PyQt6 configuration in yaml format providing the most simple script.

Related tags

Deep Learningyamlpyqt5pyqt6
Overview

PyamlQt（ぴゃむるきゅーと）

PyPI version

PyQt6 configuration in yaml format providing the most simple script.

Requirements

  • yaml
  • PyQt6, ( PyQt5 )

Installation

pip install PyamlQt

Demo

python3 examples/chaos.py

Template

See examples/simple_gui.py.

import sys
import os

from pyamlqt.create_widgets import create_widgets
import pyamlqt.qt6_switch as qt6_switch

qt6_mode = qt6_switch.qt6

if qt6_mode:
    from PyQt6.QtWidgets import QApplication, QMainWindow
else:
    from PyQt5.QtWidgets import QApplication, QMainWindow

YAML = os.path.join(os.path.dirname(__file__), "../yaml/chaos.yaml")

class MainWindow(QMainWindow):
    def __init__(self):
        self.number = 0
        super().__init__()

        # geometry setting ---
        self.setWindowTitle("Simple GUI")
        self.setGeometry(0, 0, 800, 720)
        
        # Template ==========================================
        self.widgets, self.stylesheet = self.create_all_widgets(YAML)
        for key in self.widgets.keys():
            self.widgets[key].setStyleSheet(self.stylesheet[key])
        # ==============================================

        # --- Your code ----
        # -*-*-*-*-*-*-*-*-*
        # -----------------
        
        self.show()

    # Template ==========================================
    def create_all_widgets(self, yaml_path: str) -> dict:
        import yaml
        widgets, stylesheet_str = dict(), dict()
        with open(yaml_path, 'r') as f:
            self.yaml_data = yaml.load(f, Loader=yaml.FullLoader)
        
            for key in self.yaml_data:
                data = create_widgets.create(self, yaml_path, key, os.path.abspath(os.path.dirname(__file__)) + "/../")
                widgets[key], stylesheet_str[key] = data[0], data[1]

        return widgets, stylesheet_str
    # ==============================================

if __name__ == '__main__':
    app = QApplication(sys.argv)
    window = MainWindow()
    # sys.exit(app.exec_())
    sys.exit(app.exec())

Elements (dev)

In yaml, you can add the following elements defined in PyQt.Widgets This may be added in the future.

  • pushbutton : definition of QPushButton
  • qlabel : definition of QLabel
  • qlcdnumber : definition of QLCDNumber
  • qprogressbar : definition of QProgressBar
  • qlineedit : definition of QLineEdit
  • qcheckbox : definition of QCheckbox
  • qslider : definition of QSlider
  • qspinbox : definition of QSpinBox
  • qcombobox : definition of QCombobox
  • image : definition of QLabel (using image path)
  • stylesheet : definition of Stylesheet (define as QLabel and setHidden=True)

YAML format

PyamlQt defines common elements for simplicity. Not all values need to be defined, but if not set, default values will be applied

key: # key name (Required for your scripts)
  type: slider # QWidgets
  x_center: 500 # x center point
  y_center: 550 # y center point
  width: 200 # QWidgets width
  height: 50 # QWidgets height
  max: 100 # QObject max value
  min: 0 # QObject min value
  default: 70 # QObject set default value
  text: "Slider" # Text
  font_size: 30 # Text size [px]
  font_color: "#ff0000" # Text color
  font: "Ubuntu" # Text font
  font_bold: false # bold-text option
  items: # Selectable items( Combobox's option )
    - a
    - b
    - c

PyQt5 Mode

If you want to use PyQt5, you have to change the qt6_switch.py file.

  • Open the file and change the qt6_mode variable to False.
  • pip3 install PyQt5
  • pip3 install -v -e .
You might also like...
Hi Guys, here I am providing examples, which will help you in Lerarning Python

LearningPython Hi guys, here I am trying to include as many practice examples of Python Language, as i Myself learn, and hope these will help you in t

null 4 Feb 3, 2022
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.

NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine

null 419 Jan 3, 2023
phylotorch-bito is a package providing an interface to BITO for phylotorch

phylotorch-bito phylotorch-bito is a package providing an interface to BITO for phylotorch Dependencies phylotorch BITO Installation Get the source co

Mathieu Fourment 2 Sep 1, 2022
arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.
arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.

arxiv-sanity, but very lite, simply providing the core value proposition of the ability to tag arxiv papers of interest and have the program recommend similar papers.

Andrej 671 Dec 31, 2022
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

ManimML ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

null 259 Jan 4, 2023
Sequential Model-based Algorithm Configuration

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

AutoML-Freiburg-Hannover 778 Jan 5, 2023
My personal Home Assistant configuration.

About This is my personal Home Assistant configuration. My guiding princile is to have full local control of all my devices. I intend everything to ru

Chris Turra 13 Jun 7, 2022
Interactive Terraform visualization. State and configuration explorer.
Interactive Terraform visualization. State and configuration explorer.

Rover - Terraform Visualizer Rover is a Terraform visualizer. In order to do this, Rover: generates a plan file and parses the configuration in the ro

Tu Nguyen 2.3k Jan 7, 2023
Gin provides a lightweight configuration framework for Python

Gin Config Authors: Dan Holtmann-Rice, Sergio Guadarrama, Nathan Silberman Contributors: Oscar Ramirez, Marek Fiser Gin provides a lightweight configu

Google 1.7k Jan 3, 2023
Releases(v0.3.0)

  • v0.3.0(Apr 28, 2022)

    Japanese

    PyamlQtはGUIデザイン初心者のためのGUI定義フォーマットです。コントリビューション大歓迎です！

    しばらくはAPIの破壊的変更が行われる可能性があります。

    変更点

    • 新しいモジュールPyamlQtWindow
      • 初期化には引数が必要です。（README.mdを読んでください）
      • デモプログラムがとてもシンプルになりました。

    English

    PyamlQt is a GUI definition format for GUI design beginners. Contributions are welcome!

    There is a possibility of destructive changes to the API for the time being.

    Changes

    • New module PyamlQtWindow.
      • Arguments are required for initialization. (Please read README.md)
      • The demo program is now very simple.
    import sys
import os

from pyamlqt.mainwindow import PyamlQtWindow
from PyQt6.QtWidgets import QApplication

YAML = os.path.join(os.path.dirname(__file__), ". /yaml/chaos.yaml")

class MainWindow(PyamlQtWindow):
    def __init__(self):
        self.number = 0
        super(). __init__("title", 0, 0, 800, 720, YAML)
        self.show()

if __name__ == '__main__':
    app = QApplication(sys.argv)
    window = MainWindow()
    sys.exit(app.exec())
    Source code(tar.gz)
    Source code(zip)

  • v0.2.0(Apr 13, 2022)

    Japanese

    PyamlQtはGUIデザイン初心者のためのGUI定義フォーマットです。コントリビューション大歓迎です！

    しばらくはAPIの破壊的変更が行われる可能性があります。

    変更点

    • rect要素とstyle要素を追加し、stylesheetの仕様が大きく変更されました。
    • 複数のyamlからのロードをサポートします。パスは絶対パスを指定するか、GitHubなどのソースコードへのURL(raw.githubusercontent.com に続くURL)を指定してください。
      • URL指定する場合は~/.cache/pyamlqt/yaml以下にyamlがダウンロードされます。
      • ロード先のyamlファイルで同じファイル名・同じキー名を指定しないでください。再帰的にロードされてメモリを消費し続けます。

    English

    PyamlQt is a GUI definition format for GUI design beginners. Contributions are welcome!

    The API may undergo destructive changes for a while.

    Changes

    • The specification of stylesheet has been significantly changed with the addition of the rect and style elements.
    • Support for loading from multiple yaml files. Paths should be absolute paths or URLs to source code such as GitHub (URLs following raw.githubusercontent.com).
      • If you specify a URL, the yaml will be downloaded under ~/.cache/pyamlqt/yaml.
      • Do not specify the same file name and the same key name in the yaml file to be loaded. They will be loaded recursively and continue to consume memory.
    Source code(tar.gz)
    Source code(zip)
Owner
Ar-Ray
1st grade of National Institute of Technology(=Kosen) student. Associate degree, Hatena Blogger
Ar-Ray
GitHub Repository https://pypi.org/project/PyamlQt
Data and Code for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning"

