minio-py VS Konva

Python

Alternatively you could look into presigned urls which can also be done in python.

The program is running a SQL query against a remote file. This example in MinIO docs demonstrates reading from the response stream. So far, so good.

>So far your instinct as product designer/manager/engineer might be to take what customers say they want at face value.

That would be the worst way to go about building anything. Taking solutions from customers as opposed to problems to identify jobs-to-be-done and reasons for non consumption isn't something someone who knows how to build products does.

The question then becomes how does someone who generally knows how to build the right things build the bare minimum feature, the original question and title of the post, given the constraints on time and resources cited in the first paragraphs.

One can do several things. For example, writing the description and code examples for a yet to be library and shop it around, see if it makes sense, then write the library.

That's what I did for example with this library: https://pypi.org/project/bmc after shopping it around here: https://github.com/minio/minio-py/issues/829#issuecomment-65...

I also do that for internal tools, libraries, SDKs. I'll send client code around and see if it makes sense to engineers. I also had non engineers who never coded use libraries to do something useful. I just give them a laptop and docs and see how they use the thing. If they can do it, I know programmers can.

To get back to the original problem, prioritizing can lead towards minimal features. We have a section called "Instances" in our issue templates. If a feature issue does not have several instances where the problem manifested for several people, we just won't do it. We need concrete examples of a problem being frequent and expensive / high impact (loss of work, or prevents work in the first place).

For example, I'll look at the analytics for our internal platform and see that my colleague who we built the thing for is not using it. Why, we ask. It turns out the Docker images are too large and take a lot of time. He loses patience. They contain several libraries that he does need.

We built a minimal image that can get him to start after 30 seconds instead of 2 minutes, and we saw usage increase.

Yesterday, I saw he was giving a demo using his local environement, not the product. I'll ask why. What's wrong. What sucks. Why did he use his laptop instead of the platform.

The general sentiment of the article is sound. Always observe, ask questions, look for the underlying problems and how frequently they happen, how expensive they are (as in what are they doing to solve that, is there someone working on it, does it cost opportunities, etc)

I used to write libraries and have non-technical people who never programmed follow the documentation and use them. My reference point is that if they could do it, then programmers will have no trouble doing it.

The next best thing is writing the doc before the actual code, and have others look at it and see if it makes sense, then I'd write the code that makes that possible.[0]

- [0]: https://github.com/minio/minio-py/issues/829#issuecomment-65...

Yes. A case of it working well: https://github.com/minio/minio-py/issues/829

I found this issue for a problem I had with MinIO. I wrote a prototype: docs first and screencast on how the API would be. I then asked the other user if they had implemented it and if the API I was thinking about would suit them as it suited me. MinIO's CTO replied that it was the correct usage, but that it was not on the roadmap, which is understandable.

I then started implementing the actual commands I needed first (host, ls, etc). Some time later, someone tweeted at us and asked how they could use the library. I then put it on PyPI (Python Package Index). I checked upon that person recently and they told be they've been using it for months without a problem. The other person also had commented and said they've been using it.

https://pypistats.org/packages/bmc

It's a really, really, small library for a niche need, also asked people for feedback here: https://news.ycombinator.com/item?id=26540342

Now I'm getting feature requests on that issue, but I'll soon do it properly in a repo to make it easier for people.

Thank you for these points. I agree. It's one of those tools that, if you have that problem, you know exactly why you need it.

This solves this issue: https://github.com/minio/minio-py/issues/829. MinIO is an S3 compatible object storage software. https://min.io/

Thanks again.

We use it in anger at Splitgraph [0] to let people upload/download datasets and Postgres table snapshots (instead of storing them directly in S3).

Pros:

* Less platform-dependent. By self-managing it, we can also run deploys to GCP / Azure / Scaleway / other providers without writing a separate adapter for e.g. Azure Blob Storage.

* Python API [1] much more pleasant to use than boto3 (and can speak to normal S3). It doesn't do everything that boto3 does, but it supports everything we need (e.g. pre-signed URLs).

