Naïve String Matching Algorithm in Python: Examples, Featured & Pros & Cons

When there is a need to find an input pattern in a string of characters, coders and programmers use the string matching algorithm. Usually, in case of a short string, Python programmers prefer to use the naïve approach in which, the program checks each position in the input string for the query pattern. In case it matches, it gives an output with the position number.

One of the biggest reasons why the naïve string matching algorithm is used is that it is fast and yields quite accurate results. Moreover, it does not require pre-processing. While the approach is simple, it still plays a foundational role in more complex applications, including those in Artificial Intelligence, especially in text analysis and natural language processing. In any case, we will be discussing these advantages at a later stage in this post.

Let’s first understand the algorithm for pattern search using the naïve approach.

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Naïve Pattern Search Algorithm

In the naïve string pattern search, the program tests the position of the input pattern P [1……i] in a string of characters T [1…..m]. 

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Note that the length of the input text or string will always be greater than or equal to that of the pattern.

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Here is the naïve pattern search algorithm for different programming languages.

Begin

 pat = pattern Size

   str = string size

   for i = 0 to (str – pat), do

      for j = 0 to pat, do

         if text[i+j] ≠ pattern[j], then

            break the loop

      done

      if j == pat, then

         display the position of i as pattern found

   done

End

This algorithm is quite an important one in computer science, as it helps give search results as an ouput.

Read : Types of AI Algorithms You Should Know

Examples of Naïve String Matching on Python

Here is an example where the naïve pattern search approach is used in a code of python.

# Python program for Naïve String Matching

# Searching algorithm 

def search(P, T): 

    X = len(P) 

    Y = len(T) 

    # A loop to shift P[] one by one */ 

    for i in range(X – Y + 1): 

        j = 0  

        # For current index i, check  

        # for pattern match */ 

        for j in range(0, X): 

            if (txt[i + j] != P[j]): 

                break

        if (j == X – 1):  

            print(“Pattern found at position “, i) 

# Driver Code 

if __name__ == ‘__main__’: 

    T = “UPGRADEDUBUPGRAABUPGRADEDU”

    P = “UPGRAD”

    search(P, T) 

Output:

Pattern found at position 0

Pattern found at position 17

Explanation: The first position is the 0th position. Since the pattern “UPGRAD” was first spotted here, the output showed that the pattern is found at position 0.

Similarly, the next pattern was found at the position 17.

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Best Case of Naïve Pattern Search

There in only one best case for naïve pattern search algorithm, unlike the two worst cases.

The best case occurs when the first character in the pattern text is nowhere in the input string.

Example:

T [] = “UPGRADEDUHIJKLUPGRA”;

P [] = “TUPGRA”;

And therefore, the number of matching patterns case is O(n).

Worst Case of Naïve Pattern Search

There are two worst cases in the naïve string searching approach.

1. When all the characters in the pattern are the same as those in the input string.

T [] = “EEEEEEEEEEEEEEEE”;

P [] = “EEE”;

1. When only the last character in the pattern differs from the input string.

T [] = “EEEEEEEEEEED”;

P [] = “EEEED”;

In such cases, the number of comparisons in O(m*(n-m+1)).

Features of Naïve String Matching Algorithm

String matching algorithm is meant for finding all the occurrences of a given pattern in a text.

Here are the top features of the algorithm.

1. It is the simplest method among all to look for patterns in an input text. It checks all the characters one by one in the given string of characters.
2. It finds the exact string matches – be it more or more exact occurrences of the pattern.
3. It is more used when there is small text. Moreover, it does not require any pre-processing phases.
4. This search method does not occupy extra space to work and look for the patterns in the string. If you are interested in applying string matching techniques in real-world applications, you can explore how to make a chatbot using Python.

Also read: Data Structure & Algorithm in Python

Advantages of Naïve Pattern Search

1. There are no pre-processing phases required in the naïve search approach, as its running time is equal to the matching time.
2. There is no extra operating space needed.
3. The comparisons of the patterns with the strings can be done in any order.

Disadvantages of Naïve String Matching

There is only one disadvantage of the naïve string matching approach, which is that it is inefficient. This is because when it has found a position, it does not use it again to find the other position. It goes back to the starting point and looks for the pattern over again. And so, it does not use the information from the previous shift again.

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Conclusion

The naïve string matching algorithm is the most preferred approach to finding the positions of said patterns in a given text for various reasons like no pre-processing requirement, no extra space for operation, etc. However, it cannot be used for rather larger texts because of its inefficiency to perform large operations faster.

We hope that this post gave you a substantially good idea about the naïve pattern search approach in python. To learn about the uses of this approach and get a broader understanding of the topic, get in touch with the experts at upGrad. We have specially designed courses for individuals looking to expand their skillset. Reach out to us today!

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