Skip to content

Instantly share code, notes, and snippets.

View wwerner's full-sized avatar

Wolfgang Werner wwerner

View GitHub Profile
@MaxLaumeister
MaxLaumeister / ipfs.service
Created September 22, 2018 01:57
systemd script for ipfs-daemon run-on-boot
[Unit]
Description=IPFS daemon
After=network.target
[Service]
### Uncomment the following line for custom ipfs datastore location
# Environment=IPFS_PATH=/path/to/your/ipfs/datastore
ExecStart=/usr/local/bin/ipfs daemon
Restart=on-failure
@moreta
moreta / vue_devtool_open_component_in_editor.md
Last active August 19, 2022 07:44
Vue devtool Open component in editor tips
@duluca
duluca / npm-scripts-for-docker.md
Last active April 8, 2024 09:52
npm scripts for Docker

These are generic npm scripts that you can copy & paste into your package.json file as-is and get access to convinience scripts to manage your Docker images all in one place.

How to Use

npm i -g mrm-task-npm-docker
npx mrm npm-docker

Contribute

Here's the code repository https://github.com/expertly-simple/mrm-task-npm-docker

@robertpainsi
robertpainsi / commit-message-guidelines.md
Last active May 3, 2024 11:43
Commit message guidelines

Commit Message Guidelines

Short (72 chars or less) summary

More detailed explanatory text. Wrap it to 72 characters. The blank
line separating the summary from the body is critical (unless you omit
the body entirely).

Write your commit message in the imperative: "Fix bug" and not "Fixed
bug" or "Fixes bug." This convention matches up with commit messages
@rtfpessoa
rtfpessoa / getopts_long.sh
Created January 21, 2017 19:06
getopts_long -- POSIX shell getopts with GNU-style long option support
#!/usr/bin/env bash
#
# getopts_long -- POSIX shell getopts with GNU-style long option support
#
# Copyright 2005-2009 Stephane Chazelas <stephane_chazelas@yahoo.fr>
#
# Permission to use, copy, modify, distribute, and sell this software and
# its documentation for any purpose is hereby granted without fee, provided
# that the above copyright notice appear in all copies and that both that
@dsyer
dsyer / startup.md
Last active October 30, 2023 07:41
Notes on Spring Boot startup performance

Anatomy of Spring Boot Start Up Timing

When a Spring Boot app starts up with default (INFO) logging, there are some noticeable gaps (pauses). It's worth focusing on the gaps when looking for efficiency savings because of the amount of time they take, and because no-one bothered to log anything, so the chances are the app is doing something repetitive. We can tweak the logging levels to try and fill in the gaps and find out what is going on in there.

Basic empty web app with actuators has three such gaps:

0                                                                        1410ms
|------|---------------------------|-----|------|---------|--------|--------|
       |           578             |     |144(5)|         | 133(6) |
@dcode
dcode / GitHub Flavored Asciidoc (GFA).adoc
Last active April 20, 2024 13:55
Demo of some useful tips for using Asciidoc on GitHub

GitHub Flavored Asciidoc (GFA)

Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.

1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.

val square : Int => Int = x => x * x
@thomasdarimont
thomasdarimont / readme.md
Last active March 15, 2024 08:56
Example for decoding a JWT Payload with your Shell (bash, zsh...)

Setup

Add this to your .profile, .bashrc, .zshrc...

decode_base64_url() {
  local len=$((${#1} % 4))
  local result="$1"
  if [ $len -eq 2 ]; then result="$1"'=='
  elif [ $len -eq 3 ]; then result="$1"'=' 
  fi
 echo "$result" | tr '_-' '/+' | openssl enc -d -base64
@fchollet
fchollet / classifier_from_little_data_script_1.py
Last active November 28, 2023 07:12
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats