How do I find the missing number from a sorted list the pythonic way?
a=[1,2,3,4,5,7,8,9,10]
I have come across this post but is there a more and efficient way to do this?
>>> a=[1,2,3,4,5,7,8,9,10]
>>> sum(xrange(a[0],a[-1]+1)) - sum(a)
6
alternatively (using the sum of AP series formula)
>>> a[-1]*(a[-1] + a[0]) / 2 - sum(a)
6
For generic cases when multiple numbers may be missing, you can formulate an O(n) approach.
>>> a=[1,2,3,4,7,8,10]
>>> from itertools import imap, chain
>>> from operator import sub
>>> print list(chain.from_iterable((a[i] + d for d in xrange(1, diff))
for i, diff in enumerate(imap(sub, a[1:], a))
if diff > 1))
[5, 6, 9]
This should work:
a = [1, 3, 4, 5, 7, 8, 9, 10]
b = [x for x in range(a[0], a[-1] + 1)]
a = set(a)
print(list(a ^ set(b)))
>>> [2, 6]
1 + 2 + 3 + ... + (n - 1) + n = (n) * (n + 1)/2
so the missing number is:
(a[-1] * (a[-1] + 1))/2 - sum(a)
set(range(a[len(a)-1])[1:]) - set(a)
Take the set of all numbers minus the set of given.
And another itertools way:
from itertools import count, izip
a=[1,2,3,4,5,7,8,9,10]
nums = (b for a, b in izip(a, count(a[0])) if a != b)
next(nums, None)
# 6
This will handle the cases when the first or last number is missing.
>>> a=[1,2,3,4,5,7,8,9,10]
>>> n = len(a) + 1
>>> (n*(n+1)/2) - sum(a)
6
If many missing numbers in list:
>>> a=[1,2,3,4,5,7,8,10]
>>> [(e1+1) for e1,e2 in zip(a, a[1:]) if e2-e1 != 1]
[6, 9]
def find(arr):
for x in range(0,len(arr) -1):
if arr[x+1] - arr[x] != 1:
print arr[x] + 1
Simple solution for the above problem, it also finds multiple missing elements.
a = [1,2,3,4,5,8,9,10]
missing_element = []
for i in range(a[0], a[-1]+1):
if i not in a:
missing_element.append(i)
print missing_element
o/p:
[6,7]
Here is the simple logic for finding mising numbers in list.
l=[-10,-5,2,4,5,9,20]
s=l[0]
e=l[-1]
x=sorted(range(s,e+1))
l_1=[]
for i in x:
if i not in l:
l_1.append(i)
print(l_1)
def findAllMissingNumbers(a):
b = sorted(a)
return list(set(range(b[0], b[-1])) - set(b))
L=[-5,1,2,3,4,5,7,8,9,10,13,55]
missing=[]
for i in range(L[0],L[-1]):
if i not in L:
missing.append(i)
print(missing)
A simple list comprehension approach that will work with multiple (non-consecutive) missing numbers.
def find_missing(lst):
"""Create list of integers missing from lst."""
return [lst[x] + 1 for x in range(len(lst) - 1)
if lst[x] + 1 != lst[x + 1]]
There is a perfectly working solution by #Abhiji. I would like to extent his answer by the option to define a granularity value. This might be necessary if the list should be checked for a missing value > 1:
from itertools import imap, chain
from operator import sub
granularity = 3600
data = [3600, 10800, 14400]
print list(
chain.from_iterable(
(data[i] + d for d in xrange(1, diff) if d % granularity == 0)
for i, diff in enumerate(imap(sub, data[1:], data))
if diff > granularity
)
)
The code above would produce the following output: [7200].
As this code snipped uses a lot of nested functions, I'd further like to provide a quick back reference, that helped me to understand the code:
Python enumerate()
Python imap()
Python chain.from_iterable()
Less efficient for very large lists, but here's my version for the Sum formula:
def missing_number_sum(arr):
return int((arr[-1]+1) * arr[-1]/2) - sum(arr)
If the range is known and the list is given, the below approach will work.
a=[1,2,3,4,5,7,8,9,10]
missingValues = [i for i in range(1, 10+1) if i not in a]
print(missingValues)
# o/p: [6]
set(range(1,a[-1])) | set(a)
Compute the union of two sets.
