habedi

Unity Naming Conventions

Using consistent naming conventions in Unity projects helps keep everything organized and easy to work with. Below is a list of recommended conventions for naming components, scripts, variables, methods, folders, and game objects in a Unity project.

---

General Rules

1. PascalCase for Classes:

• Use PascalCase for class names (e.g., PlayerController, GameManager).

habedi

# This script creates a basic Unity project structure in the current directory.
# To run the script, open a PowerShell terminal and execute the following command:
# .\CreateUnityProjectStructure.ps1

param(
    [string]$BaseDir = (Get-Location).Path
)

# Function to create a directory and handle errors
function Create-Dir {

habedi

-- Note that numbers are estimates, so the exact number of rows or index size might slightly differ from the number shown

-- For MySQL or MariaDB
select
    table_name as `table name`,
    table_rows as `row count`,
    round(data_length / (1024 * 1024 * 1024), 2) as `data size (gb)`,
    round(index_length / (1024 * 1024 * 1024), 2) as `index size (gb)`,
    round((data_length + index_length) / (1024 * 1024 * 1024), 2) as `total size (gb)`
from

habedi

#!/bin/bash

sudo dpkg --add-architecture i386
sudo apt-get update

sudo apt-get install libopenal1:i386 libgtk2.0-0:i386 libvkd3d1 gamemode # gamemode:i386

#sudo apt install gstreamer1.0-plugins-good:i386 gstreamer1.0-plugins-bad:i386 gstreamer1.0-plugins-ugly:i386 gstreamer1.0-libav:i386

# OpenSSL 1.0

habedi

import argparse
import json
import re
from pathlib import Path

import gspread
import pandas as pd
from getfilelistpy import getfilelist
from google.oauth2 import service_account
from tqdm import tqdm

habedi

#!/bin/bash

# Description: This script will create the AWS access keys using the Azure account credentials.
# First, run the docker container (code below) and then enter the Azure account credentials.
# The AWS access keys will be created and stored in the ~/.aws/credentials file in the host machine.

docker run -it --rm \
  --name aws-azure-login \
  --workdir /root \
  -v ${HOME}/.aws:/root/.aws \

habedi

from typing import Any

import numpy as np
import openai
from numpy import ndarray, dtype

class LanguageModels:
    """Enum for the supported language models."""
    OPENAI_GPT35TURBO = 'gpt-3.5-turbo'
    OPENAI_GPT4O = 'gpt-4o'

habedi

#!/bin/bash

# Download a dataset or competition data from Kaggle using the Kaggle API
# Usage: download_kaggle_dataset.sh <type> <dataset-name> <output_dir>
# Arguments:
#  type: The type of the Kaggle data to download. Either '-d' or 'dataset' for dataset, or '-c' or 'competition' for competition.
#  dataset-name: The name of the dataset or competition on Kaggle. For datasets, it should be in the format 'username/dataset-name'.
#  output_dir: The directory where the data will be downloaded and extracted.

# Examples:

habedi

#!/bin/bash

# List of the packages to be installed and their descriptions
packages=(
    "duf:Disk Usage/Free Utility"
    "fzf:A general-purpose command-line fuzzy finder"
    "bpytop:Resource monitor that shows usage and stats for processor, memory, disks, network and processes"
    "htop:Interactive process viewer"
    "nano:Easy-to-use text editor"
    "tmux:A terminal multiplexer"

habedi