top button
Flag Notify
    Connect to us
      Facebook Login
      Site Registration Why to Join

    Get Free Article Updates

Facebook Login
Site Registration

Discussion About Rust Programming?

+1 vote
109 views

What is Rust?

Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.

Features

  • Zero-cost abstractions
  • Move semantics
  • Guaranteed memory safety
  • Threads without data races
  • Trait-based generics
  • Pattern matching
  • Type inference
  • Minimal runtime
  • Efficient C bindings

Rust is a programming language that helps you write faster, more reliable software. High-level ergonomics and low-level control are often at odds with each other in programming language design; Rust stands to challenge that. Through balancing powerful technical capacity and a great developer experience, Rust gives you the option to control low-level details (such as memory usage) without all the hassle traditionally associated with such control.

Rust is intended to be a language for highly concurrent and highly safe systems, and "programming in the large", that is, creating and maintaining boundaries that preserve large-system integrity. This has led to a feature set with an emphasis on safety, control of memory layout, and concurrency. Performance of idiomatic Rust is comparable to the performance of idiomatic C++.

Video for Rust Programming

posted Apr 9 by Sandeep Bedi

  Promote This Article
Facebook Share Button Twitter Share Button Google+ Share Button LinkedIn Share Button Multiple Social Share Button


Related Articles

What is APEX?

Apex is a proprietary language which has been developed by Salesforce.com. Apex is a strongly typed, object-oriented programming language that allows developers to execute flow and transaction control statements on the Force.com platform server in conjunction with calls to the Force.com API.

Apex Code is designed explicitly for expressing business logic and manipulating data, rather than generically supporting other programming tasks such as user interfaces and interaction. 

Apex Code is therefore conceptually closer to the stored procedure languages common in traditional database environments, such as PL/SQL and Transact-SQL. But unlike those languages, which due to their heritage can be terse and difficult to use, Apex Code uses a Java-like syntax, making it straightforward for most developers to understand. 

And like Java, Apex Code is strongly typed, meaning that the code is compiled by the developer before it is executed, and that variables must be associated with specific object types during this compile process. Control structures are also Java-like, with for/while loops and iterators borrowing that syntax directly.
Because Apex Code is a process and data language, developers will primarily interact with APIs to query, manipulate and save information in their custom and standard objects. 

Developers can select data using the existing Salesforce Object Query Language (SOQL) syntax already found in the existing Web services API, as well as a new addition to that syntax that can retrieve information from multiple objects via a single query.

Video for APEX?

https://www.youtube.com/watch?v=KFCg03JTdXs​

READ MORE

What is Delphi Programming?

Delphi is both an object oriented programming language (OOP) and an Integrated Development Environment (IDE). Published by the Embarcadero company (formerly CodeGear and more formerly Borland), Delphi is an alternative to language such as Visual Basic offering development with both rapidity and good quality.

It originated from the Pascal language, which then became Object Pascal (pascal with objects support). Delphi is based on the Object Pascal language. The IDE runs on Windows, but the compiler targets Windows, macOS, iOS, Android, and Linux. Third party add-ins provide the ability compile to JavaScript for web development.

Delphi includes the RunTime Library (RTL) that provides basic functionality across all the platforms. For Windows it provides the Visual Component Library (VCL), and for cross platform development it includes FireMonkey (FMX).

Delphi includes a code editor, a visual designer, an integrated debugger, a source code control component, and support for third-party plugins. The code editor features Code Insight (code completion), Error Insight (real-time error-checking), and refactoring. 

The visual forms designer has traditionally used Visual Component Library (VCL) for native Windows development, but the FireMonkey (FMX) platform was later added for cross-platform development. Database support in Delphi is very strong. A Delphi project of a million lines to compile in a few seconds – one benchmark gave 170,000 lines per second.

It provides interfaces for the programmer to build an application using the Extensible Markup Language (XML), Extensible Stylesheet Language (XSL), Simple Object Access Protocol (SOAP), and Web Services Description Language (WSDL).

Video for Delphi Programming

https://www.youtube.com/watch?v=IKkRI1UyLEU

 

READ MORE

**What is Math Kernal Library?**
Math Kernel Library (Intel MKL) is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math. The routines in MKL are hand-optimized specifically for Intel processors.

The library supports Intel processors and is available for Windows, Linux and macOS operating systems.

Main Categories for Math Kernal Library

  • Linear algebra: BLAS routines are vector-vector (Level 1),    matrix-vector(Level 2) and matrix matrix(Level 3) operations for real and complex single and double precision data. LAPACK consists of tuned LU, Cholesky and QR factorizations, eigenvalue and least squares solvers.  
  • MKL includes a variety of Fast Fourier Transforms   (FFTs) from 1D to multidimensional, complex to complex, real to    complex, and real to real transforms of arbitrary lengths.  
  • Vector math functions include computationally intensive core mathematical operations for single and double precision real and complex data types. These are similar to libm functions from compiler libraries but operate on vectors rather than scalars to provide better performance. There are various controls for setting accuracy, error mode and denormalized number handling to customize the behavior of the routines. 
  • Statistics functions include random number generators and probability distributions. optimized for multicore processors.    Also included are compute-intensive in and out-of-core routines to    compute basic statistics, estimation of dependencies etc. 
  • Data fitting functions include splines (linear, quadratic, cubic, look-up,    stepwise constant) for 1-dimensional interpolation that can be used in data analytics, geometric modeling and surface approximation applications. 
  • Deep Neural Network
  • Partial Differential Equations    
  • Nonlinear Optimization Problem Solvers

Video for Math Kernal Library 

https://www.youtube.com/watch?v=VI9s7Zs7Z4E

READ MORE

What is Gerrit?

