np.array([e[::-1] for e in arr]) is the straight forward way of doing this, and is NOT bad numpy. or bypass numpy entirely with [e[::-1] for e in arr.tolist()]. You could also do something similar with np.vectorize or np.frompyfunc. These might scale a bit better.
'vectorize' in numpy means using compiled methods (and operators) to do the necessary iterations in compiled code. Those are nearly all numeric operations. For strings, numpy uses Python string methods. It does not have its own compiled string operations. Even the np.char functions use python string methods.
So there's no numpy equivalent to astr[::-1].
Some comparative times
In [16]: timeit np.array([s[::-1] for s in arr])
36.1 µs ± 151 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [17]: timeit np.array([s[::-1] for s in arr.tolist()])
21.1 µs ± 76.5 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [18]: timeit [s[::-1] for s in arr.tolist()]
8.29 µs ± 23.2 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)
In [20]: timeit np.vectorize(lambda s: s[::-1])(arr)
65.9 µs ± 165 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [21]: timeit np.frompyfunc(lambda s: s[::-1],1,1)(arr)
20.3 µs ± 76.5 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
Answer from hpaulj on Stack Overflownp.array([e[::-1] for e in arr]) is the straight forward way of doing this, and is NOT bad numpy. or bypass numpy entirely with [e[::-1] for e in arr.tolist()]. You could also do something similar with np.vectorize or np.frompyfunc. These might scale a bit better.
'vectorize' in numpy means using compiled methods (and operators) to do the necessary iterations in compiled code. Those are nearly all numeric operations. For strings, numpy uses Python string methods. It does not have its own compiled string operations. Even the np.char functions use python string methods.
So there's no numpy equivalent to astr[::-1].
Some comparative times
In [16]: timeit np.array([s[::-1] for s in arr])
36.1 µs ± 151 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [17]: timeit np.array([s[::-1] for s in arr.tolist()])
21.1 µs ± 76.5 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [18]: timeit [s[::-1] for s in arr.tolist()]
8.29 µs ± 23.2 ns per loop (mean ± std. dev. of 7 runs, 100,000 loops each)
In [20]: timeit np.vectorize(lambda s: s[::-1])(arr)
65.9 µs ± 165 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
In [21]: timeit np.frompyfunc(lambda s: s[::-1],1,1)(arr)
20.3 µs ± 76.5 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
The following does the job by considering a different view of the original array. This means no additional arrays (and thus memory) are required. And no for loops :)
import numpy as np
A = np.array(['2', '3', '5', '7', '11', '13', '17', '19', '23', '29', '31', '37',
'41', '43', '47', '53', '59', '61', '67', '71', '73', '79', '83',
'89', '97'], dtype='<U2')
B = A.view(np.uint32) # Interpret as individual numbers
B = B.reshape((A.shape[0],2)) # Group numbers in pairs
B[B[:,1] != 0, :] = B[B[:,1] != 0, ::-1] # Flip pairs if more than 1 digit
print(A) # ['2' '3' '5' '7' '11' '31' '71' '91' '32' '92' '13' '73' '14' '34' '74' '35' '95' '16' '76' '17' '37' '97' '38' '98' '79']
For short arrays, like the one you gave, @hpaulj's answer is faster. But for larger arrays, this method is faster. As an example, for an array of 100,000 elements, this method is approximately 5x faster compared to @hpaulj's fastest method ([s[::-1] for s in arr.tolist()]).
import numpy as np
class PythonRevStrListArr:
def __init__(self, Str, List1, Arr):
self.Str = Str
self.List1 = List1
self.Arr = Arr
def ReverseList(self):
self.List1.reverse()
print("Lis1" + self.List1)
def ReverseString(self):
self.Str[::-1]
print("Str = "+self.Str)
def ReverseArray(self):
np.flip(self.Arr)
print("Arr = "+self.Arr)
if __name__ == "__main__":
List1 = [10, 20, 30, 40, 50]
Str1 = "5, 15, 25, 35"
arr = np.array([1, 11, 21, 31, 41, 51])
obj = PythonRevStrListArr(Str1, List1, arr)
obj.ReverseArray()
obj.ReverseString()
obj.ReverseList()Hi,
I am getting following error message:
Traceback (most recent call last): File "/home/zulfi/PycharmProjects/pythonProject2/main2.py", line 27, in <module>
obj.ReverseArray()
File "/home/zulfi/PycharmProjects/pythonProject2/main2.py", line 20, in ReverseArray print("Arr = "+self.Arr)
numpy.core._exceptions.UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U21'), dtype('<U21')) -> dtype('<U21')Somebody please guide me.
Zulfi.
