#Aviator Prediction Bot Development

[plurancetechnologies]

Aviator Prediction Bot Development Company

The growing demand for innovative tools in the crash betting industry has paved the way for advanced prediction technologies. One standout product in this market is the Aviator Prediction Bot. As players seek smart ways to enhance their gaming experience, businesses must look towards developing automated solutions that meet these demands. Plurance offers comprehensive Aviator Prediction Bot Development Services designed to help gaming businesses stay competitive while keeping costs low.

What is an Aviator Crash Betting Prediction Bot?

The Aviator Crash Betting Prediction Bot is a highly sophisticated software that assists users in predicting outcomes in Aviator games. Aviator, a popular crash game, revolves around multipliers that grow until a sudden "crash" occurs. Prediction bots aim to calculate probabilities and patterns, helping users strategize their bets more effectively. These tools not only enhance user engagement but also offer a competitive edge for gaming platforms.

Building an effective prediction bot requires advanced algorithms, real-time analytics, and deep insights into game mechanics. That is where partnering with an expert Aviator Prediction Bot Development Company becomes critical to ensure that businesses deliver seamless solutions for their users.

Plurance: The Leader in Aviator Prediction Bot Development

Plurance stands as a leading name in the crash betting market, offering tailored Aviator Prediction Bot Development Solutions. With a focus on customization, accuracy, and affordability, Plurance ensures that businesses of all sizes can access cutting-edge tools to attract more players. Whether you want to integrate the bot into an existing platform or launch a standalone betting service, Plurance’s expertise can meet your requirements effectively.

By opting for Plurance’s low-cost Aviator Prediction Bot Development, businesses can avoid high overheads typically associated with advanced gaming technology. Plurance streamlines the development process by using modular frameworks, ensuring that the solution is delivered quickly and efficiently without compromising on quality.

Key Features of Plurance’s Aviator Prediction Bot Development

Advanced Prediction Algorithms: The bot leverages historical game data and real-time analytics to provide near-accurate predictions.

Seamless Integration: Businesses can easily integrate the bot into existing gaming platforms or apps.

User-Friendly Interface: Players can access predictions easily, encouraging higher engagement.

Customizable Alerts and Strategies: The bot can be tailored to meet the preferences of different user segments.

24/7 Support and Maintenance: Plurance ensures that the bot functions smoothly at all times with ongoing updates.

Unlock Business Potential with an Aviator Clone Script

For businesses seeking to build an entire crash betting platform from scratch, Plurance also offers an Aviator Clone Script. This ready-made script provides all the essential features of the Aviator game, combined with the prediction bot for a unique and engaging betting experience. With minimal development time and cost, companies can quickly establish themselves in the crash betting industry using this all-in-one solution.

Why Choose Plurance for Aviator Prediction Bot Development?

Plurance’s expertise, paired with its affordable development services, makes it a preferred partner for businesses venturing into crash betting. As a trusted Aviator Prediction Bot Development Company, Plurance ensures that businesses not only reduce costs but also launch premium solutions that drive user engagement and revenue.

With the Aviator Prediction Bot Development Services provided by Plurance, gaming businesses can stay ahead of the competition while delivering an exciting and data-driven experience for their players.

[nehatiwari454545-blog]

Web Scraping: Leave it All to AI or Add a Human Touch

What was once used by the US military as ARPANET (Advanced Research Projects Agency network) is today known as the Internet. With data grew from few gigabytes to 1.2 million terabytes today. In 1995 the internet was used by 16 million users. Today there are more than 4600 million users on internet and numbers are growing with each passing second. The last two years alone has made up for 90 per cent of the internet data today.  

This growth of internet users and their information has increased the data storage exponentially. Whatever you do on the internet, you will leave a digital trail. Even a random search by a random user will count in internet trend and affects the indexing of search engines. The data servers are now occupying space of football fields. Major companies like Google, Amazon etc are providing with cloud computing and cloud storage services to tap internet users’ data storage demand. With the need to store replicate data in case of natural catastrophe; more space is consumed by dedicated servers.

