¡Descubre el fascinante mundo de la microelectrónica! Un viaje épico desde los fundamentos atómicos hasta los componentes más avanzados de la tecnología moderna.

Este no es solo otro curso de electrónica. Es tu puerta de entrada al futuro tecnológico, donde aprenderás desde la Ley de Moore hasta las técnicas más avanzadas de diagnóstico con medidores ESR. 2

Teoría + Laboratorio = Dominio Total 3

• 🧠 Teoría: Conceptos fundamentales que cambiarán tu perspectiva
• 🔬 Laboratorio: Prácticas reales con herramientas profesionales
• 🔧 Componentes: Desde discretos hasta SMD de última generación

• SMD Decoder: Decodifica resistencias, capacitores e inductores al instante 4
• Electrodoc: Tu calculadora universal de componentes 5
• All DataSheet: Acceso instantáneo a hojas de fabricante 6
• Lupa Digital: Convierte tu celular en un microscopio profesional 7

Domina las herramientas de inteligencia artificial más poderosas: 8

• ChatGPT, Copilot, Gemini, LuzIA, Claude

• Modelo Atómico: Comprende la base de todo 9
• 14 Tipos de Energía: Desde luz hasta radioactividad 10
• Ley de Ohm Masterclass: Domina V, I, R como un profesional 11

Conoce los secretos de: 12

• Conductores: Oro, Cobre, Aluminio
• Semiconductores: Silicio, Germanio, GaAs
• Superconductores: Carbono, Cadmio, Cromo
• Superaisladores: Tecnología de vanguardia

• Multímetros Inteligentes: Medición de precisión 13
• Herramientas Especializadas: Para celulares, potencia, vehículos 14
• Instrumentación Industrial: Equipos de nivel profesional 15

Los medidores ESR son la herramienta más poderosa para diagnóstico avanzado de componentes. 16

¿Por qué ESR es REVOLUCIONARIO?

• 🎯 Diagnóstico sin desoldadura: Mide componentes en circuito
• ⚡ Detección instantánea: Identifica fallas invisibles al multímetro
• 🔬 Precisión extrema: Capacitores, inductores, resistores
• 💡 Ahorro de tiempo: Diagnósticos en segundos, no horas

Aplicaciones ESR en el curso:

• Medición de capacitores sin riesgo eléctrico 17
• Análisis de inductores con precisión profesional 18
• Verificación de resistores sin interferencias 19
• Diagnóstico de diodos y semiconductores 20

• Discretos, SMD, Potencia, Industriales, Arrays 21
• Carta de Fallas Profesional: 7 tipos de fallas y sus causas 22

• Cerámicos, Tantalio, SMD, Aceite y Papel 23
• Diagnóstico Experto: 7 fallas críticas identificadas 24

• Toroidales, SMD, Discretos – 8 tipos diferentes 25
• Medición Profesional: 4 técnicas avanzadas 18

• Diodos: LEDs, Potencia, SMD, Equivalencias 26
• SCRs: Control de potencia profesional 27
• TRIACs: Conmutación AC avanzada 28

Domina los 6 enemigos de la electrónica: 29

• ⚡ Estática: Técnicas de descarga segura
• 🌡️ Temperatura: Control térmico profesional
• 💧 Humedad: Prevención de corrosión
• 🌪️ Polvo: Mantenimiento preventivo
• 📳 Vibraciones: Estabilidad mecánica
• 🦺 EPP: Equipos de protección personal

Aprende a interpretar los 5 tipos de documentación técnica: 30

• 📖 Manual de Usuario
• ⚙️ Manual de Operación
• 🛡️ Manual de Garantía
• 🔧 Manual de Servicio (L0, L1, Esquemáticos)

Este curso no solo te enseña electrónica, te convierte en un profesional. Con herramientas de IA, medidores ESR, y conocimiento desde el nivel atómico hasta sistemas complejos.

1. Abre index.html en tu navegador
2. Sumérgete en la experiencia interactiva
3. Practica con herramientas reales
4. Domina el diagnóstico ESR

🎓 Instructor: Luis Sanchez (@sanchezluys)
🛠️ Tecnología: reveal.js – Presentaciones interactivas de nivel profesional
📅 Versión: v1.0 2024

“La microelectrónica no es solo tecnología, es el lenguaje del futuro. ¡Aprende a hablarlo!”

This library (just one class, really) provides a simple C# wrapper around customer objects in Optimizely Data Plaform (ODP), allowing you to use that repository to store user profile and preferences.

