Blogs

In modern software development, containerization has become a key practice for ensuring consistent environments across different stages of development, testing, and deployment. Spring Boot 3 offers robust support for Docker Compose and Testcontainers, making it easier to manage multi-container applications and write comprehensive integration tests. This blog post will guide you through setting up Spring Boot 3 with Docker Compose, using custom container images, and leveraging Testcontainers for integration testing. ...

Introduction: In software development, reusing configurations is a smart way to keep your code clean and modular. If you’re working with Spring Boot 3, there are some handy annotations you can use to import existing configurations into your project. In this blog post, we’ll explore how to use @Import and @ImportResource to achieve this. Importing Java Configurations with @Import: The @Import annotation is used to bring in configurations from other Java classes. This is especially useful when you have common configurations that you want to reuse across multiple applications. ...

Introduction In the world of software development, clear and informative communication is key. This principle extends to every aspect of our work, including the messages we write in Git. Whether it’s a commit message, a pull request (PR) description, or a branch name, well-crafted messages can greatly improve collaboration and project maintainability. In this guide, we’ll explore best practices for writing clear and effective messages in Git. 1. Commit Messages ...

Logging is an essential aspect of any application, providing critical insights and aiding in debugging and monitoring. In a Spring Boot 3 application, you can easily configure log levels for specific loggers to control the verbosity of logs for different packages or classes. In this blog, we’ll explore how to achieve this using properties files, YAML configuration, and programmatic approaches for both Logback and Log4j. Table of Contents Introduction Using application.properties Using application.yml Programmatic Configuration Customizing Logback Configuration Configuring Log4j Conclusion Introduction Spring Boot uses Logback as the default logging framework, but it also supports Log4j2. You can choose the logging framework that best fits your needs. In this blog, we’ll cover configuration for both Logback and Log4j. ...

Question: Given an array of strings strs, group the anagrams together. Answer: To group anagrams together, you can use a dictionary to map sorted strings to their respective groups of anagrams. Here’s how you can do it in Python: def group_anagrams(strs): anagrams = {} for word in strs: sorted_word = ''.join(sorted(word)) if sorted_word in anagrams: anagrams[sorted_word].append(word) else: anagrams[sorted_word] = [word] return list(anagrams.values()) # Example strs = ["eat", "tea", "tan", "ate", "nat", "bat"] print(group_anagrams(strs)) In this code: We iterate through each word in the input array. For each word, we sort its characters and use the sorted string as a key in the anagrams dictionary. If the sorted string already exists in the dictionary, we append the word to its list of anagrams. Otherwise, we create a new entry with the sorted string as the key and a list containing the word as its value. Finally, we return the values of the anagrams dictionary as a list, which contains lists of anagrams. This solution has a time complexity of O(n * k * log(k)), where n is the number of words in the input array and k is the maximum length of a word. The space complexity is O(n * k) due to the dictionary used to store the grouped anagrams. ...

Question: Given an array of integer nums and an integer target, return indices of the two numbers such that they add up to the target. Answer: To solve this problem, you can use a dictionary to store the indices of the numbers you’ve seen so far. As you iterate through the array, you can check if the complement of the current number (target - current number) exists in the dictionary. If it does, you’ve found the two indices that add up to the target. ...

To solve the “valid anagram” problem, we need to determine if two given strings are anagrams of each other. Two strings are anagrams if they contain the same characters with the same frequencies. Here is a Python function that solves this problem using different approaches, followed by an analysis of each approach to find the best solution. Solution 1: Sorting def is_anagram(s, t): return sorted(s) == sorted(t) Explanation: Sorting: Sort both strings and compare them. If they are anagrams, their sorted versions will be identical. If not, they will differ. Analysis: Time Complexity: O(n log n), where n is the length of the strings (sorting time). Space Complexity: O(n), due to the space required for the sorted strings. Solution 2: Counting Characters with a Dictionary def is_anagram(s, t): if len(s) != len(t): return False count_s = {} count_t = {} for char in s: count_s[char] = count_s.get(char, 0) + 1 for char in t: count_t[char] = count_t.get(char, 0) + 1 return count_s == count_t Explanation: Early Exit: Check if the lengths of the strings are different; if so, return False. Counting: Use two dictionaries to count the frequency of each character in both strings. Comparison: Compare the two dictionaries. If they are equal, the strings are anagrams; otherwise, they are not. Analysis: Time Complexity: O(n), where n is the length of the strings. Space Complexity: O(n), due to the space required for the dictionaries. Solution 3: Counting Characters with a Single Dictionary def is_anagram(s, t): if len(s) != len(t): return False count = {} for char in s: count[char] = count.get(char, 0) + 1 for char in t: if char in count: count[char] -= 1 else: return False return all(value == 0 for value in count.values()) Explanation: Early Exit: Check if the lengths of the strings are different; if so, return False. Counting and Balancing: Count the characters in the first string. Subtract the count while iterating through the second string. If a character in the second string is not in the count dictionary, return False. Final Check: Ensure all counts in the dictionary are zero. Analysis: Time Complexity: O(n), where n is the length of the strings. Space Complexity: O(n), due to the space required for the dictionary. Conclusion The best solution is Solution 3: Counting Characters with a Single Dictionary, due to its optimal time complexity O(n) and efficient space usage. Here’s the final version of the best solution: ...

To determine if any value appears more than once in an integer array, the best approach is to use a set due to its optimal balance of time complexity, space complexity, and simplicity. Here’s a comprehensive solution and explanation: Solution def contains_duplicate(nums): seen = set() for num in nums: if num in seen: return True seen.add(num) return False Explanation Initialization: Create an empty set called seen. seen = set() Iteration: Loop through each element in the array. for num in nums: Check for Duplicates: ...

Why Externalize Configuration? Externalizing configuration in Spring Boot means separating configuration parameters from the code. This separation allows the same application code to be used in different environments by simply changing the configuration rather than the code, reducing the risk of bugs and simplifying the deployment process. 1. Using application.properties or application.yml Spring Boot’s default approach for configuration is through the application.properties or application.yml files located under src/main/resources. These files are automatically loaded by Spring Boot and can be used to define properties accessible throughout the application. ...

Understanding how to create and manage these beans effectively is crucial for leveraging the full power of Spring Boot. In this blog post, we’ll dive into the various methods available for bean creation, focusing on annotations like @Component, @Service, @Repository, @Controller, and @Bean. What is a Bean in Spring Boot? In Spring Boot, a “bean” is an object that is instantiated, assembled, and otherwise managed by the Spring IoC (Inversion of Control) container. Beans are the building blocks of your application, and managing them properly allows Spring to tie your application together through dependency injection. ...