I used index position.
this way i compare index and value.
a=[0,1,2,3,4,5,7,8,9,10]
for i in a:
print i==a.index(i)
Related
Hello I have a List with a lot of element in it. These are numbers and ordered but some numbers are missing.
Example: L =[1,2,3,4,6,7,10]
Missing: M = [5,8,9]
How can I find missing numbers in Python?
Take the difference between the sets:
set(range(min(L),max(L))) - set(L)
If you are really crunched for time and L is truly sorted, then
set(range(L[0], L[-1])) - set(L)
This function should do the trick
def missing_elements(L):
s, e = L[0], L[-1]
return sorted(set(range(s, e + 1)).difference(L))
miss = missing_elements(L)
Here you are:
L =[1,2,3,4,6,7,10]
M = [i for i in range(1, max(L)) if i not in L]
# If 0 shall be included replace range(1, max(L)) to range(max(L))
With a comprehension it would look like this:
L = [1,2,3,4,6,7,10]
M = [i for i in range(min(L), max(L)+1) if i not in L]
M
#[5,8,9]
And a fun one, just to add to the bunch:
[i for a, b in zip(L, L[1:]) for i in range(a + 1, b) if b - a > 1]
L =[1,2,3,4,6,7,10]
R = range(1, max(L) + 1)
> [1,2,3,4,5,6,7,8,9,10]
M = list(set(R) - set(L))
> [5,8,9]
Note that M will not necessarily be ordered, but can easily be sorted.
Hi so i'm trying to make a function where I subtract the first number with the second and then add the third then subtract the fourth ie. x1-x2+x3-x4+x5-x6...
So far I have this, I can only add two variables, x and y. Was thinking of doing
>>> reduce(lambda x,y: (x-y) +x, [2,5,8,10]
Still not getting it
pretty simple stuff just confused..
In this very case it would be easier to use sums:
a = [2,5,8,10]
sum(a[::2])-sum(a[1::2])
-5
Use a multiplier that you revert to +- after each addition.
result = 0
mult = 1
for i in [2,5,8,10]:
result += i*mult
mult *= -1
You can keep track of the position (and thus whether to do + or -) with enumerate, and you could use the fact that -12n is +1 and -12n+1 is -1. Use this as a factor and sum all the terms.
>>> sum(e * (-1)**i for i, e in enumerate([2,5,8,10]))
-5
If you really want to use reduce, for some reason, you could do something like this:
class plusminus(object):
def __init__(self):
self._plus = True
def __call__(self, a, b):
self._plus ^= True
if self._plus:
return a+b
return a-b
reduce(plusminus(), [2,5,8,10]) # output: -5
Or just using sum and a generator:
In [18]: xs
Out[18]: [1, 2, 3, 4, 5]
In [19]: def plusminus(iterable):
....: for i, x in enumerate(iterable):
....: if i%2 == 0:
....: yield x
....: else:
....: yield -x
....:
In [20]: sum(plusminus(xs))
Out[20]: 3
Which could also be expressed as:
sum(map(lambda x: operator.mul(*x), zip(xs, itertools.cycle([1, -1]))))
I know there is nothing wrong with writing with proper function structure, but I would like to know how can I find nth fibonacci number with most Pythonic way with a one-line.
I wrote that code, but It didn't seem to me best way:
>>> fib = lambda n:reduce(lambda x, y: (x[0]+x[1], x[0]), [(1,1)]*(n-2))[0]
>>> fib(8)
13
How could it be better and simplier?
fib = lambda n:reduce(lambda x,n:[x[1],x[0]+x[1]], range(n),[0,1])[0]
(this maintains a tuple mapped from [a,b] to [b,a+b], initialized to [0,1], iterated N times, then takes the first tuple element)
>>> fib(1000)
43466557686937456435688527675040625802564660517371780402481729089536555417949051
89040387984007925516929592259308032263477520968962323987332247116164299644090653
3187938298969649928516003704476137795166849228875L
(note that in this numbering, fib(0) = 0, fib(1) = 1, fib(2) = 1, fib(3) = 2, etc.)
(also note: reduce is a builtin in Python 2.7 but not in Python 3; you'd need to execute from functools import reduce in Python 3.)