Note that you could manage Customer profiles in ODP already, this just provides a C# “link” to get the corresponding profile to the CMS server-side user context.

This allows storage of user preferences and data in ODP, which provides some benefits:

1. It’s handy and simple
2. It scales like crazy (I’m not saying users in CMS didn’t scale, but ODP is literally built for exactly this)
3. You can segment users based on profile data
4. It’s easy to re-use user data in other applications and platforms

Traditionally, Opti CMS hasn’t provided a comprehensive framework for storing user data beyond name, email, and passwords. For other preference data, Opti CMS has relied on the ASP.NET profile framework or bespoke systems.

This library (hopefully) solves this issue.

You only need to compile in the one class: OptiDataProfile.cs

Then, set two static properties:

// The name of the field that is serving as an identifier
OptiDataProfile.KeyField = "email";

// Your API Key
OptiDataProfile.ApiKey = "whatever";

(Yes, yes, I should probably write this as an injected service at some point. If you want to, go nuts. PRs are open.)

Instantiate the OptiDataProfile object with the identifier (a value for whatever you used as the KeyField). This should correspond to how the user is dentified in CMS — either username or email would work.

For example, if we were using email:

var profile = new OptiDataProfile("deane@deanebarker.net");

If a customer object doesn’t exist in ODP for that key, it will be created.

When the object is created in C#, all the profile data is cached in a local dictionary, under the Attributes property. Values are stored as object.

Some convenience accessors are also provided.

var address = profile.GetValue("address"); // Returns an object
var address = profile.GetString("address"); // Returns a string
var address = profile["address"]; // Returns a string

You can provide a default value to be used if GetValue returns null or GetString returns null or whitespace.

var mood = profile.GetString("mood", "Unknown");

You can write back to ODP one value at a time:

profile.SetValue("mood", "Happy");

Note: that attribute must already exist on the “Customer” schema in ODP.

That will write immediately, and update the local object cache (it does this interally — it doesn’t write and then reload all the attributes).

You can write multiple keys at once:

profile.SetValues(new Dictionary<string,object>()
{
  { "mood", "Happy" },
  { "eyecolor", "blue" }
});

Or you can pass in an object that will be reflected — property names will become dictionary keys.

profile.SetValues(new {
  mood = "Happy",
  eyecolor = "blue"
});

(Clearly, that last method presents issues with property naming. Your attribute keys would have to obey C# syntax rules — no spaces, no hyphens, etc. If your keys violate those rules, then you’ll need to use the Dictionary method.)

Normally, you need to pass in an ID to instatiate an object. This isn’t ideal if you’re instantiating the object in different locations in your code.

You can set a static method to be used for this, which allows you to centralize this logic. This method should return a string.

OptiDataProfile.IdProvider = () => {
  var email = GetEmailSomehow();
  return email;
};

This method takes no parameters — the intention is that you would retrieve the ID from Session or HttpContext or some other global construct.

Once this method is set, then anywhere in your code, you can call this:

var profile = OptiDataProfile.GetCurrentProfile();

(See ProfileController.cs for examples of this method.)

That will call the IdProvider method internally, and feed the result into the constructor, returning a populated profile. If your IdProvider returns null, then GetCurrentProfile will return null as well.

LLaMA Server combines the power of LLaMA C++ (via PyLLaMACpp) with the beauty of Chatbot UI.

🦙LLaMA C++ (via 🐍PyLLaMACpp) ➕ 🤖Chatbot UI ➕ 🔗LLaMA Server 🟰 😊

UPDATE: Greatly simplified implementation thanks to the awesome Pythonic APIs of PyLLaMACpp 2.0.0!

UPDATE: Now supports better streaming through PyLLaMACpp!

UPDATE: Now supports streaming!

• Better Streaming

• Streaming

• Non-streaming

• Get your favorite LLaMA models by

  • Download from 🤗Hugging Face;
  • Or follow instructions at LLaMA C++;
  • Make sure models are converted and quantized;

• Create a models.yml file to provide your model_home directory and add your favorite South American camelids, e.g.:

model_home: /path/to/your/models
models:
  llama-7b:
    name: LLAMA-7B
    path: 7B/ggml-model-q4_0.bin  # relative to `model_home` or an absolute path

See models.yml for an example.