The surfing of the internet as much as it can be fun for regular users like us, for data scientists and businesses that desire some relevant information can become an uphill task. To find a needle in a haystack is easier than finding desired data on internet manually. The amount of data created and stored by a single large company is so vast that private data centres are employed. By this, we can envision how much data is available on the internet.

The role of data science, data mining and data scraping has increased tremendously. Web scraping services are used majorly for data extraction and data analysis. Web scraping is used for diverse purposes like business competition, research and analysis, consumer insights, security purposes, government purposes etc.

What is Web Scraping?

The extraction of data from websites is called web scraping or web harvesting. The specific data is copied from websites to local database or spreadsheet. Web scraping services or data scraping services use hypertext protocol or Extensible hypertext protocol for data extraction. The scraping can be done manually by visiting the particular page and copying data manually into a spreadsheet.

The manually scraping is possible when we are working for personal usage and data we are working with is limited. When we are dealing with a large amount of data an automated process is essential. It is implemented using a bot.

Web scraping and web crawling often mistaken for same but are different. Web crawling is done by search engines for indexing of hyperlinks, whereas web scraping does the data extraction. Web crawling is used in web scraping for fetching pages.

The websites now a day are highly advanced with using gifs, scripts, flash animations etc in an integrated ecosystem. Websites are developed, keeping human in mind, not bots therefore data extraction become a challenging task. The data extraction is based on the data stored by websites in text form. The mark-up languages such as HTML and XHTML are used for the development of a basic framework for any website. The specialised software use this rich text data for extraction.

There are simple plug-ins such as Scraper, Data Scraper for Google chrome used for web scraping. There specialised software such as ParseHub, OutwitHub, etc employed for slightly advance level of web scraping. The major e-commerce companies such as Amazon and social networking companies such as Facebook provide their APIs (Application programming interface) for public data extraction.

AI is a necessary evil in data scraping. The quantity of data has forced the implementation of AI. The AI as helpful it can be, unnerve people with wild sci-fi fantasy that pales the Matrix trilogy in comparison.

Also Read: 12 Best WordPress plugins every Sales and Marketing website must have

The legality of web scraping

“Just like the wild west, the Internet has no rules”. The times have changed in the wild west and on the Internet. The computer fraud and abuse laws criminalise any act of breaking into any private computer systems and accessing non-publically available data. In 2016 hiQ  Labs, a data science company web scrapped the publically available LinkedIn profiles. LinkedIn terms this as a violation of the company’s policy on data usage without permission and authorization. The hiQ took LinkedIn to court. In a landmark judgement for web scraping legality, the court ruled in favour of hiQ stating, “web scraping of public data is not a violation of computer fraud and abuse act.”

Also Read: Data scraping for BI: Picking the right service is vital

The morality of web scraping

The web scraping is used in business for online price monitoring, price comparison, product review data. The real estate companies use it to gather competitor real state listing. The websites use other website public data for their convenience without having to work for it. The web scraping lies in the grey area of morality where few times its use cab be justified with internet policy and sometimes complete violation of basic internet ethics.  

If you are searching for cheaply available phones with a certain price range and use web scraping tool on a major e-commerce website for data extraction then it quite ethical and can be justified. When you extract data for a content-based site with its USP being uniquely available content such as blogging websites and created a mirror site then it cannot be justified.

A basic moral conscience is necessary for making a righteous judgment in the age of the internet where the lines are quite blurred.

Concept of the good bot and bad bot

The supporting of web scraping often linked with freedom of the internet and fair use of public data but the picture is not as rosy as it seems. There are many bad bots ie malicious automated software available which can steal data by breaking into user accounts, overload servers with providing junk data and harm websites.

The AI bot gets a bad reputation due to malicious bot crawling the internet space. Many websites prohibit web scraping. The websites use advance tools for bot detection and prevent them from viewing their pages. This solution to this is the use of DOM parsing, simulation of human behaviour etc to extract data from sites.

Does it require adding a magic touch?

We are leaving in the age of artificial intelligence. It is the intelligence demonstrated by machines. The machines are incapable of thinking by themselves. The highly complex software is used to develop machine intelligence that learns, adapt and collects data. The AI is now used in several areas from traffic regulation, pilot training in the aviation industry, critical fields such as nuclear reactors etc. The AI has made possible rooming of the rover on Mars.

