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raylib in numbers

raylib recently hit version 3.5, it's been more than 7.5 years since I started working in this project and for the last 2 years I've been compiling some numbers about the project evolution.

All of the graphs presented show an increasing popularity and usage of the project. It's interesting to see that during the first 5 years of development, raylib was not specially popular, it was used mostly by me to teach videogames development to my students, actually, that was the origin of the library, but in the last two years project exposure has grown exponentially.

Let's check the numbers!

Requirements

First you need to install pandoc.

I used brew install pandoc to install via Homebrew since I'm on a mac.

Writing your presentation

Make a slides.md for your slides (or name it whatever you want!). I put images in an /images/ folder. You can see how links and images and all of that work from this sample:

Grouping results and removing unwanted ones

Here we want to scrape product name, price and rating from ebay product pages:

url = 'https://www.ebay.com/itm/Sony-PlayStation-4-PS4-Pro-1TB-4K-Console-Black/203084236670' 

wanted_list = ['Sony PlayStation 4 PS4 Pro 1TB 4K Console - Black', 'US $349.99', '4.8'] 

scraper.build(url, wanted_list)

The list is moving out!

If you share this list, please use this link instead: https://lambdaurora.dev/optifine_alternatives

It may still be only a redirection link, but it will have a better web display of the list soon. And the list being on GitHub/GitHub pages improves load times.

The gist version of this list will stop being updated.

Why?

How to Install FAR, HD Texture Pack, and ReShade (GShade) for NieR:Automata on Linux

About

Links

FAR (Fix (NieR) Automata Resolution) -- Required by HD Texture Pack.
HD Texture Pack

	#include "raylib.h"
	#include <gst/gst.h>
	#include <gst/app/gstappsink.h>


	GstElement* createPipeline(const char* filename)
	{
	GError *error;
	gchar *pipelineString = g_strdup_printf ("filesrc location=%s ! tee name=t ! queue ! decodebin ! videoconvert ! appsink name=output caps=video/x-raw,format=RGBA,pixel-aspect-ratio=1/1 t. ! queue ! decodebin ! audioconvert ! audioresample ! autoaudiosink", filename);
	GstElement *pipeline = gst_parse_launch (pipelineString, &error);

	// To compile: clang++ -arch x86_64 -arch arm64 -std=c++20 library_injector.cpp -lbsm -lEndpointSecurity -o library_injector,
	// then codesign with com.apple.developer.endpoint-security.client and run the
	// program as root.

	#include <EndpointSecurity/EndpointSecurity.h>
	#include <algorithm>
	#include <array>
	#include <bsm/libbsm.h>
	#include <cstddef>
	#include <cstdint>

	Permission is hereby granted, free of charge, to any person obtaining a copy
	of this software and associated documentation files (the "Software"), to deal
	in the Software without restriction, including without limitation the rights
	to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	copies of the Software, and to permit persons to whom the Software is
	furnished to do so, subject to the following conditions:

	The above copyright notice and this permission notice shall be included in
	all copies or substantial portions of the Software.

	import inspect
	import logging
	import os
	from pathlib import Path

	import torch
	from psutil import cpu_count
	from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer
	from transformers.generation_utils import GenerationMixin
	from transformers.modeling_outputs import BaseModelOutputWithPast, Seq2SeqLMOutput

	from keras.datasets import mnist
	from keras.layers import Input, Dense, Reshape, Flatten
	from keras.layers import BatchNormalization
	from keras.layers.advanced_activations import LeakyReLU
	from keras.models import Sequential, Model
	from keras.optimizers import Adam
	import matplotlib.pyplot as plt
	import numpy as np