A Gura parser implementation for Python

Overview

Gura Python parser

CI

This repository contains the implementation of a Gura (compliant with version 1.0.0) format parser in Python.

Installation

pip install gura-parser

Usage

import gura

gura_string = """
# This is a Gura document.
title: "Gura Example"

an_object:
    username: "Stephen"
    pass: "Hawking"

# Line breaks are OK when inside arrays
hosts: [
  "alpha",
  "omega"
]
"""

# Loads: transforms a Gura string into a dictionary
parsed_gura = gura.loads(gura_string)
print(parsed_gura)  # {'title': 'Gura Example', 'an_object': {'username': 'Stephen', 'pass': 'Hawking'}, 'hosts': ['alpha', 'omega']}

# Access a specific field
print(f"Title -> {parsed_gura['title']}")

# Iterate over structure
for host in parsed_gura['hosts']:
    print(f'Host -> {host}')

# Dumps: transforms a dictionary into a Gura string
print(gura.dumps(parsed_gura))

Contributing

All kind of contribution is welcome! If you want to contribute just:

  1. Fork this repository.
  2. Create a new branch and introduce there your new changes.
  3. Make a Pull Request!

Or you can join to our community in Discord!

Tests

To run all the tests: python -m unittest. More info in official Unittest docs

Building

  1. Create a virtual environment: python3 -m venv venv
  2. Activate it: source venv/bin/activate
  3. Install some dependencies: pip install -r requirements.txt
  4. Clean and build rm -rf ./dist/* && python3 setup.py sdist

License

This repository is distributed under the terms of the MIT license.

You might also like...
A fast python implementation of Ray Tracing in One Weekend using python and Taichi
A fast python implementation of Ray Tracing in One Weekend using python and Taichi

ray-tracing-one-weekend-taichi A fast python implementation of Ray Tracing in One Weekend using python and Taichi. Taichi is a simple "Domain specific

Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree

This is a Python implementation of cover trees, a data structure for finding nearest neighbors in a general metric space (e.g., a 3D box with periodic

A fast Evolution Strategy implementation in Python

Evostra: Evolution Strategy for Python Evolution Strategy (ES) is an optimization technique based on ideas of adaptation and evolution. You can learn

🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.

OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th

Python implementation of Wu et al (2018)'s registration fusion
Python implementation of Wu et al (2018)'s registration fusion

reg-fusion Projection of a central sulcus probability map using the RF-ANTs approach (right hemisphere shown). This is a Python implementation of Wu e

A Python implementation of global optimization with gaussian processes.
A Python implementation of global optimization with gaussian processes.

Bayesian Optimization Pure Python implementation of bayesian global optimization with gaussian processes. PyPI (pip): $ pip install bayesian-optimizat

Implementation of Kalman Filter in Python
Implementation of Kalman Filter in Python

Kalman Filter in Python This is a basic example of how Kalman filter works in Python. I do plan on refactoring and expanding this repo in the future.

Releases(1.4.4)
Owner
Gura Config Lang
Gura configuration language by JWare
Gura Config Lang
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch

Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t

Phil Wang 40 Dec 22, 2022
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of

VITA 44 Dec 23, 2022
City-seeds - A random generator of cultural characteristics intended to spark ideas and help draw threads

City Seeds This is a random generator of cultural characteristics intended to sp

Aydin O'Leary 2 Mar 12, 2022
An implementation of Deep Graph Infomax (DGI) in PyTorch

DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom

Petar Veličković 491 Jan 03, 2023
MRQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) data.

Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr

Center for Computational Imaging and Personalized Diagnostics 58 Dec 02, 2022
Code for paper 'Hand-Object Contact Consistency Reasoning for Human Grasps Generation' at ICCV 2021

GraspTTA Hand-Object Contact Consistency Reasoning for Human Grasps Generation (ICCV 2021). Project Page with Videos Demo Quick Results Visualization

Hanwen Jiang 47 Dec 09, 2022
This repository contains the implementation of the HealthGen model, a generative model to synthesize realistic EHR time series data with missingness

HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize

0 Jan 20, 2022
Intrinsic Image Harmonization

Intrinsic Image Harmonization [Paper] Zonghui Guo, Haiyong Zheng, Yufeng Jiang, Zhaorui Gu, Bing Zheng Here we provide PyTorch implementation and the

VISION @ OUC 44 Dec 21, 2022
Clustergram - Visualization and diagnostics for cluster analysis in Python

Clustergram Visualization and diagnostics for cluster analysis Clustergram is a diagram proposed by Matthias Schonlau in his paper The clustergram: A

Martin Fleischmann 96 Dec 26, 2022
paper list in the area of reinforcenment learning for recommendation systems

paper list in the area of reinforcenment learning for recommendation systems

HenryZhao 23 Jun 09, 2022
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization

CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

THUDM 28 Dec 09, 2022
Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

SEDE SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their natural language description

Rupert. 83 Nov 11, 2022
[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。

QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具,最短只需一行命令即可将普通的Python脚本打包成EXE可执行程序,并选择性添加CUDA和NoAVX的支持,尽可能兼容更多的用户环境。 感觉还可

QPT Family 545 Dec 28, 2022
Implementation of CVPR'2022:Surface Reconstruction from Point Clouds by Learning Predictive Context Priors

Surface Reconstruction from Point Clouds by Learning Predictive Context Priors (CVPR 2022) Personal Web Pages | Paper | Project Page This repository c

136 Dec 12, 2022
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased

Kaihua Tang 824 Jan 03, 2023
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

XCL 191 Dec 31, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
An easy-to-use app to visualise attentions of various VQA models.

Ask Me Anything: A tool for visualising Visual Question Answering (AMA) An easy-to-use app to visualise attentions of various VQA models. Please click

Apoorve 37 Nov 13, 2022
OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Documentation: https://mmsegmentation.readthedocs.io/ English | 简体中文 Introduction MMSegmentation is an open source semantic segmentation toolbox based

OpenMMLab 5k Dec 31, 2022
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

DOC | Quick Start | 中文 Breaking News !! 🔥 🔥 🔥 OGB-LSC KDD CUP 2021 winners announced!! (2021.06.17) Super excited to announce our PGL team won TWO

1.5k Jan 06, 2023