People are apprehensive of AI and believing a new world order where machine rules human. These make up for a good sci-fi script or story but the reality is too mechanical. AI has made it possible to work in an environment where humans could not survive. The sensitive area such as military, national security etc relies on AI for information processing. Human lives depend on AI proper working.

The internet is brimming with boundless data. The manual data extraction can be tedious in past but with data storage reaching in terabytes, it is nearly impossible. We have to implement AI for web harvesting and data mining services. The AI can extract store and process data from thousands of pages in a few seconds. The manual scraping does only a few hundred pages in days.  The AI has made it possible to scrape websites with a gigantic database and analyses it for forming business strategies and predictions.

Does that mean the AI has replaced human in web scraping area at least? Well, the answer is not binary. The AI does a spectacular job in web harvesting but the human touch is indispensable. When data is extracted just like an ore is extracted. It has to go through various processes of floatation, smelting etc to be useful. The data gathered from the site could be repetitive, redundant and in the wrong format. When we are extracting this kind of data we are overloading storage with unnecessary data. Data verification and data scrubbing will cleanse the inaccurate and corrupt records from the extracted data. These are quite state of art tools but the ultimate power lies in the hands of a human.

The intelligence of the machine is called artificial for a reason. The AI extracting data cannot determine its necessity for a purpose like a human does. Let us suppose a company want to launch a new clothing line for teenage girls. They are extracting data for what teenage girls find fashionable. Many times websites want to remain on the forward listing of search engines pages and use the metadata incorrectly. The AI being AI will extract the data for teenage fashion and data will imply something else.

Also Read: How Digitalization is transforming the Business of B2B Industry Data

Many websites prevent web crawling by using CAPTCHAS, embedding information in media objects, login access requirement, changing website HTML regularly etc. The AI right now cannot trespass these mechanisms of prevention of web scraping.

In a situation like these, human touch became essential. As they say, “The artificial intelligence has the same relation to intelligence as an artificial rose is to real rose.”

[marketfuturereports]

Aircraft Simulation Cabin Market Size, Share and Growth Forecast by Regions 2019-2023

26th August 2019 – The global Aircraft Simulation Cabin Market is expected to display higher growth rate over the next five years. Rapid surge in the market is credited to the rapid advancement in aviation sector. Increasing adoption of aircraft simulation cabin to reduce production and operational cost during production of aircrafts is expected to drive the growth of the market over the forecast period. Globally, aircraft simulation cabin market is predicted to generate massive revenue over the next five years, providing numerous opportunities for industry participants to invest in research and development of aircraft simulation cabin.

Moreover, increasing demand for aircraft simulation cabin from aerospace & defense sector is expected to foster market expansion in the near future. Aircraft simulation cabin helps to design and test highly complex aircraft parts. Additionally, necessary reduction in aircraft weight & composite materials, fuel coupling piping fatigue analysis, and airworthiness analysis of engine systems are performed with the help of aircraft simulation cabin. It also assist in understanding rotor dynamics and performing nacelle meshing analysis, thus strengthening market growth over the coming years.

Access Aircraft Simulation Cabin Market Report with TOC

Use of aircraft simulation cabin to implement various business strategies such as portfolio management, demand management and financial management is expected to garner huge support for market growth in the upcoming years. Effective adoption of portfolio management, demand management and financial management helps to resolve workload related issues and achieve cost efficiency. Aircraft cabin simulator is designed with the help of systematic approach.

The aircraft simulation cabin market is broadly categorized into three major segments based on the application type such as flight simulation cabin, airports and training purposes. Flight simulation cabin segment is growing rapidly in the market with substantial revenue generation in the last few years.

Leading players of Aircraft Simulation Cabin including:

• Bot-Aircraft

• Diamond Aircraft Industries Gmbh

• Embention

• Esterline Belgium

• Flightsafety International

• Frasca International

• Ids Ingegneria Dei Sistemi Spa

• L-3 Link

• Merlin Simulation

• Micro Nav, Ltd.

• Multi-Simulations, Llc

• Nita, Llc.

