Nahid Chowdhury ovichowdhury

For creating a solution

dotnet new sln -n SolutionName

dotnet new webapi -n Todo.API

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

	CREATE TABLE accounts (
	account_id SERIAL PRIMARY KEY,
	account_name VARCHAR(100) NOT NULL,
	account_type VARCHAR(20) NOT NULL -- 'Asset', 'Liability', 'Equity', 'Income', 'Expense'
	);

	CREATE TABLE transactions (
	transaction_id SERIAL PRIMARY KEY,
	account_id INTEGER REFERENCES accounts(account_id),
	transaction_date DATE NOT NULL DEFAULT CURRENT_DATE,

	import React, { useEffect, useState } from 'react'
	import {
	APIProvider,
	Map,
	AdvancedMarker,
	Pin,
	InfoWindow,
	MapMouseEvent,
	useMap,
	useMapsLibrary,

	# generate a private key with the correct length
	openssl genrsa -out private-key.pem 3072

	# generate corresponding public key
	openssl rsa -in private-key.pem -pubout -out public-key.pem

	# optional: create a self-signed certificate
	openssl req -new -x509 -key private-key.pem -out cert.pem -days 360

	# optional: convert pem to pfx

	# -c = Number of concurrent request
	# -n = Total Number of Request
	# -p = Post Request

	# for get request
	ab -c 10 -n 500 https://127.0.0.1:5060/faceapi/encodings

	# for post request
	ab -p body_encodings.json -T application/json -c 10 -n 500 -l http://127.0.0.1:5060/faceapi/encodings

	# Create a linux user
	> sudo adduser <name> --home /home/<name>
	> sudo usermod -aG sudo <username>

	* Keep feature branch up to date with main *

	//in feature branch
	git fetch
	git rebase origin/main
	// if conflict arise and resolved manually
	git rebase --continue
	git push --force

	# for cuda memory allocation error
	# add this line so that memory can grow by tf
	# face_service.py

	from tensorflow as tf
	physical_devices = tf.config.experimental.list_physical_devices('GPU')
	tf.config.experimental.set_memory_growth(physical_devices[0], True)