.NET Foundation Election 2021 Nominations are Open!

.NET Foundation Election 2021 Nominations are Open!

It’s that time of the year again, dear friends – nominations are now open for the 2021 .NET Foundation Election! On behalf of the Board and Nomination Committee, we would like to welcome all of you to participate in whatever way you can: by applying as a candidate yourself, suggesting somebody else, or simply preparing to vote and help spread the word.

As a board member, you get to influence and shape the future of one of the biggest platforms there is—.NET—and everything it entails. You won’t be doing this alone. You’ll be working side by side with other passionate souls on the board, committees, TSG, Microsoft, community members, and more. You can review the expectations for board members here.

We’ve made a few changes over the years as we’ve learned and grown with the community’s help, and last year we started with a staggered election to avoid swapping out everybody on the board. Therefore, this year we’ll select three new board members this time around, for a period of 1 or 2 years. We also decided to introduce a Nomination Committee to help with the process and narrow down the final list of candidates.

If you have any questions or concerns, please reach out to the Nomination Committee, as we are here to help. As a reminder, the Nomination Committee members have volunteered their time and are not current board members or candidates.

The nomination period closes on July 23rd.

Full Responsive Side Navigation For React using react-pro-sidebar

Description:

A fully customizable and responsive side navigation component for React, which comes with drop-down menus, nested sub-menu etc. This component is used by thousands of apps.

Features:

RTL support.
Unlimited number of nested sub menus.
Fully customizable as per your need.
Supports drop-down menus.
Supports custom styling.

How to use it?

1. You will need to install the component using npm or yarn.

#npm
npm install react-pro-sidebar

#yarn
yarn add react-pro-sidebar

2. Import the side navigation component, like this:

import { ProSidebar, Menu, MenuItem, SubMenu } from ‘react-pro-sidebar’;
import ‘react-pro-sidebar/dist/css/styles.css’;

3. React code to create side menu.

<ProSidebar>
<Menu iconShape=”square”>
<MenuItem icon={<FaGem />}>Dashboard</MenuItem>
<SubMenu title=”Components” icon={<FaHeart />}>
<MenuItem>Component 1</MenuItem>
<MenuItem>Component 2</MenuItem>
</SubMenu>
</Menu>
</ProSidebar>;

4. If you want then, you can create sidebar layout.

import { ProSidebar, SidebarHeader, SidebarFooter, SidebarContent } from ‘react-pro-sidebar’;

<ProSidebar>
<SidebarHeader>
{/**
* You can add a header for the sidebar ex: logo
*/}
</SidebarHeader>
<SidebarContent>
{/**
* You can add the content of the sidebar ex: menu, profile details, …
*/}
</SidebarContent>
<SidebarFooter>
{/**
* You can add a footer for the sidebar ex: copyright
*/}
</SidebarFooter>
</ProSidebar>;

The post Full Responsive Side Navigation For React using react-pro-sidebar appeared first on Lipku.com.

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Create Multi-level Side Navigation for React Project

Description:

Create beautiful minimal multi-level side navigation for your React project and its clean and easy to implement in your project.

How to use it?

1. You will need to install the component using npm or yarn like this:

#npm
npm install react-minimal-side-navigation

#yarn
yarn add react-minimal-side-navigation

2. Import the side navigation component.

import React from ‘react’;
import {Navigation} from ‘react-minimal-side-navigation’;
import ‘react-minimal-side-navigation/lib/ReactMinimalSideNavigation.css’;

3. Now create the side navigation bar using React code, like following.

function App() {
return (
<>
<Navigation
// you can use your own router’s api to get pathname
activeItemId=”/management/members”
onSelect={({itemId}) => {
// maybe push to the route
}}
items={[
{
title: ‘Dashboard’,
itemId: ‘/dashboard’,
// you can use your own custom Icon component as well
// icon is optional
elemBefore: () => <Icon name=”inbox” />,
},
{
title: ‘Management’,
itemId: ‘/management’,
elemBefore: () => <Icon name=”users” />,
subNav: [
{
title: ‘Projects’,
itemId: ‘/management/projects’,
// Requires v1.9.1+ (https://github.com/abhijithvijayan/react-minimal-side-navigation/issues/13)
elemBefore: () => <Icon name=”cloud-snow” />,
},
{
title: ‘Members’,
itemId: ‘/management/members’,
elemBefore: () => <Icon name=”coffee” />,
},
],
},
{
title: ‘Another Item’,
itemId: ‘/another’,
subNav: [
{
title: ‘Teams’,
itemId: ‘/management/teams’,
},
],
},
]}
/>
</>
);
}

The post Create Multi-level Side Navigation for React Project appeared first on Lipku.com.