A rarely seen trick is that a lambda function can refer to itself recursively:
fib = lambda n: n if n < 2 else fib(n-1) + fib(n-2)
By the way, it's rarely seen because it's confusing, and in this case it is also inefficient. It's much better to write it on multiple lines:
def fibs():
a = 0
b = 1
while True:
yield a
a, b = b, a + b
I recently learned about using matrix multiplication to generate Fibonacci numbers, which was pretty cool. You take a base matrix:
[1, 1]
[1, 0]
and multiply it by itself N times to get:
[F(N+1), F(N)]
[F(N), F(N-1)]
This morning, doodling in the steam on the shower wall, I realized that you could cut the running time in half by starting with the second matrix, and multiplying it by itself N/2 times, then using N to pick an index from the first row/column.
With a little squeezing, I got it down to one line:
import numpy
def mm_fib(n):
return (numpy.matrix([[2,1],[1,1]])**(n//2))[0,(n+1)%2]
>>> [mm_fib(i) for i in range(20)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181]
This is a closed expression for the Fibonacci series that uses integer arithmetic, and is quite efficient.
fib = lambda n:pow(2<<n,n+1,(4<<2*n)-(2<<n)-1)%(2<<n)
>> fib(1000)
4346655768693745643568852767504062580256466051737178
0402481729089536555417949051890403879840079255169295
9225930803226347752096896232398733224711616429964409
06533187938298969649928516003704476137795166849228875L
It computes the result in O(log n) arithmetic operations, each acting on integers with O(n) bits. Given that the result (the nth Fibonacci number) is O(n) bits, the method is quite reasonable.
It's based on genefib4 from http://fare.tunes.org/files/fun/fibonacci.lisp , which in turn was based on an a less efficient closed-form integer expression of mine (see: http://paulhankin.github.io/Fibonacci/)
If we consider the "most Pythonic way" to be elegant and effective then:
def fib(nr):
return int(((1 + math.sqrt(5)) / 2) ** nr / math.sqrt(5) + 0.5)
wins hands down. Why use a inefficient algorithm (and if you start using memoization we can forget about the oneliner) when you can solve the problem just fine in O(1) by approximation the result with the golden ratio? Though in reality I'd obviously write it in this form:
def fib(nr):
ratio = (1 + math.sqrt(5)) / 2
return int(ratio ** nr / math.sqrt(5) + 0.5)
More efficient and much easier to understand.
This is a non-recursive (anonymous) memoizing one liner
fib = lambda x,y=[1,1]:([(y.append(y[-1]+y[-2]),y[-1])[1] for i in range(1+x-len(y))],y[x])[1]
fib = lambda n, x=0, y=1 : x if not n else fib(n-1, y, x+y)
run time O(n), fib(0) = 0, fib(1) = 1, fib(2) = 1 ...
I'm Python newcomer, but did some measure for learning purposes. I've collected some fibo algorithm and took some measure.
from datetime import datetime
import matplotlib.pyplot as plt
from functools import wraps
from functools import reduce
from functools import lru_cache
import numpy
def time_it(f):
#wraps(f)
def wrapper(*args, **kwargs):
start_time = datetime.now()
f(*args, **kwargs)
end_time = datetime.now()
elapsed = end_time - start_time
elapsed = elapsed.microseconds
return elapsed
return wrapper
#time_it
def fibslow(n):
if n <= 1:
return n
else:
return fibslow(n-1) + fibslow(n-2)
#time_it
#lru_cache(maxsize=10)
def fibslow_2(n):
if n <= 1:
return n
else:
return fibslow_2(n-1) + fibslow_2(n-2)
#time_it
def fibfast(n):
if n <= 1:
return n
a, b = 0, 1
for i in range(1, n+1):
a, b = b, a + b
return a
#time_it
def fib_reduce(n):
return reduce(lambda x, n: [x[1], x[0]+x[1]], range(n), [0, 1])[0]
#time_it
def mm_fib(n):
return (numpy.matrix([[2, 1], [1, 1]])**(n//2))[0, (n+1) % 2]
#time_it
def fib_ia(n):
return pow(2 << n, n+1, (4 << 2 * n) - (2 << n)-1) % (2 << n)
if __name__ == '__main__':
X = range(1, 200)
# fibslow_times = [fibslow(i) for i in X]
fibslow_2_times = [fibslow_2(i) for i in X]
fibfast_times = [fibfast(i) for i in X]
fib_reduce_times = [fib_reduce(i) for i in X]
fib_mm_times = [mm_fib(i) for i in X]
fib_ia_times = [fib_ia(i) for i in X]
# print(fibslow_times)
# print(fibfast_times)
# print(fib_reduce_times)
plt.figure()
# plt.plot(X, fibslow_times, label='Slow Fib')
plt.plot(X, fibslow_2_times, label='Slow Fib w cache')
plt.plot(X, fibfast_times, label='Fast Fib')
plt.plot(X, fib_reduce_times, label='Reduce Fib')
plt.plot(X, fib_mm_times, label='Numpy Fib')
plt.plot(X, fib_ia_times, label='Fib ia')
plt.xlabel('n')
plt.ylabel('time (microseconds)')
plt.legend()
plt.show()
The result is usually the same.
