"""
/***************************************************************************
 LDMP - A QGIS plugin
 This plugin supports monitoring and reporting of land degradation to the UNCCD
 and in support of the SDG Land Degradation Neutrality (LDN) target.
                              -------------------
        begin                : 2017-05-23
        git sha              : $Format:%H$
        copyright            : (C) 2017 by Conservation International
        email                : trends.earth@conservation.org
 ***************************************************************************/
"""

import dataclasses
import datetime
import enum
import functools
import json
import math
import os
import typing
import uuid
from pathlib import Path

import numpy as np
import qgis.core
import qgis.gui
import qgis.utils
import te_algorithms.gdal.land_deg.config as ld_conf
from osgeo import gdal, osr
from qgis.PyQt import QtCore, QtWidgets, uic
from qgis.PyQt.QtCore import QSettings
from te_schemas.jobs import JobStatus
from te_schemas.productivity import ProductivityMode
from te_schemas.results import Band as JobBand
from te_schemas.results import RasterResults, RasterType, ResultType, VectorResults

from . import (
    GetTempFilename,
    conf,
    layers,
    metadata,
    metadata_dialog,
    utils,
    worker,
)
from .areaofinterest import (
    try_get_aoi_geometry,
    try_prepare_area_of_interest,
)
from .jobs.manager import job_manager, set_results_extents, update_uris_if_needed
from .jobs.models import Job
from .logger import log
from .region_selector import RegionSelector
from .utils import push_message

Ui_DlgDataIOLoadTE, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgDataIOLoadTE.ui")
)
Ui_DlgDataIOImportSOC, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgDataIOImportSOC.ui")
)
Ui_DlgDataIOImportPopulation, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgDataIOImportPopulation.ui")
)
Ui_DlgDataIOImportProd, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgDataIOImportProd.ui")
)
Ui_DlgDataIOAddLayersToMap, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgDataIOAddLayersToMap.ui")
)
Ui_DlgJobsDetails, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/DlgJobsDetails.ui")
)
Ui_WidgetDataIOImportSelectFileInput, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/WidgetDataIOImportSelectFileInput.ui")
)
Ui_WidgetDataIOImportSelectRasterOutput, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/WidgetDataIOImportSelectRasterOutput.ui")
)
Ui_WidgetDataIOSelectTELayerExisting, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/WidgetDataIOSelectTELayerExisting.ui")
)
Ui_WidgetDataIOSelectTELayerImport, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/WidgetDataIOSelectTELayerImport.ui")
)
Ui_WidgetDataIOSelectTEDatasetExisting, _ = uic.loadUiType(
    str(Path(__file__).parents[0] / "gui/WidgetDataIOSelectTEDatasetExisting.ui")
)


class tr_data_io:
    def tr(message):
        return QtCore.QCoreApplication.translate("tr_data_io", message)


class LayerValidationStatus(enum.Enum):
    """Status of layer selection validation."""

    VALID = "valid"
    NO_REGION = "no_region"
    NO_LAYERS = "no_layers"


# Legacy script-name aliases used for dataset dropdown matching.
DATASET_SCRIPT_NAME_ALIASES = {
    "drought-vulnerability-summary": {
        "drought-vulnerability-summary",
        "drought-summary",
    },
}


def _script_name_matches_dataset(script_name: str, dataset_name: str) -> bool:
    if script_name == dataset_name:
        return True

    aliases = DATASET_SCRIPT_NAME_ALIASES.get(dataset_name, set())
    return script_name in aliases


# Shared message constants for layer/dataset selection widgets
# These are lazily evaluated to ensure translation system is initialized
def _get_no_region_message() -> str:
    return tr_data_io.tr("Select a region first")


def _get_no_layers_message() -> str:
    return tr_data_io.tr("No layers available in this region")


def _get_no_datasets_message() -> str:
    return tr_data_io.tr("No datasets available in this region")


@dataclasses.dataclass()
class Band:
    job: Job
    path: Path
    band_index: int
    band_info: JobBand

    def get_name_info(self):
        if self.job.task_name:
            name_info_parts = [self.job.task_name]
        else:
            name_info_parts = []
        # Add area name and band title
        name_info_parts.append(self.job.local_context.area_of_interest_name)
        name_info_parts.append(
            layers.get_band_title(JobBand.Schema().dump(self.band_info))
        )

        # Add date with defensive handling
        if self.job.start_date:
            try:
                if hasattr(self.job.start_date, "strftime"):
                    name_info_parts.append(
                        utils.utc_to_local(self.job.start_date).strftime(
                            "%Y-%m-%d %H:%M"
                        )
                    )
            except (AttributeError, ValueError, TypeError):
                pass  # Skip date if it can't be formatted

        return " - ".join(name_info_parts)

    def get_hover_info(self):
        if self.job.task_name:
            hover_info_parts = [self.job.task_name]
        else:
            hover_info_parts = []
        hover_info_parts.append(self.job.local_context.area_of_interest_name + "\n")
        hover_info_parts.append(
            layers.get_band_title(JobBand.Schema().dump(self.band_info)) + "\n"
        )

        # Add date with defensive handling
        if self.job.start_date:
            try:
                if hasattr(self.job.start_date, "strftime"):
                    hover_info_parts.append(
                        utils.utc_to_local(self.job.start_date).strftime(
                            "%Y-%m-%d %H:%M"
                        )
                        + "\n"
                    )
            except (AttributeError, ValueError, TypeError):
                pass  # Skip date if it can't be formatted

        # TODO: figure out a way to cleanup the metadata so it is
        # presentable and useful - likely need to have each script
        # contain a dictionary of metadata fields that should be
        # shown to the user by default


@dataclasses.dataclass()
class Dataset:
    job: Job
    path: Path

    def get_name_info(self):
        name_info_parts = []
        name_info_parts.append(self.job.local_context.area_of_interest_name)
        name_info_parts.append(self.job.visible_name)

        # Add date with defensive handling
        if self.job.start_date:
            try:
                if hasattr(self.job.start_date, "strftime"):
                    name_info_parts.append(
                        utils.utc_to_local(self.job.start_date).strftime(
                            "%Y-%m-%d %H:%M"
                        )
                    )
            except (AttributeError, ValueError, TypeError):
                pass  # Skip date if it can't be formatted

        return " - ".join(name_info_parts)

    def get_hover_info(self):
        hover_info_parts = []
        hover_info_parts.append(self.job.visible_name + " - ")
        hover_info_parts.append(self.job.local_context.area_of_interest_name + "\n")

