"""File containing the Validator class."""

from __future__ import annotations

import sys
from pathlib import Path
import csv
import ast
import runrunner as rrr
from runrunner import Runner, Run

from sparkle.platform import CommandName
from sparkle.solver import Solver
from sparkle.instance import InstanceSet
from sparkle.types.objective import SparkleObjective
from sparkle.tools.runsolver_parsing import get_solver_output, get_solver_args


class Validator():
    """Class to handle the validation of solvers on instance sets."""
    def __init__(self: Validator,
                 out_dir: Path = Path(),
                 tmp_out_dir: Path = Path()) -> None:
        """Construct the validator."""
        self.out_dir = out_dir
        self.tmp_out_dir = tmp_out_dir

    def validate(self: Validator,
                 solvers: list[Path] | list[Solver] | Solver | Path,
                 configurations: list[dict] | dict | Path,
                 instance_sets: list[InstanceSet],
                 objectives: list[SparkleObjective],
                 cut_off: int,
                 subdir: Path = None,
                 dependency: list[Run] | Run = None,
                 sbatch_options: list[str] = [],
                 run_on: Runner = Runner.SLURM) -> Run:
        """Validate a list of solvers (with configurations) on a set of instances.

        Args:
            solvers: list of solvers to validate
            configurations: list of configurations for each solver we validate.
                If a path is supplied, will use each line as a configuration.
            instance_sets: set of instance sets on which we want to validate each solver
            objectives: list of objectives to validate
            cut_off: maximum run time for the solver per instance
            subdir: The subdir where to place the output in the outputdir. If None,
                a semi-unique combination of solver_instanceset is created.
            dependency: Jobs to wait for before executing the validation.
            sbatch_options: list of slurm batch options
            run_on: whether to run on SLURM or local
        """
        if not isinstance(solvers, list) and isinstance(configurations, list):
            # If we receive one solver but multiple configurations, we cas the
            # Solvers to a list of the same length
            solvers = [solvers] * len(configurations)
        elif not isinstance(configurations, list) and isinstance(solvers, list):
            # If there is only one configuration, we cast it to a list of the same
            # length as the solver list
            configurations = [configurations] * len(solvers)
        if not isinstance(solvers, list) or len(configurations) != len(solvers):
            print("Error: Number of solvers and configurations does not match!")
            sys.exit(-1)
        # Ensure we have the object representation of solvers
        solvers = [Solver(s) if isinstance(s, Path) else s for s in solvers]
        cmds = []
        out_paths = []
        for index, (solver, config) in enumerate(zip(solvers, configurations)):
            if config is None:
                config = {}
            elif isinstance(config, Path):
                # Point to the config line in file
                config = {"config_path": config}
            for instance_set in instance_sets:
                if subdir is None:
                    out_path = self.out_dir / f"{solver.name}_{instance_set.name}"
                else:
                    out_path = self.out_dir / subdir
                out_path.mkdir(exist_ok=True)
                for instance_path in instance_set._instance_paths:
                    cmds.append(" ".join(
                        solver.build_cmd(instance=instance_path.absolute(),
                                         objectives=objectives,
                                         seed=index,
                                         cutoff_time=cut_off,
                                         configuration=config)))
                out_paths.extend([out_path] * len(instance_set._instance_paths))
        return rrr.add_to_queue(
            runner=run_on,
            cmd=cmds,
            name=CommandName.VALIDATION,
            base_dir=self.tmp_out_dir,
            path=out_paths,
            dependencies=dependency,
            sbatch_options=sbatch_options,
        )

    def retrieve_raw_results(self: Validator,
                             solver: Solver,
                             instance_sets: InstanceSet | list[InstanceSet],
                             subdir: Path = None,
                             log_dir: Path = None) -> None:
        """Checks the raw results of a given solver for a specific instance_set.

        Writes the raw results to a unified CSV file for the resolve/instance_set
        combination.

