Dadangdut33

Here is how i managed to use and style editorjs for my use.

Some notes:

• To obtain the content we pass setRef, so a higher component can get the content easily
• You might not need to style the .dark style yourself if you are using mantine's TypographyStylesProvider because it should do the color just fine. (i styled it in my css because i forgot that it exists)
• I use this component for both editing and rendering results, that's why there is editable and not-editable class
• To improve ssr i render the results plainly in server side using editorjs-parser

Dadangdut33

If you want to serve files using public folder in next js and you want to have upload ability you should use this custom server because next js wont serve dynamically created or uploaded images.

To counter this, we can use express' static method.

Package needed:

• express
• cross-env (optional, you might be able to use other lib like dotnev)

(methods tested on next js 14 using nextjs app)

Dadangdut33

import { passRequirements } from "@/lib/constant";
// example
/*
export const passRequirements = [
  { re: /[0-9]/, label: "Number" },
  { re: /[a-z]/, label: "lowercase letter" },
  { re: /[A-Z]/, label: "Uppercase letter" },
  { re: /[$&+,:;=?@#|'<>.^*()%!-]/, label: "Special symbol" },
];
*/

Dadangdut33

import { Input as MantineInput, TextInput } from "@mantine/core";
import { UseFormReturnType } from "@mantine/form";
import { LegacyRef, forwardRef } from "react";
import PhoneInput, { DefaultInputComponentProps, Value } from "react-phone-number-input";
import "react-phone-number-input/style.css";

// eslint-disable-next-line react/display-name
const CustomInput = forwardRef((inputProps: DefaultInputComponentProps, ref: LegacyRef<HTMLInputElement>) => {
  const { error, ...rest } = inputProps;
  return (

Dadangdut33

About

Powershell support the following hashing algorithm:

• SHA1
• SHA256
• SHA384
• SHA512
• MD5

I created simple script that you can add to your powershell $PROFILE

Dadangdut33

1. Install CUDA 11.8 first

$ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
$ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
$ wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb
$ sudo dpkg -i cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb
$ sudo cp /var/cuda-repo-wsl-ubuntu-11-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
$ sudo apt-get update
$ sudo apt-get -y install cuda

Dadangdut33

Confirm GPU access in WSL

In an Ubuntu terminal, enter nvidia-smi. If that fails, make sure your Nvidia drivers are up-to-date (current version: 511.23). Win10 version also needs to be at least 21H2 (Winkey + R then winver in Windows to check version).

Install CUDA Toolkit 11.2

Current versions of TF use CUDA 11.2 and cuDNN 8.1. Tested build configurations Run the below commands in a terminal:

wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.2.2/local_installers/cuda-repo-wsl-ubuntu-11-2-local_11.2.2-1_amd64.deb

Dadangdut33

# GlobalClass.py
from typing import Optional, TYPE_CHECKING

if TYPE_CHECKING:
    from MainWindow import MainWindow  # Forward declaration for type hinting

class GlobalClass:
    def __init__(self):
        self.mw: Optional[MainWindow] = None
        self.x = 1

Dadangdut33

# Global
git config --global core.ignorecase false

# local
git config --local core.ignorecase false

Dadangdut33

import ctypes
import win32.lib.win32con as win32con
import win32gui # pip install pywin32
from time import sleep

kernel32 = ctypes.WinDLL('kernel32')
user32 = ctypes.WinDLL('user32')

a = input('Input value here:')