        # Add date with defensive handling
        if self.job.start_date:
            try:
                if hasattr(self.job.start_date, "strftime"):
                    hover_info_parts.append(
                        utils.utc_to_local(self.job.start_date).strftime(
                            "%Y-%m-%d %H:%M"
                        )
                    )
            except (AttributeError, ValueError, TypeError):
                pass  # Skip date if it can't be formatted

        return "".join(hover_info_parts)


class RemapVectorWorker(worker.AbstractWorker):
    def __init__(
        self,
        layer,
        out_file,
        attribute,
        remap_dict,
        in_data_type,
        out_res,
        out_data_type=gdal.GDT_Int16,
        output_bounds=None,
    ):
        worker.AbstractWorker.__init__(self)

        self.l = layer
        self.out_file = out_file
        self.attribute = attribute
        self.remap_dict = remap_dict
        self.in_data_type = in_data_type
        self.out_res = out_res
        self.out_data_type = out_data_type
        self.output_bounds = output_bounds

    def work(self):
        self.toggle_show_progress.emit(True)
        self.toggle_show_cancel.emit(True)

        crs_src_string = self.l.crs().toProj()
        crs_src = qgis.core.QgsCoordinateReferenceSystem()
        crs_src.createFromProj(crs_src_string)
        crs_dst = qgis.core.QgsCoordinateReferenceSystem("epsg:4326")
        t = qgis.core.QgsCoordinateTransform(
            crs_src, crs_dst, qgis.core.QgsProject.instance()
        )

        l_out = qgis.core.QgsVectorLayer(
            "{datatype}?crs=proj4:{crs}".format(
                datatype=self.in_data_type, crs=crs_dst.toProj()
            ),
            "land cover (transformed)",
            "memory",
        )
        l_out.dataProvider().addAttributes(
            [qgis.core.QgsField("code", QtCore.QVariant.Int)]
        )
        l_out.updateFields()

        feats = []
        n = 1

        for f in self.l.getFeatures():
            if self.killed:
                log("Processing killed by user while remapping vector")

                return None
            geom = f.geometry()
            geom.transform(t)
            new_f = qgis.core.QgsFeature()
            new_f.setGeometry(geom)
            new_f.setAttributes([self.remap_dict[f.attribute(self.attribute)]])
            feats.append(new_f)
            n += 1
            # Commit the changes every 5% of the way through the length of the
            # features

            if n > (self.l.featureCount() / 20):
                l_out.dataProvider().addFeatures(feats)
                l_out.commitChanges()
                # Note there will be two progress bars that will fill to 100%,
                # first one for this loop, and then another for rasterize, both
                # with the same title.
                self.progress.emit(100 * float(n) / self.l.featureCount())
                feats = []

        if not l_out.isValid():
            log(
                'Error remapping and transforming vector layer from "{}" to "{}")'.format(
                    crs_src_string, crs_dst.toProj()
                )
            )

            return None

        # Write l_out to a shapefile for usage by gdal rasterize
        temp_shp = GetTempFilename(".shp")
        log("Writing temporary shapefile to {}".format(temp_shp))
        err = qgis.core.QgsVectorFileWriter.writeAsVectorFormat(
            l_out, temp_shp, "UTF-8", crs_dst, "ESRI Shapefile"
        )

        if err != qgis.core.QgsVectorFileWriter.NoError:
            log("Error writing layer to {}".format(temp_shp))

            return None

        log("Rasterizing...")
        res = gdal.Rasterize(
            self.out_file,
            temp_shp,
            format="GTiff",
            xRes=self.out_res,
            yRes=-self.out_res,
            noData=-32768,
            attribute="code",
            outputSRS="epsg:4326",
            outputType=self.out_data_type,
            creationOptions=["COMPRESS=LZW"],
            outputBounds=self.output_bounds,
            callback=self.progress_callback,
        )
        os.remove(temp_shp)

        if res:
            return True
        else:
            return None

    def progress_callback(self, fraction, message=None, data=None):
        if self.killed:
            return False
        else:
            self.progress.emit(100 * fraction)

            return True


class RasterizeWorker(worker.AbstractWorker):
    def __init__(
        self, in_file, out_file, out_res, attribute, out_data_type=gdal.GDT_Int16
    ):
        worker.AbstractWorker.__init__(self)

        self.in_file = in_file
        self.out_file = out_file

        self.out_res = out_res
        self.out_data_type = out_data_type
        self.attribute = attribute

    def work(self):
        self.toggle_show_progress.emit(True)
        self.toggle_show_cancel.emit(True)

        res = gdal.Rasterize(
            self.out_file,
            self.in_file,
            format="GTiff",
            xRes=self.out_res,
            yRes=-self.out_res,
            noData=-32768,
            attribute=self.attribute,
            outputSRS="epsg:4326",
            outputType=self.out_data_type,
            creationOptions=["COMPRESS=LZW"],
            callback=self.progress_callback,
        )

        if res:
            return True
        else:
            return None

    def progress_callback(self, fraction, message, data):
        if self.killed:
            return False
        else:
            self.progress.emit(100 * fraction)

            return True


class RasterImportWorker(worker.AbstractWorker):
    def __init__(
        self,
        in_file,
        out_file,
        out_res,
        resample_mode,
        out_data_type=gdal.GDT_Byte,
        output_bounds=None,
    ):
        worker.AbstractWorker.__init__(self)

        self.in_file = in_file
        self.out_file = out_file
        self.out_res = out_res
        self.resample_mode = resample_mode
        self.out_data_type = out_data_type
        self.output_bounds = output_bounds

    def work(self):
        self.toggle_show_progress.emit(True)
        self.toggle_show_cancel.emit(True)

        warp_kwargs = dict(
            format="GTiff",
            dstNodata=-32768,
            dstSRS="epsg:4326",
            outputType=self.out_data_type,
            resampleAlg=self.resample_mode,
            creationOptions=["COMPRESS=LZW", "NUM_THREADS=ALL_CPUS"],
            callback=self.progress_callback,
        )

        if self.out_res:
            warp_kwargs["xRes"] = self.out_res
            warp_kwargs["yRes"] = -self.out_res

        if self.output_bounds:
            warp_kwargs["outputBounds"] = self.output_bounds

        res = gdal.Warp(
            self.out_file,
            self.in_file,
            **warp_kwargs,
        )

        if res:
            return True
        else:
            return None

    def progress_callback(self, fraction, message, data):
        if self.killed:
            return False
        else:
            self.progress.emit(100 * fraction)

            return True


class RemapRasterWorker(worker.AbstractWorker):
    def __init__(self, in_file, out_file, remap_list):
        worker.AbstractWorker.__init__(self)

        self.in_file = in_file
        self.out_file = out_file
        self.remap_list = remap_list

    def work(self):
        self.toggle_show_progress.emit(True)
        self.toggle_show_cancel.emit(True)