• Set up python environment:

conda create -n llama python=3.9
conda activate llama

• Install LLaMA Server:

  • From PyPI:

  python -m pip install llama-server

  • Or from source:

  python -m pip install git+https://github.com/nuance1979/llama-server.git

• Start LLaMA Server with your models.yml file:

llama-server --models-yml models.yml --model-id llama-7b

• Check out my fork of Chatbot UI and start the app;

git clone https://github.com/nuance1979/chatbot-ui
cd chatbot-ui
git checkout llama
npm i
npm run dev

• Open the link http://localhost:3000 in your browser;
  • Click “OpenAI API Key” at the bottom left corner and enter your OpenAI API Key;
  • Or follow instructions at Chatbot UI to put your key into a .env.local file and restart;

  cp .env.local.example .env.local
  <edit .env.local to add your OPENAI_API_KEY>

• Enjoy!

• Try a larger model if you have it:

llama-server --models-yml models.yml --model-id llama-13b  # or any `model_id` defined in `models.yml`

• Try non-streaming mode by restarting Chatbot UI:

export LLAMA_STREAM_MODE=0  # 1 to enable streaming
npm run dev

I am not fluent in JavaScript at all but I was able to make the changes in Chatbot UI by chatting with ChatGPT; no more StackOverflow.

LLaMA Server combines the power of LLaMA C++ (via PyLLaMACpp) with the beauty of Chatbot UI.

🦙LLaMA C++ (via 🐍PyLLaMACpp) ➕ 🤖Chatbot UI ➕ 🔗LLaMA Server 🟰 😊

UPDATE: Greatly simplified implementation thanks to the awesome Pythonic APIs of PyLLaMACpp 2.0.0!

UPDATE: Now supports better streaming through PyLLaMACpp!

UPDATE: Now supports streaming!

• Better Streaming

• Streaming

• Non-streaming

• Get your favorite LLaMA models by

  • Download from 🤗Hugging Face;
  • Or follow instructions at LLaMA C++;
  • Make sure models are converted and quantized;

• Create a models.yml file to provide your model_home directory and add your favorite South American camelids, e.g.:

model_home: /path/to/your/models
models:
  llama-7b:
    name: LLAMA-7B
    path: 7B/ggml-model-q4_0.bin  # relative to `model_home` or an absolute path

See models.yml for an example.

• Set up python environment:

conda create -n llama python=3.9
conda activate llama

• Install LLaMA Server:

  • From PyPI:

  python -m pip install llama-server

  • Or from source:

  python -m pip install git+https://github.com/nuance1979/llama-server.git

• Start LLaMA Server with your models.yml file:

llama-server --models-yml models.yml --model-id llama-7b

• Check out my fork of Chatbot UI and start the app;

git clone https://github.com/nuance1979/chatbot-ui
cd chatbot-ui
git checkout llama
npm i
npm run dev

• Open the link http://localhost:3000 in your browser;
  • Click “OpenAI API Key” at the bottom left corner and enter your OpenAI API Key;
  • Or follow instructions at Chatbot UI to put your key into a .env.local file and restart;

  cp .env.local.example .env.local
  <edit .env.local to add your OPENAI_API_KEY>

• Enjoy!

• Try a larger model if you have it:

llama-server --models-yml models.yml --model-id llama-13b  # or any `model_id` defined in `models.yml`

• Try non-streaming mode by restarting Chatbot UI:

export LLAMA_STREAM_MODE=0  # 1 to enable streaming
npm run dev

I am not fluent in JavaScript at all but I was able to make the changes in Chatbot UI by chatting with ChatGPT; no more StackOverflow.

This repository is designed to help anyone with very little or no computing background learn the basics of DevOps. Course is self-paced and when you’re finished with it, you’ll know how to manage resouces in Azure Cloud, using Infrastructure as Code approach.

Learning path is just a collection of publicly available courses, grouped by a specific topic. Some section have homework part – you can use it for a self-evalution.

if you have any questions regarding this tutorial, please do not hesitate to contact me (using Reddit,Linkedin or by pushing pull request to this repository).

Accounts:

• Github account

• Microsoft/Azure account

• Docker Hub Account

Software:

• Some linux-based environment (like Ubuntu, Fedora, Suse etc.)

• Some software for managing Azure (like Azure CLI, Azure Powershell, Azure Cloud Shell etc.)

