- XDebug v3+ inside Docker (e.g. php:7.3-apache Docker image)
- Running Docker v20.10+
- VSCode with PHP Debug Extension (Felix Becker)
- Using Docker Compose for orchestration
Discover gists
In some cases, only these lines will work
for product in IntelliJIdea WebStorm DataGrip PhpStorm CLion PyCharm GoLand RubyMine; do
rm -rf ~/.config/$product*/eval 2> /dev/null
rm -rf ~/.config/JetBrains/$product*/eval 2> /dev/null
done
But if not, try these
UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli
. Please find it here: https://github.com/ericmjl/pyds-cli
Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.
Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.
Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!
>>> docker exec -it CONTAINERID /bin/sh
/app # telnet
/bin/sh: telnet: not found
/app # apk update
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/main/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/community/x86_64/APKINDEX.tar.gz
v3.7.0-243-gf26e75a186 [http://dl-cdn.alpinelinux.org/alpine/v3.7/main]
v3.7.0-229-g087f28e29d [http://dl-cdn.alpinelinux.org/alpine/v3.7/community]
{ | |
"books": [ | |
{ | |
"book": "Genesis", | |
"verses": 1533, | |
"chapters": 50 | |
}, | |
{ | |
"book": "Exodus", | |
"verses": 1213, |
// To run: | |
// clang core-audio-sine-wave.c -framework AudioUnit && ./a.out | |
#include <AudioUnit/AudioUnit.h> | |
#define SAMPLE_RATE 48000 | |
#define TONE_FREQUENCY 440 | |
#define M_TAU 2.0 * M_PI | |
OSStatus RenderSineWave( | |
void *inRefCon, |
background: 使用 fly.io 的日本机器安装 cloudflare tunnel 利用它代理部署了 edgetunnel 的 cloudflare worker 的域名 实现指定使用日本的IP地址。
同时 也可以通过使用指定中转IP 实现使用全球任意地区的cloudflare IP
菜单点击 Access -> Tunnels
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
# | |
# This is how I used it: | |
# $ cat ~/.bash_history | python bash-to-zsh-hist.py >> ~/.zsh_history | |
import sys | |
import time |
# ----------------------------------------------------------------------------- | |
# From https://en.wikipedia.org/wiki/Minkowski–Bouligand_dimension: | |
# | |
# In fractal geometry, the Minkowski–Bouligand dimension, also known as | |
# Minkowski dimension or box-counting dimension, is a way of determining the | |
# fractal dimension of a set S in a Euclidean space Rn, or more generally in a | |
# metric space (X, d). | |
# ----------------------------------------------------------------------------- | |
import scipy.misc | |
import numpy as np |
:root { | |
--primary-color: #005fff; | |
--primary-color-alpha: #005fff1a; | |
} | |
html, | |
body { | |
margin: 0; | |
padding: 0; | |
height: 100%; |