Fiboslow_2 with recursion and cache, Fib integer arithmetic and Fibfast algorithms seems the best ones. Maybe my decorator not the best thing to measure performance, but for an overview it seemed good.
Another example, taking the cue from Mark Byers's answer:
fib = lambda n,a=0,b=1: a if n<=0 else fib(n-1,b,a+b)
I wanted to see if I could create an entire sequence, not just the final value.
The following will generate a list of length 100. It excludes the leading [0, 1] and works for both Python2 and Python3. No other lines besides the one!
(lambda i, x=[0,1]: [(x.append(x[y+1]+x[y]), x[y+1]+x[y])[1] for y in range(i)])(100)
Output
[1,
2,
3,
...
218922995834555169026,
354224848179261915075,
573147844013817084101]
Here's an implementation that doesn't use recursion, and only memoizes the last two values instead of the whole sequence history.
nthfib() below is the direct solution to the original problem (as long as imports are allowed)
It's less elegant than using the Reduce methods above, but, although slightly different that what was asked for, it gains the ability to to be used more efficiently as an infinite generator if one needs to output the sequence up to the nth number as well (re-writing slightly as fibgen() below).
from itertools import imap, islice, repeat
nthfib = lambda n: next(islice((lambda x=[0, 1]: imap((lambda x: (lambda setx=x.__setitem__, x0_temp=x[0]: (x[1], setx(0, x[1]), setx(1, x0_temp+x[1]))[0])()), repeat(x)))(), n-1, None))
>>> nthfib(1000)
43466557686937456435688527675040625802564660517371780402481729089536555417949051
89040387984007925516929592259308032263477520968962323987332247116164299644090653
3187938298969649928516003704476137795166849228875L
from itertools import imap, islice, repeat
fibgen = lambda:(lambda x=[0,1]: imap((lambda x: (lambda setx=x.__setitem__, x0_temp=x[0]: (x[1], setx(0, x[1]), setx(1, x0_temp+x[1]))[0])()), repeat(x)))()
>>> list(islice(fibgen(),12))
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144]
def fib(n):
x =[0,1]
for i in range(n):
x=[x[1],x[0]+x[1]]
return x[0]
take the cue from Jason S, i think my version have a better understanding.
Starting Python 3.8, and the introduction of assignment expressions (PEP 572) (:= operator), we can use and update a variable within a list comprehension:
fib = lambda n,x=(0,1):[x := (x[1], sum(x)) for i in range(n+1)][-1][0]
This:
Initiates the duo n-1 and n-2 as a tuple x=(0, 1)
As part of a list comprehension looping n times, x is updated via an assignment expression (x := (x[1], sum(x))) to the new n-1 and n-2 values
Finally, we return from the last iteration, the first part of the x
To solve this problem I got inspired by a similar question here in Stackoverflow Single Statement Fibonacci, and I got this single line function that can output a list of fibonacci sequence. Though, this is a Python 2 script, not tested on Python 3:
(lambda n, fib=[0,1]: fib[:n]+[fib.append(fib[-1] + fib[-2]) or fib[-1] for i in range(n-len(fib))])(10)
assign this lambda function to a variable to reuse it:
fib = (lambda n, fib=[0,1]: fib[:n]+[fib.append(fib[-1] + fib[-2]) or fib[-1] for i in range(n-len(fib))])
fib(10)
output is a list of fibonacci sequence:
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
I don't know if this is the most pythonic method but this is the best i could come up with:->
Fibonacci = lambda x,y=[1,1]:[1]*x if (x<2) else ([y.append(y[q-1] + y[q-2]) for q in range(2,x)],y)[1]
The above code doesn't use recursion, just a list to store the values.