        Args:
            solver: The solver for which to check the raw result path
            instance_sets: The set of instances for which to retrieve the results
            subdir: Subdir where the CSV is to be placed, passed to the append method.
            log_dir: The directory to search for log files. If none, defaults to
                the log directory of the Solver.
        """
        if isinstance(instance_sets, InstanceSet):
            instance_sets = [instance_sets]
        if log_dir is None:
            log_dir = solver.raw_output_directory
        for res in log_dir.iterdir():
            if res.suffix != ".rawres":
                continue
            solver_args = get_solver_args(res.with_suffix(".log"))
            solver_args = ast.literal_eval(solver_args)
            instance_path = Path(solver_args["instance"])
            # Remove default args
            if "config_path" in solver_args:
                # The actual solver configuration can be found elsewhere
                row_idx = int(solver_args["seed"])
                config_path = Path(solver_args["config_path"])
                if not config_path.exists():
                    config_path = log_dir / config_path
                config_str = config_path.open("r").readlines()[row_idx]
                solver_args = Solver.config_str_to_dict(config_str)
            else:
                for def_arg in ["instance", "solver_dir", "cutoff_time",
                                "seed", "objectives"]:
                    if def_arg in solver_args:
                        del solver_args[def_arg]
            solver_args = str(solver_args).replace('"', "'")

            for instance_set in instance_sets:
                if instance_path.name in instance_set._instance_names:
                    out_dict = get_solver_output(
                        ["-o", res.name, "-v", res.with_suffix(".val").name],
                        "", log_dir)
                    self.append_entry_to_csv(solver.name,
                                             solver_args,
                                             instance_set,
                                             instance_path.name,
                                             out_dict["status"],
                                             out_dict["quality"],
                                             out_dict["runtime"],
                                             subdir=subdir)
                    res.unlink()
                    res.with_suffix(".val").unlink(missing_ok=True)
                    res.with_suffix(".log").unlink(missing_ok=True)

    def get_validation_results(self: Validator,
                               solver: Solver,
                               instance_set: InstanceSet,
                               source_dir: Path = None,
                               subdir: Path = None,
                               config: str = None) -> list[list[str]]:
        """Query the results of the validation of solver on instance_set.

        Args:
            solver: Solver object
            instance_set: Instance set
            source_dir: Path where to look for any unprocessed output.
                By default, look in the solver's tmp dir.
            subdir: Path where to place the .csv file subdir. By default will be
                'self.outputdir/solver.name_instanceset.name/validation.csv'
            config: Path to the configuration if the solver was configured, None
                    otherwise
        Returns
            A list of row lists with string values
        """
        if source_dir is None:
            source_dir = self.out_dir / f"{solver.name}_{instance_set.name}"
        if any(x.suffix == ".rawres" for x in source_dir.iterdir()):
            self.retrieve_raw_results(
                solver, instance_set, subdir=subdir, log_dir=source_dir)
        if subdir is None:
            subdir = Path(f"{solver.name}_{instance_set.name}")
        csv_file = self.out_dir / subdir / "validation.csv"
        # We skip the header when returning results
        csv_data = [line for line in csv.reader(csv_file.open("r"))][1:]
        if config is not None:
            # We filter on the config string by subdict
            if isinstance(config, str):
                config = Solver.config_str_to_dict(config)
            csv_data = [line for line in csv_data if
                        config.items() == ast.literal_eval(line[1]).items()]
        return csv_data

    def append_entry_to_csv(self: Validator,
                            solver: str,
                            config_str: str,
                            instance_set: InstanceSet,
                            instance: str,
                            status: str,
                            quality: str,
                            runtime: str,
                            subdir: Path = None) -> None:
        """Append a validation result as a row to a CSV file."""
        if subdir is None:
            subdir = Path(f"{solver}_{instance_set.name}")
        out_dir = self.out_dir / subdir
        if not out_dir.exists():
            out_dir.mkdir(parents=True)
        csv_file = out_dir / "validation.csv"
        if not csv_file.exists():
            # Write header
            with csv_file.open("w") as out:
                csv.writer(out).writerow(("Solver", "Configuration", "InstanceSet",
                                          "Instance", "Status", "Quality", "Runtime"))
        with csv_file.open("a") as out:
            writer = csv.writer(out)
            writer.writerow((solver, config_str, instance_set.name, instance, status,
                             quality, runtime))
