Words-per-minute - A terminal app written in python utilizing the curses module that tests the user's ability to type

Overview

words-per-minute

A terminal app written in python utilizing the curses module that tests the user's ability to type.

How to Run?

Since this is a terminal app, it must be run from the terminal. For our purposes, we are going to use the windows command prompt. In order to run the program we simply need to open the command prompt inside the directory where the main program code is located and then type in: python wpm.py

Just as it is shown below: alt text

After running the command, the user will be greeted by the following screen:

alt text

How the Program Works

First, the user will be shown a random sentence on the terminal screen. Then the user must type the shown sentence exactly as it is written on the screen. The words per minute counter (WPM on screen) will be continously changing and will depend on the user's accuracy in typing the correct keys and/or the amount of time the user takes to complete typing the entire sentence.

Below is an example sentence, where the correct keystrokes are highlighted as green and the incorrect keystrokes are highlighted as red.

alt text

When the user finishes typiing an entire sentence correctly. Their wpm score will be shown, and the top 5 scores recorded so far will also be shown:

alt text

Notes

  1. The user must have python installed on their computer.

  2. The program currently randomizes 40 different sentences. If the user wishes to add more sentences, they can make up their own, or they can visit the random sentence generator website and add a sentence to a new line in the test.txt file.

  3. If the user wishes to wipe the current top 5 score, they need to simply go in the high_score.txt file, erase all of its contents and simply save the empty file.

Owner
Tanim Islam
I am a Computer Engineering major at City College of New York, and the main plan is to do something revolutionary for the tech industry.
Tanim Islam
source code for paper: WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach.

WhiteningBERT Source code and data for paper WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach. Preparation git clone https://github.com

49 Dec 17, 2022
Train and use generative text models in a few lines of code.

blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa

Dan Carroll 16 Nov 07, 2022
Script to download some free japanese lessons in portuguse from NHK

Nihongo_nhk This is a script to download some free japanese lessons in portuguese from NHK. It can be executed by installing the packages with: pip in

Matheus Alves 2 Jan 06, 2022
Creating a Feed of MISP Events from ThreatFox (by abuse.ch)

ThreatFox2Misp Creating a Feed of MISP Events from ThreatFox (by abuse.ch) What will it do? This will fetch IOCs from ThreatFox by Abuse.ch, convert t

17 Nov 22, 2022
test

Lidar-data-decode In this project, you can decode your lidar data frame(pcap file) and make your own datasets(test dataset) in Windows without any hug

46 Dec 05, 2022
Biterm Topic Model (BTM): modeling topics in short texts

Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua

Maksim Terpilowski 49 Dec 30, 2022
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation

CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener

fastNLP 342 Jan 05, 2023
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you

Eliyar Eziz 2.3k Dec 29, 2022
ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体

ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体,包括上市公司所属行业关系、行业上级关系、产品上游原材料关系、产品下游产品关系、公司主营产品、产品小类共6大类。 上市公司4,654家,行业511个,产品95,559条、上游材料56,824条,上级行业480条,下游产品390条,产品小类52,937条,所属行业3,946条。

liuhuanyong 415 Jan 06, 2023
Snips Python library to extract meaning from text

Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur

Snips 3.7k Dec 30, 2022
This repository contains the codes for LipGAN. LipGAN was published as a part of the paper titled "Towards Automatic Face-to-Face Translation".

LipGAN Generate realistic talking faces for any human speech and face identity. [Paper] | [Project Page] | [Demonstration Video] Important Update: A n

Rudrabha Mukhopadhyay 438 Dec 31, 2022
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

Yuchao Zhang 204 Jul 14, 2022
My implementation of Safaricom Machine Learning Codility test. The code has bugs, logical I guess I made errors and any correction will be appreciated.

Safaricom_Codility Machine Learning 2022 The test entails two questions. Question 1 was on Machine Learning. Question 2 was on SQL I ran out of time.

Lawrence M. 1 Mar 03, 2022
CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus

CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus CVSS is a massively multilingual-to-English speech-to-speech translation corpus, co

Google Research Datasets 118 Jan 06, 2023
DVC-NLP-Simple-usecase

dvc-NLP-simple-usecase DVC NLP project Reference repository: official reference repo DVC STUDIO MY View Bag of Words- Krish Naik TF-IDF- Krish Naik ST

SUNNY BHAVEEN CHANDRA 2 Oct 02, 2022
Question and answer retrieval in Turkish with BERT

trfaq Google supported this work by providing Google Cloud credit. Thank you Google for supporting the open source! 🎉 What is this? At this repo, I'm

M. Yusuf Sarıgöz 13 Oct 10, 2022
Precision Medicine Knowledge Graph (PrimeKG)

PrimeKG Website | bioRxiv Paper | Harvard Dataverse Precision Medicine Knowledge Graph (PrimeKG) presents a holistic view of diseases. PrimeKG integra

Machine Learning for Medicine and Science @ Harvard 103 Dec 10, 2022
A Japanese tokenizer based on recurrent neural networks

Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following

325 Jan 05, 2023
A simple Flask site that allows users to create, update, and delete posts in a database, as well as perform basic NLP tasks on the posts.

A simple Flask site that allows users to create, update, and delete posts in a database, as well as perform basic NLP tasks on the posts.

Ian 1 Jan 15, 2022
Implementation of Multistream Transformers in Pytorch

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Phil Wang 47 Jul 26, 2022