harvey h

harvey h


Laravel Performance Optimization Tips

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Laravel Performance Optimization Tips

Hyper-advanced AI Coordinating Continuous integration Technologies


Your comments are my commits

GitHub comment-based interface to testing buildbots. Simply ping @jlbuild in a comment, PR, issue, etc... and @jlbuild will do its best to build the relevant Julia version on all platforms, post download links and even execute small chunks of code across those plat forms.

The syntax of a @jlbuild command is as follows:

@jlbuild [hash] [!tag1] [!tag2]....
[julia code]

All pieces within square brackets are optional. If the comment being made is within a pull request, is a comment upon a specific commit, or in some other fashion is obviously related to a single Julia revision, @jlbuild should automatically figure out which commit you're discussing and build the appropriate version. However, you can always specify the version manually, e.g. @jlbuild 1a2b3c4d.

Tags are used to alter the default behavior of jlbuild somewhat. As of this writing, two tags are available:

!nuke instructs the buildbots to completely clean out the buildbots before building this version of Julia, a very important feature when dealing with buildsystem changes. Example: @jlbuild 1a2b3c4d !nuke.

!filter=x,y,z filters the buildbots that will be scheduled. Filters are comma-separated strings, where any builder that contains any of the filtering criterion will be included. Example: @jlbuild !nuke !filter=linux64,win,ppc.

!flags=x,y,z will add extra flags to the make invocation that builds julia. Example: @jlbuild !filter=arm !flags=BUILD_CUSTOM_LIBCXX=1,BUILD_LLVM_CLANG=1.

Finally, Julia code can be included to be run using the newly-built version of Julia. Binary artifacts from the build will also be posted for easy access.

Download Details:

Author: jlbuild
Source Code: https://github.com/jlbuild/jlbuild.jl 
License: MIT license

#julia #ai #technologies 

Hyper-advanced AI Coordinating Continuous integration Technologies
Nat  Grady

Nat Grady


CRAN Task View: WebTechnologies

CRAN Task View: Web Technologies and Services

This Task View contains information about to use R and the world wide web together. The base version of R does not ship with many tools for interacting with the web. Thankfully, there are an increasingly large number of tools for interacting with the web. This task view focuses on packages for obtaining web-based data and information, frameworks for building web-based R applications, and online services that can be accessed from R. A list of available packages and functions is presented below, grouped by the type of activity. The rOpenSci Task View: Open Data provides further discussion of online data sources that can be accessed from R.

If you have any comments or suggestions for additions or improvements for this Task View, go to GitHub and submit an issue , or make some changes and submit a pull request . If you can’t contribute on GitHub, send Scott an email . If you have an issue with one of the packages discussed below, please contact the maintainer of that package. If you know of a web service, API, data source, or other online resource that is not yet supported by an R package, consider adding it to the package development to do list on GitHub .

Tools for Working with the Web from R

Core Tools For HTTP Requests

There are three main packages that should cover most use cases of interacting with the web from R. crul is an R6-based HTTP client that provides asynchronous HTTP requests, a pagination helper, HTTP mocking via webmockr, and request caching for unit tests via vcr. crul targets R developers more so than end users. httr provides more of a user facing client for HTTP requests and differentiates from the former package in that it provides support for OAuth. Note that you can pass in additional curl options when you instantiate R6 classes in crul, and the config parameter in httr. curl is a lower-level package that provides a closer interface between R and the libcurl C library , but is less user-friendly. curl underlies both crul and httr. curl may be useful for operations on web-based XML or to perform FTP operations (as crul and httr are focused primarily on HTTP). curl::curl() is an SSL-compatible replacement for base R’s url() and has support for http 2.0, SSL (https, ftps), gzip, deflate and more. For websites serving insecure HTTP (i.e. using the “http” not “https” prefix), most R functions can extract data directly, including read.table and read.csv; this also applies to functions in add-on packages such as jsonlite::fromJSON() and XML::parseXML. For more specific situations, the following resources may be useful:

  • RCurl is another low level client for libcurl. Of the two low-level curl clients, we recommend using curl. httpRequest is another low-level package for HTTP requests that implements the GET, POST and multipart POST verbs, but we do not recommend its use.
  • request provides a high-level package that is useful for developing other API client packages. httping provides simplified tools to ping and time HTTP requests, around httr calls. httpcache provides a mechanism for caching HTTP requests.
  • For dynamically generated webpages (i.e., those requiring user interaction to display results), RSelenium can be used to automate those interactions and extract page contents. It provides a set of bindings for the Selenium 2.0 webdriver using the JsonWireProtocol . It can also aid in automated application testing, load testing, and web scraping. seleniumPipes (GitHub ) provides a “pipe”-oriented interface to the same. An alternative to the former two packages is splashr that vouches to be a lightweight altnernative. rdom (not on CRAN) uses phantomjs to access a webpage’s Document Object Model (DOM).
  • For capturing static content of web pages postlightmercury is a client for the web service Mercury that turns web pages into structured and clean text.
  • Another, higher-level alternative package useful for webscraping is rvest, which is designed to work with magrittr to make it easy to express common web scraping tasks.
  • Many base R tools can be used to download web content, provided that the website does not use SSL (i.e., the URL does not have the “https” prefix). download.file() is a general purpose function that can be used to download a remote file. For SSL, the download() function in downloader wraps download.file(), and takes all the same arguments.
  • Tabular data sets (e.g., txt, csv, etc.) can be input using read.table(), read.csv(), and friends, again assuming that the files are not hosted via SSL. An alternative is to use httr::GET (or RCurl::getURL) to first read the file into R as a character vector before parsing with read.table(text=...), or you can download the file to a local directory. rio (GitHub ) provides an import() function that can read a number of common data formats directly from an https:// URL. The repmis function source_data() can load and cache plain-text data from a URL (either http or https). That package also includes source_Dropbox() for downloading/caching plain-text data from non-public Dropbox folders and source_XlsxData() for downloading/caching Excel xlsx sheets.
  • Authentication: Using web resources can require authentication, either via API keys, OAuth, username:password combination, or via other means. Additionally, sometimes web resources that require authentication be in the header of an http call, which requires a little bit of extra work. API keys and username:password combos can be combined within a url for a call to a web resource (api key: http://api.foo.org/?key=yourkey; user/pass: http://username:password@api.foo.org), or can be specified via commands in RCurl or httr. OAuth is the most complicated authentication process, and can be most easily done using httr. See the 6 demos within httr, three for OAuth 1.0 (linkedin, twitter, vimeo) and three for OAuth 2.0 (facebook, GitHub, google). ROAuth is a package that provides a separate R interface to OAuth. OAuth is easier to to do in httr, so start there. googleAuthR provides an OAuth 2.0 setup specifically for Google web services, and AzureAuth provides similar functionality for Azure Active Directory.

Handling HTTP Errors/Codes

  • fauxpas brings a set of Ruby or Python like R6 classes for each individual HTTP status code, allowing simple and verbose messages, with a choice of using messages, warnings, or stops.
  • httpcode is a simple package to help a user/package find HTTP status codes and associated messages by name or number.

Parsing Structured Web Data

The vast majority of web-based data is structured as plain text, HTML, XML, or JSON (javascript object notation). Web service APIs increasingly rely on JSON, but XML is still prevalent in many applications. There are several packages for specifically working with these format. These functions can be used to interact directly with insecure webpages or can be used to parse locally stored or in-memory web files.

  • XML: There are two packages for working with XML: XML and xml2 (GitHub ). Both support general XML (and HTML) parsing, including XPath queries. The package xml2 is less fully featured, but more user friendly with respect to memory management, classes (e.g., XML node vs. node set vs. document), and namespaces. Of the two, only the XML supports de novo creation of XML nodes and documents. The XML2R (GitHub ) package is a collection of convenient functions for coercing XML into data frames. An alternative to XML is selectr , which parses CSS3 Selectors and translates them to XPath 1.0 expressions. XML package is often used for parsing xml and html, but selectr translates CSS selectors to XPath, so can use the CSS selectors instead of XPath.
  • HTML: All of the tools that work with XML also work for HTML, though HTML is - in practice - more prone to be malformed. Some tools are designed specifically to work with HTML. xml2::read_html() is a good first function to use for importing HTML. htmltools provides functions to create HTML elements. htmltab (GitHub ) extracts structured information from HTML tables, similar to XML::readHTMLTable of the XML package, but automatically expands row and column spans in the header and body cells, and users are given more control over the identification of header and body rows which will end up in the R table. The selectorgadget browser extension can be used to identify page elements. RHTMLForms reads HTML documents and obtains a description of each of the forms it contains, along with the different elements and hidden fields. scrapeR provides additional tools for scraping data from HTML documents. htmltidy (GitHub ) provides tools to “tidy” messy HTML documents. htm2txt uses regex to converts html documents to plain text by removing all html tags. Rcrawler does crawling and scraping of web pages.
  • JSON: There are several packages for reading and writing JSON: rjson, RJSONIO, and jsonlite. jsonlite includes a different parser from RJSONIO called yajl . We recommend using jsonlite. Check out the paper describing jsonlite by Jeroen Ooms https://arxiv.org/abs/1403.2805 . jqr provides bindings for the fast JSON library, jq . jsonvalidate (GitHub ) validates JSON against a schema using the “is-my-json-valid” Javascript library; ajv does the same using the ajv Javascript library. ndjson (GitHub ) supports the “ndjson” format.
  • RSS/Atom: feedeR can be used to parse RSS or Atom feeds. tidyRSS parses RSS, Atom XML/JSON and geoRSS into a tidy data.frame.
  • swagger can be used to automatically generate functions for working with an web service API that provides documentation in Swagger.io format.

Tools for Working with URLs

  • The httr::parse_url() function can be used to extract portions of a URL. The RCurl::URLencode() and utils::URLencode() functions can be used to encode character strings for use in URLs. utils::URLdecode() decodes back to the original strings. urltools (GitHub ) can also handle URL encoding, decoding, parsing, and parameter extraction.
  • iptools can facilitate working with IPv4 addresses, including for use in geolocation.
  • urlshorteneR offers URL expansion and analysis for Bit.ly, Goo.gl, and is.gd. longurl uses the longurl.org API to provide similar functionality.
  • gdns provides access to Google’s secure HTTP-based DNS resolution service.

Tools for Working with Scraped Webpage Contents

  • Several packages can be used for parsing HTML documents. boilerpipeR provides generic extraction of main text content from HTML files; removal of ads, sidebars and headers using the boilerpipe Java library. RTidyHTML interfaces to the libtidy library for correcting HTML documents that are not well-formed. This library corrects common errors in HTML documents. W3CMarkupValidator provides an R Interface to W3C Markup Validation Services for validating HTML documents.
  • For XML documents, the XMLSchema package provides facilities in R for reading XML schema documents and processing them to create definitions for R classes and functions for converting XML nodes to instances of those classes. It provides the framework for meta-computing with XML schema in R. xslt is an extension for the xml2 package to transform XML documents by applying an xslt style-sheet. (It can be seen as a modern replacement for Sxslt, which is an interface to Dan Veillard’s libxslt translator, and the SXalan package.) This may be useful for webscraping, as well as transforming XML markup into another human- or machine-readable format (e.g., HTML, JSON, plain text, etc.). SSOAP provides a client-side SOAP (Simple Object Access Protocol) mechanism. Beware, SSOAP itself may not install, and/or its dependencies. The best bet is to get the web service maintainers to switch to REST. XMLRPC provides an implementation of XML-RPC, a relatively simple remote procedure call mechanism that uses HTTP and XML. This can be used for communicating between processes on a single machine or for accessing Web services from within R.
  • Rcompression (not on CRAN): Interface to zlib and bzip2 libraries for performing in-memory compression and decompression in R. This is useful when receiving or sending contents to remote servers, e.g. Web services, HTTP requests via RCurl.
  • tm.plugin.webmining: Extensible text retrieval framework for news feeds in XML (RSS, ATOM) and JSON formats. Currently, the following feeds are implemented: Google Blog Search, Google Finance, Google News, NYTimes Article Search, Reuters News Feed, Yahoo Finance and Yahoo Inplay.
  • webshot uses PhantomJS to provide screenshots of web pages without a browser. It can be useful for testing websites (such as Shiny applications).


  • securitytxt identifies and parses web Ssecurity policy files.

Other Useful Packages and Functions

  • Javascript: V8 (GitHub ) is an R interface to Google’s open source, high performance JavaScript engine. It can wrap Javascript libraries as well as NPM packages. The SpiderMonkey package provides another means of evaluating JavaScript code, creating JavaScript objects and calling JavaScript functions and methods from within R. This can work by embedding the JavaScript engine within an R session or by embedding R in an browser such as Firefox and being able to call R from JavaScript and call back to JavaScript from R. The js package wraps V8 and validates, reformats, optimizes and analyzes JavaScript code.
  • Email:: mailR is an interface to Apache Commons Email to send emails from within R. sendmailR provides a simple SMTP client. gmailr provides access the Google’s gmail.com RESTful API.
  • Mocking:: webmockr is a library for stubbing and setting expectations on HTTP requests. It is inspired from Rubys webmock. This package only helps mock HTTP requests, and returns nothing when requests match expectations. webmockr integrates with the HTTP packages crul and httr. See Testing for mocking with returned responses.
  • Testing:: vcr provides an interface to easily cache HTTP requests in R package test suites (but can be used outside of testing use cases as well). vcr relies on webmockr to do the HTTP request mocking. vcr integrates with the HTTP packages crul and httr. httptest provides a framework for testing packages that communicate with HTTP APIs, offering tools for mocking APIs, for recording real API responses for use as mocks, and for making assertions about HTTP requests, all without requiring a live connection to the API server at runtime. httptest only works with httr.
  • Miscellaneous: webutils contains various functions for developing web applications, including parsers for application/x-www-form-urlencoded as well as multipart/form-data. mime (GitHub ) guesses the MIME type for a file from its extension. rsdmx provides tools to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework. The package currently focuses on the SDMX XML standard format (SDMX-ML). robotstxt provides functions and classes for parsing robots.txt files and checking access permissions; spiderbar does the same. uaparserjs (GitHub ) uses the javascript “ua-parser” library to parse User-Agent HTTP headers. rjsonapi consumes APIs that Follow the JSON API Specification . rapiclient is a client for consuming APIs that follow the Open API format . restfulr models a RESTful service as if it were a nested R list.

Web and Server Frameworks

  • Model Operationalization (previously DeployR) is a Microsoft product that provides support for deploying R and Python models and code to a server as a web service to later consume.
  • The shiny package makes it easy to build interactive web applications with R.
  • dash is a web framework which is available for Python, R and Julia, with components written in React.js.
  • Other web frameworks include: fiery that is meant to be more flexible but less easy to use than shiny (reqres and routr are utilities used by fiery that provide HTTP request and response classes, and HTTP routing, respectively); rcloud provides an iPython notebook-style web-based R interface; and Rook, which contains the specification and convenience software for building and running Rook applications.
  • The opencpu framework for embedded statistical computation and reproducible research exposes a web API interfacing R, LaTeX and Pandoc. This API is used for example to integrate statistical functionality into systems, share and execute scripts or reports on centralized servers, and build R based apps.
  • Several general purpose server/client frameworks for R exist. Rserve and RSclient provide server and client functionality for TCP/IP or local socket interfaces. httpuv provides a low-level socket and protocol support for handling HTTP and WebSocket requests directly within R. Another related package, perhaps which httpuv replaces, is websockets . servr provides a simple HTTP server to serve files under a given directory based on httpuv.
  • Several packages offer functionality for turning R code into a web API. FastRWeb provides some basic infrastructure for this. plumber allows you to create a REST API by decorating existing R source code.
  • The WADL package provides tools to process Web Application Description Language (WADL) documents and to programmatically generate R functions to interface to the REST methods described in those WADL documents. (not on CRAN)
  • The RDCOMServer provides a mechanism to export R objects as (D)COM objects in Windows. It can be used along with the RDCOMClient package which provides user-level access from R to other COM servers. (not on CRAN)
  • rapporter.net provides an online environment (SaaS) to host and run rapport statistical report templates in the cloud.
  • radiant (GitHub ) is Shiny-based GUI for R that runs in a browser from a server or local machine.
  • The Tiki Wiki CMS/Groupware framework has an R plugin (PluginR ) to run R code from wiki pages, and use data from their own collected web databases (trackers). A demo: https://r.tiki.org/tiki-index.php .
  • The MediaWiki has an extension (Extension:R ) to run R code from wiki pages, and use uploaded data. A mailing list used to be available: R-sig-mediawiki.
  • whisker: Implementation of logicless templating based on Mustache in R. Mustache syntax is described in http://mustache.github.io/mustache.5.html
  • CGIwithR (not on CRAN) allows one to use R scripts as CGI programs for generating dynamic Web content. HTML forms and other mechanisms to submit dynamic requests can be used to provide input to R scripts via the Web to create content that is determined within that R script.

Web Services

Cloud Computing and Storage

  • The cloudyr project , which is currently under active development on GitHub, aims to provide interfaces to popular Amazon, Azure and Google cloud services without the need for external system dependencies.
  • Amazon Web Services is a popular, proprietary cloud service offering a suite of computing, storage, and infrastructure tools. aws.signature provides functionality for generating AWS API request signatures.
    • Elastic Cloud Compute (EC2) is a cloud computing service. segue (not on CRAN) is a package for managing EC2 instances and S3 storage, which includes a parallel version of lapply() for the Elastic Map Reduce (EMR) engine called emrlapply(). It uses Hadoop Streaming on Amazon’s EMR in order to get simple parallel computation.
    • DBREST: RAmazonDBREST provides an interface to Amazon’s Simple DB API.
    • paws (GitHub ) is an interface to nearly all AWS APIs, including compute, storage, databases, and machine learning. It also requires no external system dependencies.
  • Azure is Microsoft’s cloud computing service. It provides Paas, SaaS and IaaS and supports many different tools and frameworks, including both Microsoft-specific and third-party systems.
    • Azure Active Directory (AAD) is a centralised directory and identity service. AzureAuth is an R client for AAD; use this to obtain OAuth tokens for authenticating with other Azure services, including Resource Manager and storage (see next).
    • Azure Resource Manager (ARM) is a service for deploying other Azure services. AzureRMR is an R interface to ARM, and allows managing subscriptions, resource groups, resources and templates. It exposes a general R6 class framework that can extended to provide extra functionality for specific services (see next).
    • Azure Storage Accounts are a general-purpose data storage facility. Different types of storage are available: file, blob, table, Data Lake, and more. AzureStor provides an R interface to storage. Features include clients for file, blob and Data Lake Gen2 storage, parallelized file transfers, and an interface to Microsoft’s cross-platform AzCopy commandline utility. Also supplied is an ARM interface, to allow creation and managing of storage accounts.
    • Data Science Virtual Machines (DSVMs) are Azure VMs that come preloaded with a wide variety of software for statistics and machine learning, including R, Python, TensorFlow, and Spark. AzureVM is a package for managing DSVMs from within R. It also allows deploying arbitrary VMs by supplying a suitable deployment template.
    • AzureContainers provides a unified facility for working with containers in Azure. Specifically, it includes R interfaces to Azure Container Instances (ACI) , Azure Docker Registry (ACR) and Azure Kubernetes Service (AKS) . Create Docker images and push them to an ACR repository; spin up ACI containers; deploy Kubernetes services in AKS.
    • Azure Data Explorer , also known as Kusto , is a fast, scalable data exploration and analytics service. AzureKusto (not yet on CRAN) is an R interface to ADE/Kusto. It includes a dplyr client interface similar to that provided by dbplyr for SQL databases, a DBI client interface, and an ARM interface for deploying and managing Kusto clusters and databases.
  • googleComputeEngineR interacts with the Google Compute Engine API, and lets you create, start and stop instances in the Google Cloud.
  • Cloud Storage: googleCloudStorageR interfaces with Google Cloud Storage. boxr (GitHub ) is a lightweight, high-level interface for the box.com API . rdrop2 is a Dropbox interface that provides access to a full suite of file operations, including dir/copy/move/delete operations, account information (including quotas) and the ability to upload and download files from any Dropbox account.
  • Docker: analogsea is a general purpose client for the Digital Ocean v2 API. In addition, the package includes functions to install various R tools including base R, RStudio server, and more. There’s an improving interface to interact with docker on your remote droplets via this package.
  • crunch GitHub provides an interface to the crunch.io storage and analytics platform. crunchy GitHub facilitates making Shiny apps on Crunch.
  • rrefine provides a client for the OpenRefine (formerly Google Refine) data cleaning service.

Document and Code Sharing

  • Code Sharing: gistr (GitHub ) works with GitHub gists (gist.github.com ) from R, allowing you to create new gists, update gists with new files, rename files, delete files, get and delete gists, star and un-star gists, fork gists, open a gist in your default browser, get embed code for a gist, list gist commits, and get rate limit information when authenticated. git2r provides bindings to the git version control system and gh is a client for the GitHub API. gitlabr is a GitLab -specific client.
  • Data archiving: dataverse (GitHub ) provides access to Dataverse 4 APIs. rfigshare (GitHub ) connects with Figshare.com . dataone (GitHub ) provides a client for DataONE repositories.
  • Google Drive/Google Documents: The RGoogleDocs package is an example of using the RCurl and XML packages to quickly develop an interface to the Google Documents API. RGoogleStorage provides programmatic access to the Google Storage API. This allows R users to access and store data on Google’s storage. We can upload and download content, create, list and delete folders/buckets, and set access control permissions on objects and buckets.
  • Google Sheets: googlesheets (GitHub ) can access private or public Google Sheets by title, key, or URL. Extract data or edit data. Create, delete, rename, copy, upload, or download spreadsheets and worksheets. gsheet (GitHub ) can download Google Sheets using just the sharing link. Spreadsheets can be downloaded as a data frame, or as plain text to parse manually.
  • imguR (GitHub ) is a package to share plots using the image hosting service Imgur.com . knitr also has a function imgur_upload() to load images from literate programming documents.

Data Analysis and Processing Services

  • Geospatial/Geolocation/Geocoding: Several packages connect to geolocation/geocoding services. rgeolocate (GitHub ) offers several online and offline tools. rydn (not on CRAN) is an interface to the Yahoo Developers network geolocation APIs, and ipapi can be used to geolocate IPv4/6 addresses and/or domain names using the http://ip-api.com/ API. threewords connects to the What3Words API , which represents every 3-meter by 3-meter square on earth as a three-word phrase. opencage (GitHub ) provides access to to the OpenCage geocoding service. nominatim (not on CRAN) connects to the OpenStreetMap Nominatim API for reverse geocoding. PostcodesioR (not on CRAN) provides post code lookup and geocoding for the United Kingdom. geosapi is an R client for the GeoServer REST API, an open source implementation used widely for serving spatial data. geonapi provides an interface to the GeoNetwork legacy API, an opensource catalogue for managing geographic metadata. ows4R is a new R client for the OGC standard Web-Services, such Web Feature Service (WFS) for data and Catalogue Service (CSW) for metadata.
  • Machine Learning as a Service: Several packages provide access to cloud-based machine learning services. OpenML (GitHub ) is the official client for the OpenML API . clarifai (GitHub ) is a Clarifai.com client that enables automated image description. rLTP (GitHub ) accesses the ltp-cloud service . languagelayeR is a client for Languagelayer, a language detection API. googlepredictionapi (not on CRAN): is an R client for the Google Prediction API , a suite of cloud machine learning tools. yhatr lets you deploy, maintain, and invoke models via the Yhat REST API. datarobot works with Data Robot’s predictive modeling platform. mscsweblm4r (GitHub ) interfaces with the Microsoft Cognitive Services Web Language Model API and mscstexta4r (GitHub ) uses the Microsoft Cognitive Services Text Analytics REST API. rosetteApi links to the Rosette text analysis API. googleLanguageR provides interfaces to Google’s Cloud Translation API, Natural Language API, Cloud Speech API, and the Cloud Text-to-Speech API.
  • Machine Translation: translate provides bindings for the Google Translate API v2 and translateR provides bindings for both Google and Microsoft translation APIs. RYandexTranslate (GitHub ) connects to Yandex Translate . transcribeR provides automated audio transcription via the HP IDOL service.
  • Document Processing: abbyyR GitHub and captr (GitHub ) connect to optical character recognition (OCR) APIs. pdftables (GitHub ) uses the PDFTables.com webservice to extract tables from PDFs.
  • Mapping: osmar provides infrastructure to access OpenStreetMap data from different sources to work with the data in common R manner and to convert data into available infrastructure provided by existing R packages (e.g., into sp and igraph objects). osrm (GitHub ) provides shortest paths and travel times from OpenStreetMap. osmplotr (GitHub ) extracts customizable map images from OpenStreetMap. RgoogleMaps serves two purposes: it provides a comfortable R interface to query the Google server for static maps, and use the map as a background image to overlay plots within R. R2GoogleMaps provides a mechanism to generate JavaScript code from R that displays data using Google Maps. RKMLDevice allows to create R graphics in Keyhole Markup Language (KML) format in a manner that allows them to be displayed on Google Earth (or Google Maps), and RKML provides users with high-level facilities to generate KML. plotKML can visualization spatial and spatio-temporal objects in Google Earth. ggmap allows for the easy visualization of spatial data and models on top of Google Maps, OpenStreetMaps, Stamen Maps, or CloudMade Maps using ggplot2. mapsapi is an sf-compatible interface to Google Maps API. leafletR: Allows you to display your spatial data on interactive web-maps using the open-source JavaScript library Leaflet. openadds (GitHub ) is an Openaddresses client, and banR provides access to the “Base Adresses Nationale” (BAN) API for French addresses.
  • Online Surveys: qualtRics provide functions to interact with Qualtrics . WufooR (GitHub ) can retrieve data from Wufoo.com forms. redcapAPI (GitHub ) can provide access to data stored in a REDCap (Research Electronic Data CAPture) database, which is a web application for building and managing online surveys and databases developed at Vanderbilt University. formr facilitates use of the formr survey framework, which is built on openCPU. Rexperigen is a client for the Experigen experimental platform .
  • Visualization: Plot.ly is a company that allows you to create visualizations in the web using R (and Python), which is accessible via plotly. googleVis provides an interface between R and the Google chart tools. The RUbigraph package provides an R interface to a Ubigraph server for drawing interactive, dynamic graphs. You can add and remove vertices/nodes and edges in a graph and change their attributes/characteristics such as shape, color, size.
  • Other :

Social Media Clients

  • plusser has been designed to to facilitate the retrieval of Google+ profiles, pages and posts. It also provides search facilities. Currently a Google+ API key is required for accessing Google+ data.
  • Rfacebook provide an interface to the Facebook API.
  • The Rflickr package provides an interface to the Flickr photo management and sharing application Web service. (not on CRAN)
  • instaR (GitHub ) is a client for the Instagram API .
  • Rlinkedin (not on CRAN) is a client for the LinkedIn API. Auth is via OAuth.
  • rpinterest connects to the Pintrest API.
  • vkR is a client for VK, a social networking site based in Russia.
  • meetupr is a client for the Meetup.com API.
  • Twitter: twitteR (GitHub ) provides an interface to the Twitter web API. It claims to be deprecated in favor of rtweet (GitHub ). twitterreport (not on CRAN) focuses on report generation based on Twitter data. streamR provides a series of functions that allow users to access Twitter’s filter, sample, and user streams, and to parse the output into data frames. OAuth authentication is supported. tweet2r is an alternative implementation geared toward SQLite and postGIS databases. graphTweets produces a network graph from a data.frame of tweets. tweetscores (not on CRAN) implements a political ideology scaling measure for specified Twitter users.
  • brandwatchR is a package to retrieve a data from the Brandwatch social listening API. Both raw text and aggregate statistics are available, as well as project and query management functions.

Web Analytics Services

  • Google Trends: gtrendsR offers functions to perform and display Google Trends queries. RGoogleTrends provides an alternative.
  • Google Analytics: googleAnalyticsR, ganalytics, and RGA provide functions for accessing and retrieving data from the Google Analytics APIs . The latter supports OAuth 2.0 authorization. RGA provides a shiny app to explore data. searchConsoleR links to the Google Search Console (formerly Webmaster Tools).
  • Online Advertising: fbRads can manage Facebook ads via the Facebook Marketing API. RDoubleClick (not on CRAN) can retrieve data from Google’s DoubleClick Campaign Manager Reporting API. RSmartlyIO (GitHub ) loads Facebook and Instagram advertising data provided by Smartly.io .
  • Other services: RSiteCatalyst has functions for accessing the Adobe Analytics (Omniture SiteCatalyst) Reporting API.
  • RAdwords (GitHub ) is a package for loading Google Adwords data.
  • webreadr (GitHub ) can process various common forms of request log, including the Common and Combined Web Log formats and AWS logs.

Web Services for R Package Development

  • R-Hub http://log.r-hub.io/ is a project to enable package builds across all architectures. rhub is a package that interfaces with R-Hub to allow you to check a package on the platform.

Other Web Services

Fitness Apps: fitbitScraper (GitHub ) retrieves Fitbit data. RGoogleFit provides similar functionality for Google Fit .

Push Notifications: RPushbullet provides an easy-to-use interface for the Pushbullet service which provides fast and efficient notifications between computers, phones and tablets. pushoverr (GitHub ) can sending push notifications to mobile devices (iOS and Android) and desktop using Pushover . notifyme (GitHub ) can control Phillips Hue lighting.

Reference/bibliography/citation management: RefManageR imports and manage BibTeX and BibLaTeX references with RefManager. rorcid (GitHub ) is a programmatic interface the Orcid.org API, which can be used for identifying scientific authors and their publications (e.g., by DOI). rdatacite connects to DataCite , which manages DOIs and metadata for scholarly datasets. scholar provides functions to extract citation data from Google Scholar. rscopus provides functions to extract citation data from Elsevier Scopus APIs. Convenience functions are also provided for comparing multiple scholars and predicting future h-index values. mathpix convert an image of a formula (typeset or handwritten) via Mathpix webservice to produce the LaTeX code. zen4R provides an Interface to Zenodo REST API, including management of depositions, attribution of DOIs by ‘Zenodo’ and upload of files.

Literature: rplos is a programmatic interface to the Web Service methods provided by the Public Library of Science journals for search. europepmc connects to the Europe PubMed Central service. pubmed.mineR is a package for text mining of PubMed Abstracts that supports fetching text and XML from PubMed. jstor provides functions and helpers to import metadata, ngrams and full-texts from Data for Research service by JSTOR. aRxiv is a client for the arXiv API, a repository of electronic preprints for computer science, mathematics, physics, quantitative biology, quantitative finance, and statistics. roadoi provides an interface to the Unpaywall API for finding free full-text versions of academic papers. rcoreoa is an interface to the CORE API , a search interface for open access scholarly articles. rcrossref is an interface to Crossref’s API, crminer extracts full text from scholarly articles retrieved via Crossref’s Text and Data Mining service; fulltext is a general purpose package to search for, retrieve and extract full text from scholarly articles; and rromeo (GitHub ) is an interface to the SHERPA/RoMEO API , a database of scientific journal archival policies regarding pre-, post-print, and accepted manuscript.

Automated Metadata Harvesting: oai and OAIHarvester harvest metadata using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) standard. rresync is a client for the ResourceSync framework , a sort of replacement for OAI-PMH.

Wikipedia: WikipediR (GitHub ) is a wrapper for the MediaWiki API, aimed particularly at the Wikimedia ‘production’ wikis, such as Wikipedia. WikidataR (GitHub ) can request data from Wikidata.org , the free knowledgebase. wikipediatrend (GitHub ) provides access to Wikipedia page access statistics. WikidataQueryServiceR is a client for the Wikidata Query Service .

bigrquery (GitHub ): An interface to Google’s bigquery.

sparkbq (GitHub ): Google BigQuery support for sparklyr.

cymruservices queries Team Cymru web security services.

datamart: Provides an S4 infrastructure for unified handling of internal datasets and web based data sources. Examples include dbpedia, eurostat and sourceforge.

discgolf (GitHub ) provides a client to interact with the API for the Discourse web forum platform. The API is for an installed instance of Discourse, not for the Discourse site itself.

rdpla ((GitHub)[https://github.com/ropensci/rdpla\]) works with the Digital Public Library of America API.

factualR: Thin wrapper for the Factual.com server API.

internetarchive: API client for internet archive metadata.

jSonarR: Enables users to access MongoDB by running queries and returning their results in data.frames. jSonarR uses data processing and conversion capabilities in the jSonar Analytics Platform and the JSON Studio Gateway , to convert JSON to a tabular format.

livechatR is a client for the LiveChat API .

mockaRoo (not on CRAN) uses the MockaRoo API to generate mock or fake data based on an input schema.

pivotaltrackR provides an interface to the API for Pivotal Tracker , an agile project management tool.

randNames (GitHub ) generates random names and personal identifying information using the https://randomapi.com/ API.

Rblpapi (GitHub ) is a client for Bloomberg Finance L.P. ROpenFIGI (GitHub ) provides an interface to Bloomberg’s OpenFIGI API.

rerddap: A generic R client to interact with any ERDDAP instance, which is a special case of OPeNDAP ( https://en.wikipedia.org/wiki/OPeNDAP ), or Open-source Project for a Network Data Access Protocol . Allows user to swap out the base URL to use any ERDDAP instance.

restimizeapi provides an interface to trading website estimize.com .

RForcecom: RForcecom provides a connection to Force.com and Salesforce.com.

Two packages, owmr and ROpenWeatherMap, work with the Open Weather Map API .

RSauceLabs (GitHub ) connects to SauceLabs .

RStripe provides an interface to Stripe , an online payment processor.

RZabbix links with the Zabbix network monitoring service API .

slackr (GitHub ) is a client for Slack.com messaging platform.

shutterstock (GitHub ) is to access Shutterstock library from R.

stackr (not on CRAN): An unofficial wrapper for the read-only features of the Stack Exchange API .

telegram (GitHub ) connects with the Telegram Bot API.

trelloR (GitHub ) connects to the Trello API .

tuber is a YouTube API client and tubern is a client for the YouTube Analytics and Reporting API

udapi connects to Urban Dictionary.

useRsnap (not on CRAN) provides an interface to the API for Usersnap , a tool for collecting feedback from web application users.

yummlyr (GitHub ) provides an interface to the Yummly recipe database.

zendeskR: This package provides a wrapper for the Zendesk API.

ZillowR is a client for the Zillow real estate service.

docuSignr provides an interface to the DocuSign Rest API .

giphyr is an R interface to the Giphy API for GIF’s

duckduckr is an R interface DuckDuckGo’s Instant Answer API

CRAN packages:

Related links:

Maintainer:Scott Chamberlain, Thomas Leeper, Patrick Mair, Karthik Ram, Christopher Gandrud
Contact:myrmecocystus at gmail.com

Do not edit this README by hand. See CONTRIBUTING.md .

Download Details:

Author: Cran-task-views
Source Code: https://github.com/cran-task-views/WebTechnologies 

#r #web #technologies 

CRAN Task View: WebTechnologies

iPhone App Development Services | Hire iPhone App Developer India

We provide end-to-end iPhone app development services for iOS devices. Hire our iOS/iPhone app developers to build innovative custom iOS apps. Expert App Devs is a leading iPhone app development services partner that provides businesses with secure and scalable solutions. We fuel your apps with the right technology stack, architecture layout, and interface design to improve downloads, maximize retention and enhance customer lifetime value for your business. Our iPhone-first solutions are engineered to make your business future-ready.

#iosappdevelopment #hireiosappdeveloppers #expertappdevs #business #iosapplication #technologies #usa #uk #uae #iphone #iosappdeveloper

iPhone App Development Services | Hire iPhone App Developer India

Laravel The Preferred Web-Application Development Framework

Are you looking to Boost your business through rich-featured, sleek & charismatic UI integrated Web Applications?

Choose Laravel, a PHP-based Framework that is freely accessible across online repositories with an open-source license, with a default built-in wide array of PHP modules, components, security mechanisms, and database elements, furnishing a dynamic Laravel solution to the user. This allows users to craft feather-light, platform-independent and easy-to-customize web applications as per your requirements, which enables your services to reach out globally, accelerating your business productivity to a higher level.

#laravel  #webappdevelopment #framework #programming #technologies 

Laravel The Preferred Web-Application Development Framework

What Does It Take to Automate Businesses and Various Industries?

Industries always seek to adopt efficient processes that can lead to faster development and growth of the business. Nowadays, lots of entrepreneurs have shifted their gears towards automation for growing their businesses. For an established setup, there is so much to manage. From handling staff timings, raw materials, financial investments, and operational workflows, each of these factors is rated in terms of productivity. Process automation via machines handles the entire workflow optimizing time and costs. Cost reduction further boosts business productivity.


#AutomateBusinesses #Costreduction #technologies #RoboticProcessAutomation #ArtificialIntelligence #business #newblog  #newarticle 

What Does It Take to Automate Businesses and Various Industries?

Why Laravel Framework is Superior for Mobile App Development?

To build a world-class mobile app, you need a robust and trustworthy Laravel Framework. It is your chosen technology that keeps your data safe and constantly checks with the smooth running of backend operations. Laravel got founded with the same thought process. The creators of Laravel technology believe in simplifying the development process. With the latest version of Laravel 5.4, the founders have reinforced the same ideology embedded with new features.


#laravelframework  #php #backend #technologies #newblog  #MobileAppDevelopment #newarticle #softwareasaservice #saas #softwaredeveloper #ecommercewebsite #fullstackdeveloper #softwareengineer 

Why Laravel Framework is Superior for Mobile App Development?

GitOps: The Next Big Thing in DevOps?

Check read our most recent post for a detailed explanation of "What is GitOps?" "What is driving us in this direction?" "When and how may this technology be used in a live environment?" and "What tools are included?"


#gitops #devops #technologies #development #devopsdeveloper #developer #gitopsdeveloper

GitOps: The Next Big Thing in DevOps?
Castore  DeRose

Castore DeRose


Understanding Blockchain Traceability | Ultimate Beginners Guide

In this post, you'll learn What is Blockchain Traceability. A Comprehensive Guide On Blockchain Traceability

Blockchain, the digital distributed ledger technology, has become a prominent game-changer in the world of financial services. In addition, blockchain has shown promising applications in the domain of supply chain management thereby drawing attention to blockchain traceability. The blockchain is basically a decentralized ledger or a digital system recording the transactions between multiple parties in a transparent, verifiable, immutable, and secure manner. The record of transactions could help in monitoring every phase of a business transaction carefully. 

Even if the hype around the use of blockchain-based traceability has been gaining fuel, it is also important to know that many such applications are still in the stages of development. The following discussion helps you obtain a clear impression of traceability in blockchain with a detailed overview of technical underpinnings. In addition, an overview of the possible applications of blockchain traceability in different sectors could also enlighten readers.

Blockchain and the Supply Chain Management

Most of the discussions surrounding traceability in blockchain technology would refer to supply chain management contexts. Blockchain technology introduces promising value to the domain of supply chain management and traceability is one of them. Blockchain technology, when combined with the ability for programming business logic, by leveraging smart contracts could offer better traceability. How?

Blockchain ensures improved transparency into the details of the provenance of consumer goods. Provenance implies the chain of custody of a product from the point of origin to the point of consumption. In addition, blockchain also improves accuracy in asset tracking throughout its journey in the supply chain. The applications of blockchain in supply chain management, even in the existing technologically empowered world, could contribute to better efficiency. At the same time, blockchain could also help in ensuring auditable tracking of assets alongside restricting exploitative behaviors.        

What Does Supply Chain Management Look Like Now?

The need for traceability in blockchain refers to the various issues experienced by the existing supply chain management sector. The shipping industry spends almost half of the cost of transportation on paperwork. Furthermore, studies have also pointed out to concerns of mislabeling in food products. In addition, many products also include ingredients sourced through illegal measures. Another prominent issue in the existing supply chain management landscape refers to the counterfeiting of luxury goods. Furthermore, the counterfeiting of consumer goods such as electronics and pharmaceuticals also creates the necessity for introducing blockchain traceability.

How Can Blockchain Improve Supply Chain?

The use of public, private, and hybrid blockchain could introduce traceability, transparency, and accountability in the movement of assets. Blockchain can be helpful for the logistics sector for improving the efficiency of business processes alongside reducing costs of supply chain infrastructure. So, what is traceability in blockchain, and how it can make supply chain management better? Supply chains generally have a complex network of manufacturers, suppliers, retailers, distributors, auditors, and customers. The shared ledger infrastructure of blockchain could help in streamlining the workflow across all participants in the network. Furthermore, the shared infrastructure could ensure improved visibility for auditors regarding the activities of participants in the value chain. 

Enterprise blockchain technology has the potential for transforming conventional supply chain management by introducing traceability in blockchain technology. The three distinct use cases of blockchain in supply chain management refer to traceability, tradability, and transparency. Blockchain can leverage traceability for improving operational efficiency through mapping and visualization of enterprise supply chains. The continuously increasing demand for sourcing information about products is also a notable factor for emphasizing the need for blockchain traceability. Blockchain could help enterprises in developing a better understanding of supply chain operations alongside ensuring the engagement of consumers with real, immutable, and verifiable data. 

Traceability in blockchain also relies profoundly on the ease of capturing crucial data points such as claims and certifications. As a result, it can help in strengthening trust followed by enabling open access to the data. After registration on the blockchain, the authenticity of data points is verified by third-party attesters. It is also important to note that traceability in blockchain refers to the introduction of benefits for real-time updates and validation of information.   

How Can Blockchain Enhance Provide Chain?

Supply chains all over the world support the movement of almost any type of asset including consumer packaged goods. In addition, the global supply chains also deal with product recalls, when certain consumer products or raw supplies must be recalled for preventing illness or injury. Recalled consumer products have a formidable negative influence on millions of people all over the world with lawsuits, lost sales, and replacement costs. The answer for ‘what is traceability in blockchain’ would focus on applying blockchain for streamlining product recall alongside reducing counterfeiting.

So, what goes on in the technology surrounding the concept of traceability in blockchain technology? Blockchain is basically a ‘chain of blocks’ in which each block represents the collection of different transactions. Each block is added to the existing chain of blocks with a cryptographic hash function. If you need to access the data of a block, then you need the keys for decrypting the hash function to obtain desired data. Each block in a blockchain contains the timestamp of the transaction alongside details of the participants involved in the transaction. As a result, it offers a comprehensive audit trail in which you can find the different milestones an asset has crossed in the journey through the supply chain. 

Actual Makes use of of Blockchain Traceability

Essentially the most essential side in understanding the implications of blockchain-based traceability refers to its actual makes use of. Blockchain may allow traceability throughout varied sectors which level out the probabilities for making traceability one of many driving elements for blockchain adoption. As you will have seen already, the purposes of traceability are clearly evident within the provide chain context. Blockchain can assist in enhancing the traceability of merchandise throughout provide chains. Now, allow us to dive deeper into the varied examples of using traceability throughout varied sectors. 

The purposes of blockchain traceability within the provide chain are clearly evident from the decentralized side of blockchain. Utilizing blockchain within the provide chain may suggest that blockchain or distributed ledger know-how purposes may empower international buying and selling companions for partaking in safe transactions together with consensus concerning shared information for enhancing visibility, transparency, and effectivity. The first use instances for blockchain within the provide chain deal with the immutability of the provenance of products. As well as, using blockchain based mostly traceability in provide chain use instances additionally ensures aid from the troubles of reconciliation with a number of events. Most vital of all, blockchain may additionally supply the benefit of real-time visibility to allow monitor and hint evaluation. 

Traceability in blockchain know-how additionally works successfully for various ache factors within the agriculture sector. Traceability within the agriculture sector may empower the effectivity of crop manufacturing alongside enhancing the administration of agricultural finance. For instance, the mix of blockchain know-how and IoT sensors may assist in monitoring the crop subject. Blockchain may assist in documenting the info collected for various parameters of the crop subject reminiscent of soil moisture, temperature, gentle, humidity, and ph. As well as, the incorporation of machine studying algorithms and predictive fashions may additionally allow farmers to make insightful selections in agriculture. Moreover, blockchain traceability additionally presents optimistic implications for the administration of agricultural finance. Farmers, in addition to stakeholders, can share data throughout all steps of meals manufacturing whereas auditors may conduct audits successfully. 

The reply to ‘what’s traceability in blockchain’ for the style trade would largely confer with the issue of counterfeiting. The burden of counterfeit items is costing the style trade so much when it comes to annual gross sales yearly. On the identical time, trend manufacturers are shedding their credibility available in the market. Due to this fact, blockchain may assist in monitoring the provision chain of products for establishing a greater basis of belief for patrons. Blockchain may be sure that prospects know the place the style merchandise come from. As well as, using distinctive identifiers for verifying the originality of products is a promising good thing about traceability. The distinctive identifier can assist you discover out the place the product has been in its journey by means of the worth chain. 

The expectations of shoppers concerning the requirements of their meals are fluctuating continually with every passing day. Customers need to know the supply of their meals and the practices utilized in manufacturing the meals. Blockchain-based traceability may assist prospects know the precise native land of their meals. As well as, it additionally permits visibility into data concerning the precise producers of the meals and its freshness. Employees at every stage within the meals provide chain must replace the database with details about the product. Due to this fact, traceability within the meals provide chain may supply conclusive benefits such because the discount of meals fraud and false labelling. 

Manufacturing firms may make the most of blockchain for simpler knowledge trade with higher accuracy and safety all through sophisticated provide chains. Traceability in blockchain know-how within the manufacturing sector may guarantee entry to a everlasting digital report of supplies, substances, elements, and different merchandise. Consequently, it could possibly guarantee prolific development within the end-to-end visibility of the manufacturing course of. On the identical time, all contributors within the manufacturing course of may entry a single supply of belief. Most significantly, blockchain may additionally assist in enhancing provide chain traceability for producers. For instance, using IoT and blockchain may assist in accumulating product knowledge reminiscent of temperature, pH, moisture, and different facets at completely different factors of the product’s journey within the provide chain. 

Implementing Blockchain Traceability

Supply chain traceability is one of the significant use cases pertaining to blockchain technology. Apparently, the replacement of conventional supply chain processes with distributed ledger technology can enhance the trade volume of the US by 15%. In addition, the initiative could also boost the US GDP by almost 5%. Blockchain could offer the flexibility of tracking almost any physical or digital product across all the phases of its lifecycle. Blockchain traceability could support the expansion of sustainable and ethical production and the use of any commodity on a global level. 

You can also notice many industries depending on third-party manufacturers or multiple vendors prior to the creation and labelling of final finished goods. In some of the cases, the white-label products are sold prior to repackaging or relabeling. On the contrary, the value of traceability in blockchain refers to the transparency in process tracking. As a result, manufacturers could get a clear view of their value chain thereby ensuring that they could guarantee the efficient movement of third-party products and final product labelling. 

With the help of blockchain, you can track the movement of assets alongside recording information and showcasing records of previous assets. Blockchain leverages the use of smart contracts for employing traceability of assets. So, traceability in blockchain could ensure that any individual could notice the chain of custody and journey of an asset through the supply chain in real-time. 

Real Uses of Blockchain Traceability

The most crucial aspect in understanding the implications of blockchain-based traceability refers to its real uses. Blockchain could enable traceability across various sectors which point out the possibilities for making traceability one of the driving factors for blockchain adoption. As you have seen already, the applications of traceability are clearly evident in the supply chain context. Blockchain can help in improving the traceability of products across supply chains. Now, let us dive deeper into the various examples of the use of traceability across various sectors. 

Supply Chain

The applications of blockchain traceability in the supply chain are clearly evident from the decentralized aspect of blockchain. Using blockchain in the supply chain could imply that blockchain or distributed ledger technology applications could empower global trading partners for engaging in secure transactions along with consensus regarding shared facts for improving visibility, transparency, and efficiency. The primary use cases for blockchain in the supply chain focus on the immutability of the provenance of goods. In addition, the use of blockchain based traceability in supply chain use cases also ensures relief from the troubles of reconciliation with multiple parties. Most important of all, blockchain could also offer the advantage of real-time visibility to enable track and trace analysis. 


Traceability in blockchain technology also works effectively for different pain points in the agriculture sector. Traceability in the agriculture sector could empower the efficiency of crop production alongside improving the management of agricultural finance. For example, the combination of blockchain technology and IoT sensors could help in monitoring the crop field. Blockchain could help in documenting the data collected for different parameters of the crop field such as soil moisture, temperature, light, humidity, and ph. In addition, the incorporation of machine learning algorithms and predictive models could also enable farmers to make insightful decisions in agriculture. Furthermore, blockchain traceability also presents positive implications for the management of agricultural finance. Farmers, as well as stakeholders, can share information across all steps of food production while auditors could conduct audits effectively. 


The answer to ‘what is traceability in blockchain’ for the fashion industry would largely refer to the problem of counterfeiting. The burden of counterfeit goods is costing the fashion industry a lot in terms of annual sales every year. At the same time, fashion brands are losing their credibility in the market. Therefore, blockchain could help in monitoring the supply chain of goods for establishing a better foundation of trust for customers. Blockchain could ensure that customers know where the fashion products come from. In addition, the use of unique identifiers for verifying the originality of goods is a promising benefit of traceability. The unique identifier can help you find out where the product has been in its journey through the value chain. 


The expectations of consumers regarding the standards of their food are fluctuating constantly with each passing day. Consumers want to know the source of their food and the practices used in manufacturing the food. Blockchain-based traceability could help customers know the exact place of origin of their food. In addition, it also enables visibility into information regarding the actual producers of the food and its freshness. Workers at each stage in the food supply chain have to update the database with information about the product. Therefore, traceability in the food supply chain could offer conclusive advantages such as the reduction of food fraud and false labelling. 


Manufacturing companies could utilize blockchain for easier data exchange with better accuracy and security throughout complicated supply chains. Traceability in blockchain technology in the manufacturing sector could ensure access to a permanent digital record of materials, ingredients, parts, and other products. As a result, it can ensure prolific growth in the end-to-end visibility of the manufacturing process. At the same time, all participants in the manufacturing process could access a single source of trust. Most importantly, blockchain could also help in improving supply chain traceability for manufacturers. For example, the use of IoT and blockchain could help in collecting product data such as temperature, pH, moisture, and other aspects at different points of the product’s journey in the supply chain. 

Will Blockchain Bring Next-Generation Traceability?

The foremost challenge in the present world is the development of trust. Addressing the traceability concerns for products in supply chains of different industries can be quite difficult with considerable challenges. In addition, consumer demands are also changing constantly. Consumers want affordable and immediately accessible products albeit with keen attention to factors such as origin, validity, and quality of products. Therefore, next-generation traceability has to focus on continuous monitoring, complete visibility, and transparency alongside improved agility and flexibility in manufacturing and logistics. Blockchain traceability can provide crucial support for addressing notable traceability issues evident in present times. Blockchain could offer a detailed audit trail for assets, with a consistent digital thread empowered with smart contracts and automation. 

One of many notable elements about traceability in blockchain know-how refers back to the primary design factor of blockchain. The documentation of transactions on the blockchain in an immutable, safe and verifiable approach paves the street for traceability. Blockchain can play a vital function in enhancing traceability by providing an in depth audit path of transactions on a community. 

As well as, the advantages of safety and interoperability level in direction of favorable prospects for using blockchain traceability. Whereas traceability in blockchain already has many promising use instances for various sectors, it could possibly additionally introduce next-generation traceability. Be taught extra about using blockchain for enhancing traceability proper now!

Thank you for reading!

#blockchain #cryptocurrency #technologies 

Understanding Blockchain Traceability | Ultimate Beginners Guide



















リンク:https ://javascript.plainenglish.io/3-ways-senior-developers-stay-up-to-date-with-technology-trends-859f55566cfe

#technologies  #developer 

Athul Babu

Athul Babu


Mobile App Development Company - App Development Agency

Progressive Web Apps take benefit of the most advanced technologies to combine the best of web and mobile apps. Here we will look into modern advancements in the browser and the opportunities we, as developers, have to make a new generation of web apps.
Progressive web apps could be the subsequent big thing for the mobile web. Originally introduced by Google in 2015, they have previously attracted a lot of awareness because of the comparative ease of development and the almost instantaneous wins for the application’s user experience.