• Platinum Simulators Inc

• Reiser Simulation And Training Gmbh

• Rst Rostock System-Technik Gmbh

Request a Sample Copy of Aircraft Simulation Cabin Market Report

The market is divided by region as North America, Europe, Asia-Pacific, Latin America and Africa. North America has shown major growth in recent years owing to the rise in implementation of latest technologies in aviation sector, surge in number of research & development activities and existence of well-established infrastructure in the region. In European region, Germany, France, and United Kingdom are projected to witness steady growth.

Asia-Pacific region is estimated to hold a major share in the aircraft simulation cabin industry with massive growth in forecast period. Countries such as India, China and Singapore are leading the Asia-Pacific market with strong economic growth, rising number of aircraft production lines, and significant investment by leading industry players considering potential growth opportunities in the region.

[sonaliiiii]

The Evolution of IT Outsourcing in India: Past, Present and Future

Technology has been one of the fastest growing industries at global stage providing lucrative solutions to every other industry, leading to revolutionary results and changing the face of technological growth charts of many countries. The global businesses are changing, and IT outsourcing has been a huge help. Categorized into two- hardware and software development, IT industry has the largest private sector employers in India. From witnessing a hostile economy to conquering over 67% of the global IT outsourcing market, the industry has come a long way.

India is a leading destination for global companies seeking to outsource their non-core activates such as services, businesses, and high-end processes. But, do you think this would have been so easy like it seems today? Were there any challenges faced by our industry or it was just a piece of cake?

The Beginning of an Era: IT Outsourcing in India in 90s

India witnessed the unfurling of IT opportunities and challenges in 1968. Tata Group was the pioneer of nuclear sector and aviation and initiated its IT establishment in Mumbai. But the industry faced crisis with each step forward, as skilled and intellectual IT professionals immigrated to US and other countries for better IT scope and experience. It was a phase when US immigration laws were relaxed, and Indian wages and payments were not at par compared to other nations. There were several reasons that became obstacles in the foundation of IT outsourcing in India such as shortage of trained and skilled manpower, less young employees with good command over the English language, cut-throat competition, and non-existence of social security laws.

The Year 1991 is known as the early of IT sector as the new economic policy was formulated under the supervision of the then Prime Minister of India Shri Narasimha Rao and finance minister Dr. Manmohan Singh. India led its way to globalization as the liberalization policies diluted the socialist authorizations.

Where Does the Indian IT Outsourcing Stand Today Globally?

India is home to some of the finest IT companies of the world including Tata Consultancy Services (TCS), WIPRO, and International Business Machines Corporation (IBM). Presently, the sector holds over 75% global talent and remarks approximately 67% of the total global outsourcing market.

The progress and achievement data of Indian IT outsourcing is huge and commendable. While challenging its core competencies, the sector has attracted many significant investments from the foremost countries worldwide. According to National Association of Software & Service Companies (NASSCOM), India’s contribution in the global outsourcing market rose to 55% from 51% between 2009 to 2010. Leading global companies are not only looking for cost-effective IT solutions but also for capable staffing solutions, and business process excellence.

Future Trends of IT Outsourcing in India- More human-driven processes will be favoured

The late 2000s economic recession gave a big jolt to the IT outsourcing in India. Experts are now expecting more advantage and thriving trends for the coming years. Outsourcing has always been about cost reduction coupled with quick turn-around. However, the coming years will witness lesser focus on reducing costs. Solely price-oriented process will be eliminated. Instead, the relationship will become more human-driven among outsourced software developers and the clients. The industry will bring system integration for their clients. Risk of the projects will be shared equally by both the ends.

The coming years for IT outsourcing will be more driven towards specialization of manpower and skills. Companies will bid services under a single roof to stand out from the crowd. According to the Statista Report from 2017, India and China will become leading outsourcing countries , thus facing cut-throat competition from the top countries of Central and Eastern Europe.

The age of Automation

The global business process of outsourcing market will grasp around $220 billion by 2020 according to a Global Industry Analytics report. Meanwhile, experts are forecasting that automation will become crucial soon as markets are planning to involve bots and virtual agents to streamline their business projects and growth. On the other hand, cloud computing will increase its demand by 2020 and will impact $1 trillion in IT, as predicted by Gartner.

Conclusion

IT outsourcing has come a long way and 2019 has shown a promising future for businesses and software developers. Considering all above mentioned factors, IT outsourcing boom is inevitable encompassing every sector; employment and GDP will be positively affected for the country unless another recession hits the economy.

References: 

IT Outsourcing Evolution

The Evolution of IT Outsourcing in India: Past, Present and Future

Evolution of IT Outsourcing

[holytheoristtastemaker]

The past decade has allowed the development of a multitude of digital tools. Now they can be used to remediate the COVID-19 outbreak.

The year 2020 should have been the start of an exciting decade in medicine and science, with the development and maturation of several digital technologies that can be applied to tackle major clinical problems and diseases. These digital technologies include the internet of things (IoT) with next-generation telecommunication networks (e.g., 5G)1,2; big-data analytics3; artificial intelligence (AI) that uses deep learning4,5; and blockchain technology6. They are highly inter-related: the proliferation of the IoT (e.g., devices and instruments) in hospitals and clinics facilitates the establishment of a highly interconnected digital ecosystem, enabling real-time data collection at scale, which could then be used by AI and deep learning systems to understand healthcare trends, model risk associations and predict outcomes. This is enhanced by blockchain technology, a back-linked database with cryptographic protocols and a network of distributed computers in different organizations, integrating peer-to-peer networks to ensure that data are copied in multiple physical locations, with modified algorithms to ensure data are secured but traceable6.

However, 3 months into 2020, the world is facing an existential global health crisis: the outbreak of a novel coronavirus–caused respiratory disease (COVID-19)7. As the knowledge of COVID-19 evolves, increasing evidence suggests that it seems to be less deadly than initially thought (with a mortality rate of approximately 2%), although more contagious (89,779 cases in 70 countries, with over 3,069 deaths as of 2 March 2020) (https://www.worldometers.info/coronavirus/). The impact of COVID-19 will probably be greater than that of severe acute respiratory syndrome (SARS) in 2003, given globalization and the relative importance of China in 2020 in terms of world trade and travel.

How can this new crisis in 2020 be tackled? How does it differ from the SARS epidemic in 2003? Many countries have relied on an extrapolation of classic infection-control and public-health measures to contain the COVID-19 pandemic, similar to those used for SARS in 2003. These range from extreme quarantine measures in China (e.g., locking down over 60 million people in Hubei province) to painstaking detailed contact tracing with hundreds of contact tracers (e.g., Singapore, Hong Kong, South Korea). However, these measures may not be effective in 2020 for tackling the scale of COVID-19. Could new digital technology be used for COVID-19? In this Comment, we explore the potential application of four inter-related digital technologies (the IoT, big-data analytics, AI and blockchain) to augmenting two traditional public-health strategies for tackling COVID-19: (1) monitoring, surveillance, detection and prevention of COVID-19; and (2) mitigation of the impact to healthcare indirectly related to COVID-19 (Table 1).

Monitoring, surveillance, detection and prevention of COVID-19

First, the IoT provides a platform that allows public-health agencies access to data for monitoring the COVID-19 pandemic. For example, the ‘Worldometer’ provides a real-time update on the actual number of people known to have COVID-19 worldwide, including daily new cases of the disease, disease distribution by countries and severity of disease (recovered, critical condition or death) (https://www.worldometers.info/coronavirus/). Johns Hopkins University’s Center for Systems Science and Engineering has also developed a real-time tracking map for following cases of COVID-19 across the world, using the data collected from US Centers for Disease Control and Prevention (CDC), the World Health Organization (WHO), the European Center for Disease Prevention and Control, the Chinese Center for Disease Control and Prevention (China CDC) and the Chinese website DXY, which aggregates data from China’s National Health Commission and the China CDC (https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6).

