Let’s use Module Federation to create an extensible Dockerized express server!
Host template: https://github.com/jherr/mf-plugin-host-template
Plugin template: https://github.com/jherr/mf-plugin-template
mf-plugins library: https://www.npmjs.com/package/mf-plugins
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Do you Increase your Website Engagment?
I analysed, ranked and reviewed best live video streaming chat APIs and SDKs for your web & mobile app based on client reviews and ratings. portfolio, usecases, cost, secure streaming, live chat features, cost, support, etc.
Turn your viewers into participatients with Live Streaming Chat Solutions. There are lot of Real-time chat apis & SDks Providers have in online market now. You can easily integrte and customize real time chat solutions into your new or existing live video streaming web and iOS & android applications. Below have mentioned best real time chat api & SDk Proivders.
CONTUS Fly is one of the leading real time messaging software providers in the market for a decade. Their messaging platforms are completely customizable since they provide Chat APIs and SDKs to integrate real time chat feasibility on your live streaming applications irrespective of audience base. Engage your audience like a live concert, stadium like experience through digitally. Create channels for every live streaming event, sports or anything that would create buzz. Enable audience to interact with each other over voice, video chats and real-time text chats with engaging emojis. CONTUS Fly enables users to add emojis and stickers to captivate each audience and create fun.
To make every live streaming and broadcasting videos more engaging and entertaining, Apphitect’s instant messaging comes with exciting Instant messaging chat APIs to add chat into streaming applications. Apphitect is built with multiple real time communication features like video chat, voice chat and real-time chat to your streaming apps. Their solution surprisingly has a wide range of features to communicate, engage and increase subscription benefits.
One of the enterprise-grade real-time chat solutions built to create virtual chat experience for live streaming events and websites for big brands and startups. Irrespective of audience base, category, MirrorFly provides customizable real time chat APIs to add virtual communication mediums on live streaming and broadcasting applications. Their solution comes with absolute moderation tools and open channels to talk and listen with your audience. MirrorFly’s server infrastructure has the potential to handle concurrent messages and users and to achieve maximum sales conversion.
When it comes to building a live streaming chat app software that covers the entire platforms and demand All-in-One package (features, Customization to any extent) with a one-time payment for lifetime performance, then undoubtedly Contus Fly makes the right choice to partner with. The company offers live broadcasting SDK for Android/iOS and chat APIs for customization.
Being a leading real time chat platform provider in the market, Sendbird has its own hallmark of communication features to the world’s most prominent live streaming applications. Their real time chat solution enables broadcasting and streaming platform’ owners to create a physical equivalent digital chat experience for the audience during any live event streaming to interact, collaborate and cheer together within the same streaming screen. By creating open channels and groups, you can enable the audience to interact with each other during any streaming, engage them with polls, stickers, multiple communication channels and more.
Agora, a deep integratable API available in the market to deliver live interactive streaming experience for workplace, enterprises, gaming, retail, telehealth and social live streaming websites. With easy-to-embed SDKs, Agora empowers businesses to add HD and low latency video and voice chat features into any streaming platforms and channels. Their easy-to-embed real time chat features encourage higher levels of user engagement and opportunity to drive more audience.
Their smart and secure chat APIs deliver real-time chat feasibility for live and on-demand video streaming websites. The real time chat features provides users to communicate and engage within the same streaming platform irrespective of interaction medium and audience count. Enablex offers platform-as-a-service communication solutions for real time messaging integration with APIs hosting possibility on public, private and cloud deployment. Their APIs are enriched with multiple communication features and engagement tools like live-polls, stickers and more.
In order to increase user engagement with live and remote audiences, Pubnub offers real time messaging chat functionality with interactive features to drive event-based engagement with mass chat. Their in-app chat feature enhances live programs, event streaming and blogging content with live polling, multiple chats and more. It also enables live streaming websites to build community, channels and super groups during live streaming to bring the entire audience base to one place.
Vonage is a prime provider of communication APIs for major industrial sectors and enterprise workplaces. With its API, businesses such as live streaming applications can integrate in-app messaging features into any streaming platforms on Android, iOS and Web to empower user engagement. Their APIs are powered with scalable infrastructure and provide multiple communication mediums such as in-app voice, video and chat proactively engaging the audience.
Firekast provides a customizable live chat widget with HTML code for streaming players to enable chat within any streaming or on-demand videos. The chat widget gives the ability for brands and content owners to make the audience to interact with each other for better engagement and proactivity during streaming. The Firekast Live chat comes with moderator tools that will allow administrators to delete or ban abusive content and users from the channel or groups. Firekast’s live chat comes with a private chat widget to create public or private chat rooms to make effective collaboration and discussions.
And this is all the real time chat providers in the market to implement chat functionality in any live streaming or broadcasting platforms. More than delivering entertaining live content, creating a massive engagement and buzz for every live event is the smarter way to turn every audience into a protiable subscriber. Picking up the right software provider is more important than just handling the integration process.
#live #live-streaming-solutions #live-streaming-chat-api #live-streaming-chat-sdk #chat-api-for-live-broadcasting
Recently Adobe XD releases a new version of the plugin that you can use to export designs directly into flutter widgets or screens. Yes, you read it right, now you can make and export your favorite design in Adobe XD and export all the design in the widget form or as a full-screen design, this can save you a lot of time required in designing.
What we will do?
I will make a simple design of a dialogue box with a card design with text over it as shown below. After you complete this exercise you can experiment with the UI. You can make your own components or import UI kits available with the Adobe XD.
#developers #flutter #adobe xd design export to flutter #adobe xd flutter code #adobe xd flutter code generator - plugin #adobe xd flutter plugin #adobe xd flutter plugin tutorial #adobe xd plugins #adobe xd to flutter #adobe xd tutorial #codepen for flutter.
