I am trying to write a function that returns true or false if a given string has exactly 6 consecutive characters with the same value. If the string has more or less than 6, it will return false:
I am not allowed to use lists, sets or import any packages. I am only restricted to while loops, for loops, and utilizing basic mathematical operations
Two example runs are shown below:
Enter a string: 367777776
True
Enter a string: 3677777777776
False
Note that although I entered numbers, it is actually a string within the function argument for example: consecutive('3777776')
I tried to convert the string into an ASCII table and then try and filter out the numbers there. However, I
def consecutive(x):
storage= ' '
acc=0
count=0
for s in x:
storage+= str(ord(s)) + ' '
acc+=ord(s)
if acc == acc:
count+=1
for s in x-1:
return count
My intention is to compare the previous character's ASCII code to the current character's ASCII code in the string. If the ASCII doesnt match, I will add an accumulator for it. The accumulator will list the number of duplicates. From there, I will implement an if-else statement to see if it is greater or less than 6 However, I have a hard time translating my thoughts into python code.
Can anyone assist me?
That's a pretty good start!
A few comments:
Variables storage and acc play the same role, and are a little more complicated than they have to be. All you want to know when you arrive at character s is whether or not s is identical to the previous character. So, you only need to store the previously seen character.
Condition acc == acc is always going to be True. I think you meant acc == s?
When you encounter an identical character, you correctly increase the count with count += 1. However, when we change characters, you should reset the count.
With these comments in mind, I fixed your code, then blanked out a few parts for you to fill. I've also renamed storage and acc to previous_char which I think is more explicit.
def has_6_consecutive(x):
previous_char = None
count = 0
for s in x:
if s == previous_char:
???
elif count == 6:
???
else:
???
previous_char = ???
???
You could use recursion. Loop over all the characters and for each one check to see of the next 6 are identical. If so, return true. If you get to the end of the array (or even within 6 characters of the end), return false.
For more info on recursion, check this out: https://www.programiz.com/python-programming/recursion
would something like this be allowed?
def consecF(n):
consec = 1
prev = n[0]
for i in n:
if i==prev:
consec+=1
else:
consec=1
if consec == 6:
return True
prev = i
return False
n = "12111123333221"
print(consecF(n))
You can try a two pointer approach, where the left pointer is fixed at the first instance of some digit and the right one is shifted as long as the digit is seen.
def consecutive(x):
left = 0
while left != len(x):
right = left
while right < len(x) and x[right] == x[left]:
right += 1
length = (right - 1) - left + 1 # from left to right - 1 inclusive, x[left] repeated
if length == 6: # found desired length
return True
left = right
return False # no segment found
tests = [
'3677777777776',
'367777776'
]
for test in tests:
print(f"{test}: {consecutive(test)}")
Output
3677777777776: False
367777776: True
You should store the current sequence of repeated chars.
def consecutive(x):
sequencechar = ' '
repetitions = 0
for ch in x:
if ch != sequencechar:
if repetitions == 6:
break
sequencechar = ch
repetitions = 1
else:
repetitions += 1
return repetitions == 6
If I could, I would not have given the entire solution, but this still is a simple problem. However one has to take care of some points.
As you see the current sequence is stored, and when the sequence is ended and a new starts, on having found a correct sequence it breaks out of the for loop.
Also after the for loop ends normally, the last sequence is checked (which was not done in the loop).
For instance:
8 > 10 = true, since 8 is divisible by 2 three times and 10 only once.
How can I compare two integers from any range of numbers? Are the modulo and divide operator capable of doing this task?
Use binary caculate to judge it
def devided_by_two(i)
return i.to_s(2).match(/0*$/).to_s.count('0')
end
To make integer divisibility by 2, just transcode it to binary and judge how many zero from end of banary number. The code I provide can be more simple I think.
Yes, they are capable. A number is even if, when you divide it by two, the remainder is zero.
Hence, you can use a loop to continuously divide by two until you get an odd number, keeping a count of how many times you did it.