Gerrit is a free, web-based team code collaboration tool. Software developers in a team can review each other's modifications on their source code using a Web browser and approve or reject those changes. 

It integrates closely with Git, a distributed version control system.

Gerrit is a fork of Rietveld, another code review tool. Both namesakes are of Dutch designer Gerrit Rietveld.
Code reviews mean different things to different people. To some it’s a formal meeting with a projector and an entire team going through the code line by line. To others it’s getting someone to glance over the code before it is committed.

Gerrit is intended to provide a lightweight framework for reviewing every commit before it is accepted into the code base. Changes are uploaded to Gerrit but don’t actually become a part of the project until they’ve been reviewed and accepted. 

In many ways this is simply tooling to support the standard open source process of submitting patches which are then reviewed by the project members before being applied to the code base. However Gerrit goes a step further making it simple for all committers on a project to ensure that changes are checked over before they’re actually applied. Because of this Gerrit is equally useful where all users are trusted committers such as may be the case with closed-source commercial development. 

Either way it’s still desirable to have code reviewed to improve the quality and maintainability of the code. After all, if only one person has seen the code it may be a little difficult to maintain when that person leaves.

Gerrit is firstly a staging area where changes can be checked over before becoming a part of the code base. It is also an enabler for this review process, capturing notes and comments about the changes to enable discussion of the change. 

This is particularly useful with distributed teams where this conversation can’t happen face to face. Even with a co-located team having a review tool as an option is beneficial because reviews can be done at a time that is convenient for the reviewer. 

This allows the developer to create the review and explain the change while it is fresh in their mind. Without such a tool they either need to interrupt someone to review the code or switch context to explain the change when they’ve already moved on to the next task.

Video for Gerrit

https://www.youtube.com/watch?v=a0xMde2GI00

READ MORE

What is Lasagne?

Lasagne is a lightweight library to build and train neural networks in Theano.

Features:

  • Supports feed-forward networks such as Convolutional Neural Networks (CNNs), recurrent networks including Long Short-Term Memory (LSTM), and any combination thereof
  • Allows architectures of multiple inputs and multiple outputs, including auxiliary classifiers
  • Many optimization methods including Nesterov momentum, RMSprop and ADAM
  • Freely definable cost function and no need to derive gradients due to Theano's symbolic differentiation
  • Transparent support of CPUs and GPUs due to Theano's expression compiler

Main Principles

  • Simplicity: Be easy to use, easy to understand and easy to extend, to facilitate use in research
  • Transparency: Do not hide Theano behind abstractions, directly process and return Theano expressions or Python / numpy data types
  • Modularity: Allow all parts (layers, regularizers, optimizers, ...) to be used independently of Lasagne
  • Pragmatism: Make common use cases easy, do not overrate uncommon cases
  • Restraint: Do not obstruct users with features they decide not to use
  • Focus: "Do one thing and do it well"

How to Install

pip install -r https://raw.githubusercontent.com/Lasagne/Lasagne/master/requirements.txt
pip install https://github.com/Lasagne/Lasagne/archive/master.zip

Video for Lasagne

https://www.youtube.com/watch?v=t22HUAnefhw
 

READ MORE

What is Keras?

Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.

Features

  • Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility).
  • Supports both convolutional networks and recurrent networks, as well as combinations of the two.
  • Runs seamlessly on CPU and GPU.

Main Benefits

  • User friendliness. Keras is an API designed for human beings, not machines. It puts user experience front and center. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error.
  • Modularity. A model is understood as a sequence or a graph of standalone, fully-configurable modules that can be plugged together with as few restrictions as possible. In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions, regularization schemes are all standalone modules that you can combine to create new models.
  • Easy extensibility. New modules are simple to add (as new classes and functions), and existing modules provide ample examples. To be able to easily create new modules allows for total expressiveness, making Keras suitable for advanced research.
  • Work with Python. No separate models configuration files in a declarative format. Models are described in Python code, which is compact, easier to debug, and allows for ease of extensibility

Python Install

pip install keras

Video for Keras

https://www.youtube.com/watch?v=4-gQBRAoVAA 

READ MORE
Contact Us
+91 9880187415
sales@queryhome.net
support@queryhome.net
#280, 3rd floor, 5th Main
6th Sector, HSR Layout
Bangalore-560102
Karnataka INDIA.
QUERY HOME
...