Initial evaluation for removing matplotlib and pytest as dependencies.

CITATION.cff

@@ -0,0 +1,10 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+  - family-names: Wilczak
+    given-names: Daniel
+  - family-names: Nguyen
+    given-names: Jack
+title: "EasyGA - Genetic Algorithms made Easy"
+version: 2.0.4
+date-released: 2021-13-05

EasyGA/EasyGA.py

@@ -7,7 +7,7 @@ import decorators
 # Import all the data structure prebuilt modules
 from structure import Population as make_population
 from structure import Chromosome as make_chromosome
-from structure import Gene       as make_gene
+from structure import Gene as make_gene
 from structure import Population
 from structure import Chromosome
 from structure import Gene
@@ -17,23 +17,23 @@ from examples import Fitness
 from termination import Termination
 
 # Parent/Survivor Selection Methods
-from parent   import Parent
+from parent import Parent
 from survivor import Survivor
 
 # Genetic Operator Methods
 from crossover import Crossover
-from mutation  import Mutation
+from mutation import Mutation
 
 # Default Attributes for the GA
 from attributes import Attributes
 
 # Database class
-from database import sql_database
-from sqlite3  import Error
+# from database import SQLDatabase
+# from sqlite3  import Error
 
 # Graphing package
-from database import matplotlib_graph
-import matplotlib.pyplot as plt
+# from database import MatplotlibGraph
+# import matplotlib.pyplot as plt
 
 
 class GA(Attributes):
@@ -46,7 +46,6 @@ class GA(Attributes):
     https://github.com/danielwilczak101/EasyGA/wiki
     """
 
-
     def evolve(self: GA, number_of_generations: float = float('inf'), consider_termination: bool = True) -> None:
         """
         Evolves the ga until the ga is no longer active.
@@ -63,9 +62,12 @@ class GA(Attributes):
         if self.population is None:
             self.initialize_population()
 
-        cond1 = lambda: number_of_generations > 0  # Evolve the specified number of generations.
-        cond2 = lambda: not consider_termination   # If consider_termination flag is set:
-        cond3 = lambda: cond2() or self.active()   #     check termination conditions.
+        # Evolve the specified number of generations.
+        def cond1(): return number_of_generations > 0
+        # If consider_termination flag is set:
+        def cond2(): return not consider_termination
+        # check termination conditions.
+        def cond3(): return cond2() or self.active()
 
         while cond1() and cond3():
 
@@ -74,10 +76,11 @@ class GA(Attributes):
 
                 # Create the database here to allow the user to change the
                 # database name and structure before running the function.
-                self.database.create_all_tables(self)
+                # self.database.create_all_tables(self)
 
                 # Add the current configuration to the config table
-                self.database.insert_config(self)
+                # self.database.insert_config(self)
+                pass
 
             # Otherwise evolve the population.
             else:
@@ -102,10 +105,9 @@ class GA(Attributes):
             if int(adapt_counter) < int(adapt_counter + self.adapt_rate):
                 self.adapt()
 
-            number_of_generations   -= 1
+            number_of_generations -= 1
             self.current_generation += 1
 
-
     def update_population(self: GA) -> None:
         """
         Updates the population to the new population
@@ -113,7 +115,6 @@ class GA(Attributes):
         """
         self.population.update()
 
-
     def reset_run(self: GA) -> None:
         """
         Resets a run by re-initializing the
@@ -123,7 +124,6 @@ class GA(Attributes):
         self.current_generation = 0
         self.run += 1
 
-
     def adapt(self: GA) -> None:
         """Adapts the ga to hopefully get better results."""
 
