sandys

MOTA (Many of the Above) is Honest voting - you dont have to fear about vote wasting

This is very easy to describe to voters: vote for everyone you approve of.
MOTA does one thing very well - it removes any reason to vote against your favorite candidate.

Intuitive Explanation

In any voting system, if there's only ONE candidate - not voting and voting for the candidate are the same.
For TWO candidates - it is better to pick the one you like more.

sandys

1. If ur upgrading from an older fedora,
  1.1 `sudo dnf remove docker-*`
  1.2 `sudo dnf config-manager --disable docker-*`
  1.2 please ensure `/etc/default/grub` doesnt contain `systemd.unified_cgroup_hierarchy=0`. If it does contain, then remove it and run `sudo grub2-mkconfig -o /boot/grub2/grub.cfg`
2. reboot
3. set firewall correctly using `sudo firewall-cmd --zone=docker --change-interface=docker0`
4. in `/etc/sysconfig/docker` please ensure `--live-restore` is removed
5. reboot
6. docker should work

sandys

why this code ?

• tiangolo/full-stack-fastapi-template#104
• tiangolo/fastapi#551

P.S. How to quickly run postgres (using docker)

sandys

1. Download git-filter-repo script
2. name the file as clean.py
3. run python /tmp/clean.py --force --strip-blobs-bigger-than 100M --refs

sandys

docker network create pg

docker run -it --rm -P -p 5432:5432 --name pg -e POSTGRES_PASSWORD=password -e POSTGRES_USER=postgres -e POSTGRES_DB=production -v pgdata:/var/lib/postgresql/data --network=pg postgres

pgdata is the name of the docker volume. You can check it using docker volume ls and docker volume inspect pgdata. You can delete the docker volume by docker volume rm pgdata and prune all volumes using docker volume prune docker volumes are created in your central docker directory (usually /var/lib/docker/overlay2 ). You generally dont need to care about this.

You can now access it in many ways:

sandys

const withPlugins = require('next-compose-plugins');
const withTM = require('next-transpile-modules')(['reusecore', 'common']);
const withOptimizedImages = require('next-optimized-images');
const withFonts = require('next-fonts');
const withCSS = require('@zeit/next-css');

const path = require("path");

module.exports = withPlugins(
  [

sandys

#

... import xgboost.sklearn as xgb 
... from sklearn.model_selection import GridSearchCV 
... from sklearn.model_selection import TimeSeriesSplit 
...  
... cv = 2 
...  
... trainX= [[1], [2], [3], [4], [5]] 
... trainY = [1, 2, 1, 2, 1] 

sandys

user@instance-mumbai:~/docker-setup-v2/flask$ dig files.pythonhosted.org A

; <<>> DiG 9.10.3-P4-Ubuntu <<>> files.pythonhosted.org A ;; global options: +cmd ;; Got answer: ;; ->>HEADER<<- opcode: QUERY, status: NOERROR, id: 3624 ;; flags: qr rd ra; QUERY: 1, ANSWER: 5, AUTHORITY: 0, ADDITIONAL: 1

;; OPT PSEUDOSECTION: ; EDNS: version: 0, flags:; udp: 512

sandys

[Unit]
Description=Datadog Docker Swarm
After=systemd-journald.service
Requires=systemd-journald.service

[Service]

ExecStart=/bin/zsh -c "coproc  while true; do ncat --ssl intake.logs.datadoghq.com 10516; done ;journalctl -o json -f | jq -r --unbuffered '\"c441ade4f5f4d04c  \" + ({ message:.MESSAGE, service_name:.COM_DOCKER_SWARM_SERVICE_NAME, container:.CONTAINER_NAME, containerid:.CONTAINER_ID_FULL, host:._HOSTNAME,pid:(._PID // \"-\"), timestamp:(.__REALTIME_TIMESTAMP|tonumber/1000000|todate),\"syslog.severity\":((.PRIORITY|tonumber))  }|tostring)' >&p 2>&p"

sandys

wget https://developer.nvidia.com/compute/cuda/9.1/Prod/local_installers/cuda-repo-ubuntu1604-9-1-local_9.1.85-1_amd64
sudo add-apt-repository ppa:graphics-drivers
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"

curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey |   sudo apt-key add -