The (pseudo-code) function for assigning a "divisibility by two, continuously" value to a number would be something like:
def howManyDivByTwo(x):
count = 0
while x % 2 == 0:
count = count + 1
x = x / 2 # make sure integer division
return count
That shouldn't be too hard to turn into Ruby (or any procedural-type language, really), such as:
def howManyDivByTwo(x)
count = 0
while x % 2 == 0
count = count + 1
x = x / 2
end
return count
end
print howManyDivByTwo(4), "\n"
print howManyDivByTwo(10), "\n"
print howManyDivByTwo(11), "\n"
print howManyDivByTwo(65536), "\n"
This outputs the correct:
2
1
0
16
Astute readers will have noticed there's an edge case in that function, you probably don't want to try passing zero to it. If it was production code, you'd need to catch that and act intelligently since you can divide zero by two until the cows come home, without ever reaching an odd number.
What value you return for zero depends on needs you haven't specified in detail. Theoretically (mathematically), you should return infinity but I'll leave that up to you.
Notice that you will likely mess up much of your code if you redefine such basic method. Knowing that, this is how it's done:
class Integer
def <=> other
me = self
return 0 if me.zero? and other.zero?
return -1 if other.zero?
return 1 if me.zero?
while me.even? and other.even?
me /= 2
other /= 2
end
return 0 if me.odd? and other.odd?
return -1 if me.odd?
return 1 if other.odd? # This condition is redundant, but is here for symmetry.
end
end
I'm looking for an innovative way to check if a number has only one on bit in a signed int.
I am well aware that I can simply do a loop with a counter, some modular division, and a bit shift. But I'm curious if there is a better way since we are only looking for ONE bit to be on.
bool HasOnlyOneBit (int numb)
{
//return true if numb has only one bit (I.E. is equal to 1, 2, 4, 8, 16... Int.MinValue)
}
return x == (x & -x);
This answer works because of the way two's complement notation is designed.
First, an example. Assume we have 8-bit signed integers.
00010000 = 16
11110000 = -16
The bitwise and will give you 00010000 as a result, equal to your original value! The reason that this works is because when negating in 2's complement, first invert all the bits, then add 1. You'll have a bunch of zeros and a bunch of carries until a one falls into place. The bitwise and then checks if we have the right bit set.
In the case of a number that isn't a power of two:
00101010 = 42
& 11010110 = -42
----------
00000010 != 42
Your result will still have only a single bit, but it won't match the original value. Therefore your original value had multiple bits set.
Note: This technique returns true for 0, which may or may not be desirable.
This is a famous problem
(x & x-1) == 0
Power of 2 from Wiki : here
64 = 01000000 (x)
63 = 00111111 (x-1)
______________
& = 00000000 == 0
______________
Case when some other bits are ON
18 = 00010010 (x)
17 = 00010001 (x-1)
______________
& = 00010000 != 0
______________
I'd recommend you take a look at the Bit Twiddling Hacks page and choose the most suitable option under "Determining if an integer is a power of 2" or "Counting bits set".
return (x && ((x & x-1) == 0))
return (x && (0x8000000000000000ULL % x));
This is a simplification of the following code:
if (x == 0) {
return false;
} else if (0x8000000000000000ULL % x) {
return false;
} else {
return true;
}
Explanation: 0x8000000000000000 is the highest "1 bit only" value for an 64 bit register. Only a division by an other "1 bit only" value will result in no remainder.
Take the log to base 2 of your number, if it's an integer your number has only 1 1 bit. Not sure that I think this is better than any of your excluded options.
Python3 memory-efficient solution
return n > 0 and (n & (n-1)) == 0
I'm checking if two strings a and b are permutations of each other, and I'm wondering what the ideal way to do this is in Python. From the Zen of Python, "There should be one -- and preferably only one -- obvious way to do it," but I see there are at least two ways:
sorted(a) == sorted(b)
and
all(a.count(char) == b.count(char) for char in a)
but the first one is slower when (for example) the first char of a is nowhere in b, and the second is slower when they are actually permutations.
Is there any better (either in the sense of more Pythonic, or in the sense of faster on average) way to do it? Or should I just choose from these two depending on which situation I expect to be most common?
Here is a way which is O(n), asymptotically better than the two ways you suggest.
import collections
def same_permutation(a, b):
d = collections.defaultdict(int)
for x in a:
d[x] += 1
for x in b:
d[x] -= 1
return not any(d.itervalues())
## same_permutation([1,2,3],[2,3,1])
#. True
## same_permutation([1,2,3],[2,3,1,1])
#. False
"but the first one is slower when (for example) the first char of a is nowhere in b".
