Based on our record, Dask should be more popular than Raygun. It has been mentiond 16 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Raygun is a cloud-based platform that makes sure your web and mobile applications are free of errors, as well as your users are satisfied. It specializes in JavaScript error monitoring and offers a wide range of features to help you easily detect and fix issues. - Source: dev.to / 5 months ago
We can make the process a little easier by using our agile processes together with a continuous deployment strategy. For example, our friends at Raygun, discovered that “when a team gets locked into a sprint it can become much harder to recognize and fix bugs”. - Source: dev.to / 9 months ago
Regarding your last question, when I mention sub-processors who we don't have an SCC with I'm thinking about vendors like RayGun. It's a system we use to monitor alerts and warnings coming from our app when in the hands of our end-users. We have configured the tool so we get absolutely no personal information - no names, emails, id's or any of that sort. It's nothing more than technical data dumps from the inner... Source: over 1 year ago
Error logging and monitoring are crucial for any application, Appwrite being no exception. We wanted to make it extremely easy to collect and monitor your logs while staying true to our philosophy of being completely platform agnostic. With Appwrite 0.12, we've introduced support for some amazing open source logging providers like Sentry, Raygun and AppSignal! - Source: dev.to / over 2 years ago
We have RayGun for logging/reporting on the client-side of the apps. They are showing nothing interesting from those devices. They seem to fail silently. Source: almost 3 years ago
We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: over 2 years ago
I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: over 2 years ago
Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 2 years ago
To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / over 2 years ago
I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: over 2 years ago
Sentry.io - From error tracking to performance monitoring, developers can see what actually matters, solve quicker, and learn continuously about their applications - from the frontend to the backend.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Rollbar - Rollbar collects errors that happen in your application, notifies you, and analyzes them so you can debug and fix them. Ruby, Python, PHP, Node.js, JavaScript, and Flash libraries available.
NumPy - NumPy is the fundamental package for scientific computing with Python
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.