My 2 cents
# One Liner
def nthfibonacci(n):
return long(((((1+5**.5)/2)**n)-(((1-5**.5)/2)**n))/5**.5)
OR
# Steps
def nthfibonacci(nth):
sq5 = 5**.5
phi1 = (1+sq5)/2
phi2 = -1 * (phi1 -1)
n1 = phi1**(nth+1)
n2 = phi2**(nth+1)
return long((n1 - n2)/sq5)
Why not use a list comprehension?
from math import sqrt, floor
[floor(((1+sqrt(5))**n-(1-sqrt(5))**n)/(2**n*sqrt(5))) for n in range(100)]
Without math imports, but less pretty:
[int(((1+(5**0.5))**n-(1-(5**0.5))**n)/(2**n*(5**0.5))) for n in range(100)]
import math
sqrt_five = math.sqrt(5)
phi = (1 + sqrt_five) / 2
fib = lambda n : int(round(pow(phi, n) / sqrt_five))
print([fib(i) for i in range(1, 26)])
single line lambda fibonacci but with some extra variables
Similar:
def fibonacci(n):
f=[1]+[0]
for i in range(n):
f=[sum(f)] + f[:-1]
print f[1]
A simple Fibonacci number generator using recursion
fib = lambda x: 1-x if x < 2 else fib(x-1)+fib(x-2)
print fib(100)
This takes forever to calculate fib(100) in my computer.
There is also closed form of Fibonacci numbers.
fib = lambda n: int(1/sqrt(5)*((1+sqrt(5))**n-(1-sqrt(5))**n)/2**n)
print fib(50)
This works nearly up to 72 numbers due to precision problem.
Lambda with logical operators
fibonacci_oneline = lambda n = 10, out = []: [ out.append(i) or i if i <= 1 else out.append(out[-1] + out[-2]) or out[-1] for i in range(n)]
here is how i do it ,however the function returns None for the list comprehension line part to allow me to insert a loop inside ..
so basically what it does is appending new elements of the fib seq inside of a list which is over two elements
>>f=lambda list,x :print('The list must be of 2 or more') if len(list)<2 else [list.append(list[-1]+list[-2]) for i in range(x)]
>>a=[1,2]
>>f(a,7)
You can generate once a list with some values and use as needed:
fib_fix = []
fib = lambda x: 1 if x <=2 else fib_fix[x-3] if x-2 <= len(fib_fix) else (fib_fix.append(fib(x-2) + fib(x-1)) or fib_fix[-1])
fib_x = lambda x: [fib(n) for n in range(1,x+1)]
fib_100 = fib_x(100)
than for example:
a = fib_fix[76]
I want to swap each pair of characters in a string. '2143' becomes '1234', 'badcfe' becomes 'abcdef'.
How can I do this in Python?
oneliner:
>>> s = 'badcfe'
>>> ''.join([ s[x:x+2][::-1] for x in range(0, len(s), 2) ])
'abcdef'
s[x:x+2] returns string slice from x to x+2; it is safe for odd len(s).
[::-1] reverses the string in Python
range(0, len(s), 2) returns 0, 2, 4, 6 ... while x < len(s)
The usual way to swap two items in Python is:
a, b = b, a
So it would seem to me that you would just do the same with an extended slice. However, it is slightly complicated because strings aren't mutable; so you have to convert to a list and then back to a string.
Therefore, I would do the following:
>>> s = 'badcfe'
>>> t = list(s)
>>> t[::2], t[1::2] = t[1::2], t[::2]
>>> ''.join(t)
'abcdef'
Here's one way...
>>> s = '2134'
>>> def swap(c, i, j):
... c = list(c)
... c[i], c[j] = c[j], c[i]
... return ''.join(c)
...
>>> swap(s, 0, 1)
'1234'
>>>
''.join(s[i+1]+s[i] for i in range(0, len(s), 2)) # 10.6 usec per loop
or
''.join(x+y for x, y in zip(s[1::2], s[::2])) # 10.3 usec per loop
or if the string can have an odd length:
''.join(x+y for x, y in itertools.izip_longest(s[1::2], s[::2], fillvalue=''))
Note that this won't work with old versions of Python (if I'm not mistaking older than 2.5).
The benchmark was run on python-2.7-8.fc14.1.x86_64 and a Core 2 Duo 6400 CPU with s='0123456789'*4.
