| docker config inspect pxc_proxysql_cnf | jq '.[0].Spec.Data' -r | base64 --decode > proxysql.cfg |
"A phantom type is a parametrised type whose parameters do not all appear on the right-hand side of its definition..." Haskell Wiki, PhantomType
The following write-up is intended as an introduction into using phantom types in ReasonML.
Taking a look at the above definition from the Haskell wiki, it states that phantom types are parametrised types where not all parameters appear on the right-hand side. Let's try to see if we can implement a similar example as in said wiki.
This cheat sheet provides a detailed overview of the exposed lifecycle events and available commands (and entrypoints) of the Serverless framework, that can be hooked by plugins (internal and external ones). The document is structured by the commands invoked by the user.
Lifecycle events are shown as the globally available outer events (all providers) and sub lifecycle events that are provider specific in the called order. Currently only the AWS provider is shown. If you have information about the other provider,
| from __future__ import with_statement | |
| from alembic import context | |
| from sqlalchemy import engine_from_config, pool | |
| from logging.config import fileConfig | |
| from models import Base | |
| config = context.config | |
| fileConfig(config.config_file_name) |
| #!/usr/bin/env bash | |
| # Installs: | |
| # Iterm2 | |
| # Powerline fonts (for Menlo) | |
| # Material Design (color scheme) | |
| # Fish | |
| # Oh-my-fish | |
| # Agnoster theme (works well with Material) |
| ssh-keygen -t rsa -b 4096 -m PEM -f jwtRS256.key | |
| # Don't add passphrase | |
| openssl rsa -in jwtRS256.key -pubout -outform PEM -out jwtRS256.key.pub | |
| cat jwtRS256.key | |
| cat jwtRS256.key.pub |
To 'clone' a container, you'll have to make an image of that container first, you can do so by "committing" the container. Docker will (by default) pause all processes running in the container during commit to preserve data-consistency.
For example;
docker commit --message="Snapshot of my container" my_container my_container_snapshot:yymmdd
| function errexit() { | |
| local err=$? | |
| set +o xtrace | |
| local code="${1:-1}" | |
| echo "Error in ${BASH_SOURCE[1]}:${BASH_LINENO[0]}. '${BASH_COMMAND}' exited with status $err" | |
| # Print out the stack trace described by $function_stack | |
| if [ ${#FUNCNAME[@]} -gt 2 ] | |
| then | |
| echo "Call tree:" | |
| for ((i=1;i<${#FUNCNAME[@]}-1;i++)) |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real