HyperDict - Self linked dictionary in Python

Overview

Hyper Dictionary

Advanced python dictionary(hash-table), which can link it-self keys and make calculations into the keys of the dict

Installation

Use the package manager pip to install foobar.

pip install HyperDict

Usage

The syntax of expressions:

{'key' : '...$(expression)$...'}

Initialization:

from HyperDict import HyperDict
from json import dumps
dictionary = HyperDict({}) # {} - your dict

Examples:

example = Hyperdict(
    {
        'a': 5,
        'b': '$(a)$'
    }
)

print(dumps(example))

    {
       'a': 5,
       'b': 5
    }
example = Hyperdict(
    {
        'a': 5,
        'b': '$(a + x)$ ' # here with a space
    }
)

print(dumps(example))

    {
       'a': 5,
       'b': '5 '
    }
example = Hyperdict(
    {
        'a': 5,
        'b': 100,
        'c': '$(b + d)$',
        'd': '$(b + a)$'
    }
)

print(dumps(example))

    {
        'a': 5,
        'b': 100,
        'c': 205,
        'd': 105
    }
example = Hyperdict(
    {
        'a': ['one_item'],
        'b': '$(a + ["another_item"])$'
    }
)

print(dumps(example))

    {
        'a': ['one_item'],
        'b': ['one_item', 'another_item']
    }
some_func = lambda arg: arg + 1

example = Hyperdict(
    {
        'a': 5,
        'b': '$(some_func(a))$'
    }
)

print(dumps(example))

    {
       'a': 5,
       'b': 5
    }

Changing:

example = Hyperdict(
    {
        'a': 5,
        'b': '$(a)$'
    }
)
print(example) 
# >>> {'a': 5, 'b': 5}
example['a'] = 'another_val'
print(example)
# >>> {'a': 'another_val', 'b': 'another_val'}
example['a'] = '4'
print(example) 
# >>> {'a': 'another_val', 'b': 4}

# !!! 'b' links 'a', but 'a' doesn't link 'b'

Warning

# Keys of your dict must be only strings
{5: 'abc', True: []} # is prohibited
{'5': 'abc', 'True': []} # is allowed

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

Nicholas Lee 3 Jan 09, 2022
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces

JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c

OMRON SINIC X 24 Dec 28, 2022
A CV toolkit for my papers.

PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to

Hang Zhang 2k Jan 04, 2023
Official source code of Fast Point Transformer, CVPR 2022

Fast Point Transformer Project Page | Paper This repository contains the official source code and data for our paper: Fast Point Transformer Chunghyun

182 Dec 23, 2022
QuadTree Attention for Vision Transformers (ICLR2022)

This repository contains codes for quadtree attention. This repo contains codes for feature matching, image classficiation, object detection and seman

tangshitao 222 Dec 28, 2022
Repository relating to the CVPR21 paper TimeLens: Event-based Video Frame Interpolation

TimeLens: Event-based Video Frame Interpolation This repository is about the High Speed Event and RGB (HS-ERGB) dataset, used in the 2021 CVPR paper T

Robotics and Perception Group 544 Dec 19, 2022
[ICCV 2021] Learning A Single Network for Scale-Arbitrary Super-Resolution

ArbSR Pytorch implementation of "Learning A Single Network for Scale-Arbitrary Super-Resolution", ICCV 2021 [Project] [arXiv] Highlights A plug-in mod

Longguang Wang 229 Dec 30, 2022
Object Detection with YOLOv3

Object Detection with YOLOv3 Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Python 3.8 OpenCV Numpy Documentation Yolo ile ilgili detaylı b

Ayşe Konuş 0 Mar 27, 2022
Catalyst.Detection

Accelerated DL R&D PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentatio

Catalyst-Team 12 Oct 25, 2021
Learning Spatio-Temporal Transformer for Visual Tracking

STARK The official implementation of the paper Learning Spatio-Temporal Transformer for Visual Tracking Hiring research interns for visual transformer

Multimedia Research 484 Dec 29, 2022
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"

DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct

TensorLayer Community 159 Nov 22, 2022
Source code for paper: Knowledge Inheritance for Pre-trained Language Models

Knowledge-Inheritance Source code paper: Knowledge Inheritance for Pre-trained Language Models (preprint). The trained model parameters (in Fairseq fo

THUNLP 31 Nov 19, 2022
The final project of "Applying AI to 2D Medical Imaging Data" of "AI for Healthcare" nanodegree - Udacity.

Pneumonia Detection from X-Rays Project Overview In this project, you will apply the skills that you have acquired in this 2D medical imaging course t

Omar Laham 1 Jan 14, 2022
Beyond imagenet attack (accepted by ICLR 2022) towards crafting adversarial examples for black-box domains.

Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet

Alibaba-AAIG 37 Nov 23, 2022
CVPR 2021 - Official code repository for the paper: On Self-Contact and Human Pose.

TUCH This repo is part of our project: On Self-Contact and Human Pose. [Project Page] [Paper] [MPI Project Page] License Software Copyright License fo

Lea Müller 45 Jan 07, 2023
Depression Asisstant GDSC Challenge Solution

Depression Asisstant can help you give solution. Please using Python version 3.9.5 for contribute.

Ananda Rauf 1 Jan 30, 2022
Kaggle: Cell Instance Segmentation

Kaggle: Cell Instance Segmentation The goal of this challenge is to detect cells in microscope images. with simple view on how many cels have been ann

Jirka Borovec 9 Aug 12, 2022
CMSC320 - Introduction to Data Science - Fall 2021

CMSC320 - Introduction to Data Science - Fall 2021 Instructors: Elias Jonatan Gonzalez and José Manuel Calderón Trilla Lectures: MW 3:30-4:45 & 5:00-6

Introduction to Data Science 6 Sep 12, 2022
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag

Hyeonwoo Kang 2.4k Jan 04, 2023
Quantify the difference between two arbitrary curves in space

similaritymeasures Quantify the difference between two arbitrary curves Curves in this case are: discretized by inidviudal data points ordered from a

Charles Jekel 175 Jan 08, 2023