• Docker Engine

• Git

• Ansible

1. The Origins of DevOps
2. Guide to DevOps
3. DevOps Model from Amazon

1. Running Windows Subsystem for Linux
2. Linux Fundametals

1. Deploy a Linux environmet (could be a Virtual Machine, Container Instance, Windows Subsystem for Linux etc.)
2. Install some webserver and reconfigure it so it would run on a custom port (like 8088)
3. Configure and apply a custom response page for the webserver (something like “Hello World!”)

1. Introduction to Git
2. Learn Git Branching
3. Introduction to GitHub in Visual Studio Code
4. Working with Git in Visual Studio Code

1. Fork this repository
2. Clone forked repository to your local environment (could be PC, Virtual Machine, WSL etc.)
3. Locally create a new branch and modify README.md file in it (by appending it with “Hello World!” line)
4. Commit and push all changes to remote Github repository (forked one, not the original)

1. What is Python?
2. LearnPython.org interactive Python tutorial
3. Perform mathematical operations on numeric data in Python
4. [Optional][Advanced] An Introduction to Interactive Programming in Python

1. What is virtualization?
2. What are containers?
3. What is Docker?
4. Introduction to Docker containers
5. Containers for Beginners

1. Create Dockerfile (base image can be any prefferable Linux image) in which a webserver is installed and started
2. Build an image from the Dockerfile (for that you’ll need installed Docker Engine) and run the container (don’t forget to expose port for HTTP)
3. Validate that you can access the webserver
4. Publish your image to your Docker Hub Registry (for that you’ll need account in Docker Registry)

1. Continuous Integration Explained
2. Create your first GitHub Action

1. Create a new Github repository.
2. Create and configure Github Action, which builds Dockerfile and publishes it in Docker Hub Registry once every day.

1. Introduction to Azure fundamentals
2. Create an Azure account
3. Manage services with the Azure portal

1. Services and identity types of Azure AD
2. Service Principals vs Managed Identities
3. Create a service principal
4. Manage secrets with Azure Key Vault
5. Azure role-based access control

1. Register a new application in Azure Active Directory.
2. Generate and store a secret for the application.
3. Create a Key Vault and grant access to the application: on resouce level – Contributor role, on Vault level – policy which would allow to create and read secrets.
4. Using non-GUI approach (Powershell, Azure CLI etc.): authenticate to Azure using application’s credentials; create a new secret, read it, delete the whole Key Vault.

1. Deploy resources using ARM template
2. Use Azure Key Vault to pass secure parameters
3. Deploy ARM templates by using GitHub Actions

1. Create a new Key Vault and add a secret with some value, which will be used as virtual machines password
2. Deploy DNS Forwarder with your own parameters file, which for an user password would use Key Vault refference
3. Check the result by logging in VM using a password from the Key Vault

1. Fundamentals of computer networking
2. Connect on-prem to Azure using VPN Gateway
3. Connect on-prem to Azure using ExpressRoute
4. Design an IP addressing schema
5. Intro to VNet peering
6. Hub and Spoke topology
7. Design and implement private access to Azure Services

1. Create two VNets with different IP ranges (which doesn’t overlap) and a storage account
2. Expose storage account’s fileshare privately (using private endpoint) on both networks
3. Establish between networks VNet peering
4. Create two virtual machines – one in the first network with public IP and another in the second network without public IP
5. Connect remotely to publicly available machine and using it connect to the privately available VM
6. From both VMs resolve privately exposed fileshare (using nslookup or any other prefferable way) and validate that in both cases IP is private

1. Choose the right integration and automation services in Azure
2. Configure Azure Container Instances
3. Publish Azure Functions by using Azure Functions Core Tools
4. Create a Python function in Azure from the command line
5. Monitor GitHub events by using a webhook with Azure Functions
6. Create a function on Linux using a custom container

1. Deploy function for showing your public IP and check how it works
2. [Optional][Advanced] Configure the same function but as a custom Docker container, deploy that image to Azure Container Instance with public IP address (with exposed HTTP port) and validate the result

1. Introduction to Azure DevOps
2. Implement CI/CD with Azure DevOps
3. Host your own build agent in Azure Pipelines

1. Create a new organization and project in Azure DevOps.
2. Deploy and configure self-hosted build agent on Azure Container Instance.
3. Use self-hosted agent for deploying a Python web app.

1. Ansible Overview
2. Ansible Introduction
3. Run web server using Ansible
4. Ansible User Guide
5. Configure Ansible on an Azure VM

1. Install Ansible with Azure modules
2. Choose some ARM template from Azure Quickstart Templates and deploy it using azure_rm_deployment

What is Infrastructure as Code (IaC)?