Recent improvements in the browser and the availability of service workers and the Cache and Push APIs have enabled web developers to enable users to install web apps to their home screen, receive push notifications and even operate offline.Progressive web apps take advantage of the much more generous web ecosystem, plugins and community and the comparative ease of deploying and maintaining a website when compared to a native application in the respective app stores.

For those of you who develop on both mobile and web, you’ll comprehend that a website can be built in less time, that an API does not need to be managed with backwards-compatibility (all users will operate the same version of your website’s code, unlike the version fragmentation of native apps) and that the app will regularly be easier to deploy and maintain.

Why Progressive Web Apps?

A study has revealed that, on average, a mobile app loses 20% of its users for each step between the user’s initial contact with the app and the user commencing to use the app. A user must foremost discover the app in an app store, download it, install it and then, eventually, open it. When a user discovers your progressive web app, they will be capable to quickly start using it, dropping the unnecessary downloading and installation stages. And when the user returns to the app, they will be advised to install the app and update to a full-screen experience.

However, a native app is not all bad. Mobile applications with push notifications accomplish up to three times more recognition than their counterparts without a push, and a user is three times more likely to open a mobile application than a website. In addition, a well-designed mobile application employs fewer data and is much more accelerated because some resources reside on the device.A progressive web application takes benefit of a mobile app’s characteristics, ending in advanced user retention and performance, without the complications associated with maintaining a mobile application.

Features Of A Progressive Web App

Before we dive into the code, it is necessary to know that progressive web apps have the subsequent characteristics:
Progressive. By definition, a progressive web app must run on any device and improve progressively, taking benefit of any features available on the user’s device and browser.
Discoverable. Because a progressive web app is a website, it should be accessible in search engines. This is a major improvement over native applications, which still linger behind websites in searchability.
Linkable. As another characteristic obtained from websites, a well-designed website should use the URI to show the contemporary state of the application. This will allow the web app to retain or reload its state when the user bookmarks or shares the app’s URL.
Responsive. A progressive web app’s UI must be suitable for the device’s form factor and screen size.
App-like. A progressive web app should look like a native app and be built on the application shell model, with the least page refreshes.
Re-engageable. Mobile app users are more liable to reuse their apps, and progressive web apps are designed to achieve the same goals through features such as push notifications.
Installable. A progressive web app can be installed on the device’s home screen, making it immediately available.
Safe. Because a progressive web app has a more friendly user experience and because all network requests can be prevented through service workers, the app must be hosted over HTTPS to prevent man-in-the-middle attacks.


When should you develop a progressive web app? Native is normally recommended for applications that you assume users to return to frequently, and a progressive web app is not distinct. Flipkart uses a progressive web app for its traditional e-commerce platform.

When evaluating whether your next application should be a progressive web app, a website or a native mobile application, first distinguish your users and the most essential user actions. Being “progressive,” a progressive web app operates in all browsers, and the experience is heightened whenever the user’s browser is updated with new and enhanced features and APIs.

Thus, there is no give-and-take in the user experience with a progressive web app compared to a traditional website; however, you may have to determine what functionality to support offline, and you will have to expedite navigation (remember that in standalone mode, the user does not have access to the back button). If your website already has an application-like interface, employing the concepts of progressive web apps will only make it better.
If certain features are needed for important user actions but are not yet available due to a lack of cross-browser support, then a native mobile application might be the more suitable option, ensuring the same experience for all users.

Delight users and boost conversions with next-gen Progressive web app development services with Mobdev

#pwa #progressive web app #technologies #mobile #mobile-apps

Mobile App Development Company - App Development Agency
Gerhard  Brink

Gerhard Brink


Top Big Data Technologies Rising in 2021

Big Data applications are no longer a thing of the future – they are here and are steadily gaining steam globally. In this blog, we will explore different types of Big Data technologies and how they are driving success across industries.

Table of Contents

Introduction to Big Data

In the digital era, businesses generate and encounter large quantities of data on an everyday basis. “Big Data” is essentially a term used to describe this massive collection of data that exponentially increases with time. It is now imperative for companies to adopt smart data management systems if they want to extract relevant information from the vast and diverse stockpile.

According to Gartner, Big Data has the following characteristics:

  • It is high-volume and high-velocity.
  • Contains a huge variety of information assets.
  • Requires cost-effective and innovative forms of processing.
  • Enhances decision making in organisations.

Today, we are witnessing a new crop of big data companies that are utilising emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to move beyond the conventional tools of management. Let us understand their reasons for doing so.

#big data #top big data technologies #top big data technologies rising in 2021 #technologies #echnologies rising #top big data technologies rising

Top Big Data Technologies Rising in 2021

Juned Ghanchi


Technologies That Will Change Mobile App Development Completely | 5 Best Things

At this very moment, more than 1 billion smartphone devices are accommodating close to 7 million mobile apps across all the niches. The mobile apps penetrated every living space and all business niches imaginable. This could only be possible because of apps’ voracious capacity to incorporate new and innovative technologies that continue to keep coming with unique value propositions.

When location-sensing technologies such as beacons and geofencing first appeared, they quickly became part of the mobile app ecosystem. The emergence of cloud computing, Augmented Reality (AR), Virtual Reality (VR), artificial intelligence (AI), chatbots, and many other technologies just coincided with mobile app development.

Every new technology and development trend became an essential ingredient of mobile apps. Mobile apps emerged over time as the preferred playground for all tech experiments. Mobile apps also continued to become more sophisticated, richly featured, dynamically capable, and versatile thanks to these new technologies.

In recent years, the following technologies played the most crucial role in transforming mobile apps. These can also be taken as the upcoming app development trends to watch out for.

Read More: https://5bestthings.com/technologies-that-will-change-mobile-app-development-completely/

#mobile app development #app development #technologies

Technologies That Will Change Mobile App Development Completely | 5 Best Things
Tom Hopper

Tom Hopper


Companies That Use Shopify | Shopify Customers List

The most ideal approach to produce greatest leads is by making business shrewd ventures toward the beginning of the missions. The Shopify email list is an exhaustive information base that can change your mission results fundamentally and help create most extreme leads. The information is gathered from dependable sources and confirmed flawlessly to guarantee that your missions acquire the cutthroat edge. Email Data Group has a devoted group of information specialists that order the information from dependable sources and approve them through a few stages to guarantee greatest reaction rates. Additionally, the Shopify client list is stacked with consent based information for fruitful and conveyance driven missions. In the event that speedy reactions and guaranteed expectations are your mission objectives, be judicious and purchase Shopify mailing rundown and add energy to worldwide missions.
For More Information reach us at:
Call Us: (800) 710-4895
Email Us: info@emaildatagroup.net
Companies That Use Quickbooks
Companies That Use Peoplesoft
Companies Using MongoDB

#technologies #b2b

Companies That Use Shopify | Shopify Customers List
Samanta  Moore

Samanta Moore


Beginner's Guide To Java

Java is a prominent programming language that is class-based, object-oriented and is made to have minimal dependencies during execution. The language is conventionally preferred by several organizations and institutions for developing web and mobile applications, enterprise software, computing applications, Big Data Analytics, and several other features.

Founded by James Gosling in 1991, it was initially aimed at interactive television creation, which was filtered to a functional programming language in 1996 with a syntax identical to that of C and C++. Java is a swift, secure, and reliable option amongst major programming languages chosen by companies and individual developers.

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Beginner's Guide To Java