Hype Driven Development (HDD) is an ironic term in software development that refers to the tendency to adopt technologies or practices because they are currently trendy, rather than selecting them based on their actual suitability for the project. Developers or companies practicing HDD often embrace new frameworks, tools, or programming languages because they are gaining a lot of attention, without sufficiently analyzing whether these solutions are truly the best fit for their specific needs.
Typical characteristics of HDD include:
Overall, Hype Driven Development often leads to overcomplicated architectures, technical debt, and a significant investment of time in learning constantly changing technologies.
A batch in computing and data processing refers to a group or collection of tasks, data, or processes that are processed together in one go, rather than being handled individually and immediately. It is a collected set of units (e.g., files, jobs, or transactions) that are processed as a single package, rather than processing each unit separately in real-time.
Here are some typical features of a batch:
Collection of tasks: Multiple tasks or data are gathered and processed together.
Uniform processing: All tasks within the batch undergo the same process or are handled in the same manner.
Automated execution: A batch often starts automatically at a specified time or when certain criteria are met, without requiring human intervention.
Examples:
A batch is designed to improve efficiency by grouping tasks and processing them together, often during times when system load is lower, such as overnight.
Batch Processing is a method of data processing where a group of tasks or data is collected as a "batch" and processed together, rather than handling them individually in real time. This approach is commonly used to process large amounts of data efficiently without the need for human intervention while the process is running.
Here are some key features of batch processing:
Scheduled: Tasks are processed at specific times or after reaching a certain volume of data.
Automated: The process typically runs automatically, without the need for immediate human input.
Efficient: Since many tasks are processed simultaneously, batch processing can save time and resources.
Examples:
Batch processing is especially useful for repetitive tasks that do not need to be handled immediately but can be processed at regular intervals.
Contract Driven Development (CDD) is a software development approach that focuses on defining and using contracts between different components or services. These contracts clearly specify how various software parts should interact with each other. CDD is commonly used in microservices architectures or API development to ensure that communication between independent modules is accurate and consistent.
Contracts as a Single Source of Truth:
Separation of Implementation and Contract:
Contract-Driven Testing:
Consumer-Driven Contract
test can be used to ensure that the data and formats expected by the consumer are provided by the provider.Management Overhead:
Versioning and Backward Compatibility:
Over-Documentation:
Contract Driven Development is especially suitable for projects with many independent components where clear and stable interfaces are essential. It helps prevent misunderstandings and ensures that the communication between services remains robust through automated testing. However, the added complexity of managing contracts needs to be considered.
Gearman is an open-source job queue manager and distributed task handling system. It is used to distribute tasks (jobs) and execute them in parallel processes. Gearman allows large or complex tasks to be broken down into smaller sub-tasks, which can then be processed in parallel across different servers or processes.
Gearman operates on a simple client-server-worker model:
Client: A client submits a task to the Gearman server, such as uploading and processing a large file or running a script.
Server: The Gearman server receives the task and splits it into individual jobs. It then distributes these jobs to available workers.
Worker: A worker is a process or server that listens for jobs from the Gearman server and processes tasks that it can handle. Once the worker completes a task, it sends the result back to the server, which forwards it to the client.
Distributed Computing: Gearman allows tasks to be distributed across multiple servers, reducing processing time. This is especially useful for large, data-intensive tasks like image processing, data analysis, or web scraping.
Asynchronous Processing: Gearman supports background job execution, meaning a client does not need to wait for a job to complete. The results can be retrieved later.
Load Balancing: By using multiple workers, Gearman can distribute the load of tasks across several machines, offering better scalability and fault tolerance.
Cross-platform and Multi-language: Gearman supports various programming languages like C, Perl, Python, PHP, and more, so developers can work in their preferred language.
Batch Processing: When large datasets need to be processed, Gearman can split the task across multiple workers for parallel processing.
Microservices: Gearman can be used to coordinate different services and distribute tasks across multiple servers.
Background Jobs: Websites can offload tasks like report generation or email sending to the background, allowing them to continue serving user requests.
Overall, Gearman is a useful tool for distributing tasks and improving the efficiency of job processing across multiple systems.
