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1. Intro NumPy has helpful methods to create an array from text files like CSV and TSV. In real life our data often lives in the file system, hence these methods decrease the development/analysis time dramatically. numpy.loadtxt(fname, dtyp

1. Intro We can learn about creating a NumPy array from plain text files like CSV, and TSV in another tutorial . In this tutorial, we will see methods that help us in saving the NumPy array on the file system. We can further use them to cre

1. Intro In this tutorial, we will learn various ways to create a NumPy array from the Python structure like the list, tuple, and others. It will be helpful in use cases where we want to leverage the power of NumPy operations on existing da

Every algorithm which solves useful problems has one or many data structures. Data structures are mechanisms to keep data (primitive data type) arranged inside a computer's memory in some structure. They help algorithms to meet efficiency w

AWS DynamoDB is a managed NoSQL document database service. It's a proprietary NoSQL database created by AWS. Amazon uses it on its eCommerce website. Hence its performance and scalability are proven. I have used it in a high volume data pro

In this article, we will learn how a react UI is wired in an HTML page (an index page) and display Hello World text in a paragraph. We had already learned about basic setup, JSX, and ES6 concepts in an earlier tutorial . This tutorial is ve

As per React website, It is a declarative, flexible, and efficient JavaScript Library for web user interface development. In this tutorial, we will learn how to get started with this framework and at the end of it, we will be able to set up

In this tutorial, we will learn basic concepts of algorithms and their application. We will also learn about Pseudo Code. Introduction The algorithm is not a concept unique to computation. It is everywhere. Even we use it knowingly or unkno

In this tutorial, we will learn how to set up Apache Spark for local development and get started with Java applications. We will use an Apache log file to show a few basic RDD operations. Tools & Libraries used: Apache spark 2.1.1 Gradl

Big Data has come a long way. Apache spark is one of the fastest big data computational engines. We will answer often asked questions about the basics of Apache Spark in this article. What problems Apache Spark solves and how does it solve

Typically mobile web apps really suck!! They are slow and sluggish and the situation could get even worse with shaky internet connectivity. Hence, businesses and app developers are more inclined toward building native apps (including hybrid

JSON (JavaScript Object Notation) is the most used structured data interchange format of the current generation. It is very common for REST clients to use it for data exchange. Several web client frameworks (e.g. AngularJS) natively handle

Jersey (JAX-RS) supports multiple files upload. A dynamic number of files can also be uploaded. In this tutorial we will solve the following problems: Upload more than one file. Upload dynamic numbers of files. Support to upload multiple fi

Jersey provides an easy mechanism to let clients upload files to the server. In this tutorial, we will learn a single file upload to Jersey (JAX-RS) endpoint. 1. Include Jersey media multipart dependency in Gradle File: build.gradle (snippe

In Spring Boot support for Jersey is provided by org.springframework.boot:spring-boot-starter-jersey Gradle dependency. When the static file URL pattern is matched with URLs that Jersey handles, additional configurations are required for Sp

There are multiple ways for consuming HTML form data (application/x-www-form-urlencoded) in Jersey. Using @FormParam annotation we can inject Form values in the Resource method. We can use it just like other @*Param. Jersey resource method

It will reduce our code and improve readability, if we define injections of various @*Param values in a distinct class and reuse that in various resources. In Jersey (JAX-RS) we can achieve same using @BeanParam injection. Aggregate @*Param

In Jersey (JAX-RS), to consume HTTP request parameter, cookie, header, path variable and matrix parameter string values, we have following options: Primitive types - int, char, float, long, double, byte and others. Types with constructor wh

URL with matrix URI looks like: https://www.example.com/map;lat=50;long=20;scale=32000 ;lat=50;long=20;scale=32000 represents matrix parameters. Please refer W3C article on it . Using @MatrixParam annotation we can get matrix parameters val

Usually, RESTful web services will not use request cookies. There might be some cases where we need it. We had tested or used the following tools and technologies in this project: Jersey (v 2.21) Gradle Build System (v 2.9) Spring Boot (v 1