@@ -134,7 +134,6 @@ class GA(Attributes):
         self.set_all_fitness()
         self.sort_by_best_fitness()
 
-
     def adapt_probabilities(self: GA) -> None:
         """
         Modifies the parent ratio and mutation rates based on the adapt
@@ -154,7 +153,7 @@ class GA(Attributes):
 
         # Difference between best and i-th chromosomes
         best_chromosome = self.population[0]
-        tol = lambda i: self.dist(best_chromosome, self.population[i])
+        def tol(i): return self.dist(best_chromosome, self.population[i])
 
         # Too few converged: cross more and mutate less
         if tol(amount_converged//2) > tol(amount_converged//4)*2:
@@ -169,13 +168,14 @@ class GA(Attributes):
                       self.max_gene_mutation_rate)
 
         # Weighted average of x and y
-        average = lambda x, y: weight * x + (1-weight) * y
+        def average(x, y): return weight * x + (1-weight) * y
 
         # Adjust rates towards the bounds
-        self.selection_probability    = average(bounds[0], self.selection_probability)
-        self.chromosome_mutation_rate = average(bounds[1], self.chromosome_mutation_rate)
-        self.gene_mutation_rate       = average(bounds[2], self.gene_mutation_rate)
-
+        self.selection_probability = average(
+            bounds[0], self.selection_probability)
+        self.chromosome_mutation_rate = average(
+            bounds[1], self.chromosome_mutation_rate)
+        self.gene_mutation_rate = average(bounds[2], self.gene_mutation_rate)
 
     def adapt_population(self: GA) -> None:
         """
@@ -202,7 +202,7 @@ class GA(Attributes):
                     self.crossover_individual_impl(
                         self.population[n],
                         parent,
-                        weight = -3/4,
+                        weight=-3/4,
                     )
 
                 # If negative weights can't be used or division by 0, use positive weight
@@ -210,7 +210,7 @@ class GA(Attributes):
                     self.crossover_individual_impl(
                         self.population[n],
                         parent,
-                        weight = +1/4,
+                        weight=+1/4,
                     )
 
             # Stop if we've filled up an entire population
@@ -218,20 +218,19 @@ class GA(Attributes):
                 break
 
         # Replace worst chromosomes with new chromosomes, except for the previous best chromosome
-        min_len = min(len(self.population)-1, len(self.population.next_population))
+        min_len = min(len(self.population)-1,
+                      len(self.population.next_population))
         if min_len > 0:
             self.population[-min_len:] = self.population.next_population[:min_len]
         self.population.next_population = []
         self.population.mating_pool = []
 
-
     def initialize_population(self: GA) -> None:
         """
         Sets self.population using the chromosome implementation and population size.
         """
         self.population = self.make_population(self.population_impl())
 
-
     def set_all_fitness(self: GA) -> None:
         """
         Sets the fitness of each chromosome in the population.
@@ -252,15 +251,14 @@ class GA(Attributes):
             if chromosome.fitness is None or self.update_fitness:
                 chromosome.fitness = self.fitness_function_impl(chromosome)
 
-
     def sort_by_best_fitness(
-            self: GA,
-            chromosome_list: Optional[
-                Union[MutableSequence[Chromosome],
-                Iterable[Chromosome]]
-                ] = None,
-            in_place: bool = True,
-        ) -> MutableSequence[Chromosome]:
+        self: GA,
+        chromosome_list: Optional[
+            Union[MutableSequence[Chromosome],
+                  Iterable[Chromosome]]
+        ] = None,
+        in_place: bool = True,
+    ) -> MutableSequence[Chromosome]:
         """
         Sorts the chromosome list by fitness based on fitness type.
         1st element has best fitness.
@@ -315,7 +313,6 @@ class GA(Attributes):
         else:
             return sorted(chromosome_list, key=key, reverse=reverse)
 
-
     def get_chromosome_fitness(self: GA, index: int) -> float:
         """
         Computes the converted fitness of a chromosome at an index.
@@ -339,7 +336,6 @@ class GA(Attributes):
         """
         return self.convert_fitness(self.population[index].fitness)
 
-
     def convert_fitness(self: GA, fitness: float) -> float:
         """
         Calculates a modified version of the fitness for various
@@ -376,23 +372,19 @@ class GA(Attributes):
 
         return max_fitness - fitness + min_fitness
 
-
     def print_generation(self: GA) -> None:
         """Prints the current generation."""
         print(f"Current Generation \t: {self.current_generation}")
 
-
     def print_population(self: GA) -> None:
         """Prints the entire population."""
         print(self.population)
 
-
     def print_best_chromosome(self: GA) -> None:
         """Prints the best chromosome and its fitness."""
         print(f"Best Chromosome \t: {self.population[0]}")
         print(f"Best Fitness    \t: {self.population[0].fitness}")
 
-
     def print_worst_chromosome(self: GA) -> None:
         """Prints the worst chromosome and its fitness."""
         print(f"Worst Chromosome \t: {self.population[-1]}")

EasyGA/attributes.py

@@ -6,8 +6,8 @@ from dataclasses import dataclass, field, _MISSING_TYPE
 from types import MethodType
 import random
 
-import sqlite3
-import matplotlib.pyplot as plt
+# import sqlite3
+# import matplotlib.pyplot as plt
 
 from structure import Population
 from structure import Chromosome
@@ -19,13 +19,13 @@ from parent import Parent
 from survivor import Survivor
 from crossover import Crossover
 from mutation import Mutation
-from database import sql_database, matplotlib_graph
-from database import sql_database as Database, matplotlib_graph as Graph
+# from database import SQLDatabase, MatplotlibGraph, SQLDatabase as Database, MatplotlibGraph as Graph
 
 #========================================#
 # Default methods not defined elsewhere. #
 #========================================#
 
+
 def rand_1_to_10(self: Attributes) -> int:
     """
     Default gene_impl, returning a random integer from 1 to 10.
@@ -37,6 +37,7 @@ def rand_1_to_10(self: Attributes) -> int:
     """
     return random.randint(1, 10)
 
+
 def use_genes(self: Attributes) -> Iterator[Any]:
     """
     Default chromosome_impl, generates a chromosome using the gene_impl and chromosome length.
@@ -56,6 +57,7 @@ def use_genes(self: Attributes) -> Iterator[Any]:
     for _ in range(self.chromosome_length):
         yield self.gene_impl()
 
+
 def use_chromosomes(self: Attributes) -> Iterator[Iterable[Any]]:
     """
     Default population_impl, generates a population using the chromosome_impl and population size.
@@ -75,6 +77,7 @@ def use_chromosomes(self: Attributes) -> Iterator[Iterable[Any]]:
     for _ in range(self.population_size):
         yield self.chromosome_impl()
 
+
 def dist_fitness(self: Attributes, chromosome_1: Chromosome, chromosome_2: Chromosome) -> float:
     """
     Measures the distance between two chromosomes based on their fitnesses.
@@ -91,6 +94,7 @@ def dist_fitness(self: Attributes, chromosome_1: Chromosome, chromosome_2: Chrom
     """
     return sqrt(abs(chromosome_1.fitness - chromosome_2.fitness))
 
+
 def simple_linear(self: Attributes, weight: float) -> float:
     """
     Returns a random value between 0 and 1, with increased probability
@@ -182,26 +186,27 @@ class AttributesData:
 
     parent_selection_impl: Callable[["Attributes"], None] = None
     crossover_individual_impl: Callable[["Attributes"], None] = None
-    crossover_population_impl: Callable[["Attributes", Chromosome, Chromosome], None] = None
+    crossover_population_impl: Callable[[
+        "Attributes", Chromosome, Chromosome], None] = None
     survivor_selection_impl: Callable[["Attributes"], None] = None
     mutation_individual_impl: Callable[["Attributes", Chromosome], None] = None
     mutation_population_impl: Callable[["Attributes"], None] = None
     termination_impl: Callable[["Attributes"], bool] = None
 
-    database: Database = field(default_factory=sql_database.SQL_Database)
-    database_name: str = "database.db"
-    save_data: bool = True
-    sql_create_data_structure: str = """
-        CREATE TABLE IF NOT EXISTS data (
-            id INTEGER PRIMARY KEY,
-            config_id INTEGER DEFAULT NULL,
-            generation INTEGER NOT NULL,
-            fitness REAL,
-            chromosome TEXT
-        );
-    """
+    # database: Database = field(default_factory=SQLDatabase)
+    #database_name: str = "database.db"
+    #save_data: bool = True
+    # sql_create_data_structure: str = """
+    #    CREATE TABLE IF NOT EXISTS data (
+    #        id INTEGER PRIMARY KEY,
+    #        config_id INTEGER DEFAULT NULL,
+    #        generation INTEGER NOT NULL,
+    #        fitness REAL,
+    #        chromosome TEXT
+    #    );
+    # """
 
