1961. Check If String Is a Prefix of Array
Problem Description
The problem gives us two primary inputs: a string s
and an array of strings words
. The core task is to determine whether the string s
can be constructed by concatenating the first k
strings from the words
array, where k
is a positive integer and cannot exceed the length of words
. If s
can be created in this way, we refer to it as a prefix string of words
.
Intuition
To approach this problem, our main goal is to check if s
matches with a concatenation of the beginning subset of words
. To do that, we can iterate through the words
array and keep concatenating words until the total length of concatenated words equals the length of s
. The solution approach is straightforward:
- We maintain a running total of the lengths of the strings we have taken from the
words
array. - For each word in
words
, we increase this running total by the length of the current word. - If at any point the running total matches the length of
s
, we then check if the concatenation of the words thus far equalss
. - If the concatenation is a match, we return
true
indicatings
is a prefix string. - If we traverse all of
words
without finding a match, we returnfalse
.
The loop breaks early if the total length of concatenated words exceeds the length of s
since it cannot possibly be a prefix string if it's longer than s
.
Solution Approach
The solution implementation uses a simple algorithmic approach utilizing elementary control structures found in Python:
- We initialize a variable
t
to 0. This variable serves as the running total of lengths of strings from thewords
array that have been concatenated. - We iterate over each word
w
in thewords
array using afor
loop, and with each iteration, we add the length ofw
to our running totalt
. - For each word, after updating
t
, we comparet
with the length ofs
to check if we've reached or exceeded the length ofs
.- If the length
t
is equal to the length ofs
, we concatenate allwords
up to the currenti
index (through slicingwords[: i + 1]
) and compare the concatenated result withs
. - If they match,
s
is indeed a prefix string, and we returntrue
. - If the lengths match but the strings do not, or if we finish the loop without ever matching lengths, we return
false
.
- If the length
- The code exploits Python's list slicing and string joining capabilities to achieve this without needing a separate string builder or array.
Here is a step-by-step breakdown of the algorithm:
- Set
t = 0
. - Loop
i, w in enumerate(words)
:t += len(w)
increases total concatenated length.- Check if
len(s) == t
to see if lengths match.- If they do, verify string match with
''.join(words[: i + 1]) == s
. - If match is true, return
true
.
- If they do, verify string match with
- If no match is found after the loop completes, return
false
.
This algorithm uses a linear approach, iterating over the array once and stopping early if a match is found. On a complexity level, it operates in O(n) time with respect to the number of words, and potentially O(m) with respect to the length of s
because of the string comparison step.
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Let's consider a small example to illustrate the solution approach.
Suppose we have a string s = "applepenapple"
and an array of strings words = ["apple", "pen"]
. We want to determine if s
can be formed by concatenating the entire words
array.
Here are the steps we would follow:
- We initialize
t
to 0. This is our running total of the lengths of the strings we've concatenated from thewords
array. - We begin a loop over
words
withi, w in enumerate(words)
:- For the first iteration,
w = "apple"
andt
is updated tot += len(w)
which givest = 5
. - We then compare
t
withlen(s)
. Sincelen(s) = 13
andt = 5
, they do not match, so we continue without checking for a string match.
- For the first iteration,
- In the second iteration:
w = "pen"
and nowt
is updated tot += len(w)
which results int = 8
.- We compare
t
withlen(s)
again. Sincelen(s) = 13
andt = 8
, they still do not match, so we continue.
- Since we've reached the end of the
words
array withoutt
equalinglen(s)
, we continue to concatenate the words from the beginning of thewords
array untilt
equalslen(s)
, if possible. - The concatenated result of
words
is"applepen"
, which does not match the entire strings = "applepenapple"
. - Even if we repeat the
words
array once more (which is not part of this solution but just for understanding), the concatenated result would be"applepenapplepen"
, which exceedss
. - Since we cannot form
s
by concatenating thewords
array, the final result would befalse
.
In this example, s
cannot be a prefix string of words
because the concatenation of all the strings in words
does not equal s
, and furthermore, there is remaining substring in s
that can’t be matched by elements within words
. Thus, following the solution approach, we return false
.
Solution Implementation
1from typing import List # This line is to import the List type from the typing module
2
3class Solution:
4 def isPrefixString(self, s: str, words: List[str]) -> bool:
5 # Initialize total_length to 0 to keep track of the combined length of words in "words"
6 total_length = 0
7
8 # Iterate over the words list with an index i and word w
9 for i, word in enumerate(words):
10 # Update total_length by adding the length of the current word
11 total_length += len(word)
12
13 # Check if the combined length of words matches the length of s
14 if len(s) == total_length:
15 # Check if the concatenated words from the begin up to the current word equals s
16 # If it matches, our string s is a prefix and we return True
17 return ''.join(words[: i + 1]) == s
18
19 # If no prefix match is found after iterating through all words, return False
20 return False
21
1class Solution {
2 public boolean isPrefixString(String s, String[] words) {
3 // Initialize a StringBuilder to construct the prefix from words array
4 StringBuilder prefix = new StringBuilder();
5
6 // Iterate through each word in the words array
7 for (String word : words) {
8 // Append the current word to the prefix
9 prefix.append(word);
10
11 // Check if the length of the constructed prefix is same as the input string
12 if (s.length() == prefix.length()) {
13 // Compare the constructed prefix with the input string
14 return s.equals(prefix.toString());
15 }
16 }
17
18 // Return false if no prefix matches the input string
19 return false;
20 }
21}
22
1class Solution {
2public:
3 // Function to determine if the given string 's' is a prefix string
4 // created by concatenating elements from 'words' array.
5 bool isPrefixString(string s, vector<string>& words) {
6 string currentConcatenation = ""; // This will store the concatenation of words so far.
7
8 // Iterate over the words in the given words vector.
9 for (const string& word : words) {
10 // Add the current word to our concatenation string.
11 currentConcatenation += word;
12
13 // Check if the length of the current concatenation matches the length of 's'.
14 // If they match, perform a value comparison to see if they are equal.
15 if (currentConcatenation.size() == s.size()) {
16 return currentConcatenation == s; // Return true if they're exactly the same.
17 }
18 }
19 // If we exit the loop, the prefix condition has not been met.
20 return false;
21 }
22};
23
1// Function to determine if the given string 's' is a prefix string
2// created by concatenating elements from 'words' array.
3function isPrefixString(s: string, words: string[]): boolean {
4 let currentConcatenation: string = ""; // This will store the concatenation of words so far.
5
6 // Iterate over the words in the given words array.
7 for (const word of words) {
8 // Add the current word to our concatenation string.
9 currentConcatenation += word;
10
11 // Check if the length of the current concatenation matches the length of 's'.
12 // If they match, perform a value comparison to see if they are equal.
13 if (currentConcatenation.length === s.length) {
14 return currentConcatenation === s; // Return true if they're exactly the same.
15 }
16 }
17
18 // If we exit the loop, any prefix created doesn't match 's' exactly.
19 return false;
20}
21
Time and Space Complexity
Time Complexity
The time complexity of the code is O(n*k)
where n
is the number of words in the list and k
is the average length of the words. This is because in the worst case, the code iterates through each word in the words
list (O(n)
) and for each word it adds the length of the word to t
(O(k)
since in the worst case the length of the word can be as much as the length of s
). Moreover, joining the words is another O(n*k)
because all words might be joined in the worst case (when s
is exactly the concatenation of all words in the list).
Space Complexity
The space complexity is O(s)
, where s
is the length of the input string s
. In the worst case, when s
is a prefix string formed by concatenating all of the words in words
, the space taken by ''.join(words[:i + 1])
will be O(s)
since it needs to store the entire concatenated string equivalent to s
in memory temporarily.
Learn more about how to find time and space complexity quickly using problem constraints.
In a binary min heap, the maximum element can be found in:
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