr.
>>> eval("'foo'")
'foo'
When we call eval("'foo'"), it's the same as we type 'foo' in the interpreter. It's as we directly type the contents of the outer string "" in the interpreter.
>>> eval('foo')
Traceback (most recent call last):
File "<pyshell#5>", line 1, in <module>
eval('foo')
File "<string>", line 1, in <module>
NameError: name 'foo' is not defined
If we call eval('foo'), it's the same as we type foo in the interpreter. But there is no foo variable available and an exception is raised.
>>> str(x)
'foo'
>>> x.__str__()
'foo'
>>>
str is just the string representation of the object (remember, x variable refers to 'foo'), so this function returns string.
>>> str(5)
'5'
String representation of integer 5 is '5'.
>>> str('foo')
'foo'
And string representation of string 'foo' is the same string 'foo'.
The feedback you get on the interactive interpreter uses repr too. When you type in an expression (let it be expr), the interpreter basically does result = expr; if result is not None: print repr(result). So the second line in your example is formatting the string foo into the representation you want ('foo'). And then the interpreter creates the representation of that, leaving you with double quotes.
Why when I combine %r with double-quote and single quote escapes and print them out, it prints it the way I'd write it in my .py file but not the way I'd like to see it?
I'm not sure what you're asking here. The text single ' and double " quotes, when run through repr, includes escapes for one kind of quote. Of course it does, otherwise it wouldn't be a valid string literal by Python rules. That's precisely what you asked for by calling repr.
Also note that the eval(repr(x)) == x analogy isn't meant literal. It's an approximation and holds true for most (all?) built-in types, but the main thing is that you get a fairly good idea of the type and logical "value" from looking the the repr output.
str() is used for creating output for end user while repr() is used for debugging during development. And it's an official representation of the object.
Example:
>>> import datetime
>>> today = datetime.datetime.now()
>>> str(today)
'2018-04-08 18:00:15.178404'
>>> repr(today)
'datetime.datetime(2018, 4, 8, 18, 3, 21, 167886)'
From output we see that repr() shows the official representation of date object.
1) The result of repr('foo') is the string 'foo'. In your Python shell, the result of the expression is expressed as a representation too, so you're essentially seeing repr(repr('foo')).
2) eval calculates the result of an expression. The result is always a value (such as a number, a string, or an object). Multiple variables can refer to the same value, as in:
x = 'foo'
y = x
x and y now refer to the same value.
3) I have no idea what you meant here. Can you post an example, and what you'd like to see?
When you say
foo = 'bar'
baz(foo)
you are not passing foo to the baz function. foo is just a name used to represent a value, in this case 'bar', and that value is passed to the baz function.
I type following code
z=1+2j
z=list(str(z))
I get output as
['(','1','+','2','j',')']
but when I write the following code
z=input('')
z=list(str(z))
print(z)
I get output as
['1','+','2','j']
and not the curve brackets in the list why?
When using input(), you entered 4 characters: 1,+,2,j. Together, they may have the same semantic value to you as the number 1+2j, but as far as Python is concerned, the former case is just four characters. Python doesn't have any way of knowing you think those characters should be converted to a single numerical value.
You can observe the differences with a few print statements.
And you can explicitly declare that this four-character string should be interpreted as a complex number, with complex():
a = input('') # input: "1+2j"
print(a) # i+2j
print(type(a)) # <class 'str'>
b = complex(a)
print(b) # (1+2j)
print(type(b)) # <class 'complex'>
You probably meant:
z = "1+2j"
When you typed the code
z=1+2j
z=list(str(z))
Type of z is complex. Calling the function str on it will simply give you what __str__ function of class complex returns. In your case, str(z) would return
'(1+2j)'
When you do z=list(str(z)), it gives you a list of all the characters in str(z). Now z points to a list not to a complex object.
When you run this
z=input('')
z=list(str(z))
print(z)
input('') gives you a str type value. Whatever you enter here is converted to the list when you call z=list(str(z)).