        ds_in = gdal.Open(self.in_file)

        band = ds_in.GetRasterBand(1)

        block_sizes = band.GetBlockSize()
        x_block_size = block_sizes[0]
        y_block_size = block_sizes[1]
        xsize = band.XSize
        ysize = band.YSize

        driver = gdal.GetDriverByName("GTiff")
        ds_out = driver.Create(
            self.out_file, xsize, ysize, 1, gdal.GDT_Int16, ["COMPRESS=LZW"]
        )
        src_gt = ds_in.GetGeoTransform()
        ds_out.SetGeoTransform(src_gt)
        out_srs = osr.SpatialReference()
        out_srs.ImportFromWkt(ds_in.GetProjectionRef())
        ds_out.SetProjection(out_srs.ExportToWkt())

        blocks = 0

        for y in range(0, ysize, y_block_size):
            if self.killed:
                log(
                    "Processing of {} killed by user after processing {} out of {} blocks.".format(
                        self.in_file, y, ysize
                    )
                )

                break
            self.progress.emit(100 * float(y) / ysize)

            if y + y_block_size < ysize:
                rows = y_block_size
            else:
                rows = ysize - y

            for x in range(0, xsize, x_block_size):
                if x + x_block_size < xsize:
                    cols = x_block_size
                else:
                    cols = xsize - x

                d = band.ReadAsArray(x, y, cols, rows).astype(np.int16)

                d_original = d.copy()

                for value, replacement in zip(self.remap_list[0], self.remap_list[1]):
                    d[d_original == int(value)] = int(replacement)

                ds_out.GetRasterBand(1).WriteArray(d, x, y)
                blocks += 1

        if self.killed:
            del ds_out
            os.remove(self.out_file)

            return None
        else:
            return True


def get_unique_values_vector(layer, field, max_unique=100):
    idx = layer.fields().lookupField(field)
    values = layer.uniqueValues(idx)

    if len(values) > max_unique:
        return None
    else:
        return list(values)


def _get_min_max_tuple(values, min_min, max_max, nodata):
    values[values < nodata] = np.nan
    mn = np.nanmin(values)

    if mn < min_min:
        return None
    mx = np.nanmax(values)

    if mx > max_max:
        return None

    return (mn, mx)


def get_vector_stats(layer, attribute, min_min=0, max_max=1000, nodata=0):
    values = np.asarray(
        [feat.attribute(attribute) for feat in layer.getFeatures()], dtype=np.float32
    )

    return _get_min_max_tuple(values, min_min, max_max, nodata)


def get_raster_stats(f, band_num, sample=True, min_min=0, max_max=1000, nodata=0):
    # Note that anything less than nodata value is considered no data

    if sample:
        # Note need float to correctly mark and ignore nodata for for nanmin
        # and nanmax
        values = layers.get_sample(f, band_num, n=1e6).astype("float32")

        return _get_min_max_tuple(values, min_min, max_max, nodata)
    else:
        src_ds = gdal.Open(f)
        b = src_ds.GetRasterBand(band_num)

        block_sizes = b.GetBlockSize()
        x_block_size = block_sizes[0]
        y_block_size = block_sizes[1]
        xsize = b.XSize
        ysize = b.YSize

        stats = (None, None)

        for y in range(0, ysize, y_block_size):
            if y + y_block_size < ysize:
                rows = y_block_size
            else:
                rows = ysize - y

            for x in range(0, xsize, x_block_size):
                if x + x_block_size < xsize:
                    cols = x_block_size
                else:
                    cols = xsize - x

                d = b.ReadAsArray(x, y, cols, rows)

                mn, mx = _get_min_max_tuple(d, min_min, max_max, nodata)

                if not mn or not mx:
                    return None
                else:
                    if not stats[0] or mn < stats[0]:
                        stats[0] = mn

                    if not stats[1] or mx > stats[1]:
                        stats[1] = mx

        return stats


def get_unique_values_raster(f, band_num, sample=True, max_unique=60):
    if sample:
        values = np.unique(layers.get_sample(f, band_num, n=1e6)).tolist()

        if len(values) > max_unique:
            values = None

        return values
    else:
        src_ds = gdal.Open(f)
        b = src_ds.GetRasterBand(band_num)

        block_sizes = b.GetBlockSize()
        x_block_size = block_sizes[0]
        y_block_size = block_sizes[1]
        xsize = b.XSize
        ysize = b.YSize

        for y in range(0, ysize, y_block_size):
            if y + y_block_size < ysize:
                rows = y_block_size
            else:
                rows = ysize - y

            for x in range(0, xsize, x_block_size):
                if x + x_block_size < xsize:
                    cols = x_block_size
                else:
                    cols = xsize - x

                if x == 0 and y == 0:
                    v = np.unique(b.ReadAsArray(x, y, cols, rows).ravel())
                else:
                    v = np.unique(
                        np.concatenate((v, b.ReadAsArray(x, y, cols, rows).ravel()))
                    )

                if v.size > max_unique:
                    return None

        return v.tolist()


class DlgJobsDetails(QtWidgets.QDialog, Ui_DlgJobsDetails):
    def __init__(self, parent=None):
        """Constructor."""
        super().__init__(parent)

        self.setupUi(self)
        self.task_status.hide()
        self.statusLabel.hide()


class DlgDataIOLoadTE(QtWidgets.QDialog, Ui_DlgDataIOLoadTE):
    file_browse_btn: QtWidgets.QPushButton
    file_lineedit: QtWidgets.QLineEdit
    parsed_name_la: QtWidgets.QLabel
    parsed_name_le: QtWidgets.QLineEdit
    parsed_result_la: QtWidgets.QLabel
    parsed_result_path_le: QtWidgets.QLineEdit

    buttonBox: QtWidgets.QDialogButtonBox

    job: typing.Optional[Job]

