As an all-encompassing marketplace, RapidAPI has become a popular option for developers and vendors alike. So what does it have to offer and how can you harness it effectively to get the most out of its features and benefits? On the surface, the concept of RapidAPI is simple; it aims to act as your one-stop-shop for a wide variety of RESTful APIs which can be deployed to tackle a plethora of potential projects.
Ever feel like the world is moving by so rapidly, that it feels like something got left behind in the rush? That’s how we feel about being able to debug your applications easily. Technology has advanced rapidly, but the ease of debugging has not. With the introduction of serverless computing, the way enterprises are designed and how they build their production applications was changed.
Customer experience is a key factor in competitive differentiation in the digital economy. The online business model has changed, and today, the focus has shifted from brands to customers. It would not be an exaggeration to say that customer experience plays a central role in any business model.
This article is a continuation of Part I (A comprehensive guide to migrating from Python 2(Legacy Python) to Python 3), which details the changes, and improvements in Python 3, and why they are essential. The rest of the article describes automated tools, strategies, and the role of testing in the migration from Python 2 to 3.
My computer programming teacher had always told me that 10% of our time is spent developing 90% of our application, and the other 90% of our time finishing the last 10% of our project. Even with a good project plan and a concept that makes logical sense, most of our time will be consumed with fixing errors. Moreover, with JavaScript, our application can run without obvious errors preventing it from being run, so we have to employ several techniques to make sure everything is running smoothly.
When requirements change for your product, there arises a need to change not only the codebase but also the existing data that already lives in production. If you’re performing the changes locally, the whole process seems fairly simple. You test your new feature against a sparkling clean database, the test suite is green, and the feature looks great. Then you deploy, and everything goes to hell because you forgot that production was in a slightly different state.
Have you ever been neck-deep building a new feature? You're working at capacity. You need to test something out so you paste an API key into your source file with every intention of removing it later. But you forget. You push to GitHub. It's an easy mistake, and potentially a very expensive one. In this article, Julien Cretel explores the nuances of this kind of data leak, offers suggestions for recovery when leaks happen and gives us options for preventing them in the first place.
Python powers many applications we use in our day-to-day like Reddit, Instagram, Dropbox, and Spotify. The adoption of Python 3 has been a subject of debate in the Python community. While Python 3 has been out for more than a decade now, there wasn’t much incentive to migrate from the stable Python 2.7 in the earlier releases. If you’re still running on legacy python, it’s high time to migrate as it has reached the end of its life since Jan 2020.
At Rollbar we love workflow automation. With our new Notifications API, you can automate setting up of custom notification rules for all your Rollbar projects. As more of our customers switch to microservices, we wanted to build a programmatic way to set up these rules for multiple projects or services in just a few seconds, without having to go to the UI.