RSS stands for Really Simple Syndication or Rich Site Summary. It's a web feed format used to deliver regularly updated content from websites in a standardized form, without having to visit the website directly. RSS feeds typically contain titles, summaries, and links to full articles or content.
Subscribing to feeds: Users can subscribe to RSS feeds from websites that offer them. These feeds provide information about new content on the site.
Using an RSS reader: To read RSS feeds, you use an RSS reader or feed reader (apps or programs). These readers collect and display all subscribed content in one place. Popular RSS readers include Feedly or Inoreader.
Automatic updates: The RSS reader regularly checks the subscribed feeds for new content and displays it to the user. This way, you can get all the latest updates from different sites centrally without visiting each one.
RSS is a convenient way to keep track of updates from many different websites in one place.
CaptainHook is a PHP-based Git hook manager that helps developers automate tasks related to Git repositories. It allows you to easily configure and manage Git hooks, which are scripts that run automatically at certain points during the Git workflow (e.g., before committing or pushing code). This is particularly useful for enforcing coding standards, running tests, validating commit messages, or preventing bad code from being committed.
CaptainHook can be integrated into projects via Composer, and it offers flexibility for customizing hooks and plugins, making it easy to enforce project-specific rules. It supports multiple PHP versions, with the latest requiring PHP 8.0.
An Entity is a central concept in software development, particularly in Domain-Driven Design (DDD). It refers to an object or data record that has a unique identity and whose state can change over time. The identity of an entity remains constant, regardless of how its attributes change.
Unique Identity: Every entity has a unique identifier (e.g., an ID) that distinguishes it from other entities. This identity is the primary distinguishing feature and remains the same throughout the entity’s lifecycle.
Mutable State: Unlike a value object, an entity’s state can change. For example, a customer’s properties (like name or address) may change, but the customer remains the same through its unique identity.
Business Logic: Entities often encapsulate business logic that relates to their behavior and state within the domain.
Consider a Customer entity in an e-commerce system. This entity could have the following attributes:
If the customer’s name or address changes, the entity is still the same customer because of its unique ID. This is the key difference from a Value Object, which does not have a persistent identity.
Entities are often represented as database tables, where the unique identity is stored as a primary key. In an object-oriented programming model, entities are typically represented by a class or object that manages the entity's logic and state.
Domain-Driven Design (DDD) is an approach to software development that focuses on modeling the underlying business domain. The goal is to create software solutions that closely align with the requirements and understanding of the real-world business area. DDD was popularized by Eric Evans in his book "Domain-Driven Design: Tackling Complexity in the Heart of Software."
The core idea behind DDD is that the structure and behavior of the software should reflect the underlying business domain to ensure effective collaboration between developers, domain experts, and other stakeholders.
Domain: The business domain is the central focus of DDD, referring to the area of business or industry that the software is designed to represent (e.g., e-commerce, finance).
Ubiquitous Language: A shared language used by developers and domain experts to describe the domain clearly and accurately. This helps avoid misunderstandings.
Entities and Value Objects:
Aggregates: A cluster of related objects (entities and value objects) that are treated as a single unit. Aggregates always have a Root Entity, which serves as the main entry point.
Repositories: Handle storing and retrieving aggregates. They provide an abstraction for accessing and saving objects.
Services: Methods or operations that implement domain logic but don't belong directly to any specific entity.
Bounded Context: A clearly defined area within the domain where specific terms and concepts are used in a precise way. Different bounded contexts may have different models for the same terms.
Domain Events: Events that occur within the domain and indicate that something relevant has happened, potentially leading to a change in state.
Domain-Driven Design is especially helpful in complex projects where business logic is central and frequently evolving.
Breaking Changes refer to modifications in software, an API, or a library that cause existing code or dependencies to stop functioning as expected. These changes break backward compatibility, meaning older versions of the code that rely on the previous version will no longer work without adjustments.
Typical examples of Breaking Changes include:
Dealing with Breaking Changes usually involves developers updating or adapting their software to remain compatible with new versions. Typically, Breaking Changes are introduced in major version releases to signal to users that there may be incompatibilities.