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setupUi(self)
        self.reset_widgets()
        self.job = None
        self.file_browse_btn.clicked.connect(self.parse_job_file)
        self.buttonBox.accepted.connect(self.ok_clicked)
        self.buttonBox.rejected.connect(self.reject)
        self.buttonBox.button(self.buttonBox.Ok).setEnabled(False)

    def reset_widgets(self):
        self.parsed_name_la.setEnabled(False)
        self.parsed_name_le.clear()
        self.parsed_name_le.setEnabled(False)
        self.parsed_result_la.setEnabled(False)
        self.parsed_result_path_le.clear()
        self.parsed_result_path_le.setEnabled(False)

    def show_job_info(self):
        self.parsed_name_la.setEnabled(True)
        self.parsed_name_le.setText(self.job.get_basename())
        self.parsed_name_le.setEnabled(True)
        self.parsed_result_la.setEnabled(True)
        try:
            # Get URI from the first result that has one
            local_path = ""
            for result in self.job._get_results_list():
                if hasattr(result, "uri") and result.uri:
                    local_path = str(result.uri.uri)
                    break
        except (IndexError, AttributeError):
            local_path = ""
        self.parsed_result_path_le.setText(local_path)
        self.parsed_result_path_le.setEnabled(True)

    def parse_job_file(self):
        self.reset_widgets()
        self.job = None
        self.buttonBox.button(self.buttonBox.Ok).setEnabled(False)
        file_dialog = QtWidgets.QFileDialog(self)
        file_dialog.setFileMode(QtWidgets.QFileDialog.ExistingFile)
        file_dialog.setNameFilter("*.json")
        file_dialog.setDirectory(conf.settings_manager.get_value(conf.Setting.BASE_DIR))

        if file_dialog.exec():
            chosen_raw_path = file_dialog.selectedFiles()[0]
            job, error_message = self.parse_chosen_path(chosen_raw_path)

            if job is not None:
                self.file_lineedit.setText(chosen_raw_path)
                self.job = job
                self.show_job_info()
                self.buttonBox.button(self.buttonBox.Ok).setEnabled(True)
            else:
                self.file_lineedit.clear()
                QtWidgets.QMessageBox.critical(
                    self, tr_data_io.tr("Could not load file"), error_message
                )

    def parse_chosen_path(
        self, raw_path: str
    ) -> typing.Tuple[typing.Optional[Job], str]:
        path = Path(raw_path)
        job = None
        error_message = ""

        if path.is_file():
            try:
                raw_data = json.loads(path.read_text())

                # Check if this is a results-only JSON (not a full Job)
                # by looking for the "type" field with a known ResultType value
                raw_data = self._wrap_results_only_json(raw_data, path)

                job = Job.Schema().load(raw_data)
                update_uris_if_needed(job, path)

                # Check if extents need to be recalculated
                needs_recalc = False
                # Get first raster result for extent checking
                raster_result = (
                    job.get_first_result_by_type(RasterResults) if job.results else None
                )
                if raster_result and hasattr(raster_result, "rasters"):
                    for raster in raster_result.rasters.values():
                        if hasattr(raster, "extent") and raster.extent is None:
                            needs_recalc = True
                            break
                        elif hasattr(raster, "extents") and (
                            raster.extents is None or None in raster.extents
                        ):
                            needs_recalc = True
                            break

                # Recalculate extents if needed
                if needs_recalc:
                    log("Detected missing extents, recalculating...")
                    set_results_extents(job, force=True)
                else:
                    set_results_extents(job)

            except (json.JSONDecodeError, KeyError):
                error_message = tr_data_io.tr(
                    "Could not parse the selected file into a valid JSON"
                )

        return job, error_message

    def _wrap_results_only_json(self, raw_data: dict, path: Path) -> dict:
        """
        Wrap a results-only JSON in a Job structure if needed.

        If the JSON contains only results data (identified by having a "type"
        field with a known ResultType value), wrap it in a minimal Job structure
        with reasonable defaults. Also handles list of results.

        Args:
            raw_data: The parsed JSON data (dict or list of result dicts)
            path: Path to the JSON file (used for generating defaults)

        Returns:
            Either the original data (if already a Job) or wrapped in Job structure
        """
        # Known result type values that indicate this is a results-only JSON
        result_type_values = {rt.value for rt in ResultType}

        # Check if this is a list of results
        is_results_list = (
            isinstance(raw_data, list)
            and len(raw_data) > 0
            and isinstance(raw_data[0], dict)
            and raw_data[0].get("type") in result_type_values
        )

        # Check if this looks like a results-only JSON (single result)
        is_single_result = (
            isinstance(raw_data, dict) and raw_data.get("type") in result_type_values
        )

        if is_results_list or is_single_result:
            # For list results, use the first result for metadata extraction
            primary_result = raw_data[0] if is_results_list else raw_data
            result_type = primary_result.get("type")

            log(
                f"Detected results-only JSON with type '{result_type}'"
                f"{' (list of ' + str(len(raw_data)) + ' results)' if is_results_list else ''}, "
                "wrapping in Job structure"
            )

            # Extract name from primary result for task_name, or use filename
            results_name = primary_result.get("name", "")
            task_name = results_name if results_name else path.stem

            # Try to infer area of interest name from filename or results
            aoi_name = path.stem.replace("_", " ").replace("-", " ")

            # Generate current timestamp
            now = datetime.datetime.now(datetime.timezone.utc)
            timestamp = now.isoformat()

            # Build the wrapped Job structure
            wrapped = {
                "id": str(uuid.uuid4()),
                "params": {},
                "progress": 100,
                "start_date": timestamp,
                "end_date": timestamp,
                "status": "GENERATED_LOCALLY",
                "local_context": {
                    "base_dir": str(path.parent),
                    "area_of_interest_name": aoi_name,
                },
                "results": raw_data,
                "task_name": task_name,
                "task_notes": f"Imported from results file: {path.name}",
                "script": {
                    "id": "imported-results",
                    "name": "Imported Results",
                    "name_readable": "Imported Results",
                    "run_mode": "local",
                },
            }
            return wrapped

        # Not a results-only JSON, return as-is
        return raw_data

    def ok_clicked(self):
        log("Importing job...")
        job_manager.import_job(self.job, Path(self.file_lineedit.text()))
        self.accept()


class ImportSelectFileInputWidget(
    QtWidgets.QWidget, Ui_WidgetDataIOImportSelectFileInput
):
    inputFileChanged = QtCore.pyqtSignal(bool)
    inputTypeChanged = QtCore.pyqtSignal(bool)

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setupUi(self)

        self.radio_raster_input.toggled.connect(self.radio_raster_input_toggled)

        self.btn_raster_dataset_browse.clicked.connect(self.open_raster_browse)
        self.btn_polygon_dataset_browse.clicked.connect(self.open_vector_browse)

        self.groupBox_output_resolution.clicked.connect(self.output_res_toggled)

