leto | key value storage example powered by hashicorp raft | Architecture library

I'm trying to develop my first R shiny app. I am trying to do that user can decide what year he wanna see.

The error that I'm running is:

I am trying to mimic a visual that depicts multiple relationships by time period, like this (time period = generation):

However, my efforts have not panned out thus far; I'm still getting blank output in the browser. Hard coded data and code in the snippet:

I would like to know how to check if the date that I inputted is valid.

I have two tables in a SQLite DB. One contains player information, including an id, first name and surname. The second contains a list of instances where a game has been played, including the date, what type of game was played, and which player participated (i.e., several players might play the same game on the same day and so there could be multiple records with the only differences listing a different player id).

The tables look like this (apologies for formatting - I'm new):

tbl_players

I'm building an app which basically checks if ad user was fired by HR if it was it sends teams message with 3 options. The options are delete user , disable user and do nothing with the user. After administrator clicks on appropriate option the teams sends another message with confirmation that it was done and what option was used for that action.

So the problem is I can only make an if statement to return only 2 of 3 options. Is there away to make it check all 3 options and return only one which was used ?

The submitActionId is always correct when I click on the options

Here is my if statement if(equals(body('KDVPRequestUserDelete')['submitActionId'], 'Confirm'),'Delete','Disabled')

My teams action button looks like this:

I'm making a lyrics command. Because of discord limit I have to split the message into parts. My current solution just splits the message at 2000 characters.

I have two table with the following data:

I am currently trying to learn machine learning techniques and wanted to recreate a simple image recognition algorithm with tensorflow. Therefore I made two Python-files: One for training and one for prediction.

Tested on Ubuntu 18.04 Used Python Version: 3.7 Used Numpy Version: 1.18.1 Used Tensorflow Version: 1.14 and 2.1.0 (outputs below are from Version 1.14)

My images are from http://www.cs.columbia.edu/CAVE/databases/pubfig/download/#dev The set consists of about 3000 images of cropped faces from 60 people.

train_model.py:

My distro does not offer any gsl <2.6 any more.

Given:

• Alien::GSL 1.01
• /tmp/gsl-2.5.tar.gz

How do I force it to compile that gsl instead of downloading from GNU FTP version 2.6, which I already have on the system anyway but is not delectable to Math::GSL 0.40?

I unsuccessfully tried:

• copying the tarball into the unpacked Alien::GSL base directory
• messing with alien_repository

This is for a throw-away project. I'm okay with manual installation instructions and patching toolchain code.