-    graph: Callable[[Database], Graph] = matplotlib_graph.Matplotlib_Graph
+    # graph: Callable[[Database], Graph] = MatplotlibGraph
 
     def __post_init__(self: AttributesData) -> None:
         """
@@ -312,7 +317,8 @@ class Attributes(AttributesData):
         chromosome : Chromosome
             The chromosome to be saved.
         """
-        self.database.insert_current_chromosome(self.current_generation, chromosome)
+        self.database.insert_current_chromosome(
+            self.current_generation, chromosome)
 
     #===========================#
     # Descriptors which convert #
@@ -328,13 +334,20 @@ class Attributes(AttributesData):
     population_impl = AsMethod("population_impl", use_chromosomes)
     dist = AsMethod("dist", dist_fitness)
     weighted_random = AsMethod("weighted_random", simple_linear)
-    parent_selection_impl = AsMethod("parent_selection_impl", Parent.Rank.tournament)
-    crossover_individual_impl = AsMethod("crossover_individual_impl", Crossover.Individual.single_point)
-    crossover_population_impl = AsMethod("crossover_population_impl", Crossover.Population.sequential)
-    survivor_selection_impl = AsMethod("survivor_selection_impl", Survivor.fill_in_best)
-    mutation_individual_impl = AsMethod("mutation_individual_impl", Mutation.Individual.individual_genes)
-    mutation_population_impl = AsMethod("mutation_population_impl", Mutation.Population.random_avoid_best)
-    termination_impl = AsMethod("termination_impl", Termination.fitness_generation_tolerance)
+    parent_selection_impl = AsMethod(
+        "parent_selection_impl", Parent.Rank.tournament)
+    crossover_individual_impl = AsMethod(
+        "crossover_individual_impl", Crossover.Individual.single_point)
+    crossover_population_impl = AsMethod(
+        "crossover_population_impl", Crossover.Population.sequential)
+    survivor_selection_impl = AsMethod(
+        "survivor_selection_impl", Survivor.fill_in_best)
+    mutation_individual_impl = AsMethod(
+        "mutation_individual_impl", Mutation.Individual.individual_genes)
+    mutation_population_impl = AsMethod(
+        "mutation_population_impl", Mutation.Population.random_avoid_best)
+    termination_impl = AsMethod(
+        "termination_impl", Termination.fitness_generation_tolerance)
 
     #=============#
     # Properties: #
@@ -347,7 +360,8 @@ class Attributes(AttributesData):
     @run.setter
     def run(self: AttributesProperties, value: int) -> None:
         if not isinstance(value, int) or value < 0:
-            raise ValueError("ga.run counter must be an integer greater than or equal to 0.")
+            raise ValueError(
+                "ga.run counter must be an integer greater than or equal to 0.")
         vars(self)["run"] = value
 
     @property
@@ -357,7 +371,8 @@ class Attributes(AttributesData):
     @current_generation.setter
     def current_generation(self: AttributesProperties, value: int) -> None:
         if not isinstance(value, int) or value < 0:
-            raise ValueError("ga.current_generation must be an integer greater than or equal to 0")
+            raise ValueError(
+                "ga.current_generation must be an integer greater than or equal to 0")
         vars(self)["current_generation"] = value
 
     @property
@@ -367,7 +382,8 @@ class Attributes(AttributesData):
     @chromosome_length.setter
     def chromosome_length(self: AttributesProperties, value: int) -> None:
         if not isinstance(value, int) or value <= 0:
-            raise ValueError("ga.chromosome_length must be an integer greater than and not equal to 0.")
+            raise ValueError(
+                "ga.chromosome_length must be an integer greater than and not equal to 0.")
         vars(self)["chromosome_length"] = value
 
     @property
@@ -377,7 +393,8 @@ class Attributes(AttributesData):
     @population_size.setter
     def population_size(self: AttributesProperties, value: int) -> None:
         if not isinstance(value, int) or value <= 0:
-            raise ValueError("ga.population_size must be an integer greater than and not equal to 0.")
+            raise ValueError(
+                "ga.population_size must be an integer greater than and not equal to 0.")
         vars(self)["population_size"] = value
 