        # Ensure the special value text (set to " ") is displayed by default
        self.spinBox_data_year.setSpecialValueText(" ")
        self.spinBox_data_year.setValue(int(self.spinBox_data_year.minimum()))

    def radio_raster_input_toggled(self):
        has_file = False

        if self.radio_raster_input.isChecked():
            self.btn_raster_dataset_browse.setEnabled(True)
            self.lineEdit_raster_file.setEnabled(True)
            self.comboBox_bandnumber.setEnabled(True)
            self.label_bandnumber.setEnabled(True)
            self.btn_polygon_dataset_browse.setEnabled(False)
            self.lineEdit_vector_file.setEnabled(False)
            self.label_fieldname.setEnabled(False)
            self.comboBox_fieldname.setEnabled(False)
            self.groupBox_output_resolution.setChecked(False)

            if self.lineEdit_raster_file.text():
                has_file = True
        else:
            self.btn_raster_dataset_browse.setEnabled(False)
            self.lineEdit_raster_file.setEnabled(False)
            self.comboBox_bandnumber.setEnabled(False)
            self.label_bandnumber.setEnabled(False)
            self.btn_polygon_dataset_browse.setEnabled(True)
            self.lineEdit_vector_file.setEnabled(True)
            self.label_fieldname.setEnabled(True)
            self.comboBox_fieldname.setEnabled(True)
            self.groupBox_output_resolution.setChecked(True)

            if self.lineEdit_vector_file.text():
                has_file = True
        self.inputTypeChanged.emit(has_file)

    def output_res_toggled(self):
        # Ensure the groupBox_output_resolution remains checked if vector
        # output is chosen

        if self.radio_raster_input.isChecked():
            pass
        else:
            self.groupBox_output_resolution.setChecked(True)

    def open_raster_browse(self):
        if self.lineEdit_raster_file.text():
            initial_file = self.lineEdit_raster_file.text()
        else:
            initial_file = QSettings().value("LDMP/input_dir", None)
        raster_file, _ = QtWidgets.QFileDialog.getOpenFileName(
            self,
            tr_data_io.tr("Select a raster input file"),
            initial_file,
            tr_data_io.tr("Raster file (*.tif *.dat *.img *.vrt)"),
        )
        # Try loading this raster to verify the file works

        if raster_file:
            self.update_raster_layer(raster_file)

    def update_raster_layer(self, raster_file):
        layer = qgis.core.QgsRasterLayer(raster_file, "raster file", "gdal")

        if not os.access(raster_file, os.R_OK or not layer.isValid()):
            QtWidgets.QMessageBox.critical(
                None,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "Cannot read {}. Choose a different file.".format(raster_file)
                ),
            )
            self.inputFileChanged.emit(False)

            return False
        else:
            QSettings().setValue("LDMP/input_dir", os.path.dirname(raster_file))
            self.lineEdit_raster_file.setText(raster_file)
            self.comboBox_bandnumber.clear()
            self.comboBox_bandnumber.addItems(
                [str(n) for n in range(1, layer.dataProvider().bandCount() + 1)]
            )

            self.inputFileChanged.emit(True)

            return True

    def open_vector_browse(self):
        if self.lineEdit_vector_file.text():
            initial_file = self.lineEdit_vector_file.text()
        else:
            initial_file = QSettings().value("LDMP/input_dir", None)
        vector_file, _ = QtWidgets.QFileDialog.getOpenFileName(
            self,
            tr_data_io.tr("Select a vector input file"),
            initial_file,
            tr_data_io.tr("Vector file (*.shp *.kml *.kmz *.geojson)"),
        )
        # Try loading this vector to verify the file works

        if vector_file:
            self.update_vector_layer(vector_file)

    def update_vector_layer(self, vector_file):
        layer = qgis.core.QgsVectorLayer(vector_file, "vector file", "ogr")

        if not os.access(vector_file, os.R_OK) or not layer.isValid():
            QtWidgets.QMessageBox.critical(
                None,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "Cannot read {}. Choose a different file.".format(vector_file)
                ),
            )
            self.inputFileChanged.emit(False)

            return False
        else:
            QSettings().setValue("LDMP/input_dir", os.path.dirname(vector_file))
            self.lineEdit_vector_file.setText(vector_file)
            self.comboBox_fieldname.clear()
            self.inputFileChanged.emit(True)
            self.comboBox_fieldname.addItems(
                [field.name() for field in layer.dataProvider().fields()]
            )

            return True

    def get_vector_layer(self) -> qgis.core.QgsVectorLayer:
        vector_file = self.lineEdit_vector_file.text()
        if not vector_file:
            return None

        return qgis.core.QgsVectorLayer(
            self.lineEdit_vector_file.text(), "vector file", "ogr"
        )

    def get_raster_layer(self) -> qgis.core.QgsRasterLayer:
        """
        Returns the raster layer corresponding to the input file. If
        a file path is not specified or if the layer is invalid then it
        will return None.
        """
        raster_file = self.lineEdit_raster_file.text()
        if not raster_file:
            return None

        layer = qgis.core.QgsRasterLayer(raster_file)
        if not layer.isValid():
            return None

        return layer

    def selected_file_type(self) -> str:
        """
        Returns if current selection is "raster" or "vector".
        """
        if self.radio_raster_input.isChecked():
            return "raster"
        elif self.radio_polygon_input.isChecked():
            return "vector"

        return ""


class ImportSelectRasterOutput(
    QtWidgets.QWidget, Ui_WidgetDataIOImportSelectRasterOutput
):
    def __init__(self, parent=None):
        super().__init__(parent)

        self.setupUi(self)

        self.btn_output_file_browse.clicked.connect(self.save_raster)

    def save_raster(self):
        if self.lineEdit_output_file.text():
            initial_file = self.lineEdit_output_file.text()
        else:
            initial_file = conf.settings_manager.get_value(conf.Setting.BASE_DIR)
        raw_output_path, _ = QtWidgets.QFileDialog.getSaveFileName(
            self,
            tr_data_io.tr("Choose a name for the output file"),
            initial_file,
            tr_data_io.tr("Raster file (*.tif)"),
        )

        if raw_output_path:
            output_path = Path(raw_output_path)
            output_path = output_path.parent / f"{output_path.stem}.tif"

            if os.access(os.path.dirname(str(output_path)), os.W_OK):
                self.lineEdit_output_file.setText(str(output_path))

                return True
            else:
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "Cannot write to {}. Choose a different file.".format(
                            raw_output_path
                        )
                    ),
                )

                return False


def extents_within_tolerance(
    geom1: qgis.core.QgsGeometry, geom2: qgis.core.QgsGeometry
) -> bool:
    """
    Check if the two geometries are overlapping and to which extent based on
    the tolerance setting, which is based on a ratio of the non-overlapping
    area to the total area of the reference geometry.
    Ensure the two geometries are in the same CRS.
    """
    if geom1.equals(geom2):
        return True

    diff_geom = geom1.difference(geom2)
    if diff_geom.isNull():
        return False