Quick Tip: Reversing a string in Python (in 1 line of code)
How do I reverse a string in Python? - Stack Overflow
linux - How to print string array in reverse order in python - Stack Overflow
Python: Reversing Array, List and String: problem with print
Videos
You can easily reverse a string in python like this:
print("Hello"[::-1])
This syntax reverses the string by converting it to an array (in python strings are actually arrays of characters) and then slicing it The syntax for the array slicing is as follows: [start:end:step]
where empty start means 0 and empty stop means the length of the array. So [::-1] means to slice the array from the 1st element to the last element in reverse order.
Hope you enjoyed it!
Using slicing:
>>> 'hello world'[::-1]
'dlrow olleh'
Slice notation takes the form [start:stop:step]. In this case, we omit the start and stop positions since we want the whole string. We also use step = -1, which means, "repeatedly step from right to left by 1 character".
What is the best way of implementing a reverse function for strings?
My own experience with this question is academic. However, if you're a pro looking for the quick answer, use a slice that steps by -1:
>>> 'a string'[::-1]
'gnirts a'
or more readably (but slower due to the method name lookups and the fact that join forms a list when given an iterator), str.join:
>>> ''.join(reversed('a string'))
'gnirts a'
or for readability and reusability, put the slice in a function
def reversed_string(a_string):
return a_string[::-1]
and then:
>>> reversed_string('a_string')
'gnirts_a'
Longer explanation
If you're interested in the academic exposition, please keep reading.
There is no built-in reverse function in Python's str object.
Here is a couple of things about Python's strings you should know:
In Python, strings are immutable. Changing a string does not modify the string. It creates a new one.
Strings are sliceable. Slicing a string gives you a new string from one point in the string, backwards or forwards, to another point, by given increments. They take slice notation or a slice object in a subscript:
string[subscript]
The subscript creates a slice by including a colon within the braces:
string[start:stop:step]
To create a slice outside of the braces, you'll need to create a slice object:
slice_obj = slice(start, stop, step)
string[slice_obj]
A readable approach:
While ''.join(reversed('foo')) is readable, it requires calling a string method, str.join, on another called function, which can be rather relatively slow. Let's put this in a function - we'll come back to it:
def reverse_string_readable_answer(string):
return ''.join(reversed(string))
Most performant approach:
Much faster is using a reverse slice:
'foo'[::-1]
But how can we make this more readable and understandable to someone less familiar with slices or the intent of the original author? Let's create a slice object outside of the subscript notation, give it a descriptive name, and pass it to the subscript notation.
start = stop = None
step = -1
reverse_slice = slice(start, stop, step)
'foo'[reverse_slice]
Implement as Function
To actually implement this as a function, I think it is semantically clear enough to simply use a descriptive name:
def reversed_string(a_string):
return a_string[::-1]
And usage is simply:
reversed_string('foo')
What your teacher probably wants:
If you have an instructor, they probably want you to start with an empty string, and build up a new string from the old one. You can do this with pure syntax and literals using a while loop:
def reverse_a_string_slowly(a_string):
new_string = ''
index = len(a_string)
while index:
index -= 1 # index = index - 1
new_string += a_string[index] # new_string = new_string + character
return new_string
This is theoretically bad because, remember, strings are immutable - so every time where it looks like you're appending a character onto your new_string, it's theoretically creating a new string every time! However, CPython knows how to optimize this in certain cases, of which this trivial case is one.
Best Practice
Theoretically better is to collect your substrings in a list, and join them later:
def reverse_a_string_more_slowly(a_string):
new_strings = []
index = len(a_string)
while index:
index -= 1
new_strings.append(a_string[index])
return ''.join(new_strings)
However, as we will see in the timings below for CPython, this actually takes longer, because CPython can optimize the string concatenation.
Timings
Here are the timings:
>>> a_string = 'amanaplanacanalpanama' * 10
>>> min(timeit.repeat(lambda: reverse_string_readable_answer(a_string)))
10.38789987564087
>>> min(timeit.repeat(lambda: reversed_string(a_string)))
0.6622700691223145
>>> min(timeit.repeat(lambda: reverse_a_string_slowly(a_string)))
25.756799936294556
>>> min(timeit.repeat(lambda: reverse_a_string_more_slowly(a_string)))
38.73570013046265
CPython optimizes string concatenation, whereas other implementations may not:
... do not rely on CPython's efficient implementation of in-place string concatenation for statements in the form a += b or a = a + b . This optimization is fragile even in CPython (it only works for some types) and isn't present at all in implementations that don't use refcounting. In performance sensitive parts of the library, the ''.join() form should be used instead. This will ensure that concatenation occurs in linear time across various implementations.