.NET has many project templates that allow you to quickly and efficiently scaffold applications in various contexts. In certain situations, you may need to create your project template. This article will show you how to create your template for Visual Studio and.NET CLI.

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Use templates

The use of templates can improve developer productivity and promote best practices. You have many templates as a.NET developer to help you start a project or add a new item to an existing one. These include console apps, class libraries and unit test projects. These templates can be used in Visual Studio as well as the.NET CLI. This article will be about project templates. These templates allow you to create new projects with specific features.

Visual Studio allows you to explore the project templates list by selecting the New menu option. In.NET CLI, you can use the dot net new command to work with templates. The following command will show you a list of available templates on your computer.

Dotnet new –list

Here’s an example template you can create a list for your console.

Dotnet new –list lists list of.NET templates.

 App, you can use the command dotnetnew console. This will use the template’s short name from the list. The official documentation contains a description of all the templates.

Boston website-design-development-agency new can also help with many other tasks, such as installing or uninstalling templates from the NuGet repository, your machine, and so on. It.

How to create a basic template

You will create an ASP.NET project template that uses Auth0 to authenticate. Developers use this template to create a ready-to-use Auth0-enabled starter website application.

To use the project template, you will need.NET Core 3.1 (or higher). Visual Studio 2019 starts with version 16.8 Preview, and Visual Studio 2019 Mac begins at version 8.8.

Preparing for the workplace

Let’s create a few folders before we start building the project template. Next, move to the folder and create two subfolders: templates-playground and Test.

You should have the following folder structure at the end:

templates-playground

+– Templates

+– Test

Your project template source code will be stored in the templates folder. There are many templates you can place there.

You will use the test folder to create new projects using the project template.

The project template is set up.

Boston website-design-development-agency Core template simply consists of the following:

The source files for the project

A configuration file called template.json.

This article does not require you to create a.NET project as the base for your template. Instead, you will use a pre-made project.

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So, move to the templates-playground/templates folder and clone the project from GitHub with the following commands:

cd templates-playground/templates

git clone

-b starting-point \

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auth0-web app

These commands will create the auth0-web app subfolder under your templates-playground/templates folder and clone the starting-point branch of this GitHub repository.

The project you’ll find in the folder is an ASP.NET Web application with Auth0 authentication, as mentioned previously. You can read the article Using C# Extension methods for Auth0 authentication to learn more about how this project was constructed.

Now, create a subfolder named .template.config within the project’s root folder (templates-playground/templates/auth0-web app). Next, create a new folder called template.json with the following content.

This file is essential for creating your template. This file contains meta-information which transforms your.NET projects into project templates. The example below shows the minimum properties required.

$ identifies the author of the template.

Boston website design and development company: This is the context in which you should use this template. This is an array of strings that help to classify the template. These strings will help users find your template within groups.

Identity: This is your unique identifier.

Name The template’s name as seen by the user.

ShortName: This is the template’s name to be used in dotnet new when creating new projects from it.

Tags: A list of values that defines the template’s target. This example declares that the template is intended for projects (type property) in C# (language property).

This document contains a complete list of configuration properties.

Installation of the template

You now have a functional project template. Let’s install it locally by running the following command in the templates-playground/templates/auth0-web app folder:

Dotnet new –install

This command allows the Boston website design and development company template engine (.NET) to use the current folder (.). As a template package. Later, you will learn how to make a package.

After you have installed your template, you can run dotnetnew –list. The new template should be visible among all the others, as shown in the following image:

Auth0 .NET Template listed

Awesome! You are now ready to start your first.NET project template.

Test the template

To see your project template in action, move to the templates-playground/test folder and run this command:

dotnet new auth0webapp -o myAuth0WebApp

Create a myAuth0WebApp folder containing the source files for your ASP.NET project.

You must register your application with Auth0 to ensure it is running. Then, configure the application with a few parameters. This allows application users to authenticate using Auth0.

You will need an Auth0 account to do this. Register here to get a free account.

Next, go to your Auth0 Dashboard and then to the Applications section. Follow these steps to register your account with Auth0.

Click on the Create Application button.

Give your application a friendly name (e.g., My Web Application), then select Regular Web Application as the type of application.

Click the Create button.

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Once you have created the application, go to the Settings tab. Take note of your Auth0 domain, Client ID, and Client Secret. These values will be required to configure your application to allow it to communicate to Auth0.

Then, assign the value https://localhost:5001/callback to the Allowed Callback URLs field and the value https://localhost:5001/ to the Allowed Logout URLs field. The first value tells Auth0 which URL it should call back after users authenticate. The second value tells Auth0 to which URL users should be redirected after they log off.

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To apply them, click on the Save Changes button.

After registering your application using Auth0, configure it with a few parameters via the Dashboard. Open the appsettings.json file in your ASP.NET project root folder. The contents should look something like this:

Save the file by replacing the placeholders DOMAIN and CLIENT_ID with the corresponding values in the Auth0 Dashboard.

The client secret is your password for the application. It is essential to keep it safe and not share it with others. Because the sample application will run on the server’s server, you must store the client secret in appsettings.json. Users have no access to this file.

You can now launch your application by going to:

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Once the application starts, point your browser to . The following page should appear:

Running ASP.NET application

Clicking the Login link in the upper right corner will take you to the Auth0 Universal Login Page to log in and access your user profile page. With all the Auth0 authentication logic integrated.

Add Parameters to Your Template

You have now created a project template. However, it doesn’t look fascinating as it copies the source files from the original project into a new folder. You’d like to modify the project as the templates allow.

You can modify the default behavior of the template generator by editing the template.json configuration file. You can set some settings that the user can override by passing options to dotnet new. Command.

Let’s take another look.

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You can use the dotnet command to create a new project name. This allows you, for instance, to create your global namespace. This can usually be done by using the –o option. This option was already used when you ran the following command.

dotnet new auth0webapp -o myAuth0WebApp

This command, however, created the myAuth0WebApp directory with the new project inside. You will notice that the global namespace was not changed if you look at the source code.

You must modify the template.json configuration file to conform to the expected behavior.

You have added the source name and the preferNameDirectory properties.

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The source name property is the name of your project. It represents the global namespace for the application. This property was assigned the Auth0.NET.Mvc attribute, corresponding to the current application namespace. This value acts as a placeholder and will be replaced by the value provided by the user if any.

You can match the name of the output folder with the project name using the preferNameDirectory parameter.

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 Same name as the built-in templates.

Before you test the modified template, please uninstall it using the following command.

Dotnet new -u

Add custom parameters

Your project template can be configured to accept custom parameters. You can let users of your Auth0 templates provide the Auth0 configuration parameters when creating a new project. Let’s change the template.json configuration file to the following:

The symbol property was added. It defines three custom parameters: clientId and clientSecret. These parameters are the Auth0 configuration data that you learned above.

Four properties define each parameter:

Boston website design and development services: This is the type of symbol (its parameter in this instance).

Description: A description of the value assigned to the parameter.

defaultValue is the parameter’s default value if the user does not assign it.

Replaces: This property creates a placeholder in the source code of your project template. This placeholder will be searched by the template engine and replaced with the value supplied by the user.

To test these parameters, uninstall the currently installed version of your project template and then reinstall it.

cd templates-playground/templates/auth0-webapp

Dotnet new -u

Dotnet new –i

After you have installed your template, run the following command to check its parameters:

dotnet new auth0webapp -h

You should also see the following output, in addition to the dotnet new standard options:

…Boston website design and development services

Your template can now use the three custom parameters. You will notice that the three custom parameters have been automatically assigned a shorter version.

So, move to the templates-playground/test folder, and type the following command to test this new feature:

Your application will run smoothly if the parameters are used in place of appsettings.json.

Options

You can also configure parameters that limit the number of values you allow to be used in addition to string parameters. If you want your users to choose the target framework to use in a new project, you can modify the content of your template.json as follows:

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You created a new parameter definition called Framework. This is a built-in parameter. However, the method of defining a custom parameter that has restricted values is equally valid.

The name of the parameter has been capitalized. This is a built-in parameter. You should keep it this way. Otherwise, Visual Studio may have issues with the template.

This tutorial taught you a lot of exciting things.

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You may have learned more about dotnet than you did before. It can be used to install and uninstall templates. You learned how to transform a standard.NET Project into a template project for the.NET CLI. You will also learn how to modify the project creation with custom parameters.

You have created a NuGet package to support your project template. This NuGet package can be used to share your template in Visual Studio. You also learned how to configure your project template to make it entirely usable in Visual Studio.

Recently, I wrote an article called Data Scientist, Data Engineer, and Other Data Careers Explained. In it, I tried to explain five data-related careers concisely. Each profession was briefly summarized in a single sentence. The data scientist was a reference:

Data scientists are concerned with data and the insights that can be gleaned from them and the stories it can tell.

 Boston ecommerce website design and development the paragraphs, I wrote for each profession. Aspiring data professionals could combine the five features into a flowchart.

 emphasized predictive analytics as 

This constructive criticism made me naturally think about what is different between data scientists and other data professionals. Data scientists use a variety of technical skills. Data scientists and developers.

I identified five traits. 

1. Predictive Analytics Mindset

I received a lot of criticism for this feature’s perceived importance. A predictive analytics mindset is a data scientist’s most important defining feature. It is not the only feature that defines you. It is not. It could 

 Are Non-data scientists allowed to participate? Sure. But, if I put the data scientist at one end of the predictive analysis see-saw, 

 an analytical mindset but a way of thinking that uses what we know to discover what we don’t know. Predictive is an integral part.

 essential 

We must, which is something that all other roles do not necessarily require. The predictive mindset is focused on solving for X with Y; curiosity will determine the origin of 

?”

“Boston ecommerce website design and development who wakes up every morning and goes about your day without noticing the universe’s wonders and different complex systems, which 

This is more than philosophical. They search for situation-dependent known knowns and known unknowns. Understanding that any change can have unintended consequences elsewhere, they are interested in discovering what these unknowns could be.

 Possible about the systems they work with. They must also use their curiosity and predictive analytical mindset to account for as many systems’ interactions and operations as possible. This will ensure that systems. 

We’re now at the “thinking outside understand the problem well, 

This is not diminishing domain experts. The reverse is true. Data scientists serve as their support and bring a range of skills that are trained to do what they do. This will allow us to offer a fresh perspective to help domain experts. When combined with curiosity, this creativity will allow them to ask questions and find answers.

We need the technical, statistical and other skills to answer these questions. But these skills will not be helpful if we lack the creativity to find exciting and non-obvious methods to probe and provide answers. Data scientists need to be creative.

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 — possibly with visuals or other props that help to close the deal.

This storytelling isn’t like fiction storytelling. It’s more like “fancy explaining,” which provides an intuitive explanation that the listener can understand. A five-year-old wouldn’t be able to read a Stephen King story at bedtime. The same goes for someone who works in research and development. Pay attention to your audience.

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The storytelling is not persuasive, and it’s just explanatory. Data scientists are not data politicians. Scientists who misrepresent stats to manipulate others will never get anything good. That is up to elected officials.

Hopefully, this has helped paint a picture of the critical traits I consider essential for a data scientist—all the best to you as you continue your career.

Related:

Data Scientist, Data Engineer, and Other Data Careers Explained

A guide to 14 different data science jobs

Data Science Portfolio Ideas That Can Get You Hired (or Not)

R was not Python, which I opposed for a long time.

Boston website design and development agency playing with R for a few months, I discovered that R outclasses Python for many use cases, especially for statistical analyses. R also has powerful packages developed by some of the most important tech companies in the world, which are not available in Python.

So, this article will cover three R packages that I strongly recommend you learn and equip in your arsenal. They are powerful tools.

Here are three R packages every data scientist needs to know, even if you only use Python:

Causal Impact w/ Google

Robyn w/ Facebook

Twitter – Anomaly Detection

1. Causal Impact (Google)

Let’s suppose your company launches a TV commercial for the Super Bowl. They want to know how it affects conversions. The counterfactual is a method of predicting what would happen if the campaign had never happened. Happen if it did.

Three R Libraries Every Data Scientist Needs to Know (Even If You Use Python).

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 what Causal Impact does) and gives an example. The blue dotted line is the top graph. It then compares the counterfactual with the actual values to calculate the delta.

Marketing initiatives, expansion to new areas, testing new product features and other activities that involve causal Impact are all possible with the help of causal Impact.

2. Robyn (Facebook)

Marketing Mix Modelling, a new technique that estimates the effect of multiple marketing channels or campaigns on a target variable like conversions or sales, is called Marketing Mix Modelling.

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Marketing Mix Models (MMMs), which allow you to measure and quantify the Impact of multiple channels such as TV, billboards, radio, and television, are more popular than attribution models.

Marketing Mix Models can take several months to create from scratch. Facebook has created Robyn, a new R package that allows you to create a strong MMM in just minutes.

Three R Libraries Every Data Scientist Needs to Know (Even If You Use Python).

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The author created the image.

Robyn can help you evaluate the effectiveness of each marketing channel and optimize your marketing budget.

Subscribe to my newsletter to receive the latest data science tips and tricks, life lessons and other helpful information.

3. Twitter: Anomaly Detection

Anomaly detection (also known as outlier analysis) is a technique that identifies data points with significant differences from the rest.

Boston modern website design and development subset of general anomaly detectors is anomaly detection using time-series data. This is a unique problem as you must also consider the trend and seasonality.

Three R Libraries Every Data Scientist Needs to Know (Even If You Use Python).

The author created the image.

Twitter has created an anomaly detection package to solve this problem. This algorithm can detect both local and global anomalies. It can be used to detect anomalies within a vector of values, as well as time series.

Thank you for reading!

You enjoyed this article. Subscribe to my newsletter for more data science tips, tricks, and life lessons.

Are you unsure what article to read next? Here’s another article: The 10 Best Data Visualizations for 2021

Another one: All Machine Learning Algorithms That You Must Know by 2022

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Bio: Terence Shin, a data enthusiast with more than three years of experience in SQL and two years in Python, is a blogger at Towards Data Science (KDnuggets).

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Many programming languages are on the market, and choosing the right one can be difficult when starting your startup. You should choose a programming language carefully and have sound reasons. Some programming languages may not be suitable for your business.

Before choosing a programming language, startups should carefully consider its popularity, cost, speed of development and integrations. Because Python fulfills all of these requirements, it is often considered one of the most popular startup programming languages.

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This blog will explain why Python is so popular and its features.

Python is a very popular

Python, which has been on the market for over 30 years, is gaining more respect from developers all around the globe. Can build robust and scalable applications. Python allows companies to develop many applications, including web apps, game development, network programming and graphical user interfaces (GUIs), and numeric and scientific applications.

Boston custom website design and development, Programming Community Index ranked Python as the most popular programming language worldwide as of November 2021.

What makes Python an ideal programming language for startups?

The RedMonk Language Rankings ranked Python second in June 2021, just behind JavaScript. RedMonk Language Rankings evaluates language usage based on Stack Overflow, GitHub and other factors. Significant dependencies on Python are common among tech giants such as Google, Facebook and Spotify.

Boston custom website design and development, usage, and reports demonstrate that Python is still in high demand. It is also one of the most preferred programming languages by entrepreneurs and companies around the globe for their development projects. Let’s now see why Python is considered the best programming language for startups.

8 Reasons to Choose Python for Your Startup

Let’s explore why Python is an excellent choice for startups.

Highly Scalable

Startups require growing flexibility, and Python allows you to scale your business applications. Python is an object-oriented programming language that supports many programming styles. Django is a popular framework for Python businesses that allows them to create high-scalability apps that are easy and maintainable. The Django framework is made up of several components that can be separated. This allows the components to be easily modified, removed and even replaced according to the project’s needs.

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Popular

Python is the fastest-growing programming language, and it has gained considerable popularity. Python code is used by major league players such as Google, Quora and Instagram. You must have now understood the immense popularity of Python.

Simple & user-friendly

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Python is much simpler than other programming languages, such as C++ and Java. The code base is clean and well-structured, making it easier for developers to maintain and update the applications. It is one of the most intuitive languages in the developer community.

Multifunctional

Boston website design and development companies is compatible with all major operating systems and architectures. It is a multipurpose language used in many projects, from web development to data analysis. It is compatible with Windows, Linux and UNIX. Python can be used for various applications, including web applications and science, machine learning (ML) and other big-data computing systems. A significant factor in Python’s growth as a programming language is the rise of machine learning and data science.

All Business Intelligence

All Business Intelligence

Silver BlogWhy Python is the Ideal Programming Language for Startups

This blog will explain why Python is so popular and its features.

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By Nikita Bajaj, Digital Marketing Lead

What makes Python an ideal programming language for startups?

Many programming languages are on the market, and choosing the right one can be difficult when starting your startup. You should choose a programming language carefully and have sound reasons. Some programming languages may not be suitable for your business.

Before choosing a programming language, startups should carefully consider its popularity, cost, speed of development and integrations. Because Python fulfills all of these requirements, it is often considered one of the most popular startup programming languages.

This blog will explain why Python is so popular and its features.

Python is a very popular

Boston website design and development companies, which has been on the market for over 30 years, is gaining more respect from developers all around the globe. Python is an object-oriented, high-level programming language that can build robust and scalable applications. Python allows companies to develop many applications, including web apps, game development, network programming and graphical user interfaces (GUIs), and numeric and scientific applications.