This section of the PyGAD's library documentation discusses the pygad.helper module.

The pygad.helper module has 2 submodules:

1. pygad.helper.unique: A module of methods for creating unique genes.
2. pygad.helper.misc: A module of miscellaneous helper methods.

The pygad.helper.unique module has a class named Unique with the following helper methods. Such methods help to check and fix duplicate values in the genes of a solution.

1. solve_duplicate_genes_randomly(): Solves the duplicates in a solution by randomly selecting new values for the duplicating genes.
2. solve_duplicate_genes_by_space(): Solves the duplicates in a solution by selecting values for the duplicating genes from the gene space
3. unique_int_gene_from_range(): Finds a unique integer value for the gene out of a range defined by start and end points.
4. unique_float_gene_from_range(): Finds a unique float value for the gene out of a range defined by start and end points.
5. select_unique_value(): Selects a unique value (if possible) from a list of gene values.
6. unique_genes_by_space(): Loops through all the duplicating genes to find unique values that from their gene spaces to solve the duplicates. For each duplicating gene, a call to the unique_gene_by_space() is made.
7. unique_gene_by_space(): Returns a unique gene value for a single gene based on its value space to solve the duplicates.
8. find_two_duplicates(): Identifies the first occurrence of a duplicate gene in the solution.
9. unpack_gene_space(): Unpacks the gene space for selecting a value to resolve duplicates by converting ranges into lists of values.
10. solve_duplicates_deeply(): Sometimes it is impossible to solve the duplicate genes by simply randomly selecting another value for either genes. This function solve the duplicates between 2 genes by searching for a third gene that can make assist in the solution.

The pygad.helper.misc module has a class called Helper with some methods to help in different stages of the GA pipeline. It is introduced in PyGAD 3.5.0.

1. change_population_dtype_and_round(): For each gene in the population, round the gene value and change the data type.
2. change_gene_dtype_and_round(): Round the change the data type of a single gene.
3. mutation_change_gene_dtype_and_round(): Decides whether mutation is done by replacement or not. Then it rounds and change the data type of the new gene value.
4. validate_gene_constraint_callable_output(): Validates the output of the user-defined callable/function that checks whether the gene constraint defined in the gene_constraint parameter is satisfied or not.
5. get_gene_dtype(): Returns the gene data type from the gene_type instance attribute.
6. get_random_mutation_range(): Returns the random mutation range using the random_mutation_min_val and random_mutation_min_val instance attributes.
7. get_initial_population_range(): Returns the initial population values range using the init_range_low and init_range_high instance attributes.
8. generate_gene_value_from_space(): Generates/selects a value for a gene using the gene_space instance attribute.
9. generate_gene_value_randomly(): Generates a random value for the gene. Only used if gene_space is None.
10. generate_gene_value(): Generates a value for the gene. It checks whether gene_space is None and calls either generate_gene_value_randomly() or generate_gene_value_from_space().
11. filter_gene_values_by_constraint(): Receives a list of values for a gene. Then it filters such values using the gene constraint.
12. get_valid_gene_constraint_values(): Selects one valid gene value that satisfy the gene constraint. It simply calls generate_gene_value() to generate some gene values then it filters such values using filter_gene_values_by_constraint().