How do I see the type of a variable? (e.g. unsigned 32 bit)
Use the type() builtin function:
>>> i = 123
>>> type(i)
<type 'int'>
>>> type(i) is int
True
>>> i = 123.456
>>> type(i)
<type 'float'>
>>> type(i) is float
True
To check if a variable is of a given type, use isinstance:
>>> i = 123
>>> isinstance(i, int)
True
>>> isinstance(i, (float, str, set, dict))
False
Note that Python doesn't have the same types as C/C++, which appears to be your question.
You may be looking for the type() built-in function.
See the examples below, but there's no "unsigned" type in Python just like Java.
Positive integer:
>>> v = 10
>>> type(v)
<type 'int'>
Large positive integer:
>>> v = 100000000000000
>>> type(v)
<type 'long'>
Negative integer:
>>> v = -10
>>> type(v)
<type 'int'>
Literal sequence of characters:
>>> v = 'hi'
>>> type(v)
<type 'str'>
Floating point integer:
>>> v = 3.14159
>>> type(v)
<type 'float'>
It is so simple. You do it like this.
print(type(variable_name))
How to determine the variable type in Python?
So if you have a variable, for example:
one = 1
You want to know its type?
There are right ways and wrong ways to do just about everything in Python. Here's the right way:
Use type
>>> type(one)
<type 'int'>
You can use the __name__ attribute to get the name of the object. (This is one of the few special attributes that you need to use the __dunder__ name to get to - there's not even a method for it in the inspect module.)
>>> type(one).__name__
'int'
Don't use __class__
In Python, names that start with underscores are semantically not a part of the public API, and it's a best practice for users to avoid using them. (Except when absolutely necessary.)
Since type gives us the class of the object, we should avoid getting this directly. :
>>> one.__class__
This is usually the first idea people have when accessing the type of an object in a method - they're already looking for attributes, so type seems weird. For example:
class Foo(object):
def foo(self):
self.__class__
Don't. Instead, do type(self):
class Foo(object):
def foo(self):
type(self)
Implementation details of ints and floats
How do I see the type of a variable whether it is unsigned 32 bit, signed 16 bit, etc.?
In Python, these specifics are implementation details. So, in general, we don't usually worry about this in Python. However, to sate your curiosity...
In Python 2, int is usually a signed integer equal to the implementation's word width (limited by the system). It's usually implemented as a long in C. When integers get bigger than this, we usually convert them to Python longs (with unlimited precision, not to be confused with C longs).
For example, in a 32 bit Python 2, we can deduce that int is a signed 32 bit integer:
>>> import sys
>>> format(sys.maxint, '032b')
'01111111111111111111111111111111'
>>> format(-sys.maxint - 1, '032b') # minimum value, see docs.
'-10000000000000000000000000000000'
In Python 3, the old int goes away, and we just use (Python's) long as int, which has unlimited precision.
We can also get some information about Python's floats, which are usually implemented as a double in C:
>>> sys.float_info
sys.floatinfo(max=1.7976931348623157e+308, max_exp=1024, max_10_exp=308,
min=2.2250738585072014e-308, min_exp=-1021, min_10_exp=-307, dig=15,
mant_dig=53, epsilon=2.2204460492503131e-16, radix=2, rounds=1)
Conclusion
Don't use __class__, a semantically nonpublic API, to get the type of a variable. Use type instead.
And don't worry too much about the implementation details of Python. I've not had to deal with issues around this myself. You probably won't either, and if you really do, you should know enough not to be looking to this answer for what to do.
print type(variable_name)
I also highly recommend the IPython interactive interpreter when dealing with questions like this. It lets you type variable_name? and will return a whole list of information about the object including the type and the doc string for the type.
e.g.
In [9]: var = 123
In [10]: var?
Type: int
Base Class: <type 'int'>
String Form: 123
Namespace: Interactive
Docstring:
int(x[, base]) -> integer
Convert a string or number to an integer, if possible. A floating point argument will be truncated towards zero (this does not include a string
representation of a floating point number!) When converting a string, use the optional base. It is an error to supply a base when converting a
non-string. If the argument is outside the integer range a long object
will be returned instead.
a = "cool"
type(a)
//result 'str'
<class 'str'>
or
do
`dir(a)`
to see the list of inbuilt methods you can have on the variable.
