Systems | Development | Analytics | API | Testing

Testing is necessary to produce working code, but it can be difficult and takes a lot of time! By reducing the time and cost of testing, we can increase the pace at which we can ship reliable and working features to customers. In this article, we'll explore easy and quick ways to collect and generate data and create schemas for testing.

Dialyzer (DIscrepancy AnaLYZer for ERlang programs) is a powerful static analysis tool that helps developers identify potential issues in their Elixir code without executing it. It excels at finding type mismatches, unreachable code, and unnecessary functions through sophisticated flow analysis. In part one of this two-part series, we'll first get to grips with the basics of Dialyzer. In part two, we'll examine more advanced use cases.

It is essential that you test sites and web applications to ensure their reliability, functionality, and user experience. Thanks to its rich API and impressive list of features, TestCafe has emerged as one of the most popular choices for automated end-to-end testing in Node.js. In this guide, you'll learn what TestCafe is, understand how it works, explore its features, and see it in action with a complete example. Time to become a TestCafe testing expert!

Efficient management of database interactions is one of the most important tasks when building Python web applications. SQLAlchemy — a comprehensive SQL toolkit and Object-Relational Mapping (ORM) library — is widely used in the Python ecosystem for this purpose. However, integrating SQLAlchemy with Flask can be a complex process. So developers created Flask-SQLAlchemy to provide a seamless way to use SQLAlchemy in Flask applications, making database management a straightforward process.

ActiveRecord: Rails' de facto ORM. We use it every day, and it makes life a lot easier; we type less, read less, have complexity hidden from us, and don't have to specify all kinds of boilerplate we'd otherwise have to.

In Node, managing asynchronous operations effectively (especially those involving I/O, like network requests or file system access) is crucial to prevent resource depletion. Managing async operations well also helps maintain optimal application performance when the results of operations are no longer required. The AbortController API addresses this need by providing a standardized mechanism to terminate operations gracefully.

Communication between processes in the Erlang VM happens through message passing. In fact, all communication across processes occurs through the same mechanism. All you need is an address and you can send a message to it, with the lower level building blocks being send and receive. This is true even if that address is on another node in a cluster of Elixir nodes that are aware of each other. In fact, it works in exactly the same way.

It’s not enough to just test our code's happy path (in other words, the error-free path we hope our users will take). To be really confident our code can’t be abused, either accidentally or on purpose, we must actively attack it to try and find ways of breaking it. If we don’t do this, someone else will, and they probably won’t be as friendly.

While Elixir provides built-in libraries (like HTTPoison) for making HTTP requests, the Tesla library has gained popularity due to its simplicity, ease of use, and extensibility. Tesla offers a clean and composable way to define requests, handle responses, and customize client behavior. Even so, whenever you're working with external APIs, errors are inevitable. Network issues, server downtime, rate limiting, and unexpected responses can all lead to errors in your application.

Regular expressions, commonly known as regex, are a tool for text processing and pattern matching. In Python, the re module offers a robust implementation of regex, allowing developers to handle complex text manipulation efficiently. In this article, we'll get to grips with regular expressions and provide practical code examples — from the basic to more advanced — so you can understand how to use regex in Python.