This kind of degenerate-case performance analysis is not a good idea. It's a rat-hole of lost time thinking up all kinds of obscure special cases.
Only do the O-style "overall" analysis.
Overall, the sorts are O( n log( n ) ).
The a.count(char) for char in a solution is O( n 2 ). Each count pass is a full examination of the string.
If some obscure special case happens to be faster -- or slower, that's possibly interesting. But it only matters when you know the frequency of your obscure special cases. When analyzing sort algorithms, it's important to note that a fair number of sorts involve data that's already in the proper order (either by luck or by a clever design), so sort performance on pre-sorted data matters.
In your obscure special case ("the first char of a is nowhere in b") is this frequent enough to matter? If it's just a special case you thought of, set it aside. If it's a fact about your data, then consider it.
heuristically you're probably better to split them off based on string size.
Pseudocode:
returnvalue = false
if len(a) == len(b)
if len(a) < threshold
returnvalue = (sorted(a) == sorted(b))
else
returnvalue = naminsmethod(a, b)
return returnvalue
If performance is critical, and string size can be large or small then this is what I'd do.
It's pretty common to split things like this based on input size or type. Algorithms have different strengths or weaknesses and it would be foolish to use one where another would be better... In this case Namin's method is O(n), but has a larger constant factor than the O(n log n) sorted method.
I think the first one is the "obvious" way. It is shorter, clearer, and likely to be faster in many cases because Python's built-in sort is highly optimized.
Your second example won't actually work:
all(a.count(char) == b.count(char) for char in a)
will only work if b does not contain extra characters not in a. It also does duplicate work if the characters in string a repeat.
If you want to know whether two strings are permutations of the same unique characters, just do:
set(a) == set(b)
To correct your second example:
all(str1.count(char) == str2.count(char) for char in set(a) | set(b))
set() objects overload the bitwise OR operator so that it will evaluate to the union of both sets. This will make sure that you will loop over all the characters of both strings once for each character only.
That said, the sorted() method is much simpler and more intuitive, and would be what I would use.
Here are some timed executions on very small strings, using two different methods:
1. sorting
2. counting (specifically the original method by #namin).
a, b, c = 'confused', 'unfocused', 'foncused'
sort_method = lambda x,y: sorted(x) == sorted(y)
def count_method(a, b):
d = {}
for x in a:
d[x] = d.get(x, 0) + 1
for x in b:
d[x] = d.get(x, 0) - 1
for v in d.itervalues():
if v != 0:
return False
return True
Average run times of the 2 methods over 100,000 loops are:
non-match (string a and b)
$ python -m timeit -s 'import temp' 'temp.sort_method(temp.a, temp.b)'
100000 loops, best of 3: 9.72 usec per loop
$ python -m timeit -s 'import temp' 'temp.count_method(temp.a, temp.b)'
10000 loops, best of 3: 28.1 usec per loop
match (string a and c)
$ python -m timeit -s 'import temp' 'temp.sort_method(temp.a, temp.c)'
100000 loops, best of 3: 9.47 usec per loop
$ python -m timeit -s 'import temp' 'temp.count_method(temp.a, temp.c)'
100000 loops, best of 3: 24.6 usec per loop
Keep in mind that the strings used are very small. The time complexity of the methods are different, so you'll see different results with very large strings. Choose according to your data, you may even use a combination of the two.
Sorry that my code is not in Python, I have never used it, but I am sure this can be easily translated into python. I believe this is faster than all the other examples already posted. It is also O(n), but stops as soon as possible:
public boolean isPermutation(String a, String b) {
if (a.length() != b.length()) {
return false;
}
int[] charCount = new int[256];
for (int i = 0; i < a.length(); ++i) {
++charCount[a.charAt(i)];
}
for (int i = 0; i < b.length(); ++i) {
if (--charCount[b.charAt(i)] < 0) {
return false;
}
}
return true;
}
First I don't use a dictionary but an array of size 256 for all the characters. Accessing the index should be much faster. Then when the second string is iterated, I immediately return false when the count gets below 0. When the second loop has finished, you can be sure that the strings are a permutation, because the strings have equal length and no character was used more often in b compared to a.
Here's martinus code in python. It only works for ascii strings:
def is_permutation(a, b):
if len(a) != len(b):
return False
char_count = [0] * 256
for c in a:
char_count[ord(c)] += 1
for c in b:
char_count[ord(c)] -= 1
if char_count[ord(c)] < 0:
return False
return True
I did a pretty thorough comparison in Java with all words in a book I had. The counting method beats the sorting method in every way. The results:
Testing against 9227 words.
Permutation testing by sorting ... done. 18.582 s
Permutation testing by counting ... done. 14.949 s
If anyone wants the algorithm and test data set, comment away.
First, for solving such problems, e.g. whether String 1 and String 2 are exactly the same or not, easily, you can use an "if" since it is O(1).
Second, it is important to consider that whether they are only numerical values or they can be also words in the string. If the latter one is true (words and numerical values are in the string at the same time), your first solution will not work. You can enhance it by using "ord()" function to make it ASCII numerical value. However, in the end, you are using sort; therefore, in the worst case your time complexity will be O(NlogN). This time complexity is not bad. But, you can do better. You can make it O(N).
My "suggestion" is using Array(list) and set at the same time. Note that finding a value in Array needs iteration so it's time complexity is O(N), but searching a value in set (which I guess it is implemented with HashTable in Python, I'm not sure) has O(1) time complexity:
def Permutation2(Str1, Str2):
ArrStr1 = list(Str1) #convert Str1 to array
SetStr2 = set(Str2) #convert Str2 to set
ArrExtra = []
if len(Str1) != len(Str2): #check their length
return False
elif Str1 == Str2: #check their values
return True
for x in xrange(len(ArrStr1)):
ArrExtra.append(ArrStr1[x])
for x in xrange(len(ArrExtra)): #of course len(ArrExtra) == len(ArrStr1) ==len(ArrStr2)
if ArrExtra[x] in SetStr2: #checking in set is O(1)
continue
else:
return False
return True
Go with the first one - it's much more straightforward and easier to understand. If you're actually dealing with incredibly large strings and performance is a real issue, then don't use Python, use something like C.
As far as the Zen of Python is concerned, that there should only be one obvious way to do things refers to small, simple things. Obviously for any sufficiently complicated task, there will always be zillions of small variations on ways to do it.
In Python 3.1/2.7 you can just use collections.Counter(a) == collections.Counter(b).
But sorted(a) == sorted(b) is still the most obvious IMHO. You are talking about permutations - changing order - so sorting is the obvious operation to erase that difference.
This is derived from #patros' answer.
from collections import Counter
def is_anagram(a, b, threshold=1000000):
"""Returns true if one sequence is a permutation of the other.
Ignores whitespace and character case.
Compares sorted sequences if the length is below the threshold,
otherwise compares dictionaries that contain the frequency of the
elements.
"""
a, b = a.strip().lower(), b.strip().lower()
length_a, length_b = len(a), len(b)
if length_a != length_b:
return False
if length_a < threshold:
return sorted(a) == sorted(b)
return Counter(a) == Counter(b) # Or use #namin's method if you don't want to create two dictionaries and don't mind the extra typing.
This is an O(n) solution in Python using hashing with dictionaries. Notice that I don't use default dictionaries because the code can stop this way if we determine the two strings are not permutations after checking the second letter for instance.
def if_two_words_are_permutations(s1, s2):
if len(s1) != len(s2):
return False
dic = {}
for ch in s1:
if ch in dic.keys():
dic[ch] += 1
else:
dic[ch] = 1
for ch in s2:
if not ch in dic.keys():
return False
elif dic[ch] == 0:
return False
else:
dic[ch] -= 1
return True
This is a PHP function I wrote about a week ago which checks if two words are anagrams. How would this compare (if implemented the same in python) to the other methods suggested? Comments?