Second, big data also provides opportunities for performing modeling studies of viral activity and for guiding individual country healthcare policymakers to enhance preparation for the outbreak. Using three global databases―the Official Aviation Guide, the location-based services of the Tencent (Shenzhen, China), and the Wuhan Municipal Transportation Management Bureau―Wu et al. performed a modeled study of ‘nowcasting’ and forecasting COVID-19 disease activity within and outside China that could be used by the health authorities for public-health planning and control worldwide8. Similarly, using the WHO International Health Regulations, the State Parties Self-Assessment Annual Reporting Tool, Joint External Evaluation reports and the Infectious Disease Vulnerability Index, Gilbert et al. assessed the preparedness and vulnerability of African countries in battling against COVID-19; this would help raise awareness of the respective health authorities in Africa to better prepare for the viral outbreak9.

Third, digital technology can enhance public-health education and communication. In Singapore, the government has partnered with WhatsApp (owned by Facebook) to allow the public to receive accurate information about COVID-19 and government initiatives (https://www.form.gov.sg/#!/5e33fa3709f80b00113b6891). Multiple social-media platforms (e.g., Facebook and Twitter) are currently used by healthcare agencies to provide ‘real-time’ updates and clarify uncertainties with the public. Additionally, some facial-recognition companies (e.g., SenseTime and Sunell) have adopted the thermal imaging–enabled facial recognition to identify people with an elevated temperature at various screening points in China (https://apnews.com/PR%20Newswire/354aae0738073bc95331ee72a458cb50).

Fourth, AI and deep learning can enhance the detection and diagnosis of COVID-19. The need to provide access to accurate and low-cost tests for the diagnosis of COVID-19 is a challenge. Many peripheral hospitals in China and other developing countries in Asia, the Middle-East and Africa do not have the tests or resources to accurately distinguish COVID-19 from the ‘common flu’. In Indonesia, which has only two reported case thus far, despite substantial exposure to Chinese tourists (Bali had 1.2 million Chinese tourists in 2019), health authorities decided against testing the 243 returning but asymptomatic citizens from Wuhan because of cost of the test (the reagent was quoted as costing nearly US$75,000). Alternative diagnostic and screening tests for COVID-19 will be extremely useful. In this context, China has large datasets of cases positive for COVID-19 (>70,000 cases). These are ideal datasets for deep AI and deep learning (https://www.wired.com/story/chinese-hospitals-deploy-ai-help-diagnose-covid-19/). Such AI algorithms can then be used as an initial screening tool for suspected cases (e.g., travel history to China, Iran or South Korea, or exposure to confirmed cases) so that patients at higher risk could have confirmatory laboratory-based tests or be isolated.

Although most patients have mild cases of COVID-19, physicians have to apply the same level of intensive methods to isolate, treat and monitor all patients. AI algorithms could be developed to help physicians triage patients with COVID-19 into potentially three groups: the 80% who have mild disease; the 15% who have moderate disease; and the 5% who have severe disease, including those at high risk of mortality. Finally, AI can also facilitate the discovery of novel drugs with which to treat COVID-19.

Mitigation of COVID-19’s impact

Although the focus of tackling the direct impact of COVID-19 is important, in many healthcare settings, it is important to maintain core and critical clinical service. The initial reaction in many countries is for healthcare facilities to reduce or even cease many clinical services, including closure of clinics and postponement of medical appointments or elective surgeries. However, such strategies cannot be sustained indefinitely if the COVID-19 pandemic extends beyond 6 months.

Healthcare systems should plan to use digital technology. For example, ‘virtual clinics’ could be set up through the use of tele-medicine consultations with imaging data (e.g., chest X-ray and/or CT of the thorax) uploaded from peripheral sites and interpreted remotely. This would ensure that patients continue to receive standard clinical care while reducing physical crowding of patients into hospital premises. For other key hospital activities (e.g., research and education), virtual e-learning platforms are increasingly being explored to eliminate physical meetings.

Second, the utilization of various AI-based triage systems could potentially alleviate the clinical load of physicians. An online medical ‘chat bot’ could help patients recognize early symptoms, educate people on the importance of hand hygiene and refer people for medical treatment should symptoms worsen. Additionally, phone-based software that detects and records patients’ data (e.g., daily temperature and symptoms) may prevent unnecessary hospital consultations for patients with mild flu-like symptoms. These data could also be developed into AI algorithms for the detection of COVID-19.

