Joseph Sebastian alkmst-xyz

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

Building custom layers in Keras

About Keras

Keras is currently one of the most commonly used deep learning libraries today. And part of the reason why it's so popular is its API. Keras was built as a high-level API for other deep learning libraries ie Keras as such does not perform low-level tensor operations, instead provides an interface to its backend which are built for such operations. This allows Keras to abstract a lot of the underlying details and allows the programmer to concentrate on the architecture of the model. Currently Keras supports Tensorflow, Theano and CNTK as its backends.

Let's see what I mean. Tensorflow is one of the backends used by Keras. Here's the code for MNIST classification in TensorFlow and Keras. Both models are nearly identical and applies to the same problem. But if you compare the codes you g

Moved to git repository: https://github.com/aliesbelik/load-testing-toolkit

Benchmarking & load testing

Tools to benchmark & load-test your code or services

http/s

apachebench (ab) - Standalone apachebench (ab), Apache HTTP server benchmarking tool. C
httperf - A tool for measuring web server performance. C

In the last years I've been asked multiple times about the comparison between raylib and SDL libraries. Unfortunately, my experience with SDL was quite limited so I couldn't provide a good comparison. In the last two years I've learned about SDL and used it to teach at University so I feel that now I can provide a good comparison between both.

Hope it helps future users to better understand this two libraries internals and functionality.

	# References:
	# https://cmake.org/cmake/help/latest/command/add_custom_target.html
	# https://samthursfield.wordpress.com/2015/11/21/cmake-dependencies-between-targets-and-files-and-custom-commands/
	# https://gist.github.com/socantre/7ee63133a0a3a08f3990
	# https://stackoverflow.com/questions/24163778/how-to-add-custom-target-that-depends-on-make-install
	# https://stackoverflow.com/questions/30719275/add-custom-command-is-not-generating-a-target
	# https://stackoverflow.com/questions/26024235/how-to-call-a-cmake-function-from-add-custom-target-command
	# https://blog.csdn.net/gubenpeiyuan/article/details/51096777

	cmake_minimum_required(VERSION 3.10)

	# Determines which branch(es) will cause a CI build to be started
	trigger:
	- master

	# Stages precede strategy, in other words each stage can contain a strategy (or multiple or none)
	# Full run-cylce described here: https://docs.microsoft.com/en-us/azure/devops/pipelines/process/runs?view=azure-devops
	stages:
	- stage: Prepare
	jobs:
	- job:

	# We set an environment variable in this phase so it gets picked up by pip, but we don't want to bake secrets into our container image
	FROM python:3.6-alpine AS builder

	ARG INDEX_URL
	ENV PIP_EXTRA_INDEX_URL=$INDEX_URL

	COPY requirements.txt .

	RUN pip install -U pip \
	&& pip install --user -r requirements.txt

	-- returns a child object with single parent as nested JSON object
	--
	-- {
	-- "id": 155,
	-- "name": "Stephen King",
	-- "publisher": {
	-- "id": 13,
	-- "name": "Paladin Books"
	-- }
	-- }

	import asyncio
	import psycopg2

	# dbname should be the same for the notifying process
	conn = psycopg2.connect(host="localhost", dbname="example", user="example", password="example")
	conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)

	cursor = conn.cursor()
	cursor.execute(f"LISTEN match_updates;")

	# -- coding: utf-8 --
	"""Example combination of FastAPI and Pydantic with aiosql and aiosqlite.

	This module demonstrates the minimum viable integration approach for putting
	together a few components:

	- FastAPI. This provides a very high-performance and type-driving approach to
	building APIs in Python
	- Pydantic. A powerful data validation library.
	- aiosql. Inspired by annosql and originally Clojure's yeSql, a way to programatically,