Introduction Code and data for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning". We cons

Pan Lu 81 Dec 27, 2022
Pretrained Cost Model for Distributed Constraint Optimization Problems

Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline

2 Aug 28, 2022
ExCon: Explanation-driven Supervised Contrastive Learning

ExCon: Explanation-driven Supervised Contrastive Learning Link to the paper: https://arxiv.org/pdf/2111.14271.pdf Contributors of this repo: Zhibo Zha

Zhibo (Darren) Zhang 18 Nov 01, 2022
Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

CCOP Code of our paper Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning Requirement Install OpenSelfSup Install Detectron2

Chenhongyi Yang 21 Dec 13, 2022
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging

Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging This repository contains an implementation

Computational Photography Lab @ SFU 1.1k Jan 02, 2023
Reimplementation of Learning Mesh-based Simulation With Graph Networks

Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa

Jingwei Xu 33 Dec 14, 2022
An example to implement a new backbone with OpenMMLab framework.

Backbone example on OpenMMLab framework English | 简体中文 Introduction This is an template repo about how to use OpenMMLab framework to develop a new bac

Ma Zerun 22 Dec 29, 2022
Transferable Unrestricted Attacks, which won 1st place in CVPR’21 Security AI Challenger: Unrestricted Adversarial Attacks on ImageNet.

Transferable Unrestricted Adversarial Examples This is the PyTorch implementation of the Arxiv paper: Towards Transferable Unrestricted Adversarial Ex

equation 16 Dec 29, 2022
Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation

NorCal Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation On Model Calibration for Long-Tailed Object Detec

Tai-Yu (Daniel) Pan 24 Dec 25, 2022
SMIS - Semantically Multi-modal Image Synthesis(CVPR 2020)

Semantically Multi-modal Image Synthesis Project page / Paper / Demo Semantically Multi-modal Image Synthesis(CVPR2020). Zhen Zhu, Zhiliang Xu, Anshen

316 Dec 01, 2022
An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"

RASP Setup Mac or Linux Run ./setup.sh . It will create a python3 virtual environment and install the dependencies for RASP. It will also try to insta

141 Jan 03, 2023
Implementation of Kaneko et al.'s MaskCycleGAN-VC model for non-parallel voice conversion.

MaskCycleGAN-VC Unofficial PyTorch implementation of Kaneko et al.'s MaskCycleGAN-VC (2021) for non-parallel voice conversion. MaskCycleGAN-VC is the

86 Dec 25, 2022
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the

Meta Research 1.1k Jan 03, 2023
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

CLIP-GEN [简体中文][English] 本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-F

75 Dec 29, 2022
Neighborhood Reconstructing Autoencoders

Neighborhood Reconstructing Autoencoders The official repository for Neighborhood Reconstructing Autoencoders (Lee, Kwon, and Park, NeurIPS 2021). T

Yonghyeon Lee 24 Dec 14, 2022
Custom implementation of Corrleation Module

Pytorch Correlation module this is a custom C++/Cuda implementation of Correlation module, used e.g. in FlowNetC This tutorial was used as a basis for

Clément Pinard 361 Dec 12, 2022
Building blocks for uncertainty-aware cycle consistency presented at NeurIPS'21.

UncertaintyAwareCycleConsistency This repository provides the building blocks and the API for the work presented in the NeurIPS'21 paper Robustness vi

EML Tübingen 19 Dec 12, 2022
REGTR: End-to-end Point Cloud Correspondences with Transformers

REGTR: End-to-end Point Cloud Correspondences with Transformers This repository contains the source code for REGTR. REGTR utilizes multiple transforme

Zi Jian Yew 108 Dec 17, 2022
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

torch-imle Concise and self-contained PyTorch library implementing the I-MLE gradient estimator proposed in our NeurIPS 2021 paper Implicit MLE: Backp

UCL Natural Language Processing 249 Jan 03, 2023
On Generating Extended Summaries of Long Documents

ExtendedSumm This repository contains the implementation details and datasets used in On Generating Extended Summaries of Long Documents paper at the

Georgetown Information Retrieval Lab 76 Sep 05, 2022