Configure and deploy your own IaC

Congratulations! You have successfully completed this course! Now you can explore Azure by yourself. If you still wondering where to start, check following resources:

• Azure Tips and Tricks
• Small blog about Azure
• John Savill’s Youtube channel
• Azure updates
• Azure Weekly newsletter

This is a brief summary of the top non-English and non-Spanish languages spoken per-state in the US.

This report was inspired by a 2014 article by Slate.

The raw dataset was made available by the American Community Survey (a department of the Census Bureau) and is available for download here.

Reporting on the data follows.

630423 adult speakers

4320582 adult speakers

2633385 adult speakers

5843921 adult speakers

33748857 adult speakers

4495642 adult speakers

3281254 adult speakers

552746 adult speakers

803548 adult speakers

17052403 adult speakers

8785436 adult speakers

1194450 adult speakers

2787519 adult speakers

1375973 adult speakers

11942587 adult speakers

5896315 adult speakers

2580615 adult speakers

3955505 adult speakers

4043172 adult speakers

6087734 adult speakers

5247846 adult speakers

1244327 adult speakers

9414626 adult speakers

4830132 adult speakers

5480859 adult speakers

2705306 adult speakers

896668 adult speakers

8405944 adult speakers

598518 adult speakers

1641193 adult speakers

1237068 adult speakers

8100620 adult speakers

1818055 adult speakers

2351179 adult speakers

18224612 adult speakers

10734806 adult speakers

3348376 adult speakers

3498022 adult speakers

11686497 adult speakers

3695811 adult speakers

993514 adult speakers

4107268 adult speakers

739597 adult speakers

5736382 adult speakers

21869156 adult speakers

2404658 adult speakers

7183318 adult speakers

588245 adult speakers

6029673 adult speakers

5243435 adult speakers

1705879 adult speakers

487031 adult speakers

To use this SDK, you first need to log in to blockfrost.io, create your project and retrieve the API token.

blockfrost-go can be installed through go get

$ go get https://github.com/blockfrost/blockfrost-go

package main

import (
	"context"
	"fmt"
	"log"

	"github.com/blockfrost/blockfrost-go"
)

func main() {
	api, err := blockfrost.NewAPIClient(
		blockfrost.APIClientOptions{
            ProjectID: "YOUR_PROJECT_ID_HERE", // Exclude to load from env:BLOCKFROST_PROJECT_ID
        },
	)
	if err != nil {
		log.Fatal(err)
	}

	info, err := api.Info(context.TODO())
	if err != nil {
		log.Fatal(err)
	}

	fmt.Printf("API Info:\n\tUrl: %s\n\tVersion: %s", info.Url, info.Version)
}

package main

import (
	"context"
	"flag"
	"fmt"
	"log"

	"github.com/blockfrost/blockfrost-go"
)

var (
	fp = flag.String("file", "", "Path to file")
)

func main() {
	flag.Parse()
	// Load project_id from env:BLOCKFROST_IPFS_PROJECT_ID
	ipfs := blockfrost.NewIPFSClient(blockfrost.IPFSClientOptions{})

	ipo, err := ipfs.Add(context.TODO(), *fp)
	if err != nil {
		log.Fatal(err)
	}

	fmt.Printf("IPFS Object: %+v\n", ipo)

	// Pin item to avoid being garbage collected.
	pin, err := ipfs.Pin(context.TODO(), ipo.IPFSHash)
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("Pin: %+v", pin)
}

More examples of usage can be found in example folder.

Set BLOCKFROST_PROJECT_ID env variable:

export BLOCKFROST_PROJECT_ID=<MAINNET_TOKEN>

To run specific test:

go test -run <name>

To run all tests:

make test

To generate missing .golden file

go test -gen

Licensed under the Apache License 2.0, see LICENSE

Richard Topchii on Telegram

CalendarKit is a Swift calendar UI library for iOS and Mac Catalyst. It looks similar to the Apple Calendar app out-of-the-box, while allowing customization when needed. CalendarKit is composed of multiple modules which can be used together or independently.

• Create iOS Calendar App in Swift with CalendarKit – Official Tutorial
• Live Programming with CalendarKit – For Beginners

If you have a programming question about how to use CalendarKit in your application, Create a new GitHub Issue with the question tag.

Check out the Sample App for reference.

