kentcdodds

{
  "name": "remove-ts",
  "version": "1.0.0",
  "description": "I use this to automatically fix feedback links in my workshops",
  "bin": "./remove-ts.js",
  "dependencies": {
    "@babel/core": "7.13.8",
    "@babel/preset-typescript": "7.13.0",
    "glob": "7.1.6"
  }

sindresorhus

Pure ESM package

The package that linked you here is now pure ESM. It cannot be require()'d from CommonJS.

This means you have the following choices:

1. Use ESM yourself. (preferred)
   Use import foo from 'foo' instead of const foo = require('foo') to import the package. You also need to put "type": "module" in your package.json and more. Follow the below guide.
2. If the package is used in an async context, you could use await import(…) from CommonJS instead of require(…).
3. Stay on the existing version of the package until you can move to ESM.

andywer

React - Functional error boundaries

Thanks to React hooks you have now happily turned all your classes into functional components.

Wait, all your components? Not quite. There is one thing that can still only be implemented using classes: Error boundaries.

There is just no functional equivalent for componentDidCatch and deriveStateFromError yet.

Proposed solution

jayspeidell

# Info on how to get your api key (kaggle.json) here: https://github.com/Kaggle/kaggle-api#api-credentials
!pip install kaggle
api_token = {"username":"USERNAME","key":"API_KEY"}
import json
import zipfile
import os
with open('/content/.kaggle/kaggle.json', 'w') as file:
    json.dump(api_token, file)
!chmod 600 /content/.kaggle/kaggle.json
!kaggle config path -p /content

joseluisq

How to recover a dropped stash in Git?

1. Find the stash commits

git log --graph --oneline --decorate ( git fsck --no-reflog | awk '/dangling commit/ {print $3}' )

This will show you all the commits at the tips of your commit graph which are no longer referenced from any branch or tag – every lost commit, including every stash commit you’ve ever created, will be somewhere in that graph.

omoindrot

"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

bastman

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm