Category: Uncategorized

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The Biblical Basis for Self-Defense – Kevin Creighton

I believe that armed self-defense is an extension of the Christian’s mandate to protect the innocent, to “watch over widows and orphans in their distress.” No one doubts that a policeman who carries a gun and watches over society can do such things and still be a Christian: Why, therefore, is there any doubt that an armed individual like me can carry a gun and watch over a small portion of society (my family) and yet still have a deep, abiding faith in God?

The Biblical Basis for Self-Defense – Ricochet

Go read the whole thing.

I like to say I am the most peaceful man you will ever know, but I am not a Pacifist.  Not understanding that difference can be hurtful to your health and ability to remain above room temperature. This does not counter the doctrine of the Catholic Church or any real Christian belief. It does piss off something fierce the Lefties using alleged Christian values and political jump points for the most antichrist behavior they can think of.

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Comic for January 16, 2022

https://assets.amuniversal.com/c7a90d003b9f013a8b1f005056a9545d

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Dilbert Daily Strip

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Why Is Python Popular for Data Science?

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Python is a popular high-level programming language used mainly for data science, automation, web development, and Artificial Intelligence. It is a general-purpose programming language supporting functional programming, object-oriented programming, and procedural programming. Over the years, Python is known to be the best programming language for data science, and it is commonly used by big tech companies for data science tasks.

In this tutorial, you will learn why Python is so popular for data science and why it will stay popular in the future.

What Can Python Be Used For?

As said earlier, Python is a general-purpose programming language, which means that it can be used for almost everything.

One common application of Python in web development is where Django or Flask is used as the backend for a website. For example, Instagram’s backend runs on Django, and it’s one of the largest deployments of Django.

You can also use Python for game development with Pygame, Kivy, Arcade, etcetera; though it’s rarely used. Mobile app development is not left out, Python offers many app development libraries such as Kivy and KivyMD which you can use for developing multiplatform apps; and many other libraries like Tkinter, PyQt, etc.

The main talk of this tutorial is the application of Python in Data Science. Python has been proven to be the best programming language for Data Science and you will know why in this tutorial.

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What Is Data Science?

According to Oracle, data science combines multiple fields, including statistics, scientific methods, artificial intelligence (AI), and data analysis, to extract value from data. It encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis.

Data science is applicable in different industries, and it’s helping to solve problems and discover more about the universe. In the health industry, data science helps doctors to make use of past data in making decisions, for example, diagnosis, or the right treatment for a disease. The education sector is not left out, you can now predict students dropping out of school, all thanks to data science.

Python Has a Simple Syntax

What else can make programming a lot easier than having an intuitive syntax? In Python, you need just one line to run your first program: simply type print(“Hello World!”) and run – it’s that easy.

Python has a very simple syntax, and it makes programming a lot easier and faster. There is no need for curly braces when writing functions, no semicolon is your enemy, and you don’t even need to import libraries before you write basic code.

This is one advantage Python has over other programming languages. You have fewer tendencies to make errors, and you can easily notice bugs.

Data Science is one complex field you can’t do without needing any help. Python offers all the help you need through its wide community. Whenever you get stuck, just browse it and your answer is waiting for you. Stack Overflow is a very popular website where questions and answers are posted to programming problems.

If your problem is new, which is rare, you can ask questions and people would be willing to provide answers.

Python Offers All the Libraries

You badly need water, and you have just two cups on the table. One is a quarter filled with water while the other one is almost full. Would you carry the cup with much water or the other one, though they both have water? You’d want to carry the cup containing a lot of water because you really need water. This is relatable to Python, it offers all the libraries you’d ever need for data science, you would definitely not want to use another programming language with only a few libraries available.

You will have a great experience working with these libraries because they are really easy to use. If you need to install any library, search for the library name at PyPI.org and follow the instructions towards the end of this article to install the library.

Related: Data Science Libraries for Python Every Data Scientist Should Use

Numerical Python – NumPy

NumPy is one of the most commonly used data science libraries. It allows you to work with numeric and scientific tasks in Python. Data is represented using arrays or what you may refer to as lists, which can be in any dimension: 1-dimensional (1D) array, 2-dimensional (2D) array, 3-dimensional (3D) array, and so on.

Pandas

Pandas is also a popular data science library used in data preparation, data processing, data visualization. With Pandas, you can import data in different formats such as CSV (comma-separated values) or TSV (Tab-separated values). Pandas works like Matplotlib because it allows you to make different types of plots. Another cool feature Pandas offers is that it allows you to read SQL queries. So, if you have connected to your database, and you want to write and run SQL queries in Python, Pandas is a great choice.

Matplotlib and Seaborn

Matplotlib is another awesome library Python offers. It has been developed on top of MatLab – a programming language used mainly for scientific and visualization purposes. Matplotlib allows you to plot different kinds of graphs with just a few lines of code.

You can plot graphs to visualize any data, helping you to gain insights from your data, or giving you a better representation of the data. Other libraries like Pandas, Seaborn, and OpenCV also use Matplotlib for plotting sophisticated graphs.

Seaborn (not Seaborne) is just like Matplotlib, just that you have more options – to give different parts of your graphs different colors, or hues. You can plot nice graphs and customize the look to make the data representation better.

Open Computer Vision – OpenCV

Perhaps you want to build an Optical Character Recognition (OCR) system, document scanner, image filter, motion sensor, security system, or anything else related to computer vision, you should try OpenCV. This amazing and free library offered by Python allows you to build computer vision systems over just a few lines of code. You can work with images, videos, or even your webcam feed and deploy.

Scikit-learn – Sklearn

Scikit-learn is the most popular library used specifically for machine learning tasks in data science. Sklearn offers all the utilities you need to make use of your data and build machine learning models in just a few lines of code.

There are various machine learning tasks like linear regression (simple and multiple), logistic regression, k-nearest neighbors, naive bayes, support vector regression, random forest regression, polynomial regression, including classification and clustering tasks.

Though Python is simple because of its syntax; there are tools that have been specifically designed with data science in mind. Jupyter notebook is the first tool, it is a development environment built by Anaconda, to write Python code for data science tasks. You can write and instantly run codes in cells, group them, or even include documentation, as provided by its markdown capability.

A popular alternative is Google Colaboratory, also known as Google Colab. They are similar and used for the same purpose but Google Colab has more advantages because of its cloud support. You have access to more space, not having to worry about your computer storage getting full. You can also share your notebooks, log in on any device and access it, or even save your notebook to GitHub.

How to Install Any Data Science Library in Python

Given you already have Python installed on your computer, this step-by-step section will guide you through how to install any data science library on your Windows computer. NumPy will be installed in this case, follow the steps below:

  1. Press Start and type cmd. Right-click the result and choose Run as administrator.
  1. You need PIP to install Python libraries from PyPi. If you already have, feel free to skip this step; if not, please read how to install PIP on your computer.
  2. Type pip install numpy and press Enter to run. This process will install NumPy on your computer and you can now import and use NumPy on your computer. This process should look similar to the screenshot shown below, ignore the warning and blank spaces. (If you use Linux or macOS, simply open a terminal and enter the pip install command).

It’s Time to Use Python for Data Science

Among other programming languages like R, C++, and Java; Python stands to be the best for data science. This tutorial has guided you through why Python is so popular for data science. You now know what Python offers and why big companies like Google, Meta, NASA, Tesla, etcetera use Python.

Did this tutorial succeed in convincing you that Python will remain the best programming language for data science? If yes, go on and build nice data science projects; help make life easier.

How to Import Excel Data Into Python Scripts Using Pandas

For advanced data analysis, Python is better than Excel. Here’s how to import your Excel data into a Python script using Pandas!

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Huskies Get a Surprise

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Huskies Get a Surprise

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My Mountain Husky filled up his living room with 2,000 tennis balls then headed out to see how his huskies would react when he left them alone. The normally vocal dogs were speechless at the sight of their newfound paradise but were equally concerned about where their dad went.

The Awesomer

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Watch: Mike Rowe, Tim Pool Answer Important Question: Could Liberals Survive a Zombie Apocalypse?

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You had to know that when Mike Rowe took a trip to visit Tim Pool, things were going to get a little weird. Or "sporty," as you’re about to hear Rowe say. Not as weird as having the police show up at your house in the middle of a live stream. But still a little out there. They could have discussed the pandemic and Biden’s incompetent response to the pandemic. Or discuss much more pressing matters. Such as, in the event of an apocalypse–full-blown zombies and stuff–who would fair better: liberals or conservatives?

The answer is obvious. But let’s see how they work it out.


Leftists Will NOT Survive The Apocalypse, Mike Rowe Weighs In

youtu.be

Tim Pool believes liberals won’t survive the apocalypse because people in cities won’t know how to survive. They lack hunting skills. People who are more rural will probably fare better. Starbucks hippies aren’t going to do so well when the -ish hits the fan. Guys who know how to farm will. That’s a fair assessment.

Mike Rowe doesn’t say what he feels straight-up. But here’s how he lays out both sides. It’s "Walking Dead" time. You’re gonna have to hunker down in a place with one or two groups of people. Group A are thoughtful writers and thinkers? Group B are hunters, gatherers, and builders? When things get "sporty," what side do you choose?

Rowe and Pool went on to have an interesting conversation about how things are made and the importance of making sure everything is working to make sure those things are made. This is where the incompetence of the Biden administration comes in. Pour a cup of coffee. Listen. Enjoy.

I’ll be over here scripting George A. Romero’s Podcast of the Dead starring Tim Pool and Mike Rowe. I smell money.

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Crowder Reacts LIVE to Rand Paul OWNING Dr. Fauci! | Louder With Crowder

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Louder With Crowder

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45 New Laravel Tips 2022 [VIDEO]

We continue compiling random Laravel tips into a special free repository. In this video, I’m presenting a new PR with 45 new tips and will share random 5 of them.Laravel News Links

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Laravel EasyPanel

https://repository-images.githubusercontent.com/310552467/99c0d700-6f9e-11eb-9097-464b25973236

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EasyPanel

EasyPanel is a beautiful, customizable and flexible admin panel based on Livewire for Laravel.

EasyPanel screenshots

Features :

  • Easy to install
  • Multi Language
  • RTL and LTR mode
  • Sort Data just with a click
  • Support CKEditor and Persian Font for RTL mode
  • Create CRUD for every model in 1 minute
  • Manage route prefix and addresses
  • A beautiful UI/UX with AdminMart template
  • Add/remove Admins with command line
  • UserProviders and Authentication classes are customizable and you can change them
  • You can create your own routes and customize view and components
  • Manage pagination count
  • Real time validation with Livewire
  • A small and beautiful TODO (You can disable it in config)
  • Create a nice and responsive view based on your data in config file for every CRUDs
  • Strong commands to manage package
  • Custom validation based on config file
  • Ajax search with Livewire in every column which you want

Install:

  1. Install the Package in Laravel project with Composer.
composer require rezaamini-ir/laravel-easypanel
  1. Publish EasyPanel files with one command :
php artisan panel:install

Congrats! You installed the package, follow the Usage section.

Usage:

First you have to define admins then You can create a CRUD for a model.
Follow the doc.

Define Admins

Run this command out to make a user as an admin:

php artisan panel:add [user_id]

To create a super admin you can pass --super option to the command.

For example:

php artisan panel:add 10 --super

To remove an admin you can execute this command:

php artisan panel:remove [user_id]

[user_id] : It’s id of user that you want to make as an admin

These commands use UserProvider class in EasyPanel and You can use your own class instead of that and pass it in config file

Multi Lang

If you want change language of Module You have to pass 2 steps:

1 – copy en_panel.json file in resources/lang and paste it in this folder with your lang name like fr_panel.json then customize it.
File format must have _panel.json suffix, e.g: fr_panel.json, fr is your language like : fa, en, fr, ar, ..

2 – Set your lang in easy panel config file in config/easy_panel.php in lang key, this value must be equal to your suffix language file name in the lang directory, like fr.

TODO

If you need TODO feature you have to publish TODO migration with this command

php artisan panel:migration

It will publish TODO’s migration file then you can migrate the migrations with php artisan migrate.

After pass these steps, You must set todo key in config file to true.

Now you have a TODO inside your panel for each admin.

Config

Base Config

Key Type Description
enable bool Module status
todo bool TODO feature status
rtl_model bool If you want a RTL base panel set it true
lang bool Your default language with this format : **_panel.json which you have to just use ** like en or fa
user_model string Address of User model class
auth_class string Address of user authentication class
admin_provider_class string Address of user provider class
redirect_unauthorized string If user is unauthenticated it will be redirected to this address
route_prefix string Prefix of admin panel address e.g: if set it admin address will be : http://127.0.0.1/admin
pagination_count int Count of data which is showed in read action
lazy_mode bool Lazy mode for Real-Time Validation
actions array List of enabled action which you have created a crud config for them.

CRUD Component methods

Method/Property Return Type Description
create bool Create Action for this model
update bool Update Action for this model
delete bool Delete Action for this model
with_auth bool It will fill user_id key for create and update action with auth()->user()->id
getModel string CRUD Model
searchable array Columns in model table which you want to search in read action
validationRules array Validation rules in create and update action (it uses Laravel validation system)
inputs array Input name as key and Input type as value (for update and create action)
storePaths array Where every files of inputs will store
fields array Every data which you want to show in read action (if data is related on other tables pass it as an array, key is relation name and value is column name in related table)

Examples:

Fields:

    public function fields()
    {
        return ['title', 'image', 'user.name'];
    }

Form Inputs:

    public function inputs()
    {
        return [
            'name' => 'text',
            'email' => 'email',
            'password' => 'password',
            'avatar' => 'file'
        ];
    }
    public function inputs()
    {
        return [
            'title' => 'text',
            'body' => 'ckeditor',
            'photo' => 'file',
            'status' => ['select' => [
                'published' => 'Publish Now!',
                'unpublished' => 'Publish Later..',
            ]],
        ];
    }

Dynamic value from a table

    public function inputs()
    {
        return [
            'title' => 'text',
            'body' => 'ckeditor',
            'photo' => 'file',
            'category' => ['select' => 
                Category::where('active', true)
                    ->get()
                    ->pluck('name', 'id') // [1 => 'IT', 2 => 'History', 2 => 'Medicine']
            ],
        ];
    }

What do we use in this package?

Contribution:

If you feel you can improve our package You are free to send a pull request or submit an issue 🙂

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