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Adding blog posts to your GitHub README with GitHub Actions

This article will discuss about adding your blog posts to your Github readme with Github Actions. You can add a README file to a repository to communicate important information about your project. You can find for more details about the GitHub readme from here

I was looking into some automation aspect related to GitHub readme automation – I was looking into some solution using Azure Functions and Logic Apps. And I found few solutions as well. But later I found one simple solution using GitHub Actions. Here is the GitHub Action which will run every day and use your blog RSS feed and update your Readme file.

You can create an GitHub Action and add the following code.

name: Blog posts on ReadMe
on:
schedule:
# Runs every day at 9am UTC
cron: 0 4 * * *’

jobs:
build:
# The type of runner that the job will run on
runs-on: ubuntu-latest

# Steps represent a sequence of tasks that will be executed as part of the job
steps:
uses: actions/[email protected]
name: Get RSS Feed
uses: kohrongying/[email protected]
with:
feed_url: https://dotnetthoughts.net/feed
count: 10
name: Commit file changes
run: |
git config –global user.name ‘anuraj’
git config –global user.email ‘[email protected]
git add .
git diff –quiet –cached || git commit -m “Update README”
name: Push changes
uses: ad-m/[email protected]
with:
github_token: ${{ secrets.GITHUB_TOKEN }}

And here is the screenshot of the GitHub Action running.

And here is the Updated Readme file.

This way you will be able to update your blog posts automatically in to your GitHub readme file with the help of GitHub Actions.

Happy Programming 🙂

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Building Minimal APIs In .NET 6

Around 6-ish years ago, NodeJS really hit it’s peak in popularity. In part, it was because people had no choice but to learn Javascript because of the popularity of front end JS frameworks at the time, so why not learn a backend that uses Javascript too? But also I think it was because of the simplicity of building API’s in NodeJS.

Remember at the time, you were dealing with .NET Framework’s bloated web template that generated things like an OWIN pipeline, or a global.asax file. You had things like MVC filters, middleware, and usually we were building huge multi tier monolithic applications.

I remember my first exposure to NodeJS was when a company I worked for was trying to build a microservice that could do currency conversions. The overhead of setting up a new .NET Framework API was overwhelming compared to the simplicity of a one file NodeJS application with a single endpoint. It was really a no brainer.

If you’ve followed David Fowler on Twitter at any point in the past couple of years, you’ve probably seen him mention several times that .NET developers have a tendency to not be able to create minimal API’s at all. It always has to be a dependency injected, 3 tier, SQL Server backed monolith. And in some ways, I actually agree with him. And that’s why, in .NET 6, we are getting the “minimal API” framework to allow developers to create micro APIs without the overhead of the entire .NET ecosystem weighing you down.

Getting Setup With .NET 6 Preview

At the time of writing, .NET 6 is in preview, and is not currently available in general release. That doesn’t mean it’s hard to set up, it just means that generally you’re not going to have it already installed on your machine if you haven’t already been playing with some of the latest fandangle features.

To get set up using .NET 6, you can go and read out guide here : https://dotnetcoretutorials.com/2021/03/13/getting-setup-with-net-6-preview/

Remember, this feature is *only* available in .NET 6. Not .NET 5, not .NET Core 3.1, or any other version you can think of. 6.

Introducing The .NET 6 Minimal API Framework

In .NET 5, top level programs were introduced which essentially meant you could open a .cs file, write some code, and have it run without namespaces, classes, and all the cruft holding you back. .NET 6 minimal API’s just take that to another level.

With the .NET 6 preview SDK installed, open a command prompt in a folder and type :

dotnet new web -o MinApi

Alternatively, you can open an existing console application, delete everything in the program.cs, and edit your .csproj to look like the following :

<Project Sdk=”Microsoft.NET.Sdk.Web”>
<PropertyGroup>
<TargetFramework>net6.0</TargetFramework>
</PropertyGroup>
</Project>

If you used the command to create your project (And if not, just copy and paste the below), you should end up with a new minimal API that looks similar to the following :

using Microsoft.AspNetCore.Builder;

var builder = WebApplication.CreateBuilder(args);
var app = builder.Build();

app.MapGet(“/hello”, () => “Hello, World!”);

app.Run();

This is a fully fledged .NET API, with no DI, no configuration objects, and all in a single file. Does it mean that it has to stay that way? No! But it provides a much lighter weight starting point for any API that needs to just do one single thing.

Of course, you can add additional endpoints, add logic, return complex types (That will be converted to JSON as is standard). There really isn’t much more to say because the idea is that everything is simple and just works out of the box.

Adding Dependency Injection

Let’s add a small addition to our API. Let’s say that we want to offload some logic to a service, just to keep our API’s nice and clean. Even though this is a minimal API, we can create other files if we want to right?!

Let’s create a file called HelloService.cs and add the following :

public class HelloService
{
public string SayHello(string name)
{
return $”Hello {name}”;
}
}

Next, we actually want to add a nuget package so we can have the nice DI helpers (Like AddSingleton, AddTransient) that we are used to. To do so, add the following package but ensure that the prerelease box is ticked as we need the .NET 6 version of the package, not the .NET 5 version.

Next, let’s head back to our minimal API file and make some changes so it ends up looking like so :

using Microsoft.AspNetCore.Builder;
using Microsoft.AspNetCore.Http;
using Microsoft.Extensions.DependencyInjection;

var builder = WebApplication.CreateBuilder(args);
builder.Services.AddSingleton<HelloService>(new HelloService());

var app = builder.Build();

app.MapGet(“/hello”, (HttpContext context, HelloService helloService) => helloService.SayHello(context.Request.Query[“name”].ToString()));

app.Run();

Here’s what we’ve done :

We added our HelloService as a dependency to our service collection (Much like we would with a full .NET API)
We modified our API endpoint to inject in our HttpContext and our HelloService
We used these to generate a response out, which should say “Hello {name}”. Nice!

We can obviously do similar things if we wish to load configuration. Again, you’re not limited by using the minimal API template, it’s simply just a way to give you an easier boilerplate for micro APIs that don’t come with a bunch of stuff that you don’t need.

Taking Things Further

It’s very early days yet, and as such, the actual layout and code required to build minimal API’s in .NET 6 is changing between preview releases. As such, be careful reading other tutorials out on the web on the subject, because they either become outdated very quickly *or* more often than not, they guess what the end API will look like, and not what is actually in the latest release. I saw this a lot when Records were introduced in C# 9, where people kinda “guessed” how records would work, and not how they actually did upon release.

So with that in mind, keep an eye on the preview release notes from Microsoft. The latest version is here : https://devblogs.microsoft.com/aspnet/asp-net-core-updates-in-net-6-preview-6/ and it includes how to add Swagger to your minimal API. Taking things further, don’t get frustrated if some blog you read shares code, and it doesn’t work, just keep an eye on the release notes and try things as they come out and are available.

Early Adopter Bonus

Depending on when you try this out, you may run into the following errors :

Delegate ‘RequestDelegate’ does not take 0 arguments

This is because in earlier versions of the minimal framework, you had to cast your delegate to a function like so :

app.MapGet(“/”, (Func)(() => “Hello World!”));

In the most recent preview version, you no longer have to do this, *but* the tooling has not caught up yet. So building and running via Visual Studio isn’t quite working. To run your application and get past this error, simply use a dotnet build/dotnet run command from a terminal and you should be up and running. This is actually a pretty common scenario where Visual Studio is slightly behind an SDK version, and is just what I like to call an “early adopter bonus”. If you want to play with the latest shiny new things, sometimes there’s a couple of hurdles getting there.

The post Building Minimal APIs In .NET 6 appeared first on .NET Core Tutorials.

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PyCharm 2021.2 EAP 4 is out!

With PyCharm 2021.2 EAP 4, we’ve concentrated on small details and final bug fixes before the major PyCharm 2021.2 release. One of the improvements in this version is the ability to work with the SciView tool window when you are behind a proxy. The team also worked on improving support for literal collections.

Important! PyCharm EAP builds are not fully tested and might be unstable.

The Toolbox App is the easiest way to get the EAP builds and keep both your stable and EAP versions up to date. You can also manually download the EAP builds from our website.

DOWNLOAD PYCHARM 2021.2 EAP

Python 3.10: Pattern Matching

We are continuing to develop support for PEP 634 (Pattern Matching). In this EAP release, we’ve added smart code completion for the “match” and “case” keywords, to help you deal with pattern matching statements in the right way. Additionally, PyCharm can now complete “match” statements and their corresponding “case” blocks. Once you’re done typing an initial “match” statement, you can choose Complete Current Statement (⇧⌘⏎ ) and PyCharm will complete the remaining part, including the semicolon and the first part of the “case” block. The caret will be left in place for you to start typing the rest of the “case” block.

Literal collections

PyCharm’s type checker now can identify literal collections in expected types while comparing the expected and actual types for statements. This makes it possible to use collections of literals as actual types for the comparison, which means you can provide specific values for arguments. This works even for nested collections.

Notable bug fixes:

Data Science: the SciView tool window is now available when working from behind a proxy [PY-39763].
Debugger: enabling Jupyter Exception Breakpoint no longer leads to an error when debugging Python files [PY-34427].
Console: running a file in console no longer affects the Run/Debug configuration [PY-36063].
Python & Debug consoles: you can now use the Interrupt action (Ctrl + C) [PY-49021].
Community contribution: thanks to Xuan Wu, the test runner now recognizes testing method names in Unicode [PY-48747].

Ready to join the EAP?

Some ground rules

EAP builds are free to use and expire 30 days after the build date.
You can install an EAP build side by side with your stable PyCharm version.
These builds are not fully tested and can be unstable.
Your feedback is always welcome. Please use our issue tracker and make sure to mention your build version

How to download

Download this EAP from our website. Alternatively, you can use the JetBrains Toolbox App to stay up to date throughout the entire EAP. If you’re on Ubuntu 16.04 or later, you can use snap to get PyCharm EAP and stay up to date.

The PyCharm team

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Uszipcode: Best Module To Find Zip Codes in Python

The post Uszipcode: Best Module To Find Zip Codes in Python appeared first on Python Pool.

In Python, we can build many day-to-day use applications. These applications can either be GUI-based applications based on Tkinter or PyQt5 or Web applications based …

Read more

The post Uszipcode: Best Module To Find Zip Codes in Python appeared first on Python Pool.

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Python NumPy empty array with examples

In this Python tutorial, we will discuss Python NumPy empty array with a few examples like below:

Python numpy empty array append
Python numpy array empty check
Python empty numpy array without shape
Python numpy empty 2d array
Python numpy concatenate empty array
Python numpy declare empty array
Python numpy empty string array
Python numpy empty 3d array
Python fill empty numpy array
Python Create Empty Numpy array and append rows
Python Create Empty Numpy array and append Columns

Python numpy empty array

In this section, we will discuss Python numpy empty array, specially how to create an empty array using Python NumPy.
In this method we can easily use the function np.empty().
The Python NumPy empty() function is used to create a new array of given shape and type, without initializing entries.
To work with arrays, the python library provides a numpy empty array function. It is used to create a new empty array as per user instruction means given data type and shape of array without initializing elements.
It accepts shape and data type as arguments. If data type argument is not provided then the default data type of all Values in the returned numpy array will be float.

Syntax:

Here is the Syntax of numpy.empty()

numpy.empty
(
shape,
dtype=float,
order=’C’
)

It Consists of few parameters.

Shape: Shape of the empty array, e.g:(4,3)

dtype: its an optional parameter by default value is float.

order: Whether to store multi-dimensional data in row and column-wise.

Example:

Let’s take an example to check how to implement a numpy empty array
Basically there are two ways to check numpy empty array.
Using numpy empty array function.
Using numpy zero’s array function

Using numpy empty array function

In this method, we implement a NumPy array empty function. But empty does not mean that the array values will be zeros.

import numpy as np

arr = np.empty(5)
print(arr)

In the above example, we implement a simple NumPy empty array and it returns uninitialized values with shape and data type.

Here is the Screenshot of the following given code

Python numpy empty array

To create a NumPy empty array, we can pass the empty list to the np.array() function and it will make the empty array.

Example:

import numpy as np

list = []
arr = np.array(list)
print(arr)

Here is the Screenshot of the following given code

Create numpy empty array

This is how to create an empty array using Python NumPy.

Using numpy zero’s array function

In this method, we implement a numpy zero’s array function.
This function returns a new array of given shape and type, with zeros.

Syntax:

Here is the Syntax of numpy zeros() function

numpy.zeros
(
shape,
dtype = None,
order = ‘C’
)

Example:

import numpy as np

arr = np.zeros([2,2],dtype=’int’)
print(arr)

Here is the Screenshot of the following given code

Python numpy empty array by using zeros

This is how to create a NumPy array by using zeros.

Read Python NumPy Random + Examples

Python numpy empty array append

In this section, we will discuss Python numpy empty array append.
In this method we can easily use the function numpy.append().
The Numpy append function allows us to add new values to the end of an existing NumPy array.
This function returns a copy of the existing array with the values appended to the specified axis.
If we have an empty array and want to append new rows to it inside a loop, we can use the numpy.empty() function.
After that we can then append new rows to the empty array with numpy.append() function.

Example:

Let’s take an example to check how to implement a numpy empty array with append.

import numpy as np

arr = np.empty((0,3), int)

arr2 = np.append(arr, np.array([[2,4,5]]), axis=0)
array = np.append(arr2, np.array([[7,8,9]]), axis=0)

print(array)

In the above example first, we will create an empty array by using the function np. empty() and define its datatype. After that, we appended two rows along the 0 axes by using the function numpy.append()

Here is the Screenshot of the following given code

Python numpy empty array append

Read Python NumPy zeros

Python numpy empty array append example

In this section, we will discuss Python numpy empty array append.
In this method we can easily use the list method to append with numpy empty array.
The list.append() function appends an element to the end of the list.
We can then convert this list to a numpy array with np.array() function.

Example:

import numpy as np

list = []
list.append([2,4,6])
list.append([9,5,7])
arr2 = np.array(list)
print(arr2)

Here is the Screenshot of the following given code

Python numpy empty array append list method

Python numpy array empty check

If you want to check if a NumPy array is empty or not, follow an article on Check if NumPy Array is Empty in Python.

Python empty numpy array without shape

In this section, we will discuss Python empty numpy array without shape.
In this method we can easily use the function append() to get the empty numpy array without shape.
First we will create a python list and convert that to a numpy array and take a variable y which is iterable.
It doesn’t accepts shape and datatype as an argument.

Example:

import numpy as np
y=[]
a = np.array([2,3,4,5])
for x in y:
a = np.append(a, x)
print(y)

Here is the Screenshot of the following given code

Python empty numpy array without shape

The above code we can use to create empty NumPy array without shape in Python.

Read Python NumPy nan

Python numpy empty 2d array

In this section, we will discuss Python numpy empty 2d array.
To create an empty 2D Numpy array we can pass the shape of the 2D array ( i.e. row & column count) as a tuple to the empty() function.
In this method we can easily use the function numpy.empty().
It accepts shape and data type as arguments.
It returns an empty 2d numpy array of rows and columns but all values in this 2d numpy array were not initialized.
In this method we did not provide datatype as an argument by default it takes value as float.

Syntax:

numpy.empty
(
shape,
dtype=float,
order=’C’
)

Example:

import numpy as np
arr = np.empty((4, 3), int)
print(‘Empty 2D Numpy array:’)
print(arr)

In the above example first, we will import the numpy library and create an empty 2d numpy array with 4 rows and 3 columns and print the result.

Here is the Screenshot of the following given code

Python numpy empty 2d array method

This is how to create an empty 2D Numpy array in Python.

Read Valueerror: Setting an array element with a sequence

Python Create a numpy empty 2d array

To create an empty array in Numpy 2d array we use column and row in shape argument.
Let’s use these two functions to create an empty 2D Numpy array and append items to it as rows or columns.
In this method create an empty array with 3 columns or 0 rows.

Example:

import numpy as np

arr = np.empty((0, 3), int)
print(‘Empty 2D Numpy array:’)
print(arr)

Here is the Screenshot of the following given code

Python creates a numpy empty 2d array

Python numpy concatenate empty array

In this section, we will discuss Python numpy concatenate empty array.
We need to create an array of a specific size m*n where m is the number of rows and n is number of columns filled with empty values so that when we concatenate to that array the initial values.
In this method we can easily use the function numpy.concatenate().
This function is used to join two or more given NumPy arrays along the existing axis.
The np.concatenate() function appends an element to the end of the list.
In this method we can easily use the both function np.concatenate and np.empty() to get the empty array.

Example:

import numpy as np
a = np.empty([2,2])
b = np.array([[4,5],[6,7]])
arr = np.concatenate((a,b))
print(arr)

Here is the Screenshot of the following given code

Python numpy concatenate empty array

The above code we can use to concatenate empty array in Python NumPy.

Read Python NumPy Average with Examples

Python numpy declare empty array

In this section, we will discuss Python numpy declare empty array.
In this method we can easily use the function numpy.empty().
The empty() function is used to create a new array of given shape and type, without initializing entries.

Syntax:

Here is the Syntax of numpy.empty()

numpy.empty
(
shape,
dtype=float,
order=’C’
)

Example:

To Declare an empty NumPy array of some specific data type, we can pass that data type as a dtype argument in the empty() function.

import numpy as np
a = np.empty([2,2], dtype= complex)
print(a)

In the above example, we will create an empty numpy array of complex numbers, we need to pass complex as dtype argument in the numpy.empty() function.

Here is the Screenshot of the following given code

Python numpy declare empty array

This is how to declare empty array using Python NumPy.

Declare numpy empty array in Python

To create an empty NumPy array of integers, we need to pass int as dtype argument in the numpy.empty() function.

Example:

import numpy as np
a = np.empty([3,3], dtype= ‘int’)
print(a)

In the above example, we will create an empty NumPy array of integers numbers, we need to pass int as dtype argument in the NumPy.empty() function.

Here is the Screenshot of the following given code

Python numpy declare empty array integer method

This is how to create an empty NumPy array of integers.

Read Python NumPy absolute value with examples

Python numpy empty string array

In this section, we will discuss Python numpy empty string array.
To create an empty numpy array of strings we can easily use the function numpy.empty().
To create an empty numpy array of 4 strings (with size 3), we need to pass ‘S3’ as dtype argument in the numpy.empty() function.
It accepts shape and data type as arguments.

Example:

Let’s take an example to check how to create a numpy empty string array

import numpy as np

array = np.empty(4, dtype=’S3′)
print(array)

Here ‘S3’ translates to “Unicode string of length 3

Here is the Screenshot of the following given code

Python numpy empty string array

The above code we can use to create an empty string array in Python using NumPy.

Python numpy empty 3d array

In this section, we will discuss Python numpy empty 3d array.
To create an empty 3D Numpy array we can pass the shape of the 3D array as a tuple to the empty() function.
In this method we can easily use the function numpy.empty() to get the empty 3d array.
Let’s create a empty 3D Numpy array with matrix of 3 rows and 3 columns.
In this method we didnot provide any datatype argument. But all values in this 3D numpy array were not initialized.

Example:

import numpy as np

array = np.empty((1, 3, 3)) # where 1 is the length of matrix
print(array)

In the above example first, we will import a numpy library and create an empty array in which we assign an argument as the length of the matrix which is 1 and no of rows and columns.

Here is the Screenshot of the following given code

Python numpy empty 3d array

This is an example of a Python NumPy empty 3d array.

Read Python NumPy square with examples

Python fill empty numpy array

In this section, we will discuss Python fill empty numpy array.
In this method we can easily use the function numpy.empty().
When you create an array with np.empty, you need to specify the exact shape of the output by using the shape parameter.
Let’s create an empty array and use the function a.fill().

fill() method is used to fill the numpy array with a scalar value.
In this method we didnot need to use loops to initialize an array if we are using this fill() function.