public function is_anagram($word1, $word2) {
$letters1 = str_split($word1);
$letters2 = str_split($word2);
if (count($letters1) == count($letters2)) {
foreach ($letters1 as $letter) {
$index = array_search($letter, $letters2);
if ($index !== false) {
unset($letters2[$index]);
}
else { return false; }
}
return true;
}
return false;
}
Here's a literal translation to Python of the PHP version (by JFS):
def is_anagram(word1, word2):
letters2 = list(word2)
if len(word1) == len(word2):
for letter in word1:
try:
del letters2[letters2.index(letter)]
except ValueError:
return False
return True
return False
Comments:
1. The algorithm is O(N**2). Compare it to #namin's version (it is O(N)).
2. The multiple returns in the function look horrible.
This version is faster than any examples presented so far except it is 20% slower than sorted(x) == sorted(y) for short strings. It depends on use cases but generally 20% performance gain is insufficient to justify a complication of the code by using different version for short and long strings (as in #patros's answer).
It doesn't use len so it accepts any iterable therefore it works even for data that do not fit in memory e.g., given two big text files with many repeated lines it answers whether the files have the same lines (lines can be in any order).
def isanagram(iterable1, iterable2):
d = {}
get = d.get
for c in iterable1:
d[c] = get(c, 0) + 1
try:
for c in iterable2:
d[c] -= 1
return not any(d.itervalues())
except KeyError:
return False
It is unclear why this version is faster then defaultdict (#namin's) one for large iterable1 (tested on 25MB thesaurus).
If we replace get in the loop by try: ... except KeyError then it performs 2 times slower for short strings i.e. when there are few duplicates.
In Swift (or another languages implementation), you could look at the encoded values ( in this case Unicode) and see if they match.
Something like:
let string1EncodedValues = "Hello".unicodeScalars.map() {
//each encoded value
$0
//Now add the values
}.reduce(0){ total, value in
total + value.value
}
let string2EncodedValues = "oellH".unicodeScalars.map() {
$0
}.reduce(0) { total, value in
total + value.value
}
let equalStrings = string1EncodedValues == string2EncodedValues ? true : false
You will need to handle spaces and cases as needed.
def matchPermutation(s1, s2):
a = []
b = []
if len(s1) != len(s2):
print 'length should be the same'
return
for i in range(len(s1)):
a.append(s1[i])
for i in range(len(s2)):
b.append(s2[i])
if set(a) == set(b):
print 'Permutation of each other'
else:
print 'Not a permutation of each other'
return
#matchPermutaion('rav', 'var') #returns True
matchPermutaion('rav', 'abc') #returns False
Checking if two strings are permutations of each other in Python
# First method
def permutation(s1,s2):
if len(s1) != len(s2):return False;
return ' '.join(sorted(s1)) == ' '.join(sorted(s2))
# second method
def permutation1(s1,s2):
if len(s1) != len(s2):return False;
array = [0]*128;
for c in s1:
array[ord(c)] +=1
for c in s2:
array[ord(c)] -=1
if (array[ord(c)]) < 0:
return False
return True
How about something like this. Pretty straight-forward and readable. This is for strings since the as per the OP.
Given that the complexity of sorted() is O(n log n).
def checkPermutation(a,b):
# input: strings a and b
# return: boolean true if a is Permutation of b
if len(a) != len(b):
return False
else:
s_a = ''.join(sorted(a))
s_b = ''.join(sorted(b))
if s_a == s_b:
return True
else:
return False
# test inputs
a = 'sRF7w0qbGp4fdgEyNlscUFyouETaPHAiQ2WIxzohiafEGJLw03N8ALvqMw6reLN1kHRjDeDausQBEuIWkIBfqUtsaZcPGoqAIkLlugTxjxLhkRvq5d6i55l4oBH1QoaMXHIZC5nA0K5KPBD9uIwa789sP0ZKV4X6'
b = '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'
print(checkPermutation(a, b)) #optional
def permute(str1,str2):
if sorted(str1) == sorted(str2):
return True
else:
return False
str1="hello"
str2='olehl'
a=permute(str1,str2)
print(a
from collections import defaultdict
def permutation(s1,s2):
h = defaultdict(int)
for ch in s1:
h[ch]+=1
for ch in s2:
h[ch]-=1
for key in h.keys():
if h[key]!=0 or len(s1)!= len(s2):
return False
return True
print(permutation("tictac","tactic"))