One more way using __class__:
>>> a = [1, 2, 3, 4]
>>> a.__class__
<type 'list'>
>>> b = {'key1': 'val1'}
>>> b.__class__
<type 'dict'>
>>> c = 12
>>> c.__class__
<type 'int'>
Examples of simple type checking in Python:
assert type(variable_name) == int
assert type(variable_name) == bool
assert type(variable_name) == list
It may be little irrelevant. but you can check types of an object with isinstance(object, type) as mentioned here.
The question is somewhat ambiguous -- I'm not sure what you mean by "view". If you are trying to query the type of a native Python object, #atzz's answer will steer you in the right direction.
However, if you are trying to generate Python objects that have the semantics of primitive C-types, (such as uint32_t, int16_t), use the struct module. You can determine the number of bits in a given C-type primitive thusly:
>>> struct.calcsize('c') # char
1
>>> struct.calcsize('h') # short
2
>>> struct.calcsize('i') # int
4
>>> struct.calcsize('l') # long
4
This is also reflected in the array module, which can make arrays of these lower-level types:
>>> array.array('c').itemsize # char
1
The maximum integer supported (Python 2's int) is given by sys.maxint.
>>> import sys, math
>>> math.ceil(math.log(sys.maxint, 2)) + 1 # Signedness
32.0
There is also sys.getsizeof, which returns the actual size of the Python object in residual memory:
>>> a = 5
>>> sys.getsizeof(a) # Residual memory.
12
For float data and precision data, use sys.float_info:
>>> sys.float_info
sys.floatinfo(max=1.7976931348623157e+308, max_exp=1024, max_10_exp=308, min=2.2250738585072014e-308, min_exp=-1021, min_10_exp=-307, dig=15, mant_dig=53, epsilon=2.2204460492503131e-16, radix=2, rounds=1)
Do you mean in Python or using ctypes?
In the first case, you simply cannot - because Python does not have signed/unsigned, 16/32 bit integers.
In the second case, you can use type():
>>> import ctypes
>>> a = ctypes.c_uint() # unsigned int
>>> type(a)
<class 'ctypes.c_ulong'>
For more reference on ctypes, an its type, see the official documentation.
Python doesn't have such types as you describe. There are two types used to represent integral values: int, which corresponds to platform's int type in C, and long, which is an arbitrary precision integer (i.e. it grows as needed and doesn't have an upper limit). ints are silently converted to long if an expression produces result which cannot be stored in int.
Simple, for python 3.4 and above
print (type(variable_name))
Python 2.7 and above
print type(variable_name)
It really depends on what level you mean. In Python 2.x, there are two integer types, int (constrained to sys.maxint) and long (unlimited precision), for historical reasons. In Python code, this shouldn't make a bit of difference because the interpreter automatically converts to long when a number is too large. If you want to know about the actual data types used in the underlying interpreter, that's implementation dependent. (CPython's are located in Objects/intobject.c and Objects/longobject.c.) To find out about the systems types look at cdleary answer for using the struct module.
For python2.x, use
print type(variable_name)
For python3.x, use
print(type(variable_name))
You should use the type() function. Like so:
my_variable = 5
print(type(my_variable)) # Would print out <class 'int'>
This function will view the type of any variable, whether it's a list or a class. Check this website for more information: https://www.w3schools.com/python/ref_func_type.asp
Python is a dynamically typed language. A variable, initially created as a string, can be later reassigned to an integer or a float. And the interpreter won’t complain:
name = "AnyValue"
# Dynamically typed language lets you do this:
name = 21
name = None
name = Exception()
To check the type of a variable, you can use either type() or isinstance() built-in function. Let’s see them in action:
Python3 example:
variable = "hello_world"
print(type(variable) is str) # True
print(isinstance(variable, str)) # True
Let's compare both methods performances in python3
python3 -m timeit -s "variable = 'hello_world'" "type(variable) is int"
5000000 loops, best of 5: 54.5 nsec per loop
python3 -m timeit -s "variable = 'hello_world'" "isinstance(variable, str)"
10000000 loops, best of 5: 39.2 nsec per loop
type is 40% slower approximately (54.5/39.2 = 1.390).
We could use type(variable) == str instead. It would work, but it’s a bad idea:
== should be used when you want to check the value of a variable. We would use it to see if the value of the variable is equal to "hello_world". But when we want to check if the variable is a string, is the operator is more appropriate. For a more detailed explanation of when to use one or the other, check this article.
