PySimpleGUI
mljar-supervised
PySimpleGUI | mljar-supervised | |
---|---|---|
49 | 51 | |
13,133 | 2,936 | |
- | 0.8% | |
8.6 | 8.5 | |
6 days ago | 19 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PySimpleGUI
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Shoes makes building little graphical programs for Mac, Windows, Linux simple
Just a heads up: PySimpleGUI 5 isn't open source any more [0], and the official GitHub repo was replaced with a stub [1]. From the blog post, it sounds like the people behind it will probably remove the FOSS version from PyPI soon.
It's possible the community will fork it with a version of PySimpleGUI 4 that's still kicking around, but I haven't seen one yet.
[0] https://news.ycombinator.com/item?id=39369353
[1] https://github.com/PySimpleGUI/PySimpleGUI
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PySimpleGUI 4 will be sunsetted in Q2 2024
Their old CONTRIBUTING file <https://github.com/PySimpleGUI/PySimpleGUI/blob/1fa911cafee6...> said:
> Pull requests are not being accepted for the project. This includes sending code changes via other means than "pull requests". Plainly put, code you send will not be used.
> I don't mean to be ugly. This isn't personal. Heck, I don't know "you",the reader personally. It's not about ego. It's complicated. The result is that it allows me to dedicate my life to this project. It's what's required, for whatever reason, for me to do this. That's the best explanation I have. I love and respect the users of this work.
It's obvious in hindsight that those reasons were a bald-faced lie, and the real reason was exactly that he could legally do this rug pull.
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PysimpleGUI
From https://github.com/PySimpleGUI/PySimpleGUI/issues/142
> 2023 is going to be the "Make or Break" year. I ultimately need to determine if the project is going to continue. To date, it's nowhere near sustainable. The income doesn't cover the cost of the project, meaning that it's not only unable to allow me to pay for my cost of living, but I continue to rack up debt, borrowing money, to keep the project functional.
> This isn't new information if you've followed the over 1,200 announcements I've made since Sept 2018. The data is available should you wish to look at the GitHub Sponsorships and do the simple math required to calculate income from Udemy. It would be great for the project to keep going. I'm hopeful, but more than hope's required to keep the project going.
So if you like this project and want to see it around in the future, please support it.
Github sponsors is probably the best place: https://github.com/sponsors/PySimpleGUI
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Advice on best way to build the following windows application?
The psutil package makes getting a list of running programs not very difficult. There's an example demo program that polls once a second and displays the top process using CPU time. You could use it as a starting point perhaps.
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NiceGUI – easy-to-use, Python-based UI framework
How does it compare with remi? https://github.com/rawpython/remi
Looking at the examples, for quick UIs, REMI seems simpler. And PySimpleGUI (https://github.com/PySimpleGUI/PySimpleGUI) offers REMI as a backend to deploy on web too (PySimpleGUI is pretty simple to learn).
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I made a simple random password generator
Random Password Generator (what an orginal name!) or RPG for short is a simple password generator that uses PySimpleGUI GUI framework, in order to have a user-friendly interface and also because i wanted to have fun.
- How to make progress bar work using PySimpleGUI?
- When to switch languages for a project
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PySimpleGUI: How to use slider to change variable and plot with matplotlib?
Another approach when the data is easy to graph is to use the Graph Element to create a graph. A Demo Program shows how to make something like this.
mljar-supervised
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Show HN: Web App with GUI for AutoML on Tabular Data
Web App is using two open-source packages that I've created:
- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised
- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury
You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.
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Fairness in machine learning
It's an Automated Machine Learning python package. It's open-source, you can see how it works on GitHub: https://github.com/mljar/mljar-supervised
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[P] Build data web apps in Jupyter Notebook with Python only
Sure, at the bottom of our website you can subscribe for newsletter.
- Show HN: AutoML Python Package for Tabular Data with Automatic Documentation
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library / framework to test multiple sklearn regression models at once
If you need a simple and fast solution, go with auto-sklearn Maybe a bit more complex, but very powerful was mljar-supervised
- Python AutoML on Tabular Data with FeatureEng, HP Tuning, Explanations, AutoDoc
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Data Science and full-stack-web development
In my case, I had experience in DS and software engineering. It gives me ability to start a company that works on Data Science tools.
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Learning Python tricks by reading other people's code. But who?
MLJAR AutoML is a Python package for Automated Machine Learning on tabular data with feature engineering, explanations, and automatic documentation.
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'start with a simple model'
I recommend trying my AutoML package. You can easily check many different algorithms. Waht is more, the baseline algorithms are checked (major class predictor for classification and mean predictor for regression). The advance of AutoML is that it is really quick. You dont need to write preprocessing code, just call fit method.
What are some alternatives?
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
optuna - A hyperparameter optimization framework
CustomTkinter - A modern and customizable python UI-library based on Tkinter
autokeras - AutoML library for deep learning
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
EasyGUI - easygui for Python
PySR - High-Performance Symbolic Regression in Python and Julia
wxPython
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
pywebview - Build GUI for your Python program with JavaScript, HTML, and CSS
mljar-examples - Examples how MLJAR can be used