While all beginning Python developers will probably start coding using Python’s Integrated Development and Learning Environment (IDLE), it won’t take long before they realize this approach has its limits. Most will look to tools that help them more efficiently build code.
We develop an analytics HTTP API in Python. This is how we discover what to improve to serve requests faster.
SDKs naturally increase in size over time. After all, it does take more bytes to implement more features. This is not a big deal for most languages—the relative size of each new feature is small, and load times and storage aren’t big concerns for code running on a server. Larger JS bundles mean longer load times, which in turn increase user misery, which then can cause the user to leave pages entirely.
Some of the tricks we used to speed up calls to our analytics API written in Python: played with asyncio, messed with SQLAlchemy, hacked deep in asyncpg, rewrote parts in Cython, found better data structures, replaced some pandas with pure numpy.
Most plugin based models load all assemblies into a single shared context. This is a common approach because it has better memory usage and startup performance. The history and rules of assembly loading in .NET is convoluted; its current status makes it difficult (and sometimes impossible) to load multiple different versions of the same assembly into a shared context. Instead of trying to struggle with existing options we decided to build a new tool: Alias.
Daniel is an Agile Software Developer specializing in all forms of mobile development, Native iOS, React-Native, and beyond
Nahla Davies is a software developer and tech writer. Before devoting her work full time to technical writing, she managed—among other intriguing things—to serve as a lead programmer at an Inc. 5,000 experiential branding organization whose clients include Samsung, Time Warner, Netflix, and Sony.
Jay V is one of the founders of Serverless Stack (SST), an open-source framework that makes it easy to build serverless apps. He spends his time trying to…
Is your organization's local development environment plagued with issues? Read on how you can use Sentry to monitor it and help you solve issues quickly.
In today’s modern web stack it’s anything but. Full stack developers are expected to write JavaScript executing in the browser, interop with multiple database technologies, and deploy server side code on different server architectures (e.g. serverless). Without the right tools, understanding how a user interaction in the browser cascades into a 500 server error deep in your server stack is nigh-impossible. Enter: distributed tracing.
Adding Instrumentation to Jest Here at Sentry, we like to dogfood our product as much as possible. Sometimes, it results in unusual applications of our product…
A Content Security Policy (CSP) lets a browser know which content sources are to be trusted — and which aren’t. Learn how to update your CSP and protect your application.
Recently, Sentry converted 100% of its frontend React codebase from JavaScript to TypeScript. This year-long effort spanned over a dozen members of the engineering team, 1,100 files, and 95,000 lines of code.
Like many companies, Sentry uses feature flags to determine when certain users see certain features. Recently, we decided to switch our feature flag software…
One of Sentry’s most-trafficked pages is our issue details page, as it helps our customers understand the root cause of an error. For those of you who are new…
