#RaspberryPi – Where is my Task Manager? let’s try #htop

Hi !

As a Windows user, I use task manager a lot. You know that moment when

  1. Your PC start to work very slow
  2. You press CTRL+SHIFT+ESC to open Task Manager
  3. Select the not amicable process
  4. And Kill it !

Bonus: another group of people uses a more classic way

  1. Press CTRL+ALT+DEL
  2. Select Task Manager

These days where I’m doing part of my developer work in a Raspberry Pi 4 (see references), I was also in the need for a “Task Manager”. So a quick Bing/Google search pointed a couple of products, and htop seems to be a very popular one. And I also like the official product description

This is htop, an interactive process viewer for Unix systems. It is a text-mode application (for console or X terminals) and requires ncurses.

Official htop page (see references)

It seems that initially the product was created for Unix, and now supports FreeBSD, OpenBSD, macOS, and more. And, of course, it runs on Raspbian.

Question: Should I write a post on how to install Raspbian for Raspberry Pi? My guess is no, there are so many of this already out, but ... if get bored.

Before I move on, let’s take a look at htop running in my device, while I’m building a docker image using some amazing TensorFlow image analysis models.

The way to install htop is very straightforward.

sudo apt-get install htop

Then you can launch the app with

htop

Super Easy ! And again, the UI gives you a lot of very useful information, and because Linux users are heavy on commands and not mouse, 99% of the actions to control the app are using these commands

  • F1 – Help (explains everything, always nice)
  • F6 – SortBy (You can sort the list processes with this option. Sorting by user, CPU usage and memory usage can be useful.)
  • F9 – Kill (You can select a process and send a kill signal)
  • F10 – Quit (sometimes you gotta leave htop)
Note: Get the commands and learn from David Walz post (see references)

Happy Coding!

Greetings @ Burlington

El Bruno

References

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#Humor – How is your #AI algorithm working? Fine …

Hi!

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Passed AZ-300 – My take on the new Microsoft exams

Cloudenius

This morning I passed the AZ-300 exam. To be honest, I was confident that I failed the exam. Especially because I ran out of time with only 80 – 90 %. In this blog post, I will explain you the good and the bad of this exam and the exam experience.

View original post 808 more words

#Azure – Sending custom Telemetry and Event information from a #RaspberryPi device to #AzureIoT Central

Hi!

Azure IoT Central is one of the amazing services we can use on Azure. I was wondering how easy is to use a Raspberry Pi using Raspbian and Azure IoT and here is my experience.

Let’s assume we had a device up to date using Raspbian, our next step will be to create an Azure IoT Central application. The official step by step is the main resource for this

Create an
Azure IoT Central application (see references)

Once we have our application, we can quickly create a new Raspberry Pi device and use it. However, I’ll do an extra step, lessons learned as a handsome developer

Create a Device Template

Go to [Device Templates] and create a new template

azure iot central create new device template

For Raspberry Pi, I’ll name this [Raspberry Pi Dev]

azure iot central create new device template raspberry pi dev

So now, I can add a new real device, in the Devices section from the left menu

azure iot central raspberry pi dev add new real device

Once you create a new real device, is important to copy and save for later the connection information. To access this, go to the top right [Connect] button

azure iot central raspberry pi dev real device connect information

Almost there, there is an official tutorial that explain how to send random telemetry information with a Python script in a Raspberry Pi. I’ll use it as base for this scenario.

Connect a
Raspberry Pi to your Azure IoT Central application (Python) (see references)

For this demo, I’ll add a custom telemetry property and a custom event to the device. Since I won’t use the device to track temperature, accelerometer, and more, I think it make sense to track some custom information.

So, I’ll go back to my Device Template definition and I’ll add a new Telemetry, named [t1], with the following information.

azure iot central raspberry pi dev new telemetry information

And now, I can run a custom version of my script that will send new telemetry information, for [t1]. Sample in line 18

After a couple of minutes running the sample script, I can see the telemetry information for T1. In this view, I enabled [Temperature] and [T1] to display the timeline.

azure iot central raspberry pi dev real device dashboard telemetry

And, next step will be to add an event, which is also a very important uses case in Azure IoT. Back in the Device Template, I add a new event named [event1]

azure iot central raspberry pi dev new event information

And added some extra lines of code to send also an event between telemetry, Line 22

In the following image, we can see how the events appears in the timeline, and we can also get some extra details clicking on each event.

azure iot central raspberry pi dev real device dashboard telemetry and events

Very cool! Next steps will be to integrate this with some image recognition scenarios.

Happy Coding!

Greetings @ Burlington

El Bruno

References

Perceptrón (Inteligencia Artificial) con JavaScript

Matías Iacono

Ufff! Sí, más de un año desde el último post y, viendo las estadísticas del blog (Claramente) la gente que lo consulta es casi nula. Pero, los que me han seguido sabrán que mudé toda la creación de contenido a mi canal de YouTube: https://youtube.com/user/lacosagorda

En el canal subo un video (Como mínimo) por semana así que todo sigue activo. De cualquier manera, vuelvo por acá y no es que vaya a decir lo que suelo y luego me muerdo a mi mismo porque no puedo cumplirlo. Sí, lo que voy a decir es que iré dejando por acá esas cosas que hago de vez en cuando por puro gusto y que, por algún motivo, no he puesto en videos.

Como ya saben, me gusta explorar más allá de las herramientas que podamos usar. No quiero quedarme con el hecho de poder saber usar tal o…

View original post 392 more words

#VSCode – How to install #docker in a #RaspberryPi 4

Hi!

In my series of posts on how to create a development environment using a Raspberry Pi4, today is time to write about installing Docker. (see references)

I was user to download and build docker to be used on the device, however now we have an easier way to do this. Thanks to http://get.docker.com we can now install docker with a single command

curl -sSL
https://get.docker.com | sh

And then, a simple check for the docker version

raspberry pi docker version in terminal

Happy coding!

Greetings @ Toronto

El Bruno

References

[Xamarin October Challenge] Best Practices

Javier Suárez | Blog

Introducción

Los retos (Challenges) han sido una de las gratas sorpresas en la comunidad de Xamarin en este año. No solo hemos tenido varios retos, además han sido recibidos y apoyados de una forma muy positiva.

¿Por qué no tener otro reto en el mes de Octubre?.

Nuevo Challenge

De esta forma nos llega de la mano de Claudio Sanchez el reto de Octubre basado en buenas prácticas. Hablamos de buenas prácticas en todos los ámbitos del desarrollo Xamarin: estructura del proyecto, DevOps, Testing, creación de APIs, etc.

¿Cómo funciona?

Como otros retos anteriores, la idea es llegar a contar con un artículo por cada día del mes. En esta ocasión todo esta centralizado en un repositorio en GitHub. En el repo puedes ver dos aspectos fundamentales:

  • Calendario de fechas: Donde ver cuales están libres y poder elegir cual prefieres ocupar.
  • Tabla de contenido: Un listado con…

View original post 98 more words

[Evento] Monkey Conf 2019

Javier Suárez | Blog

El evento

Y vuelve el evento técnico Xamarin que estabas esperando, Monkey Conf 2019!.

Monkey Conf 2019

Tras el éxito del evento del año pasado, regresamos con una nueva edición de la Monkey Conf. Volverá a ser un evento gratuito, en el que trataremos temas relacionados con desarrollo móvil, Xamarin, Xamarin.Forms, App Center, testing y más…

La fecha

Será el próximo Sábado, 30 de Noviembre de 09:30h a 18:30h (GMT+1). Tendremos dos tracks en paralelo con diferentes sesiones técnicas de 50 minutos de duración cada una. Además contaremos con regalos y sorpresas!.

¿Te apuntas?

NOTA: Las entradas del evento son gratuitas pero limitadas!

El lugar

El evento se celebrará en Liferay. Dirección detallada:

Paseo de la Castellana, 280, 28046 Madrid, Madrid

Oficinas de Liferay

Call 4 Papers

¿Has desarrollado una aplicación con Xamarin?, ¿quieres hablar acerca de como usas App Center?, ¿revisar las próximas novedades de Xamarin.Forms?…

View original post 33 more words

#Anaconda – My steps to install a virtual environment with #TensorFlow, #Keras and more

Hi!

So today post is not a post, just a selfish reminder of the steps I do when I setup a new dev machine

  • Install Anaconda (see references). I use the default settings, and important: I don’t add Anaconda to Windows PATH.
  • Open Anaconda command prompt as administrator
open anaconda as administrator

Need to be open as Admin in order to install updates

  • Install updates with the command
conda update conda 
conda update –all
  • Create a new development environment named “tfEnv” with tensorflow. Activate the environment
conda create -n tfenv tensorflow 
conda activate tfenv
  • The command to install keras is
pip install
keras

However, if it doesn’t work, I install keras with the following packages

pip install matplotlib 
pip install pillow
pip install tensorflow==1.14
conda install mingw libpython
pip install git+git://github.com/Theano/Theano.git
pip install git+git://github.com/fchollet/keras.git
  • Finally, install Jupyter notebook kernel and create a new kernel for the current virtual environment
pip install ipykernel 
ipython kernel install --user --name=tfEnv
  • There seems to be an issue to install OpenCV using pip with the command
pip install
opencv-python

So, I Install the OpenCV nonofficial package. 1st I download a compatible package from

https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl

Install with

pip install
c:\temp\opencv_python-4.1.1-cp36-cp36m-win_amd64.whl

Happy coding!

Greetings @ Toronto

El Bruno

References