== is slower: python3 -m timeit -s "variable = 'hello_world'" "type(variable) == str" 5000000 loops, best of 5: 64.4 nsec per loop
Difference between isinstance and type
Speed is not the only difference between these two functions. There is actually an important distinction between how they work:
type only returns the type of an object (it's class). We can use it to check if the variable is of type str.
isinstance checks if a given object (first parameter) is:
an instance of a class specified as a second parameter. For example, is variable an instance of the str class?
or an instance of a subclass of a class specified as a second parameter. In other words - is variable an instance of a subclass of str?
What does it mean in practice? Let’s say we want to have a custom class that acts as a list but has some additional methods. So we might subclass the list type and add custom functions inside:
class MyAwesomeList(list):
# Add additional functions here
pass
But now the type and isinstance return different results if we compare this new class to a list!
my_list = MyAwesomeList()
print(type(my_list) is list) # False
print(isinstance(my_list, list)) # True
We get different results because isinstance checks if my_list is an instance of the list (it’s not) or a subclass of the list (it is because MyAwesomeList is a subclass of the list). If you forget about this difference, it can lead to some subtle bugs in your code.
Conclusions
isinstance is usually the preferred way to compare types. It’s not only faster but also considers inheritance, which is often the desired behavior. In Python, you usually want to check if a given object behaves like a string or a list, not necessarily if it’s exactly a string. So instead of checking for string and all its custom subclasses, you can just use isinstance.
On the other hand, when you want to explicitly check that a given variable is of a specific type (and not its subclass) - use type. And when you use it, use it like this: type(var) is some_type not like this: type(var) == some_type.
I saw this one when I was new to Python (I still am):
x = …
print(type(x))```
There's no 32bit and 64bit and 16bit, python is simple, you don't have to worry about it. See how to check the type:
integer = 1
print(type(integer)) # Result: <class 'int'>, and if it's a string then class will be str and so on.
# Checking the type
float_class = 1.3
print(isinstance(float_class, float)) # True
But if you really have to, you can use Ctypes library which has types like unsigned integer.
Ctypes types documentation
You can use it like this:
from ctypes import *
uint = c_uint(1) # Unsigned integer
print(uint) # Output: c_uint(1)
# To actually get the value, you have to call .value
print(uint.value)
# Change value
uint.value = 2
print(uint.value) # 2
There are many data types in python like:
Text Type: str
Numeric Types: int, float, complex
Sequence Types: list, tuple, range
Mapping Type: dict
Set Types: set, frozenset
Boolean Type: bool
Binary Types: bytes, bytearray, memoryview
None Type: NoneType
Here I have written a code having a list containing all type of data types example and printing their type
L = [
"Hello World",
20,
20.5,
1j,
["apple", "banana", "cherry"],
("apple", "banana", "cherry"),
range(6),
{"name" : "John", "age" : 36},
{"apple", "banana", "cherry"},
frozenset({"apple", "banana", "cherry"}),
True,
b"Hello",
bytearray(5),
memoryview(bytes(5)),
None
]
for _ in range(len(L)):
print(type(L[_]))
OUTPUT:
<class 'str'>
<class 'int'>
<class 'float'>
<class 'complex'>
<class 'list'>
<class 'tuple'>
<class 'range'>
<class 'dict'>
<class 'set'>
<class 'frozenset'>
<class 'bool'>
<class 'bytes'>
<class 'bytearray'>
<class 'memoryview'>
<class 'NoneType'>
Just do not do it. Asking for something's type is wrong in itself. Instead use polymorphism. Find or if necessary define by yourself the method that does what you want for any possible type of input and just call it without asking about anything. If you need to work with built-in types or types defined by a third-party library, you can always inherit from them and use your own derivatives instead. Or you can wrap them inside your own class. This is the object-oriented way to resolve such problems.
If you insist on checking exact type and placing some dirty ifs here and there, you can use __class__ property or type function to do it, but soon you will find yourself updating all these ifs with additional cases every two or three commits. Doing it the OO way prevents that and lets you only define a new class for a new type of input instead.