Example:

import numpy as np

a = np.empty(4)
a.fill(3)
print(a)

Here is the Screenshot of the following given code

Python fill empty numpy array

The above code we can use to fill empty NumPy array in Python.

Python Create an Empty Numpy array and append rows

In this section, we will discuss Empty Numpy array and append rows.
In this method, first we will create an empty numpy array with 4 columns and 0 rows.
Now to append a new row to this empty 2D Numpy array, we can use the numpy.append().
But we need to pass the row as a numpy array of same shape only, and pass axis=0, so that it can be appended along the column.

Example:

import numpy as np

arr = np.empty((0, 4), int)
print(‘Empty 2D Numpy array:’)
print(arr)
# Append a row to the 2D numpy array
emp_arr = np.append(arr, np.array([[4, 3, 6, 7]]), axis=0)
# Append 2nd rows to the 2D Numpy array
emp_arr = np.append(emp_arr, np.array([[2, 6, 9, 10]]), axis=0)
print(‘2D Numpy array:’)
print(emp_arr)

In the above example our 2D Numpy array had 4 columns, therefore to add a new row we need to pass this row as a separate 2D NumPy array with dimension (2,4).

Here is the Screenshot of the following given code

Python Create an Empty Numpy array and append rows

The above code we can use to Create an Empty Numpy array and append rows in Python.

Read Python NumPy to list with examples

Python Create Empty Numpy array and append Columns

In this section, we will discuss Empty Numpy array and append columns.
In this method, first we will create an empty numpy array with 0 column and 4 rows.
Now to append a new column to this empty 2D Numpy array, we can use the numpy.append().
But we need to pass the column as a numpy array of same shape only and argument axis=1, so that it can be appended along the column.

Example:

import numpy as np

arr = np.empty((4, 0), int)
print(‘Empty 2D Numpy array:’)
print(arr)
# Column list1
emp_arr = np.append(arr, np.array([[4, 3, 6, 7]]).transpose(), axis=1)

print(‘2D Numpy array:’)
print(emp_arr)

In the above example our empty numpy array has 4 rows & 0 columns, so to add a new column we need to pass this column as a separate 2D numpy array with dimension (4,1).

Here is the Screenshot of the following given code

Python Create Empty Numpy array and append Columns

The above code we can use to create an empty Numpy array and append Columns in Python.

You may like the following Python tutorials:

Python NumPy read CSV
How to convert list to string in Python
Check if a list is empty in Python

In this Python tutorial, we will discuss Python NumPy empty array with a few examples like below:

Python numpy empty array append
Python numpy array empty check
Python empty numpy array without shape
Python numpy empty 2d array
Python numpy concatenate empty array
Python numpy declare empty array
Python numpy empty string array
Python numpy empty 3d array
Python fill empty numpy array
Python Create Empty Numpy array and append rows
Python Create Empty Numpy array and append Columns

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A Beautiful Notification Library For Vue.js 3

Description:

A beautiful notification library for Vue.js 3 that, enables you to create animated notifications in your application with features like, close button, custom templates and custom styles, and its easy to integrate in your project.

How can I use it?

1. You will need to install the component with npm or yarn.

#npm
npm install –save @kyvg/vue3-notification

#yarn
yarn add @kyvg/vue3-notification

2. Add the dependencies in your main.js. Like this:

import { createApp } from ‘vue’
import Notifications from ‘@kyvg/vue3-notification’

const app = createApp({…})
app.use(Notifications)

3. Now, add the global component to your App.vue. Like following.

<notifications />

4. Now, you will need to write the code that will trigger notifications from your .vue files.

#basic method
this.$notify(“Hello user!”);

#with options
this.$notify({
title: “Important message”,
text: “Hello user!”,
});

5. Or, you may want to trigger notifications from other files then you should do like this.

import { notify } from “@kyvg/vue3-notification”;

notify({
title: “Authorization”,
text: “You have been logged in!”,
});

The post A Beautiful Notification Library For Vue.js 3 appeared first on Lipku.com.

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