     @property
@@ -394,7 +411,8 @@ class Attributes(AttributesData):
         if value is None or (isinstance(value, (float, int)) and 0 <= value <= 1):
             vars(self)["max_chromosome_mutation_rate"] = value
         else:
-            raise ValueError("Max chromosome mutation rate must be between 0 and 1")
+            raise ValueError(
+                "Max chromosome mutation rate must be between 0 and 1")
 
     @property
     def min_chromosome_mutation_rate(self: AttributesProperties) -> float:
@@ -410,26 +428,27 @@ class Attributes(AttributesData):
         if value is None or (isinstance(value, (float, int)) and 0 <= value <= 1):
             vars(self)["min_chromosome_mutation_rate"] = value
         else:
-            raise ValueError("Min chromosome mutation rate must be between 0 and 1")
+            raise ValueError(
+                "Min chromosome mutation rate must be between 0 and 1")
 
-    @property
-    def database_name(self: AttributesProperties) -> str:
-        return vars(self)["database_name"]
+    # @property
+    # def database_name(self: AttributesProperties) -> str:
+    #    return vars(self)["database_name"]
 
-    @database_name.setter
-    def database_name(self: AttributesProperties, name: str) -> None:
-        # Update the database's name.
-        self.database._database_name = name
-        # Set the attribute for itself.
-        vars(self)["database_name"] = name
+    # @database_name.setter
+    # def database_name(self: AttributesProperties, name: str) -> None:
+    #    # Update the database's name.
+    #    self.database._database_name = name
+    #    # Set the attribute for itself.
+    #    vars(self)["database_name"] = name
 
-    @property
-    def graph(self: AttributesProperties) -> Graph:
-        return vars(self)["graph"]
+    # @property
+    # def graph(self: AttributesProperties) -> Graph:
+    #    return vars(self)["graph"]
 
-    @graph.setter
-    def graph(self: AttributesProperties, graph: Callable[[Database], Graph]) -> None:
-        vars(self)["graph"] = graph(self.database)
+    # @graph.setter
+    # def graph(self: AttributesProperties, graph: Callable[[Database], Graph]) -> None:
+    #    vars(self)["graph"] = graph(self.database)
 
     @property
     def active(self: AttributesProperties) -> Callable[[], bool]:

EasyGA/database/__init__.py

@@ -0,0 +1,2 @@
+from .sql_database import SQLDatabase
+from .matplotlib_graph import MatplotlibGraph

EasyGA/database/matplotlib_graph.py

@@ -3,7 +3,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 
-class Matplotlib_Graph:
+class MatplotlibGraph:
     """Prebuilt graphing functions to make visual
     represention of fitness data."""
 

EasyGA/database/sql_database.py

@@ -4,7 +4,7 @@ from sqlite3 import Error
 from tabulate import tabulate
 
 
-class SQL_Database:
+class SQLDatabase:
     """Main database class that controls all the functionality for input /
     out of the database using SQLite3."""
 

README.md

@@ -1,8 +1,8 @@
-![](https://raw.githubusercontent.com/danielwilczak101/EasyGA/media/images/easyGA_logo.png)
+![](https://raw.githubusercontent.com/danielwilczak101/EasyGA/media/images/banner-logo.png)
 
 # EasyGA - Genetic Algorithms made Easy
 
-EasyGA is a python package designed to provide an easy-to-use Genetic Algorithm. The package is designed to work right out of the box, while also allowing the user to customize features as they see fit. 
+EasyGA is a python package designed to provide an easy-to-use Genetic Algorithm. The package is designed to work right out of the box, while also allowing the user to customize features as they see fit.
 
 ## Check out our [Wiki](https://github.com/danielwilczak101/EasyGA/wiki) or [Youtube](https://www.youtube.com/watch?v=jbuDKwIiYBw) for more information.
 