    # Cannot calculate tolerance based on area if not polygon based.
    if diff_geom.type() != qgis.core.QgsWkbTypes.GeometryType.PolygonGeometry:
        return False

    area_calculator = qgis.core.QgsDistanceArea()
    diff_ratio = area_calculator.measureArea(diff_geom) / area_calculator.measureArea(
        geom1
    )

    tolerance = conf.settings_manager.get_value(conf.Setting.IMPORT_AREA_TOLERANCE)

    if (1 - diff_ratio) > tolerance:
        return True

    return False


class DlgDataIOImportBase(QtWidgets.QDialog):
    """Base class for individual data loading dialogs"""

    input_widget: ImportSelectFileInputWidget
    metadata: qgis.core.QgsLayerMetadata

    layer_loaded = QtCore.pyqtSignal(list)

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setupUi(self)

        # Make dialog resizable
        self.setSizePolicy(
            QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred
        )

        # Message bar - stays at top of dialog
        self.msg_bar = qgis.gui.QgsMessageBar()
        self.verticalLayout.insertWidget(0, self.msg_bar)

        # Create the tab widget
        self.tabWidget = QtWidgets.QTabWidget()
        self.verticalLayout.insertWidget(1, self.tabWidget)

        # === Tab 1: Input file ===
        self.tab_input_file = QtWidgets.QWidget()
        self.tab_input_file_layout = QtWidgets.QVBoxLayout(self.tab_input_file)
        self.tab_input_file_layout.setContentsMargins(10, 10, 10, 10)

        self.input_widget = ImportSelectFileInputWidget()
        self.input_widget.inputFileChanged.connect(self.on_input_file_changed)
        # Only show the file selection group, hide settings groups
        self.input_widget.groupBox_output_resolution.setParent(None)
        self.input_widget.groupBox_year.setParent(None)
        self.input_widget.groupBox.setParent(None)  # nodata group
        self.tab_input_file_layout.addWidget(self.input_widget)

        # Add region selection to Input file tab (after file selection)
        self.checkbox_clip_to_region = QtWidgets.QCheckBox(
            tr_data_io.tr("Clip to region")
        )
        self.checkbox_clip_to_region.setChecked(True)
        self.checkbox_clip_to_region.stateChanged.connect(
            self._on_clip_to_region_changed
        )
        self.tab_input_file_layout.addWidget(self.checkbox_clip_to_region)

        self.region_selector = RegionSelector()
        self.region_selector.region_changed.connect(self.on_region_changed)
        self.tab_input_file_layout.addWidget(self.region_selector)
        self.tab_input_file_layout.addStretch()

        self.tabWidget.addTab(self.tab_input_file, tr_data_io.tr("Input file"))

        # === Tab 2: Settings ===
        self.tab_settings = QtWidgets.QWidget()
        self.tab_settings_layout = QtWidgets.QVBoxLayout(self.tab_settings)
        self.tab_settings_layout.setContentsMargins(10, 10, 10, 10)

        # Re-parent the settings groups from input_widget to settings tab
        self.tab_settings_layout.addWidget(self.input_widget.groupBox_output_resolution)
        self.input_widget.groupBox_output_resolution.show()
        self.tab_settings_layout.addWidget(self.input_widget.groupBox_year)
        self.input_widget.groupBox_year.show()
        self.tab_settings_layout.addWidget(self.input_widget.groupBox)  # nodata
        self.input_widget.groupBox.show()

        # Move dialog-specific settings from UI to settings tab
        self._move_dialog_settings_to_tab()

        self.tab_settings_layout.addStretch()
        self.tabWidget.addTab(self.tab_settings, tr_data_io.tr("Settings"))

        # === Tab 3: Notes ===
        self.tab_notes = QtWidgets.QWidget()
        self.tab_notes_layout = QtWidgets.QVBoxLayout(self.tab_notes)
        self.tab_notes_layout.setContentsMargins(10, 10, 10, 10)

        # Create notes-related widgets programmatically
        self._create_notes_tab()

        self.tab_notes_layout.addStretch()
        self.tabWidget.addTab(self.tab_notes, tr_data_io.tr("Notes"))

        # The datatype determines whether the dataset resampling is done with
        # nearest neighbor and mode or nearest neighbor and mean
        self.datatype = "categorical"
        self.warp_data_type = gdal.GDT_Int16
        self.metadata = None

        self.btnMetadata = QtWidgets.QPushButton(tr_data_io.tr("Metadata"))
        layout = self.btnBox.layout()
        layout.insertWidget(0, self.btnMetadata)
        self.btnMetadata.clicked.connect(self.open_metadata_editor)

        # Output raster file - this should be moved once a job has been
        # created by calling job_manager.move_job_results().
        self._output_raster_path = GetTempFilename(".tif")

    def _move_dialog_settings_to_tab(self):
        """
        Move dialog-specific settings widgets from the UI file to the Settings tab.
        Subclasses with specific settings (like year spinboxes, aggregation options)
        should override this method to move their widgets.
        """
        pass

    def _create_notes_tab(self):
        """
        Create layer_name and notes widgets programmatically for the Notes tab.
        """
        # Layer name label
        self.layer_name_la = QtWidgets.QLabel(tr_data_io.tr("Layer name:"))
        self.tab_notes_layout.addWidget(self.layer_name_la)

        # Layer name line edit
        self.layer_name_le = QtWidgets.QLineEdit()
        self.layer_name_le.setToolTip(
            tr_data_io.tr("Name that will be assigned to the imported layer.")
        )
        self.tab_notes_layout.addWidget(self.layer_name_le)

        # Notes label
        self.task_notes_la = QtWidgets.QLabel(tr_data_io.tr("Notes:"))
        self.tab_notes_layout.addWidget(self.task_notes_la)

        # Notes text edit
        self.task_notes = QtWidgets.QTextEdit()
        self.task_notes.setToolTip(
            tr_data_io.tr("Notes associated with the imported layer.")
        )
        self.task_notes.setSizePolicy(
            QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding
        )
        self.task_notes.setMinimumHeight(100)
        self.tab_notes_layout.addWidget(self.task_notes)

    def _on_clip_to_region_changed(self, state):
        """Handle clip to region checkbox state change."""
        is_checked = state == QtCore.Qt.Checked
        self.region_selector.setEnabled(is_checked)
        # Re-validate overlap when checkbox state changes
        if self.input_widget.selected_file_type():
            self.validate_overlap()

    def is_clip_to_region_enabled(self) -> bool:
        """Returns True if clip to region is enabled."""
        return self.checkbox_clip_to_region.isChecked()

    def on_region_changed(self, region_info):
        """
        Slot raised when the region has changed.
        """
        self.validate_overlap()

    def on_input_file_changed(self, success):
        """
        Slot raised when a raster or vector file has been uploaded.
        """
        if success:
            self.validate_overlap()

    def validate_overlap(self, user_warning=True) -> bool:
        """
        Checks the range within which the geometry of the uploaded file
        overlaps with that of the selected region. The allowed range should
        be within the tolerance specified in the settings. Sends a warning
        that the output will be expanded or clipped if the extents are not
        the same. Messaging will be sent if the child dialog contains a
        'msg_bar' attribute of type QMessageBar.

        Returns True if validation passes (or clipping is disabled).
        """
        self.msg_bar.clearWidgets()

        # If clip to region is disabled, skip validation - full extent will be used
        if not self.is_clip_to_region_enabled():
            return True

        region_geom = try_get_aoi_geometry()
        if region_geom is None:
            if user_warning:
                push_message(
                    self.msg_bar,
                    tr_data_io.tr("Warning"),
                    tr_data_io.tr(
                        "No region selected. Select a region or uncheck "
                        "'Clip to region' to import the full dataset."
                    ),
                    level=qgis.core.Qgis.MessageLevel.Warning,
                )
            return False

        file_type = self.input_widget.selected_file_type()
        if not file_type:
            return False

        layer_bbox_geom = None
        source_crs = None
        if file_type == "raster":
            lyr = self.input_widget.get_raster_layer()
            if lyr:
                layer_bbox_geom = qgis.core.QgsGeometry.fromRect(lyr.extent())
                source_crs = lyr.crs()
        else:
            lyr = self.input_widget.get_vector_layer()
            if not lyr or not lyr.isValid():
                return False

            source_crs = lyr.crs()

            # Combine the geometry for all the features
            feat_iter = lyr.getFeatures()
            geoms = [
                f.geometry()
                for f in feat_iter
                if f.isValid() and not f.geometry().isNull()
            ]
            for g in geoms:
                if layer_bbox_geom is None:
                    layer_bbox_geom = g
                    continue
                layer_bbox_geom = layer_bbox_geom.combine(g)

        if layer_bbox_geom is None:
            return False

        if source_crs is None or not source_crs.isValid():
            if user_warning:
                push_message(
                    self.msg_bar,
                    self.tr("Missing or invalid CRS for input file."),
                    "",
                    qgis.core.Qgis.MessageLevel.Warning,
                    8,
                )

            return False

        # Reproject the geometry to WGS if different from region
        wgs84_crs = qgis.core.QgsCoordinateReferenceSystem.fromEpsgId(4326)
        if source_crs != wgs84_crs:
            transform_ctx = qgis.core.QgsProject.instance().transformContext()
            ct = qgis.core.QgsCoordinateTransform(source_crs, wgs84_crs, transform_ctx)
            result = layer_bbox_geom.transform(ct)
            if result != qgis.core.Qgis.GeometryOperationResult.Success:
                log("Unable to reproject source file geometry.")
                return False

        # Check if within tolerance
        if not extents_within_tolerance(region_geom, layer_bbox_geom):
            # Notify user
            if user_warning:
                reg_name = self.region_selector.region_info.area_name
                push_message(
                    self.msg_bar,
                    self.tr(f"Output file will be resized to '{reg_name}' extent."),
                    "",
                    qgis.core.Qgis.MessageLevel.Warning,
                    8,
                )
            return False

        return True

    def extent_as_list(self) -> list:
        """
        Returns the list containing xmin, ymin, xmax, ymax of the
        region geom extent or an empty list if clipping is disabled or
        the extent could not be determined.
        """
        # If clip to region is disabled, return empty list (use full extent)
        if not self.is_clip_to_region_enabled():
            return []

        geom = try_get_aoi_geometry()
        if geom is None:
            return []

        bbox = geom.boundingBox()

        if bbox is None:
            return []

        return [bbox.xMinimum(), bbox.yMinimum(), bbox.xMaximum(), bbox.yMaximum()]

    def validate_region_selection(self) -> bool:
        """
        Validates that a region is selected if clip to region is enabled.

        Returns True if validation passes, False otherwise (with error message shown).
        """
        if self.is_clip_to_region_enabled():
            if try_get_aoi_geometry() is None:
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "No region is selected. Either select a region or uncheck "
                        "'Clip to region' to import the full dataset extent."
                    ),
                )
                return False
        return True

    def get_resample_mode(self, f):
        in_res = self.get_in_res_wgs84()
        out_res = self.get_out_res_wgs84()

        if in_res < out_res:
            if self.datatype == "categorical":
                log(
                    "Resampling with mode (in res: {}, out_res: {}".format(
                        in_res, out_res
                    )
                )

                return gdal.GRA_Mode
            elif self.datatype == "continuous":
                log(
                    "Resampling with average (in res: {}, out_res: {}".format(
                        in_res, out_res
                    )
                )

                return gdal.GRA_Average
            else:
                raise ValueError("Unknown datatype")
        else:
            # If output resolution is finer than the original data, use nearest
            # neighbor
            log(
                "Resampling with nearest neighbor (in res: {}, out_res: {}".format(
                    in_res, out_res
                )
            )

            return gdal.GRA_NearestNeighbour

    def get_in_res_wgs84(self):
        ds_in = gdal.Open(self.input_widget.lineEdit_raster_file.text())
        wgs84_srs = osr.SpatialReference()
        wgs84_srs.ImportFromEPSG(4326)

        in_srs = osr.SpatialReference()
        in_srs.ImportFromWkt(ds_in.GetProjectionRef())

        tx = osr.CoordinateTransformation(in_srs, wgs84_srs)

        geo_t = ds_in.GetGeoTransform()
        x_size = ds_in.RasterXSize
        y_size = ds_in.RasterYSize
        # Work out the boundaries of the new dataset in the target projection
        (ulx, uly, ulz) = tx.TransformPoint(geo_t[0], geo_t[3])
        (lrx, lry, lrz) = tx.TransformPoint(
            geo_t[0] + geo_t[1] * x_size, geo_t[3] + geo_t[5] * y_size
        )
        log("ulx: {}, uly: {}, ulz: {}".format(ulx, uly, ulz))
        log("lrx: {}, lry: {}, lrz: {}".format(lrx, lry, lrz))
        # As an approximation of what the output res would be in WGS4, use an
        # average of the x and y res of this image

        return ((lrx - ulx) / float(x_size) + (lry - uly) / float(y_size)) / 2

    def get_out_res_wgs84(self):
        # Calculate res in degrees from input which is in meters
        res = int(self.input_widget.spinBox_resolution.value())

        return res / (111.325 * 1000)  # 111.325km in one degree

    def remap_vector(self, layer, out_file, remap_dict, attribute):
        out_res = self.get_out_res_wgs84()
        log(
            'Remapping and rasterizing {} using output resolution {}, and field "{}"'.format(
                out_file, out_res, attribute
            )
        )
        log('Remap dict "{}"'.format(remap_dict))

        target_bounds = self.extent_as_list()
        if len(target_bounds) == 0:
            log("Target bounds for remapping vector not available.")
            target_bounds = None