* minio server itself supports a large chunk of S3's functionality (e.g. SELECT API / AssumeRole / bucket versioning)

* Don't pay per request and for egress: this was a big deal since people might want to download large amounts of data from us (or make a bunch of small requests to download/upload a subset of data).

Cons:

* Have to manage own infrastructure. We run it on managed VMs so it's semi-managed, but we still have to provision block storage, set up backup policies etc.

* In a similar vein, scaling and availability all have to be DIY [2]. We haven't run into situations yet where Minio would be the bottleneck, but it might be something to keep in mind.

* Obviously not as seamless: you don't get things like Glacier or integration with other IAM.

[0] https://www.splitgraph.com/

[1] https://github.com/minio/minio-py

[2] https://docs.min.io/docs/distributed-minio-quickstart-guide....

Based on this, I found that some of the libraries are dead and no longer have any support. Only two libraries are still alive and have significant amount of stars on GitHub and downloads on NPM. They are Fabric.js and Konva.js.

I have been assigned a task to create a sort of a canva clone which will have almost same features as canva with authentication, access control and rating system(not in this phase). I need help in finding libraries similar to https://konvajs.org/ which has updated docs and great support for Nextjs.

I'm currently using konva (& react-konva) package, to utilize it in Node.js enviroment I also need canvas package installed in. However, when running the code encountering this error:

used goJS in one project and konva in another

All the UI part would make sense to do in React. The actual drawing board you likely would need to implement in canvas or SVG. It still could be a React component, but for actual drawing, you'd probably use something like Konva (https://konvajs.org/).

Konvajs - is an HTML5 Canvas JavaScript framework that enables high performance animations, transitions, node nesting, layering, filtering, caching, event handling for desktop and mobile applications, and much more.

During the development of a complex interactive UI for the configuration of a digital laboratory ecosystem, we were utilizing the Konva.js library. Konva is a wrapper around the HTML canvas that simplifies working with shapes and interacting with the canvas a lot. Everybody dealing with the plain canvas API knows how much code certain tasks require, especially when user interaction with the drawn shapes is required. The most important features Konva offers to me are

Konva.js - example

Have a go at petswitch.com if you wish... I made the original Petswitch almost ten years ago, and it's had mild success since then, including CNET writing an article about it and it receiving the prestigious honour of 'most useless website' in week 41 of 2018, as determined by theuselesswebindex.com. Aside from the obvious question of why I even made this, it was getting pretty creaky – I originally built it with PHP and ImageMagick, with the facial features being manually selected via jQuery UI. So I decided to rebuild the whole thing with a full face-to-pet ML pipeline, on static hosting. To get the human face features, the app renders the upload to a temporary img element. This is a handy way to orient the image correctly via the browser, and saves having to deal with EXIF data. It's then resized, rendered to a canvas element, converted to a base64 string, then sent via fetch to Google's Cloud Vision API, which returns landmark coordinates of the face. I use these coordinates to correct any tilt on the face, mask the eyes and mouth via a mask image, then store each masked element as an additional canvas. Detecting pet faces was trickier. Google, Amazon and Microsoft all offer object detection APIs via transfer learning, and the approach is largely the same: you supply a series of images with bounding boxes around the objects you want to detect, either added via a web interface or uploaded via their API. You train a model online from these supplied images, then the service will return the estimated coordinates of any detected objects in an uploaded image. I found a dataset of both cats and dogs that had been labelled with landmarks on their faces, then wrote a script to convert the landmarks into bounding boxes around their eyes and nose, the dimensions based on a simple formula around the distance between the eyes in each image. All in all it's been trained on about 17,000 images of cats and dogs, and the accuracy seems to be pretty good. I was pleased to discover it actually works pretty well on other pets too. I've also added some friendly pets to the Petswitch family for those that don't have a pet on hand. I decided not to use a framework for this, it's written from scratch using a series of ES6 modules – although I did use Konva to handle the manual selection of facial features if the API can't detect a face. I used ParcelJS as my task runner, and my detection APIs are hosted on Firebase Cloud Functions. Let me know if you have any questions, although I can offer no good explanation for why I created this monstrosity...