Update render script and Makefile

terminal/racket

@@ -1,10 +1,11 @@
-                                                                                    Awesome Racket (https://awesome-racket.com)
+                                                                          Awesome Racket (https://awesome-racket.com)
 
 
 
 A curated list of Awesome Racket, libraries and software. Inspired by awesome-go (https://github.com/avelino/awesome-go).
 
-!Build Status (https://github.com/avelino/awesome-racket/actions/workflows/ci.yml/badge.svg?branch=main) (https://github.com/avelino/awesome-racket/actions/workflows/ci.yml?query=branch%3Amain)
+!Build Status (https://github.com/avelino/awesome-racket/actions/workflows/ci.yml/badge.svg?branch=main) 
+(https://github.com/avelino/awesome-racket/actions/workflows/ci.yml?query=branch%3Amain)
 !Awesome (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg) (https://github.com/sindresorhus/awesome)
 
 
@@ -75,10 +76,12 @@
 - gls (https://github.com/Kalimehtar/gls) - Generic Little (Object, Type, Anything, etc) System - multiple dispatch on types.
 - graph (https://github.com/stchang/graph) - Generic graph library.
 - opt (https://gitlab.com/RayRacine/opt) - Optional and Either data type utilities. Provides util function for Typed Racket's Option type as well as defines an Either type.
-- phc-adt (https://github.com/jsmaniac/phc-adt) - Algebraic Data Types for Typed/Racket, with features tailored to compiler writing. The data types do not have to be declared before they are used, like prefab 
-structs and symbols. Behind the scenes, this library remembers all the data types in a file, and uses it to implicitly pre-declare them. Mostly stable, although some things may change a bit in the future.
+- phc-adt (https://github.com/jsmaniac/phc-adt) - Algebraic Data Types for Typed/Racket, with features tailored to compiler writing. The data types do not have to be declared before they are 
+used, like prefab structs and symbols. Behind the scenes, this library remembers all the data types in a file, and uses it to implicitly pre-declare them. Mostly stable, although some things 
+may change a bit in the future.
 - quad-tree (https://github.com/dented42/racket-quad-tree) - A fairly simple quad-tree implementation. Nothing terribly fancy. Currently rather unstable.
-- rebellion (https://docs.racket-lang.org/rebellion/index.html) - Dozens of well-documented modules to aid in general-purpose programming. Extensive. Includes multidict, range set, and much more.
+- rebellion (https://docs.racket-lang.org/rebellion/index.html) - Dozens of well-documented modules to aid in general-purpose programming. Extensive. Includes multidict, range set, and much 
+more.
 - try (https://gitlab.com/RayRacine/try) - A Typed Racket Try datatype and routines for computations that throw exceptions.
 
 Database Drivers
@@ -153,12 +156,12 @@
 - layer (https://github.com/cloudkj/layer) - Neural network inference the Unix way.
 - racket-knn (https://github.com/asbaker/racket-knn) - K Nearest Neighbors, KNN, is a lazy, supervised machine learning algorithm. This is an implementation in scheme using racket.
 - racket-ml (https://github.com/danking/racket-ml) - A collection of things I found useful for doing Machine Learning problem sets.
-- rml-core (https://github.com/johnstonskj/rml-core) - This Package is part of an expected set of packages implementing machine learning capabilities for Racket. The core of this package is the management of 
-'datasets', these datasets are assumed to be for training and testing of machine learning capabilities.
-- rml-decisiontrees (https://github.com/johnstonskj/rml-decisiontrees) - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular package implements 
-support for classification of individuals using decision trees.
-- rml-knn (https://github.com/johnstonskj/rml-knn) - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular package implements the K-Nearest Neighbor 
-approach for classification.
+- rml-core (https://github.com/johnstonskj/rml-core) - This Package is part of an expected set of packages implementing machine learning capabilities for Racket. The core of this package is 
+the management of 'datasets', these datasets are assumed to be for training and testing of machine learning capabilities.
+- rml-decisiontrees (https://github.com/johnstonskj/rml-decisiontrees) - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular 
+package implements support for classification of individuals using decision trees.
+- rml-knn (https://github.com/johnstonskj/rml-knn) - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular package implements the 
+K-Nearest Neighbor approach for classification.
 - tesseract (https://github.com/lasfter/tesseracket) - Bindings for Google's Tesseract-OCR.
 
 Macros