So I wonder if that might make any difference on comparison. How do I read / convert an InputStream into a String in Java? For example: Even that the operations in my_function dont make sense we can see that it has multiple time complexities: O(1) + O(n) + O(n). Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. 46,959 Yes, in your case *1 string concatenation requires all characters to be copied, this is a O(N+M) operation (where N and M are the sizes of the input strings). I have mentioned a few. When using the Big-O notation, we describe the algorithms efficiency based on the increasing size of the input data (n). Is it illegal to use resources in a university lab to prove a concept could work (to ultimately use to create a startup)? The examples shown in this story were developed in Python, so it will be easier to understand if you have at least the basic knowledge of Python, but this is not a prerequisite. Number of operations done will be 0 + 1 + 2 + . + x = x * (x + 1) / 2 . Shouldn't the best/average case be O(len(string))? This issue applies any time an == check is done. We use a mathematical notation called Big-O. Time Complexity: O (n) -> (split function) Space Complexity: O (n) Method #2 : Using set () + split () In this, instead of sort (), we convert strings to set (), to get ordering. The answer accepted by the question owner as the best is marked with, The answers/resolutions are collected from open sources and licensed under. Connect and share knowledge within a single location that is structured and easy to search. Answers are sorted by their score. A Medium publication sharing concepts, ideas and codes. When analyzing the time complexity of an algorithm we may find three cases: best-case, average-caseand worst-case. Lets start understanding what is computational complexity. Are defenders behind an arrow slit attackable? So immutability of strings in no way affects the equality check right? . The time complexity is O(N) and the actual time taken depends on how many characters need to be scanned before differences statistically emerge. Let us see how to compare Strings in Python. This says the worst case for strings would be O(len(string)). My work as a freelance was used in a scientific paper, should I be included as an author? What is the time complexity of String compareTo function in Java? How do I make the first letter of a string uppercase in JavaScript? This notation characterizes functions according to their growth rates: different functions with the same growth rate may be represented using the same O notation. How do I replace all occurrences of a string in JavaScript? Note that it will grow in a factorial way, based on the size of the input data, so we can say the algorithm has factorial time complexity O(n!). Why do we use perturbative series if they don't converge? Since string lengths can be compared in constant time, shouldn't this only apply to strings of equal length? This will lead to redundant CPU time usage. To do this, we'll need to find the total time required to complete the required algorithm for different inputs. The C language stores strings as a null-terminated sequence of characters, so the algorithm you describe would not work. It is important to note that when analyzing an algorithm we can consider the time complexity and space complexity. Usually, when describing the time complexity of an algorithm, we are talking about the worst-case. I am not looking for any specific programming language. Not in this case, they are immutable for other reasons. 0 + 1 * (x) * 1 + 2 * (x - 1) * 2 + 3 * (x - 3) * 3 + . + x/2 * x/2 * x/2 calculations. If your string data structure can have a string of max size x, then there can be a total of (x + 1) possible string sizes (0, 1, 2, , x). My question is why worst case? Generally string data structure stores the size in memory, rather than calculating it each time. As this will stop the further O (n) comparison, and save time. Your home for data science. Optimization 1: Check the size of both the strings, if unequal, return false. This is the best possible time complexity when the algorithm must examine all values in the input data. These are the most common time complexities expressed using the Big-O notation: Note that we will focus our study in these common time complexities but there are some other time complexities out there which you can study later. If they are ints, O==() would be O(1); if they are strings, O==() in the worst case it would be O(len(string)). After a few checks such as string length and "kind" (python may use 1, 2 or 4 bytes per character depending on unicode USC character size), its just a call to the C lib memcmp. In computer science, Big-O notation is used to classify algorithms according to how their running time or space requirements grow as the input size (n) grows. Finding the original ODE using a solution. The algorithm is simple, you check the strings char by char, so: Thanks for contributing an answer to Stack Overflow! name1 = 'Python is good' name2 = 'Python good' if name1 != name2: print (name1,'is NOT equal to',name2) After writing the above Python code to check ( string is not equal to ), Ones you will print "name1,'is . As already said, we generally use the Big-O notation to describe the time complexity of algorithms. Perhaps under the hood python is able to use ord values more efficiently than O(n) traversals? Here is another sheet with the time complexity of the most common sorting algorithms. Does Python have a string 'contains' substring method? For example: for each value in the data1 (O(n)) use the binary search (O(log n)) to search the same value in data2. Where as without any optimization, there will be. Not the answer you're looking for? Big-O notation, sometimes called asymptotic notation, is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. stringcomparisontime-complexity 16,057 Solution 1 Time for string comparison is O(n), n being the length of the string. TimeComplexity - Python Wiki This page documents the time-complexity (aka "Big O" or "Big Oh") of various operations in current CPython. Constant Time - O (1) (read as O of 1) An algorithm/code where the efficiency of execution is not impacted by the size of the input is said to have a Constant Time complexity. Even when working with modern languages, like Python, which provides built-in functions, like sorting algorithms, someday you will probably need to implement an algorithm to perform some kind of operation in a certain amount of data. Optimization 1: Check the size of both the strings, if unequal, return false. An algorithm with constant time complexity is excellent since we dont need to worry about the input size. Python's string compare is implemented in unicodeobject.c. I often need to check this against my database which has thousands of rows. If after reading all this story you still have some doubts about the importance of knowing time complexity and the Big-O notation, lets clarify some points. What properties should my fictional HEAT rounds have to punch through heavy armor and ERA? Time Complexity of String Comparison. Note By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. show that your assumption is incorrect. Method 1: Using Relational Operators The relational operators compare the Unicode values of the characters of the strings from the zeroth index till the end of the string. Now let see the example for each of these operators below. PS: as @AdvMaple pointed out, your alternative implementation is wrong, because zip stops as soon as one of its input runs out of elements, but that does not change the time-complexity question. But it scales the same. I have mentioned a few. Imports: This is one reason that a long password is considered more secure than a shorter one. I have mentioned a few. Find centralized, trusted content and collaborate around the technologies you use most. M appends of the same word will trend to O(M^2 . Would it be O(1)? The first has a time complexity of O (N) for Python2, O (1) for Python3 and the latter has O (1) which can create a lot of differences in nested statements. The character with lower Unicode value is considered to be smaller. An algorithm is said to have a quasilinear time complexity when each operation in the input data have a logarithm time complexity. Are defenders behind an arrow slit attackable? 1). Heap found a systematic method for choosing at each step a pair of elements to switch, in order to produce every possible permutation of these elements exactly once. Time for string comparison is O(n), n being the length of the string. Finally, when comparing two lists for equality, the complexity class above shows as O (N), but in reality we would need to multiply . Many languages (e.g. Time complexity doesnt say anything about how long an operation takes, just how an operation scales with a larger input set n. memcmp is much faster than the python version because of inherent language overhead. How to check whether a string contains a substring in JavaScript? Thanks for contributing an answer to Stack Overflow! In CPython (the main implementation of Python) the time complexity of the find () function is O ( (n-m)*m) where n is the size of the string in which you search, and m is the size of the string which you search. Which will be without any doubt more than O(n^3). Yes, the C implementation that == ends up calling is much faster, because it's in C rather than as a Python loop, but its worse-case big-Oh complexity is still going to be O(n). Complexity Analysis for backspace string compare Time Complexity = O (n + m), where n is the length of string S and m is the length of string T. Space Complexity = O (n + m) JAVA Code import java.util.Stack; public class BackspaceStringCompare { private static boolean backSpaceCompare(String S, String T) { return reform(S).equals(reform(T)); } How were sailing warships maneuvered in battle -- who coordinated the actions of all the sailors? Suppose we have the following unsorted list [1, 5, 3, 9, 2, 4, 6, 7, 8] and we need to find the index of a value in this list using linear search. What is the difference between String and string in C#? Your point becomes very valid when a given string is compared more than once during the runtime of a program. We do not currently allow content pasted from ChatGPT on Stack Overflow; read our policy here. Connect and share knowledge within a single location that is structured and easy to search. Remaining (x + 1) * (x - 2) / 2 cases will be calculated in O(1) time. Making statements based on opinion; back them up with references or personal experience. Now, lets go through each one of these common time complexities and see some examples of algorithms. I would expect the time complexity of comparing two arbitrary strings to amortize to O(1) since lengths will vary in the average case. Examples of frauds discovered because someone tried to mimic a random sequence. Let's look through some examples for string comparison. Nowadays, with all these data we consume and generate every single day, algorithms must be good enough to handle operations in large volumes of data. Does Python have a string 'contains' substring method? Is there a higher analog of "category with all same side inverses is a groupoid"? As you may have noticed, the time complexity of recursive functions is a little harder to define since it depends on how many times the function is called and the time complexity of a single function call. It is important to note that when analyzing the time complexity of an algorithm with several operations we need to describe the algorithm based on the largest complexity among all operations. It then returns a boolean value according to the operator used. Ok, but how we describe the time complexity of an algorithm? the python code has the same O(n) time complexity as memcmp, its just that python has a much bigger O. For example: Lets take a look at the example of a linear search, where we need to find the position of an element in an unsorted list: Note that in this example, we need to look at all values in the list to find the value we are looking for. Why do quantum objects slow down when volume increases? How Does String Comparison Work in Python? If you do your initial comparison using hashes, which are shorter than the supposed long strings, you may be able to reduce the IO and RAM requirements of the system by carefully designing your query strategy. String . A great example of an algorithm which has a factorial time complexity is the Heaps algorithm, which is used for generating all possible permutations of n objects. Why doesn't Stockfish announce when it solved a position as a book draw similar to how it announces a forced mate? How do I make the first letter of a string uppercase in JavaScript? To explain in simple terms, Time Complexity is the total amount of time taken to execute a piece of code. Python string comparison is performed using the characters in both strings. If you use optimization 1, then you would need to compare the whole length only when two strings are of equal length. Im curious how Python performs string comparisons under the hood. To make your life easier, here you can find a sheet with the time complexity of the operations in the most common data structures. String comparisons typically do a linear scan of the characters, returning false at the first index where characters do not match. Theoretically speaking, we are not developing an algorithm that will change the worst case time complexity, it is still O(n). Finally, when comparing two lists for equality, the complexity class above shows as O(N), but in reality we would need to multiply this complexity class by O==() where O==() is the complexity class for checking whether two values in the list are ==. As for the theoretical time complexity, to simplify things, we could look at strings with 1-byte chars and my assumption would be: Where: 'n' is the input string size 'm' is the integer used for multiplication Case#1: If string size is 1 Example: "a" * 16 No matter the size of the input data, the running time will always be the same. rev2022.12.11.43106. It is commonly seen in sorting algorithms (e.g. This works only on unique character strings. mergesort, timsort, heapsort). Compare Strings Character by Character in Python. However depending on the test data, you can manually optimize the matching algorithm. Time complexity doesn't say anything about how long an operation takes, just how an operation scales with a larger input set n. memcmp is much faster than the python version because of inherent language overhead. Since you database contains web links, it is possible that they belong to the same website, hence their first few characters will always be same. However, at some point in the execution of that program, the characters of the string were counted to obtain the length. Regardless of how its implemented, the comparison of two strings is going to take O(n) time. This piece of code could be an algorithm or merely a logic which is optimal and efficient. Looking at the above results I understand that string comparison is linear O(N) and not O(1). But it scales the same. Thanks for reading this story. Should I exit and re-enter EU with my EU passport or is it ok? Disconnect vertical tab connector from PCB, Counterexamples to differentiation under integral sign, revisited. MOSFET is getting very hot at high frequency PWM, Name of poem: dangers of nuclear war/energy, referencing music of philharmonic orchestra/trio/cricket. Why is there an extra peak in the Lomb-Scargle periodogram? To learn more, see our tips on writing great answers. When analyzing the time complexity of an algorithm we may find three cases: best-case, average-case and worst-case. If the searched value is lower than the value in the middle of the list, set a new right bounder. To compare two strings of length m we need m l o g / w which gives us O ( m l o g / w). How do I arrange multiple quotations (each with multiple lines) vertically (with a line through the center) so that they're side-by-side? It makes more sense when we look at the recursion tree. I just want to know which comparison takes faster. Find centralized, trusted content and collaborate around the technologies you use most. Hence total computations = x * (x + 1) / 2 + (x + 1) * (x - 2) / 2 = (x + 1) * (x - 1) which is O(n^2). Add a new light switch in line with another switch? Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Computational complexity is a field from computer science which analyzes algorithms based on the amount resources required for running it. In Python, we can compare two strings, character by character, using either a for loop or a while loop. I hope you have learned a little more about time complexity and the Big-O notation. Also, feel free to follow me on Twitter, Linkedin, and Github. rev2022.12.11.43106. Lets see some common time complexities described in the Big-O notation. How is Jesus God when he sits at the right hand of the true God? How to check whether a string contains a substring in JavaScript? Name of poem: dangers of nuclear war/energy, referencing music of philharmonic orchestra/trio/cricket. Let's understand what it means. Important points: Lists are similar to arrays with bidirectional adding and deleting capability. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Would salt mines, lakes or flats be reasonably found in high, snowy elevations? b = https://www.somerandomurls.com/directory/anotherdirectory/helloworld.html Lets take a look at the example of a binary search, where we need to find the position of an element in a sorted list: It is important to understand that an algorithm that must access all elements of its input data cannot take logarithmic time, as the time taken for reading input of size n is of the order of n. An algorithm is said to have a linear time complexity when the running time increases at most linearly with the size of the input data. Help us identify new roles for community members, Proposing a Community-Specific Closure Reason for non-English content. Dictionaries and Set use Hash Tables for insertion/deletion and lookup operations. doThis(). Theres a lot of math involved in the formal definition of the notation, but informally we can assume that the Big-O notation gives us the algorithms approximate run time in the worst case. Python3 # Python3 code to demonstrate working of # Similar characters Strings comparison # Using set () + split () We are just optimizing the algorithm. If it is a list, the n will be the length of the list and so on. We mostly will assume == checking on values in lists is O(1): e.g., checking ints and small/fixed-length strings. Time and Space Complexity of python function. Another example of an exponential time algorithm is the recursive calculation of Fibonacci numbers: If you dont know what a recursive function is, lets clarify it quickly: a recursive function may be described as a function that calls itself in specific conditions. There will be only x + 1 such cases. An algorithm is said to have a constant time when it is not dependent on the input data (n). An algorithm is said to have a logarithmic time complexity when it reduces the size of the input data in each step (it dont need to look at all values of the input data), for example: Algorithms with logarithmic time complexity are commonly found in operations on binary trees or when using binary search. Why is char[] preferred over String for passwords? Since we are doing x * (x + 1) / 2 string comparisons, hence amortized time complexity per comparison is O(1). Making statements based on opinion; back them up with references or personal experience. Another, more complex example, can be found in the Mergesort algorithm. Below represents the python code string not equal to comparison. Python uses the objects with the same values in memory which makes comparing objects faster. However, I was reading this document: Complexities of Python Operations The part: Finally, when comparing two lists for equality, the complexity class above shows as O (N), but in reality we would need to multiply this complexity class by O== (.) Now, look how the recursion tree grows just increasing the n to 6: You can find a more complete explanation about the time complexity of the recursive Fibonacci algorithm here on StackOverflow. Ready to optimize your JavaScript with Rust? Note that in this example the sorting is being performed in-place. 1. Why do we use perturbative series if they don't converge? The time complexity of the above code is O(n), and the space complexity is O(1) since we are only storing the count and the minimum length. And when you think about it, each of the if x != y: compares in the second example runs the exact same code as the single s1 == s2 compare in the first. How do I replace all occurrences of a string in JavaScript? Time complexity of string concatenation in Python; Time complexity of string concatenation in Python. the python code has the same O(n) time complexity as memcmp, its just that python has a much bigger O. When reaching the leaves it returns the value itself. Pythons string compare is implemented in unicodeobject.c. As youre reading this story right now, you may have an idea about what is time complexity, but to make sure were all on the same page, lets start understanding what time complexity means with a short description from Wikipedia. An algorithm is said to have a factorial time complexity when it grows in a factorial way based on the size of the input data, for example: As you may see it grows very fast, even for a small size input. Today we'll be finding time-complexity of algorithms in Python. Mergesort is an efficient, general-purpose, comparison-based sorting algorithm which has quasilinear time complexity, lets see an example: The following image exemplifies the steps taken by the mergesort algorithm. Can several CRTs be wired in parallel to one oscilloscope circuit? And amortized time complexity will be more than O(n). Asking for help, clarification, or responding to other answers. What about strings that are equal? When would I give a checkpoint to my D&D party that they can return to if they die? For example, if the input is a string, the n will be the length of the string. Other Python implementations (or older or still-under development versions of CPython) may have slightly different performance characteristics. PS: as @AdvMaple pointed out, your alternative implementation is wrong, because zip stops as soon as one of its input runs out of elements, but that does not change the time-complexity question. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Help us identify new roles for community members, Proposing a Community-Specific Closure Reason for non-English content. Not the answer you're looking for? However, I was reading this document: Complexities of Python Operations. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Fulltime Data Analyst openings in Miami, United States on September 07, 2022, Bayesian Networks: Combining Machine Learning and Expert Knowledge into Explainable AI, Classification vs. Regression Explained Easily, My 7 years flash black; A Slippery entry to Data Science, Filter, Aggregate and Join in Pandas, Tidyverse, Pyspark and SQL, Manage your machine learning models with HuoguoML, https://en.wikipedia.org/wiki/Computational_complexity, https://en.wikipedia.org/wiki/Big_O_notation, https://en.wikipedia.org/wiki/Time_complexity, https://vickylai.com/verbose/a-coffee-break-introduction-to-time-complexity-of-algorithms/. if a != b: If the searched value is higher than the value in the middle of the list, set a new left bounder. How do I arrange multiple quotations (each with multiple lines) vertically (with a line through the center) so that they're side-by-side? where O== (.) How many transistors at minimum do you need to build a general-purpose computer? Even though the space complexity is important when analyzing an algorithm, in this story we will focus only on the time complexity. C#) store information about the string length as metadata. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. (There might exist pre-built side data structures that could help speed it up, but Im assuming your input is just two strings and nothing else.). In this post, we will understand a little more about time complexity, Big-O notation and why we need to be concerned about it when developing algorithms. An algorithm is said to have a quadratic time complexity when it needs to perform a linear time operation for each value in the input data, for example: Bubble sort is a great example of quadratic time complexity since for each value it needs to compare to all other values in the list, lets see an example: An algorithm is said to have an exponential time complexity when the growth doubles with each addition to the input data set. Time for string comparison is O (n), n being the length of the string. a = helloworldhelloworldhelloworld What happens if the permanent enchanted by Song of the Dryads gets copied? Based on this, we can describe the time complexity of this algorithm as O(n). Time complexity doesn't say anything about how long an operation takes, just how an operation scales with a larger input set n. memcmp is much faster than the python version because of inherent language overhead. With a quick change to your python code condition = True if len(s1) == len(s2): for x,y in zip(s1, s2): Ready to optimize your JavaScript with Rust? For example: Now, lets take a look at the function get_first which returns the first element of a list: Independently of the input data size, it will always have the same running time since it only gets the first value from the list. But here is a key concept in these complexity calculations: any constant is eliminated in big-O notation. After a few checks such as string length and "kind" (python may use 1, 2 or 4 bytes per character depending on unicode USC character size), its just a call to the C lib memcmp. Otherwise, python == is very efficient, so you can assume its at worse O(n). Would like to stay longer than 90 days. Python doesn't by default do the "hashing test" to rule out obviously non-equal strings? Practically this is a huge optimization. Using advantage of Bit-level parallelism, the processor can handle a data of size w at single time, this, mean to check m characters we need m / w operations. They leverage memset and memcpy calls optimised at hardware level, which can be very fast. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. The space complexity is basically the amount of memory space required to solve a problem in relation to the input size. Lets understand what it means. Where does the idea of selling dragon parts come from? Hence better to check from the end for this case, as relative links will differ only from the end. The algorithm we're using is quick-sort, but you can try it with any algorithm you like for finding the time-complexity of algorithms in Python. Note that I tried to follow the following approach: present a little description, show a simple and understandable example and show a more complex example (usually from a real-world problem). Is this an at-all realistic configuration for a DHC-2 Beaver? Besides that, if you plan to apply to a software engineer position in a big company like Google, Facebook, Twitter, and Amazon you will need to be prepared to answer questions about time complexity using the Big-O notation. . lambda versus list comprehension performance, List: How to split and sort content of a list in python, how to convert simple text comma separated with inverted comma, Keras: What's the difference between "samples_per_epoch" and "steps_per_epoch" in fit_generator, Stripping non printable characters from a string in python in String, Python SyntaxError: invalid syntax for a valid statement in Python, Python: Concatenate a NumPy array to another NumPy array, Iterating over lists in pandas dataframe to remove everything after certain value (if the value exists) in list in Pandas, Merge: How to merge 2 i-th element of arrays, error handling speech_recognition WaitTimeOutError in Python-3.X. Some basic comparison operator is equal to (= =) and 'is' operator. Is it appropriate to ignore emails from a student asking obvious questions? Otherwise, python == is very efficient, so you can assume it's at worse O(n). A Time Complexity Question; Searching Algorithms; Sorting Algorithms; . The characters in both strings are compared one by one. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. the python code has the same O(n) time complexity as memcmp, its just that python has a much bigger O. This kind of time complexity is usually seen in brute-force algorithms. After a few checks such as string length and "kind" (python may use 1, 2 or 4 bytes per character depending on unicode USC character size), its just a call to the C lib memcmp. Storing the length becomes a useful optimization. What is the difference between String and string in C#? python string time-complexity. In Python, strings use the ASCII value of characters for comparison. As this will stop the further O(n) comparison, and save time. Another great example is the Travelling Salesman Problem. I ran some test to determine if O(==) for Strings is O(len(string)) or O(1). However depending on the test data, you can manually optimize the matching algorithm. So, when increasing the size of the input data, the bottleneck of this algorithm will be the operation that takes O(n). show that your assumption is incorrect. Why is the federal judiciary of the United States divided into circuits? Let us see how to compare two strings using != operator in Python. 2. Clarification: Normally (and Naively), we check one char at the time, which gives O ( m). (There might exist pre-built side data structures that could help speed it up, but I'm assuming your input is just two strings and nothing else.). is the complexity class for checking whether two values in the list are ==. Sometimes, while working with data, we can have a problem in which we need to perform comparison between a string and it's next element in a list and return all strings whose next element is similar list. The following recursion tree was generated by the Fibonacci algorithm using n = 4: Note that it will call itself until it reaches the leaves. In cryptography, a brute-force attack may systematically check all possible elements of a password by iterating through subsets. Using an exponential algorithm to do this, it becomes incredibly resource-expensive to brute-force crack a long password versus a shorter one. Regardless of how it's implemented, the comparison of two strings is going to take O(n) time. Asking for help, clarification, or responding to other answers. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. To learn more, see our tips on writing great answers. The amount of required resources varies based on the input size, so the complexity is generally expressed as a function of n, where n is the size of the input. How do I read / convert an InputStream into a String in Java? For example if. Dual EU/US Citizen entered EU on US Passport. Yes, the C implementation that == ends up calling is much faster, because its in C rather than as a Python loop, but its worse-case big-Oh complexity is still going to be O(n). When different characters are found then their Unicode value is compared. For example let to search string 'a'*m+'b' in string 'a'*n (m < n). We do not currently allow content pasted from ChatGPT on Stack Overflow; read our policy here. If you have any doubt or suggestion feel free to comment or send me an email. In the . In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm. If the search value is equal to the value in the middle of the list, return the middle (the index). If every one of your strings starts with http://, there will be a constant overhead to scan those first 7 characters (without tailoring the comparison algorithm to your specialized data). Repeat the steps above until the value is found or the left bounder is equal or higher the right bounder. I ran some test to determine if O (==) for Strings is O (len (string)) or O (1). If an algorithm has time complexity O (n^2), then (for example) for n = 10,000 it will take a hundred times longer than for n = 1000. And when you think about it, each of the if x != y: compares in the second example runs the exact same code as the single s1 == s2 compare in the first. By studying time complexity you will understand the important concept of efficiency and will be able to find bottlenecks in your code which should be improved, mainly when working with huge data sets. Why is char[] preferred over String for passwords? Does aliquot matter for final concentration? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Check the size of both the strings, if unequal, return false. Zorn's lemma: old friend or historical relic? As you see, the value of b is longer string on the first example and shorter on the second example. But it scales the same. Example: E.g. However depending on the test data, you can manually optimize the matching algorithm. Sort array of objects by string property value. Case-insensitive string comparison in Python. There are (x + 1) choose 2 ways of selecting two strings = x * (x + 1) / 2. Sometimes, though when it is true, the cost has been shifted to a different part of the algorithm. If you have long strings, a tendency for the beginning of many strings to have the same starting characters, and extreme performance requirements you can consider hashing the strings, comparing the hashes first, and only doing a linear comparison of the strings if the hashes match (in order to rule out the possibility of a hash collision). Is it correct to say "The glue on the back of the sticker is dying down so I can not stick the sticker to the wall"? PSE Advent Calendar 2022 (Day 11): The other side of Christmas. Python's string compare is implemented in unicodeobject.c. How were sailing warships maneuvered in battle -- who coordinated the actions of all the sailors? Looking at the above results I understand that string comparison is linear O (N) and not O (1). If you enjoyed it, please give it a clap and share it. I will explain how, by calculating the amortized time complexity. This allows O(1) time access to the string size. 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