@@ -15,6 +15,9 @@ pip3 install EasyGA
 ```
 
 ## Getting started with EasyGA(Basic Example):
+
+The goal of the basic example is to get all 5's in the chromosome.
+
 ```Python
 import EasyGA
 
@@ -30,6 +33,7 @@ ga.print_population()
 ```
 
 ### Output:
+
 ```bash
 Current Generation      : 15
 Current population:
@@ -46,6 +50,7 @@ Chromosome - 9 [7][2][8][10][3][5][5][8][1][7] / Fitness = 2
 ```
 
 ## Getting started with EasyGA (Password Cracker Example):
+
 ```Python
 import EasyGA
 import random
@@ -93,8 +98,9 @@ ga.graph.show()
 ```
 
 ## Ouput:
+
 ```
-Please enter a word: 
+Please enter a word:
 EasyGA
 Current Generation 	: 44
 Chromosome - 0 [E][a][s][y][G][A] / Fitness = 6
@@ -112,8 +118,8 @@ Chromosome - 9 [E][a][s][Y][G][A] / Fitness = 5
 <img width="500px" src="https://raw.githubusercontent.com/danielwilczak101/EasyGA/media/images/password_cracker_results.png" />
 
 ## Issues
-We would love to know if your having any issues. Please start a new issue on the [Issues Page](https://github.com/danielwilczak101/EasyGA/issues).
 
+We would love to know if your having any issues. Please start a new issue on the [Issues Page](https://github.com/danielwilczak101/EasyGA/issues).
 
 ## Local System Approach
 
@@ -122,6 +128,7 @@ Download the repository to some folder on your computer.
 ```
 https://github.com/danielwilczak101/EasyGA/archive/master.zip
 ```
-Use the run.py file inside the EasyGA folder to run your code. This is a local version of the package. 
+
+Use the run.py file inside the EasyGA folder to run your code. This is a local version of the package.
 
 ## Check out our [wiki](https://github.com/danielwilczak101/EasyGA/wiki) for more information.

docs/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/make.bat

@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.http://sphinx-doc.org/
+	exit /b 1
+)
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

docs/source/conf.py

@@ -0,0 +1,52 @@
+# Configuration file for the Sphinx documentation builder.
+#
+# This file only contains a selection of the most common options. For a full
+# list see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to document with autodoc) are in another directory,
+# add these directories to sys.path here. If the directory is relative to the
+# documentation root, use os.path.abspath to make it absolute, like shown here.
+#
+# import os
+# import sys
+# sys.path.insert(0, os.path.abspath('.'))
+
+
+# -- Project information -----------------------------------------------------
+
+project = 'EasyGA'
+copyright = '2021, Daniel Wilczak, Jack Nguyen'
+author = 'Daniel Wilczak, Jack Nguyen'
+
+
+# -- General configuration ---------------------------------------------------
+
+# Add any Sphinx extension module names here, as strings. They can be
+# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# ones.
+extensions = [
+]
+
+# Add any paths that contain templates here, relative to this directory.
+templates_path = ['_templates']
+
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This pattern also affects html_static_path and html_extra_path.
+exclude_patterns = []
+
+
+# -- Options for HTML output -------------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.  See the documentation for
+# a list of builtin themes.
+#
+html_theme = 'alabaster'
+
+# Add any paths that contain custom static files (such as style sheets) here,
+# relative to this directory. They are copied after the builtin static files,
+# so a file named "default.css" will overwrite the builtin "default.css".
+html_static_path = ['_static']

docs/source/index.rst

@@ -0,0 +1,20 @@
+.. EasyGA documentation master file, created by
+   sphinx-quickstart on Thu Aug 26 12:53:45 2021.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Welcome to EasyGA's documentation!
+==================================
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`

setup.py

@@ -13,16 +13,17 @@ setuptools.setup(
     url="https://github.com/danielwilczak101/EasyGA",
     author="Daniel Wilczak, Jack RyanNguyen, Ryley Griffith, Jared Curtis, Matthew Chase Oxamendi ",
     author_email="danielwilczak101@gmail.com",
-    long_description = long_description,
-    long_description_content_type = "text/markdown",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
     classifier=[
         "Programming Language :: Python :: 3",
         "License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)",
         "Operating System :: OS Independent",
-        ],
-    install_requires = ["matplotlib ~= 3.3.2",
-                        "pyserial ~= 3.4",
-                        "pytest>=3.7",
-                        "tabulate >=0.8.7"
-                        ],
-    )
+    ],
+    install_requires=[
+        # "matplotlib ~= 3.3.2",
+        # "pyserial ~= 3.4",
+        "pytest>=3.7",
+        "tabulate >=0.8.7"
+    ],
+)