If performance or elegance is not an issue, and you just want clarity and have the job done then simply use this:
def swap(text, ch1, ch2):
text = text.replace(ch2, '!',)
text = text.replace(ch1, ch2)
text = text.replace('!', ch1)
return text
This allows you to swap or simply replace chars or substring.
For example, to swap 'ab' <-> 'de' in a text:
_str = "abcdefabcdefabcdef"
print swap(_str, 'ab','de') #decabfdecabfdecabf
Loop over length of string by twos and swap:
def oddswap(st):
s = list(st)
for c in range(0,len(s),2):
t=s[c]
s[c]=s[c+1]
s[c+1]=t
return "".join(s)
giving:
>>> s
'foobar'
>>> oddswap(s)
'ofbora'
and fails on odd-length strings with an IndexError exception.
There is no need to make a list. The following works for even-length strings:
r = ''
for in in range(0, len(s), 2) :
r += s[i + 1] + s[i]
s = r
A more general answer... you can do any single pairwise swap with tuples or strings using this approach:
# item can be a string or tuple and swap can be a list or tuple of two
# indices to swap
def swap_items_by_copy(item, swap):
s0 = min(swap)
s1 = max(swap)
if isinstance(item,str):
return item[:s0]+item[s1]+item[s0+1:s1]+item[s0]+item[s1+1:]
elif isinstance(item,tuple):
return item[:s0]+(item[s1],)+item[s0+1:s1]+(item[s0],)+item[s1+1:]
else:
raise ValueError("Type not supported")
Then you can invoke it like this:
>>> swap_items_by_copy((1,2,3,4,5,6),(1,2))
(1, 3, 2, 4, 5, 6)
>>> swap_items_by_copy("hello",(1,2))
'hlelo'
>>>
Thankfully python gives empty strings or tuples for the cases where the indices refer to non existent slices.
To swap characters in a string a of position l and r
def swap(a, l, r):
a = a[0:l] + a[r] + a[l+1:r] + a[l] + a[r+1:]
return a
Example:
swap("aaabcccdeee", 3, 7) returns "aaadcccbeee"
Do you want the digits sorted? Or are you swapping odd/even indexed digits? Your example is totally unclear.
Sort:
s = '2143'
p=list(s)
p.sort()
s = "".join(p)
s is now '1234'. The trick is here that list(string) breaks it into characters.
Like so:
>>> s = "2143658709"
>>> ''.join([s[i+1] + s[i] for i in range(0, len(s), 2)])
'1234567890'
>>> s = "badcfe"
>>> ''.join([s[i+1] + s[i] for i in range(0, len(s), 2)])
'abcdef'
re.sub(r'(.)(.)',r"\2\1",'abcdef1234')
However re is a bit slow.
def swap(s):
i=iter(s)
while True:
a,b=next(i),next(i)
yield b
yield a
''.join(swap("abcdef1234"))
One more way:
>>> s='123456'
>>> ''.join([''.join(el) for el in zip(s[1::2], s[0::2])])
'214365'
>>> import ctypes
>>> s = 'abcdef'
>>> mutable = ctypes.create_string_buffer(s)
>>> for i in range(0,len(s),2):
>>> mutable[i], mutable[i+1] = mutable[i+1], mutable[i]
>>> s = mutable.value
>>> print s
badcfe
def revstr(a):
b=''
if len(a)%2==0:
for i in range(0,len(a),2):
b += a[i + 1] + a[i]
a=b
else:
c=a[-1]
for i in range(0,len(a)-1,2):
b += a[i + 1] + a[i]
b=b+a[-1]
a=b
return b
a=raw_input('enter a string')
n=revstr(a)
print n
A bit late to the party, but there is actually a pretty simple way to do this:
The index sequence you are looking for can be expressed as the sum of two sequences:
0 1 2 3 ...
+1 -1 +1 -1 ...
Both are easy to express. The first one is just range(N). A sequence that toggles for each i in that range is i % 2. You can adjust the toggle by scaling and offsetting it:
i % 2 -> 0 1 0 1 ...
1 - i % 2 -> 1 0 1 0 ...
2 * (1 - i % 2) -> 2 0 2 0 ...
2 * (1 - i % 2) - 1 -> +1 -1 +1 -1 ...
The entire expression simplifies to i + 1 - 2 * (i % 2), which you can use to join the string almost directly:
result = ''.join(string[i + 1 - 2 * (i % 2)] for i in range(len(string)))
This will work only for an even-length string, so you can check for overruns using min:
N = len(string)
result = ''.join(string[min(i + 1 - 2 * (i % 2), N - 1)] for i in range(N))
Basically a one-liner, doesn't require any iterators beyond a range over the indices, and some very simple integer math.
While the above solutions do work, there is a very simple solution shall we say in "layman's" terms. Someone still learning python and string's can use the other answers but they don't really understand how they work or what each part of the code is doing without a full explanation by the poster as opposed to "this works". The following executes the swapping of every second character in a string and is easy for beginners to understand how it works.
It is simply iterating through the string (any length) by two's (starting from 0 and finding every second character) and then creating a new string (swapped_pair) by adding the current index + 1 (second character) and then the actual index (first character), e.g., index 1 is put at index 0 and then index 0 is put at index 1 and this repeats through iteration of string.
Also added code to ensure string is of even length as it only works for even length.
DrSanjay Bhakkad post above is also a good one that works for even or odd strings and is basically doing the same function as below.
string = "abcdefghijklmnopqrstuvwxyz123"
# use this prior to below iteration if string needs to be even but is possibly odd
if len(string) % 2 != 0:
string = string[:-1]
# iteration to swap every second character in string
swapped_pair = ""
for i in range(0, len(string), 2):
swapped_pair += (string[i + 1] + string[i])
# use this after above iteration for any even or odd length of strings
if len(swapped_pair) % 2 != 0:
swapped_adj += swapped_pair[-1]
print(swapped_pair)
badcfehgjilknmporqtsvuxwzy21 # output if the "needs to be even" code used
badcfehgjilknmporqtsvuxwzy213 # output if the "even or odd" code used
One of the easiest way to swap first two characters from a String is
inputString = '2134'
extractChar = inputString[0:2]
swapExtractedChar = extractChar[::-1] """Reverse the order of string"""
swapFirstTwoChar = swapExtractedChar + inputString[2:]
# swapFirstTwoChar = inputString[0:2][::-1] + inputString[2:] """For one line code"""
print(swapFirstTwoChar)
#Works on even/odd size strings
str = '2143657'
newStr = ''
for i in range(len(str)//2):
newStr += str[i*2+1] + str[i*2]
if len(str)%2 != 0:
newStr += str[-1]
print(newStr)
#Think about how index works with string in Python,
>>> a = "123456"
>>> a[::-1]
'654321'
This is a generalization of the "string contains substring" problem to (more) arbitrary types.
Given an sequence (such as a list or tuple), what's the best way of determining whether another sequence is inside it? As a bonus, it should return the index of the element where the subsequence starts:
Example usage (Sequence in Sequence):
>>> seq_in_seq([5,6], [4,'a',3,5,6])
3
>>> seq_in_seq([5,7], [4,'a',3,5,6])
-1 # or None, or whatever
So far, I just rely on brute force and it seems slow, ugly, and clumsy.
I second the Knuth-Morris-Pratt algorithm. By the way, your problem (and the KMP solution) is exactly recipe 5.13 in Python Cookbook 2nd edition. You can find the related code at http://code.activestate.com/recipes/117214/
It finds all the correct subsequences in a given sequence, and should be used as an iterator:
>>> for s in KnuthMorrisPratt([4,'a',3,5,6], [5,6]): print s
3
>>> for s in KnuthMorrisPratt([4,'a',3,5,6], [5,7]): print s
(nothing)
Here's a brute-force approach O(n*m) (similar to #mcella's answer). It might be faster than the Knuth-Morris-Pratt algorithm implementation in pure Python O(n+m) (see #Gregg Lind answer) for small input sequences.
#!/usr/bin/env python
def index(subseq, seq):
"""Return an index of `subseq`uence in the `seq`uence.
Or `-1` if `subseq` is not a subsequence of the `seq`.
The time complexity of the algorithm is O(n*m), where
n, m = len(seq), len(subseq)
>>> index([1,2], range(5))
1
>>> index(range(1, 6), range(5))
-1
>>> index(range(5), range(5))
0
>>> index([1,2], [0, 1, 0, 1, 2])
3
"""
i, n, m = -1, len(seq), len(subseq)
try:
while True:
i = seq.index(subseq[0], i + 1, n - m + 1)
if subseq == seq[i:i + m]:
return i
except ValueError:
return -1
if __name__ == '__main__':
import doctest; doctest.testmod()
I wonder how large is the small in this case?
