Amazon S3 (Amazon Simple Storage Service) is the storage platform by Amazon Web Services (AWS) that provides an object storage with high availability, low latency and high durability. S3 can store any type of object and can serve as storage for internet applications, backups, disaster recovery, data archives, big data sets and multimedia.
Based on our record, Amazon S3 seems to be a lot more popular than PyPy. While we know about 198 links to Amazon S3, we've tracked only 8 mentions of PyPy. 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.
Takeaway: S3 is feature-rich and great for complex workflows. Cloud Storage is simpler and faster for global access. Explore S3 documentation. - Source: dev.to / 5 days ago
To address this, the team introduced a conditional frontend build mechanism. Using git diff with the three-dot notation, it detects whether a PR includes frontend changes compared to the main branch. If no changes are detected, the frontend build step is skipped, reusing a prebuilt version stored in AWS S3 and served via an internal Content Delivery Network (CDN). - Source: dev.to / 28 days ago
In this article, we present an architecture that demonstrates how to collect application logs from Amazon Elastic Kubernetes Service (Amazon EKS) via Vector, store them in Amazon Simple Storage Service (Amazon S3) for long-term retention, and finally query these logs using AWS Glue and Amazon Athena. - Source: dev.to / about 1 month ago
Iceberg has quietly become the foundation of the modern data lakehouse. More and more engineering teams are adopting it to store and manage analytical data in cloud storage — like Amazon S3, Google Cloud Storage, or Azure Data Lake Storage — while freeing themselves from the limitations of closed systems. - Source: dev.to / about 2 months ago
AWS Lambda is perfect for applications that process images due to its integration with AWS S3, an object storage service. A good example is an e-commerce application that renders images in different sizes. Here are the top features:. - Source: dev.to / 2 months ago
Gains than using either compiler alone. This uses the PyPy JIT framework to speed up a RISC-V simulator. https://pypy.org/ https://github.com/pydrofoil/pydrofoil Pydrofoil: A fast RISC-V emulator generated from the Sail model, using PyPy's JIT. - Source: Hacker News / about 1 month ago
"On average, PyPy is 4.4 times faster than CPython 3.7." https://pypy.org/. - Source: Hacker News / 6 months ago
If you're going the pure Python route, don't forget to try PyPy[1], an alternative JITed implementation of the language. A seriously underrated project, IMHO. Most time it speeds up execution by a factor of 2x-4x, but improvements of about two orders of magnitude are not unheard of. See for example [2]. Numeric, long-running code shoud suit PyPy optimizations well. [1] https://pypy.org/ [2]... - Source: Hacker News / 7 months ago
Python: My Python-foo is limited, so I only ported the last problem (a simple while loop) and ran it with PyPy. It takes a bit less of time:. - Source: dev.to / about 1 year ago
If you r looking for performance with almost fully supported C Extensions , pypy.org for you , 20x faster than cpython still. Source: about 2 years ago
Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.
PyInstaller - PyInstaller is a program that freezes (packages) Python programs into stand-alone executables...
Wasabi Cloud Object Storage - Storage made simple. Faster than Amazon's S3. Less expensive than Glacier.
cx_Freeze - cx_Freeze is a set of scripts and modules for freezing Python scripts into executables in much the...
AWS Lambda - Automatic, event-driven compute service
Numba - Numba gives you the power to speed up your applications with high performance functions written...