In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own.
If you already know how to use RStudio and want to learn some tips, tricks, and shortcuts, check out this Dataquest blog post.
[tidyverse](https://www.dataquest.io/blog/tutorial-getting-started-with-r-and-rstudio/#tve-jump-173bb264c2b)Packages into Memory
#data science tutorials #beginner #r tutorial #r tutorials #rstats #tutorial #tutorials
What exactly is clean data? Clean data is accurate, complete, and in a format that is ready to analyze. Characteristics of clean data include data that are:
Common symptoms of messy data include data that contain:
In this blog post, we will work with five property-sales datasets that are publicly available on the New York City Department of Finance Rolling Sales Data website. We encourage you to download the datasets and follow along! Each file contains one year of real estate sales data for one of New York City’s five boroughs. We will work with the following Microsoft Excel files:
As we work through this blog post, imagine that you are helping a friend launch their home-inspection business in New York City. You offer to help them by analyzing the data to better understand the real-estate market. But you realize that before you can analyze the data in R, you will need to diagnose and clean it first. And before you can diagnose the data, you will need to load it into R!
Benefits of using tidyverse tools are often evident in the data-loading process. In many cases, the tidyverse package
readxl will clean some data for you as Microsoft Excel data is loaded into R. If you are working with CSV data, the tidyverse
readr package function
read_csv() is the function to use (we’ll cover that later).
Let’s look at an example. Here’s how the Excel file for the Brooklyn borough looks:
The Brooklyn Excel file
Now let’s load the Brooklyn dataset into R from an Excel file. We’ll use the
readxlpackage. We specify the function argument
skip = 4 because the row that we want to use as the header (i.e. column names) is actually row 5. We can ignore the first four rows entirely and load the data into R beginning at row 5. Here’s the code:
library(readxl) # Load Excel files brooklyn <- read_excel("rollingsales_brooklyn.xls", skip = 4)
Note we saved this dataset with the variable name
brooklyn for future use.
The tidyverse offers a user-friendly way to view this data with the
glimpse() function that is part of the
tibble package. To use this package, we will need to load it for use in our current session. But rather than loading this package alone, we can load many of the tidyverse packages at one time. If you do not have the tidyverse collection of packages, install it on your machine using the following command in your R or R Studio session:
Once the package is installed, load it to memory:
tidyverse is loaded into memory, take a “glimpse” of the Brooklyn dataset:
glimpse(brooklyn) ## Observations: 20,185 ## Variables: 21 ## $ BOROUGH <chr> "3", "3", "3", "3", "3", "3", "… ## $ NEIGHBORHOOD <chr> "BATH BEACH", "BATH BEACH", "BA… ## $ `BUILDING CLASS CATEGORY` <chr> "01 ONE FAMILY DWELLINGS", "01 … ## $ `TAX CLASS AT PRESENT` <chr> "1", "1", "1", "1", "1", "1", "… ## $ BLOCK <dbl> 6359, 6360, 6364, 6367, 6371, 6… ## $ LOT <dbl> 70, 48, 74, 24, 19, 32, 65, 20,… ## $ `EASE-MENT` <lgl> NA, NA, NA, NA, NA, NA, NA, NA,… ## $ `BUILDING CLASS AT PRESENT` <chr> "S1", "A5", "A5", "A9", "A9", "… ## $ ADDRESS <chr> "8684 15TH AVENUE", "14 BAY 10T… ## $ `APARTMENT NUMBER` <chr> NA, NA, NA, NA, NA, NA, NA, NA,… ## $ `ZIP CODE` <dbl> 11228, 11228, 11214, 11214, 112… ## $ `RESIDENTIAL UNITS` <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1… ## $ `COMMERCIAL UNITS` <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0… ## $ `TOTAL UNITS` <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1… ## $ `LAND SQUARE FEET` <dbl> 1933, 2513, 2492, 1571, 2320, 3… ## $ `GROSS SQUARE FEET` <dbl> 4080, 1428, 972, 1456, 1566, 22… ## $ `YEAR BUILT` <dbl> 1930, 1930, 1950, 1935, 1930, 1… ## $ `TAX CLASS AT TIME OF SALE` <chr> "1", "1", "1", "1", "1", "1", "… ## $ `BUILDING CLASS AT TIME OF SALE` <chr> "S1", "A5", "A5", "A9", "A9", "… ## $ `SALE PRICE` <dbl> 1300000, 849000, 0, 830000, 0, … ## $ `SALE DATE` <dttm> 2020-04-28, 2020-03-18, 2019-0…
glimpse() function provides a user-friendly way to view the column names and data types for all columns, or variables, in the data frame. With this function, we are also able to view the first few observations in the data frame. This data frame has 20,185 observations, or property sales records. And there are 21 variables, or columns.
#data science tutorials #beginner #r #r tutorial #r tutorials #rstats #tidyverse #tutorial #tutorials
A famous general is thought to have said, “A good sketch is better than a long speech.” That advice may have come from the battlefield, but it’s applicable in lots of other areas — including data science. “Sketching” out our data by visualizing it using ggplot2 in R is more impactful than simply describing the trends we find.
This is why we visualize data. We visualize data because it’s easier to learn from something that we can see rather than read. And thankfully for data analysts and data scientists who use R, there’s a tidyverse package called ggplot2 that makes data visualization a snap!
In this blog post, we’ll learn how to take some data and produce a visualization using R. To work through it, it’s best if you already have an understanding of R programming syntax, but you don’t need to be an expert or have any prior experience working with ggplot2
#data science tutorials #beginner #ggplot2 #r #r tutorial #r tutorials #rstats #tutorial #tutorials