A simple approach: Convert to strings and rely on string matching.
Example using lists of strings:
>>> f = ["foo", "bar", "baz"]
>>> g = ["foo", "bar"]
>>> ff = str(f).strip("[]")
>>> gg = str(g).strip("[]")
>>> gg in ff
True
Example using tuples of strings:
>>> x = ("foo", "bar", "baz")
>>> y = ("bar", "baz")
>>> xx = str(x).strip("()")
>>> yy = str(y).strip("()")
>>> yy in xx
True
Example using lists of numbers:
>>> f = [1 , 2, 3, 4, 5, 6, 7]
>>> g = [4, 5, 6]
>>> ff = str(f).strip("[]")
>>> gg = str(g).strip("[]")
>>> gg in ff
True
Same thing as string matching sir...Knuth-Morris-Pratt string matching
>>> def seq_in_seq(subseq, seq):
... while subseq[0] in seq:
... index = seq.index(subseq[0])
... if subseq == seq[index:index + len(subseq)]:
... return index
... else:
... seq = seq[index + 1:]
... else:
... return -1
...
>>> seq_in_seq([5,6], [4,'a',3,5,6])
3
>>> seq_in_seq([5,7], [4,'a',3,5,6])
-1
Sorry I'm not an algorithm expert, it's just the fastest thing my mind can think about at the moment, at least I think it looks nice (to me) and I had fun coding it. ;-)
Most probably it's the same thing your brute force approach is doing.
Brute force may be fine for small patterns.
For larger ones, look at the Aho-Corasick algorithm.
Here is another KMP implementation:
from itertools import tee
def seq_in_seq(seq1,seq2):
'''
Return the index where seq1 appears in seq2, or -1 if
seq1 is not in seq2, using the Knuth-Morris-Pratt algorithm
based heavily on code by Neale Pickett <neale#woozle.org>
found at: woozle.org/~neale/src/python/kmp.py
>>> seq_in_seq(range(3),range(5))
0
>>> seq_in_seq(range(3)[-1:],range(5))
2
>>>seq_in_seq(range(6),range(5))
-1
'''
def compute_prefix_function(p):
m = len(p)
pi = [0] * m
k = 0
for q in xrange(1, m):
while k > 0 and p[k] != p[q]:
k = pi[k - 1]
if p[k] == p[q]:
k = k + 1
pi[q] = k
return pi
t,p = list(tee(seq2)[0]), list(tee(seq1)[0])
m,n = len(p),len(t)
pi = compute_prefix_function(p)
q = 0
for i in range(n):
while q > 0 and p[q] != t[i]:
q = pi[q - 1]
if p[q] == t[i]:
q = q + 1
if q == m:
return i - m + 1
return -1
I'm a bit late to the party, but here's something simple using strings:
>>> def seq_in_seq(sub, full):
... f = ''.join([repr(d) for d in full]).replace("'", "")
... s = ''.join([repr(d) for d in sub]).replace("'", "")
... #return f.find(s) #<-- not reliable for finding indices in all cases
... return s in f
...
>>> seq_in_seq([5,6], [4,'a',3,5,6])
True
>>> seq_in_seq([5,7], [4,'a',3,5,6])
False
>>> seq_in_seq([4,'abc',33], [4,'abc',33,5,6])
True
As noted by Ilya V. Schurov, the find method in this case will not return the correct indices with multi-character strings or multi-digit numbers.
For what it's worth, I tried using a deque like so:
from collections import deque
from itertools import islice
def seq_in_seq(needle, haystack):
"""Generator of indices where needle is found in haystack."""
needle = deque(needle)
haystack = iter(haystack) # Works with iterators/streams!
length = len(needle)
# Deque will automatically call deque.popleft() after deque.append()
# with the `maxlen` set equal to the needle length.
window = deque(islice(haystack, length), maxlen=length)
if needle == window:
yield 0 # Match at the start of the haystack.
for index, value in enumerate(haystack, start=1):
window.append(value)
if needle == window:
yield index
One advantage of the deque implementation is that it makes only a single linear pass over the haystack. So if the haystack is streaming then it will still work (unlike the solutions that rely on slicing).
The solution is still brute-force, O(n*m). Some simple local benchmarking showed it was ~100x slower than the C-implementation of string searching in str.index.
Another approach, using sets:
set([5,6])== set([5,6])&set([4,'a',3,5,6])
True