Create a new Issue from template to report a bug or request a new feature.

Video

Sample App

CalendarKit can be installed with Swift Package Manager or with CocoaPods.

The preferred way of installing CalendarKit is via the Swift Package Manager.

1. In Xcode, open your project and navigate to File → Swift Packages → Add Package Dependency…
2. Paste the repository URL (https://github.com/richardtop/CalendarKit.git) and click Next.
3. For Rules, select Version (Up to Next Major) and click Next.
4. Click Finish.

Adding Package Dependencies to Your App

⚠️ Warning: CocoaPods support is deprecated and will be removed at a later date. It’s recommended to migrate your installation of CalendarKit to using Swift Package Manager.

To install it, add the following line to your Podfile:

pod 'CalendarKit'

Adding Pods to an Xcode project

1. Subclass DayViewController
2. Implement EventDataSource protocol to show events.

CalendarKit requires EventDataSource to return an array of objects conforming to EventDescriptor protocol, specifying all the information needed to display a particular event. You’re free to use a default Event class as a model or create your own class conforming to the EventDescriptor protocol.

// Return an array of EventDescriptors for particular date
override func eventsForDate(_ date: Date) -> [EventDescriptor] {
  var models = myAppEventStore.getEventsForDate(date) // Get events (models) from the storage / API

  var events = [Event]()

  for model in models {
      // Create new EventView
      let event = Event()
      // Specify DateInterval
      event.dateInterval = DateInterval(start: model.startDate, end: model.endDate)
      // Add info: event title, subtitle, location to the array of Strings
      var info = [model.title, model.location]
      info.append("\(datePeriod.beginning!.format(with: "HH:mm")) - \(datePeriod.end!.format(with: "HH:mm"))")
      // Set "text" value of event by formatting all the information needed for display
      event.text = info.reduce("", {$0 + $1 + "\n"})
      events.append(event)
  }
  return events
}

After receiving an array of events for a particular day, CalendarKit will handle view layout and display.

To respond to the user input, override mehtods of DayViewDelegate, for example:

override func dayViewDidSelectEventView(_ eventView: EventView) {
  print("Event has been selected: \(eventview.data)")
}

override func dayViewDidLongPressEventView(_ eventView: EventView) {
  print("Event has been longPressed: \(eventView.data)")
}

CalendarKit supports localization and uses iOS default locale to display month and day names. First day of the week is also selected according to the iOS locale.

By default, CalendarKit looks similar to the Apple Calendar app and fully supports Dark Mode. If needed, CalendarKit’s look can be easily customized. Steps to apply a custom style are as follows:

1. Create a new CalendarStyle object (or copy existing one)
2. Change style by updating the properties.
3. Invoke updateStyle method with the new CalendarStyle.

let style = CalendarStyle()
style.backgroundColor = UIColor.black
dayView.updateStyle(style)

• iOS 11.0+, macOS (Catalyst) 10.15+
• Swift 5.7+

The list of features currently in development can be viewed on the issues page.

Before contributing, please review guidelines and code style.

Richard Topchii

CalendarKit is available under the MIT license. See the LICENSE file for more info.

Richard Topchii on Telegram

CalendarKit is a Swift calendar UI library for iOS and Mac Catalyst. It looks similar to the Apple Calendar app out-of-the-box, while allowing customization when needed. CalendarKit is composed of multiple modules which can be used together or independently.

• Create iOS Calendar App in Swift with CalendarKit – Official Tutorial
• Live Programming with CalendarKit – For Beginners

If you have a programming question about how to use CalendarKit in your application, Create a new GitHub Issue with the question tag.

Check out the Sample App for reference.

Create a new Issue from template to report a bug or request a new feature.

Video

Sample App

CalendarKit can be installed with Swift Package Manager or with CocoaPods.

The preferred way of installing CalendarKit is via the Swift Package Manager.

1. In Xcode, open your project and navigate to File → Swift Packages → Add Package Dependency…
2. Paste the repository URL (https://github.com/richardtop/CalendarKit.git) and click Next.
3. For Rules, select Version (Up to Next Major) and click Next.
4. Click Finish.

Adding Package Dependencies to Your App

⚠️ Warning: CocoaPods support is deprecated and will be removed at a later date. It’s recommended to migrate your installation of CalendarKit to using Swift Package Manager.