Third, many hospitals in China are collaborating with blockchain companies and pharmacies to deliver patients’ medication to their doorsteps. Through the use of blockchain, hospitals could ensure timely delivery of medications with accurate tracking.

In summary, while the world continues to rely on classic public-health measures for tackling the COVID-19 pandemic, in 2020, there is now a wide range of digital technology that can be used to augment and enhance these public-health strategies (https://www.vox.com/recode/2020/2/27/21156358/surveillance-tech-coronavirus-china-facial-recognition). There is also a longer-term goal. The immediate use and successful application of digital technology to tackle a major, global public-health challenge in 2020 will probably increase the public and governmental acceptance of such technologies for other areas of healthcare, including chronic disease in the future. As the saying goes, ‘a crisis provides an opportunity’; this first great crisis of 2020 provides a great opportunity for digital technology.

[holytheoristtastemaker]

First of all, nobody expected a lockdown. Nobody expected all the businesses will be paused or shifted to a total remote mode. And if most of the professions suffer from the lost opportunities and quarantine restrictions, developers (as they did so before for many years already) are the most used to ‘work from home’ people. And the new situation affected them not as much as others.

However, many of my friends working with aviation or travel, stayed without work. I hope, you all are ok.

I haven’t released March JS digest because of the start of the quarantine — I had a lot of work to do, and I suppose, many of you were busy with more important stuff than comparing and seeking for the best open source projects.

But now the situation is a bit better and I found some time to monitor what exactly had happened with JS repositories on GitHub in these two months, and what developers prefer for their projects when working from home.

Hence, we can grasp an overall situation and predict some trends to be followed in May. Stay safe!

Most popular JS repositories in March and April 2020

Gatsby is a free and open source framework based on React that helps developers build websites and apps. 34,978 stars by now.

marked.js is a markdown parser and compiler. Built for speed. 22,199 stars by now.

AVA is a test runner for Node.js with a concise API, detailed error output, embrace of new language features, and process isolation. 17,842 stars by now.

Immer (German for: always) is a tiny package that allows you to work with immutable state in a more convenient way. It is based on the copy-on-write mechanism. 16,266 stars by now.

Playwright is a Node library to automate Chromium, Firefox, and WebKit with a single API. Playwright is built to enable cross-browser web automation that is ever-green, capable, reliable, and fast. 11,667 stars by now.

plotly.js is an open-source JavaScript charting library behind Plotly and Dash. 11,600 stars by now.

FullCalendar is a full-sized drag & drop JavaScript event calendar. 11,168 stars by now.

Trianglify is a library that creates algorithmically generated triangle art (SVG background). 9,302 stars by now.

Nano ID is a tiny (108 bytes), secure, URL-friendly, unique string ID generator for JavaScript. 9,129 stars by now.

MDX is an authorable format that lets you seamlessly use JSX in your markdown documents. You can import components, like interactive charts or notifications, and export metadata. 8,705 stars by now.

Bull is a Redis-based queue package for handling distributed jobs and messages in NodeJS. 8,237 stars by now.

Rome is an experimental JavaScript toolchain. It includes a compiler, linter, formatter, bundler, testing framework, and more. It aims to be a comprehensive tool for anything related to the processing of JavaScript source code. 8,193 stars by now.

ioredis is a robust, performance-focused, and full-featured Redis client for Node.js. 7,505 stars by now.

Tippy.js is a tooltip, popover, dropdown, and menu solution for the web. 7,352 stars by now.

Alpine.js is a rugged, minimal framework for composing JavaScript behavior in your markup. 7,050 stars by now.

ts-node is a TypeScript execution and REPL for Node.js. 6,630 stars by now.

Rickshaw is a JavaScript toolkit for creating interactive time-series graphs, developed at Shutterstock. 6,446 stars by now.

Excalidraw is a whiteboard tool that lets you easily sketch diagrams with a hand-drawn feel. 6,115 stars by now.

fkill-cli library stands for ‘Fabulously kill processes’. Cross-platform. 6,077 stars by now.

ora is an elegant terminal spinner. 5,927 stars by now.

