Minio Reviews

Python Reviews

Minio mentions (156)

• A step-by-step guide to building an MLOps pipeline

  The meta-data and model artifacts from experiment tracking can contain large amounts of data, such as the training model files, data files, metrics and logs, visualizations, configuration files, checkpoints, etc. In cases where the experiment tool doesn't support data storage, an alternative option is to track the training and validation data versions per experiment. They use remote data storage systems such as S3... - Source: dev.to / 22 days ago

• S3 Is Showing Its Age

  > When it gets too out of hand, people will paper it over with a new, simpler abstraction layer, and the process starts again, only with a layer of garbage spaghetti underneath. I'm pretty happy that there are S3 compatible stores that you can host yourself, that aren't insanely complex. MinIO: https://min.io/ SeaweedFS: https://github.com/seaweedfs/seaweedfs Of course, many will prefer hosted/managed solutions... - Source: Hacker News / about 1 month ago

• deploying a minio service to kubernetes

  Here are the basic steps to getting a minio tenant deployed inot kubernetes. There are some pre-requisites tasks to be deployed (and will not be covered in this article) including. - Source: dev.to / 3 months ago

• Ceph: A Journey to 1 TiB/s

  I'd throw minio [1] in the list there as well for homelab k8s object storage. [1] https://min.io/. - Source: Hacker News / 5 months ago

• Opinions sought: unknown data transfer

  Can you just append the data to a blob using something like the s3 blob api? AWS, Azure and Minio https://min.io/ all support it. That way you don't have to reinvent the wheel. Source: 10 months ago

Python mentions (282)

• Choosing Between AIOHTTP and Requests: A Python HTTP Libraries Comparison

  Import aiohttp Import asyncio Async def fetch(session, url): async with session.get(url) as response: return await response.text() Async def main(): async with aiohttp.ClientSession() as session: html = await fetch(session, 'https://python.org') print(html) Asyncio.run(main()). - Source: dev.to / 16 days ago

• Marking macOS component packages available based on hardware platform type

  Flat packages are the most common used packages, but distribution packages are more robust and can contain multiple flat packages. That's enough detail for this article but if you want to know more Armin Briegel of ScriptingOSX has a great book covering a lot of the details of these package types. I highly recommend picking up a copy for reference. One of the benefits of Distribution packages is that you can... - Source: dev.to / about 2 months ago

• Python String Formatting: A Comprehensive Guide to F-strings

  F-strings, introduced in Python 3.6 and later versions, provide a concise and readable way to embed expressions inside string literals. They are created by prefixing a string with the letter ‘f’ or ‘F’. Unlike traditional formatting methods like %-formatting or str.format(), F-strings offer a more straightforward and Pythonic syntax. - Source: dev.to / 4 months ago

• Don’t Block entire Python Thread: Use Asynchronous Programming Instead

  Import aiohttp, asyncio Async def fetch_data(i, url): print('Starting', i, url) async with aiohttp.ClientSession() as session: async with session.get(url): print('Finished', i, url) Async def main(): urls = ["https://dev.to", "https://medium.com", "https://python.org"] async_tasks = [fetch_data(i+1, url) for i, url in enumerate(urls)] await... - Source: dev.to / 6 months ago

• A Comprehensive Guide to Python Threading: Advanced Concepts and Best Practices

  Threading involves the execution of multiple threads (smaller units of a process) concurrently, enabling better resource utilization and improved responsiveness. Python‘s threading module facilitates the creation, synchronization, and communication between threads, offering a robust foundation for building concurrent applications. - Source: dev.to / 6 months ago