A Gura parser implementation for Python

Related tags

Deep Learninggura-python-parser
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

null 157 Dec 26, 2022
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

Yasunori Shimura 7 Oct 31, 2022
python-timbl, originally developed by Sander Canisius, is a Python extension module wrapping the full TiMBL C++ programming interface. With this module, all functionality exposed through the C++ interface is also available to Python scripts. Being able to access the API from Python greatly facilitates prototyping TiMBL-based applications.

README: python-timbl Authors: Sander Canisius, Maarten van Gompel Contact: [email protected] Web site: https://github.com/proycon/python-timbl/ pytho

Maarten van Gompel 16 Jan 16, 2022
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

Patrick Varilly 28 Nov 25, 2022
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

Mika 251 Dec 8, 2022
🌳 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

Gustavo Rosa 30 Jan 4, 2023
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

Dan Gale 26 Nov 12, 2021
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

fernando 6.5k Jan 2, 2023
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.

Enoch Kan 35 Sep 11, 2022
Releases(1.4.4)
Owner
Gura Config Lang
Gura configuration language by JWare
Gura Config Lang
GitHub Repository https://pypi.org/project/gura/
[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding

[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding Official Pytorch implementation of Negative Sample Matter

Multimedia Computing Group, Nanjing University 69 Dec 26, 2022
CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network)

CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network) This is PneumoniaDiagnose, an artificially intellig

Azhaan 2 Jan 03, 2022
BTC-Generator - BTC Generator With Python

Что такое BTC-Generator? Это генератор чеков всеми любимого @BTC_BANKER_BOT Для

DoomGod 3 Aug 24, 2022
CityLearn Challenge Multi-Agent Reinforcement Learning for Intelligent Energy Management, 2020, PikaPika team

Citylearn Challenge This is the PyTorch implementation for PikaPika team, CityLearn Challenge Multi-Agent Reinforcement Learning for Intelligent Energ

bigAIdream projects 10 Oct 10, 2022
Neural Message Passing for Computer Vision

Neural Message Passing for Quantum Chemistry Implementation of different models of Neural Networks on graphs as explained in the article proposed by G

Pau Riba 310 Nov 07, 2022
Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad to your characters in Modo.

Applicator Kit for Modo Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad with a TrueDepth camera to

Andrew Buttigieg 3 Aug 24, 2021
World Models with TensorFlow 2

World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand

Zac Wellmer 234 Nov 30, 2022
Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability an

Liang HUANG 87 Dec 28, 2022
PyTorch implementation of neural style randomization for data augmentation

README Augment training images for deep neural networks by randomizing their visual style, as described in our paper: https://arxiv.org/abs/1809.05375

84 Nov 23, 2022
Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception, IROS 2021

For academic use only. Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception Ziwei Wang, Liyuan Pan, Yonhon Ng, Zheyu Zhuang and Robert Mahony Th

Ziwei Wang 11 Jan 04, 2023
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".

AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast

Ye Yuan 161 Dec 23, 2022
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization

Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp

Sheng Yang 10 Dec 05, 2022
A generator of point clouds dataset for PyPipes.

CloudPipesGenerator Documentation | Colab Notebooks | Video Tutorials | Master Degree website A generator of point clouds dataset for PyPipes. TODO Us

1 Jan 13, 2022
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

TU Delft 43 Dec 07, 2022
Code for Active Learning at The ImageNet Scale.

Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.

Zeyad Emam 47 Dec 12, 2022
"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".

NAS-Bench-301 This repository containts code for the paper: "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search". The

AutoML-Freiburg-Hannover 57 Nov 30, 2022
App customer segmentation cohort rfm clustering

CUSTOMER SEGMENTATION COHORT RFM CLUSTERING TỔNG QUAN VỀ HỆ THỐNG DỮ LIỆU Nên chuyển qua theme màu dark thì sẽ nhìn đẹp hơn https://customer-segmentat

hieulmsc 3 Dec 18, 2021
Answering Open-Domain Questions of Varying Reasoning Steps from Text

This repository contains the authors' implementation of the Iterative Retriever, Reader, and Reranker (IRRR) model in the EMNLP 2021 paper "Answering Open-Domain Questions of Varying Reasoning Steps

26 Dec 22, 2022
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

Rishit Dagli 32 Feb 21, 2022
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery (ICCV 2021)

Change is Everywhere Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery by Zhuo Zheng, Ailong Ma, Liangpei Zhang and Yanfei

Zhuo Zheng 125 Dec 13, 2022