import concurrent.futures
from biobridge.blocks.cell import Cell
from biobridge.blocks.tissue import Tissue
from biobridge.networks.system import System
from biobridge.genes.dna import DNA


class Cloner:
    @staticmethod
    def clone_dna(dna: DNA, degradation_rate=0.01) -> DNA:
        """
        Clone DNA with potential degradation.
        :param dna: The DNA to be cloned.
        :param degradation_rate: The probability of degradation at each nucleotide.
        :return: A new DNA object that is a clone of the input DNA with potential degradation.
        """
        cloned_dna = dna.replicate(mutation_rate=degradation_rate)
        return cloned_dna

    @staticmethod
    def clone_cell(cell: Cell, degradation_rate=0.01) -> Cell:
        """
        Create a clone of a given cell with potential DNA degradation.
        :param cell: The cell to be cloned.
        :param degradation_rate: The probability of degradation at each nucleotide.
        :return: A new cell object that is a clone of the input cell.
        """
        cloned_dna = Cloner.clone_dna(cell.dna, degradation_rate) if cell.dna else None

        cloned_cell = Cell(
            name=f"{cell.name}_clone",
            cell_type=cell.cell_type,
            receptors=cell.receptors.copy(),
            surface_proteins=cell.surface_proteins.copy(),
            dna=cloned_dna,
            health=cell.health,
            ph=cell.ph,
            osmolarity=cell.osmolarity,
            ion_concentrations=cell.ion_concentrations.copy()
        )
        # Clone mitochondria
        for organelle in cell.organelles:
            cloned_cell.add_organelle(
                    organelle, len(cell.organelles)
            )
        # Clone internal proteins
        for protein in cell.internal_proteins:
            cloned_cell.add_internal_protein(protein)
        return cloned_cell

    @staticmethod
    def grow_tissue_from_cell(cell: Cell, num_cells=10, degradation_rate=0.01) -> Tissue:
        """
        Grow a tissue from a single cell by cloning the cell multiple times.
        :param cell: The initial cell to start the tissue growth.
        :param num_cells: The number of cells to grow in the tissue.
        :param degradation_rate: The probability of degradation at each nucleotide.
        :return: A new tissue object grown from the initial cell.
        """
        cells = [cell]
        with concurrent.futures.ThreadPoolExecutor() as executor:
            futures = [executor.submit(Cloner.clone_cell, cells[-1], degradation_rate) for _ in range(num_cells - 1)]
            for future in concurrent.futures.as_completed(futures):
                cells.append(future.result())

        tissue = Tissue(
            name=f"{cell.name}_tissue",
            tissue_type=cell.cell_type,
            cells=cells,
            cancer_risk=0  # Assuming no initial cancer risk
        )
        tissue.growth_rate = 1.0  # Assuming a default growth rate
        tissue.healing_rate = 1.0  # Assuming a default healing rate
        return tissue

    @staticmethod
    def grow_system_from_tissue(tissue: Tissue, num_tissues=5, degradation_rate=0.01) -> System:
        """
        Grow a system from a single tissue by cloning the tissue multiple times.
        :param tissue: The initial tissue to start the system growth.
        :param num_tissues: The number of tissues to grow in the system.
        :param degradation_rate: The probability of degradation at each nucleotide.
        :return: A new system object grown from the initial tissue.
        """
        tissues = [tissue]
        with concurrent.futures.ThreadPoolExecutor() as executor:
            futures = [executor.submit(Cloner.grow_tissue_from_cell, tissues[-1].cells[0], len(tissues[-1].cells), degradation_rate) for _ in range(num_tissues - 1)]
            for future in concurrent.futures.as_completed(futures):
                tissues.append(future.result())

        system = System(name=f"{tissue.name}_system")
        for tissue in tissues:
            system.add_tissue(tissue)

        system.adaptation_rate = 1.0  # Assuming a default adaptation rate
        system.stress_level = 0  # Assuming no initial stress
        system.previous_cell_count = sum(len(t.cells) for t in tissues)
        system.previous_tissue_count = num_tissues
        system.state = {}  # Assuming an empty initial state
        system.health = 1.0  # Assuming full health
        system.energy = 1.0  # Assuming full energy
        return system