To install it, add the following line to your Podfile:

pod 'CalendarKit'

Adding Pods to an Xcode project

1. Subclass DayViewController
2. Implement EventDataSource protocol to show events.

CalendarKit requires EventDataSource to return an array of objects conforming to EventDescriptor protocol, specifying all the information needed to display a particular event. You’re free to use a default Event class as a model or create your own class conforming to the EventDescriptor protocol.

// Return an array of EventDescriptors for particular date
override func eventsForDate(_ date: Date) -> [EventDescriptor] {
  var models = myAppEventStore.getEventsForDate(date) // Get events (models) from the storage / API

  var events = [Event]()

  for model in models {
      // Create new EventView
      let event = Event()
      // Specify DateInterval
      event.dateInterval = DateInterval(start: model.startDate, end: model.endDate)
      // Add info: event title, subtitle, location to the array of Strings
      var info = [model.title, model.location]
      info.append("\(datePeriod.beginning!.format(with: "HH:mm")) - \(datePeriod.end!.format(with: "HH:mm"))")
      // Set "text" value of event by formatting all the information needed for display
      event.text = info.reduce("", {$0 + $1 + "\n"})
      events.append(event)
  }
  return events
}

After receiving an array of events for a particular day, CalendarKit will handle view layout and display.

To respond to the user input, override mehtods of DayViewDelegate, for example:

override func dayViewDidSelectEventView(_ eventView: EventView) {
  print("Event has been selected: \(eventview.data)")
}

override func dayViewDidLongPressEventView(_ eventView: EventView) {
  print("Event has been longPressed: \(eventView.data)")
}

CalendarKit supports localization and uses iOS default locale to display month and day names. First day of the week is also selected according to the iOS locale.

By default, CalendarKit looks similar to the Apple Calendar app and fully supports Dark Mode. If needed, CalendarKit’s look can be easily customized. Steps to apply a custom style are as follows:

1. Create a new CalendarStyle object (or copy existing one)
2. Change style by updating the properties.
3. Invoke updateStyle method with the new CalendarStyle.

let style = CalendarStyle()
style.backgroundColor = UIColor.black
dayView.updateStyle(style)

• iOS 11.0+, macOS (Catalyst) 10.15+
• Swift 5.7+

The list of features currently in development can be viewed on the issues page.

Before contributing, please review guidelines and code style.

Richard Topchii

CalendarKit is available under the MIT license. See the LICENSE file for more info.

RetroArch UWP ARM32 only
Cores | Original Project | Wiki

After long time of work I present to you this UWP release of RetroArch for Windows (ARM32) devices

With more than 70+ core

• Windows 15035+ Full cores
• Windows 14393 with few cores
• Windows 10586 with few cores
• DirectX Feature level 11, 9.3 & 9.1

• This repo for ARM32, legacy support only
• Refer to the official repo for any updates Click here
• Please don’t ask or contact me for other than ARM32
• This repo is not meant to be up-to date fork (nor redistribution)

This app supported by UWP2Win32

The current cores downloader/updater linked with my repo at docs/cores

if you want to help to get/fix more cores for ARM please submit pull request with the target core or contact me

• RetroArch Developed by RetroArch Team

• Bashar Astifan (UWP Improvements and ARM support)

• Gustave Monce (DLL dynamic loading solution)

RetroArch Team done great job to make this project if you would like to support them Click Here

• You need SDKs: 19041 and 14393
• Use Visual Studio 2022
• Goto pkg\msvc-uwp
• Use only RetroArch-msvc2019-UWP.sln
• You can build it as ReleaseANGLE
• There is also Release 14393 (no much cores)
• To ensure cores loaded correctly, you can make them built-in
• Built-in cores must be at pkg\msvc-uwp\RetroArch-msvc2019-UWP\cores

• Use ReleaseANGLE Legacy
• Or create new config from ReleaseANGLE 14393 D3D
• Define IS_LEVEL_93 in project Preprocessors
• Remove the following from project Preprocessors
• • HAVE_OZONE
• • HAVE_XMB

This project maintained for legacy hardware, when something don’t work well on modern hardware

please don’t open issue for it, I have no interests to support other than ARM32

I’m refering to the ARM32 old one, it was before super slow and the reason was:

• Only ANGLE was used to support older devices
• ANGLE don’t have support for feature level 9.1
• It will fallback to WARP device (more like software render)
• 5~ frames per seconds was expected (WARP is super slow)
• With the latest update in theory it’s expected to work under DirectX and should be fast.

I’m not affiliate with RetroArch or Libretro