Prompts is a library that stands for lightweight, beautiful, and user-friendly interactive prompts. 5,800 stars by now.

query-string helps you to parse and stringify URL query strings. 4,722 stars by now.

isomorphic-git is a pure JavaScript reimplementation of git that works in both Node.js and browser JavaScript environments. It can read and write to git repositories, fetch from and push to git remotes (such as GitHub), all without any native C++ module dependencies. 4,696 stars by now.

node-notifier is a Node.js module for sending notifications on native Mac, Windows, and Linux (or Growl as fallback). 4,454 stars by now.

Backstage is an open platform for building developer portals. It unifies all your infrastructure tooling, services, and documentation with a single, consistent UI. 4,011 stars by now.

react-ga is a JavaScript module that can be used to include Google Analytics tracking code in a website or app that uses React for its frontend codebase. It does not currently use any React code internally but has been written for use with a number of Mozilla Foundation websites that are using React, as a way to standardize our GA Instrumentation across projects. 3,723 stars by now.

jExcel is a lightweight vanilla javascript plugin to create web-based interactive tables and spreadsheets compatible with Excel or any other spreadsheet software. 3,629 stars by now.

AutoCannon is an HTTP/1.1 benchmarking tool written in Node, with support for HTTP pipelining and HTTPS. 3,604 stars by now.

Dinero.js is a library for working with monetary values in JavaScript. 3,590 stars by now.

Redwood is an opinionated, full-stack, serverless web application framework that will allow you to build and deploy JAMstack applications with ease. 3,341 stars by now.

franc is s natural language detection. 3,334 stars by now.

webpack-blocks is a library that helps you by providing functional building blocks for your webpack config: easier way to configure webpack and to share configuration between projects. 2,820 stars by now.

hotkey to trigger an action on a target element when a key or sequence of keys is pressed on the keyboard. This triggers a focus event on form fields or a click event on others. 2,041 stars by now.

Serialize JavaScript to a superset of JSON that includes regular expressions and functions. 2,012 stars by now.

React Easy State is a simple React state management. 2,006 stars by now.

Qoa is a minimal interactive command-line prompts. The library utilizes a simple & minimal usage syntax and contains 7 configurable console interfaces, such as plain text, confirmation & password/secret prompts as well as single keypress, quiz & multiple-choice navigable menus. 1,931 stars by now.

kasaya is a “WYSIWYG” scripting language and runtime for browser automation. 1,808 stars by now.

match-sorter is a simple, expected, and deterministic best-match sorting of an array in JavaScript. 1,788 stars by now.

Crank.js helps you to write JSX-driven components with functions, promises, and generators. 1,622 stars by now.

Ervy brings charts to terminal. 1,481 stars by now.

iHateRegex.io is a regex cheat sheet for the haters. This project gives you a visual representation of regular expressions, embed regular expression visualization on your sites, code highlighting and validation, and more. 1,479 stars by now.

Stryker is a mutation testing for JavaScript and friends. 1,469 stars by now.

react-enroute is a simple React router with a small footprint for modern browsers. This package is not meant to be a drop-in replacement for react-router, just a smaller simpler alternative. 1,441 stars by now.

OpenChakra is a visual editor and code generator for React using Chakra UI. You can draft components with the simple drag and drop UI. 1,429 stars by now.

jest-dom stands for custom jest matchers to test the state of the DOM. 1,417 stars by now.

Notyf is a minimalistic JavaScript library for toast notifications. It’s responsive, A11Y compatible, dependency-free and tiny (~3KB). Easy integration with React, Angular, and Vue. 1,361 stars by now.

on-change allows you to watch an object or array for changes. 1,354 stars by now.

React Awesome Slider is a 60fps content transition slider that renders an animated set of production-ready UI general-purpose sliders. 1,317 stars by now.

Panolens.js is an event-driven and WebGL based panorama viewer. Lightweight and flexible. It's built on top of Three.JS. 1,254 stars by now.

Uppload is a JavaScript image uploader. It’s highly customizable with 30+ plugins, completely free and open-source, and can be used with any file uploading backend. 1,235 stars by now.

telebot is a library supporting an easy way to write Telegram bots in Node.js. 898 stars by now.

Thank you for reading!