        remap_vector_worker = worker.StartWorker(
            RemapVectorWorker,
            "rasterizing and remapping values",
            layer,
            out_file,
            attribute,
            remap_dict,
            self.vector_datatype,
            out_res,
            target_bounds,
        )

        if not remap_vector_worker.success:
            QtWidgets.QMessageBox.critical(
                None, tr_data_io.tr("Error"), tr_data_io.tr("Vector remapping failed.")
            )

            return False
        else:
            return True

    def remap_raster(self, out_file, remap_list):
        # First warp the raster to the correct CRS
        temp_tif = GetTempFilename(".tif")
        warp_ret = self.warp_raster(temp_tif)

        if not warp_ret:
            return False

        remap_raster_worker = worker.StartWorker(
            RemapRasterWorker, "remapping values", temp_tif, out_file, remap_list
        )
        os.remove(temp_tif)

        if not remap_raster_worker.success:
            QtWidgets.QMessageBox.critical(
                None, tr_data_io.tr("Error"), tr_data_io.tr("Raster remapping failed.")
            )

            return False
        else:
            return True

    def rasterize_vector(self, in_file, out_file, attribute):
        out_res = self.get_out_res_wgs84()
        log(
            f"Rasterizing {out_file} using output resolution {out_res}, "
            f'and field "{attribute}"'
        )
        rasterize_worker = worker.StartWorker(
            RasterizeWorker,
            "rasterizing vector file",
            in_file,
            out_file,
            out_res,
            attribute,
        )

        if not rasterize_worker.success:
            QtWidgets.QMessageBox.critical(
                None, tr_data_io.tr("Error"), tr_data_io.tr("Rasterizing failed.")
            )

            return False
        else:
            return True

    def warp_raster(self, out_file):
        # Select a single output band
        in_file = self.input_widget.lineEdit_raster_file.text()
        band_number = int(self.input_widget.comboBox_bandnumber.currentText())
        temp_tif = GetTempFilename(".tif")
        target_bounds = self.extent_as_list()

        gdal.Translate(
            temp_tif,
            in_file,
            bandList=[band_number],
            outputType=self.warp_data_type,
        )

        # Convert target_bounds [xmin, ymin, xmax, ymax] to the
        # outputBounds format expected by gdal.Warp: [minX, minY, maxX, maxY]
        # These are in WGS84, matching the dstSRS used by RasterImportWorker.
        if len(target_bounds) == 0:
            log("Target bounds for warping raster not available.")
            output_bounds = None
        else:
            ext_str = ",".join(map(str, target_bounds))
            log(f"Target bounds for warped raster: {ext_str}")
            output_bounds = target_bounds

        log("Importing {} to {}".format(in_file, out_file))

        if self.input_widget.groupBox_output_resolution.isChecked():
            out_res = self.get_out_res_wgs84()
            resample_mode = self.get_resample_mode(temp_tif)
        else:
            out_res = None
            resample_mode = gdal.GRA_NearestNeighbour

        raster_import_worker = worker.StartWorker(
            RasterImportWorker,
            "importing raster",
            temp_tif,
            out_file,
            out_res,
            resample_mode,
            self.warp_data_type,
            output_bounds,
        )
        os.remove(temp_tif)

        if not raster_import_worker.success:
            QtWidgets.QMessageBox.critical(
                self, tr_data_io.tr("Error"), tr_data_io.tr("Raster import failed.")
            )
            return False
        else:
            return True

    def open_metadata_editor(self):
        dlg = metadata_dialog.DlgDatasetMetadata(self)
        dlg.exec()
        self.metadata = dlg.get_metadata()

    def save_metadata(self, job):
        metadata.init_dataset_metadata(job, self.metadata)

    def done(self, value):
        """
        Common dialog done handler.

        Subclasses should override validate_input() to add their validation
        logic and call ok_clicked() on success.
        """
        if value == QtWidgets.QDialog.Accepted:
            if getattr(self, "_validating", False):
                # Re-entry from validate_input() calling super().done() —
                # forward directly to QDialog.done() to close the dialog
                # instead of recursing back into validate_input().
                super().done(value)
                return
            self._validating = True
            try:
                self.validate_input(value)
            finally:
                self._validating = False
        else:
            super().done(value)

    def _validate_base_input(self, value):
        """
        Common input validation for all import dialogs.

        Validates region selection and input file selection.
        Subclasses should call this method first in their validate_input().

        Returns:
            True if validation passes, None/False otherwise.
        """
        # First check region selection if clipping is enabled
        if not self.validate_region_selection():
            return

        if self.input_widget.radio_raster_input.isChecked():
            if self.input_widget.lineEdit_raster_file.text() == "":
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr("Choose an input raster file."),
                )

                return
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()

            if in_file == "":
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr("Choose an input polygon dataset."),
                )

                return
            layer = self.input_widget.get_vector_layer()

            if (
                layer.wkbType() == qgis.core.QgsWkbTypes.Polygon
                or layer.wkbType() == qgis.core.QgsWkbTypes.MultiPolygon
            ):
                self.vector_datatype = "polygon"
            elif layer.wkbType() == qgis.core.QgsWkbTypes.Point:
                self.vector_datatype = "point"
            else:
                QtWidgets.QMessageBox.critical(
                    None,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "Cannot process {}. Unknown geometry type:{}".format(
                            in_file, layer.wkbType()
                        )
                    ),
                )
                log(
                    "Failed to process {} - unknown geometry type {}.".format(
                        in_file, layer.wkbType()
                    )
                )

                return

        return True

    def validate_input(self, value):
        """
        Validate input before accepting the dialog.

        Subclasses should override this method to add their validation logic,
        calling self._validate_base_input(value) first.

        On successful validation, subclasses should call:
            super().done(value)
            self.ok_clicked()
        """
        raise NotImplementedError("Subclasses must implement validate_input()")

    def get_layer_name(self, default_name: str) -> str:
        """
        Get the layer name from the notes tab, or return the default if empty.

        Args:
            default_name: Default name to use if user didn't specify one.

        Returns:
            The layer name to use.
        """
        layer_name = self.layer_name_le.text().strip()
        if not layer_name:
            layer_name = default_name
        return layer_name

    def get_task_notes(self) -> str:
        """Get the task notes from the notes tab."""
        return self.task_notes.toPlainText()

    def finalize_import(self, job):
        """
        Finalize the import by importing the job and saving metadata.

        This should be called at the end of ok_clicked() in subclasses.

        Args:
            job: The Job object created by job_manager.create_job_from_dataset()
        """
        job_manager.import_job(job, Path(self._output_raster_path))
        job_manager.move_job_results(job)
        self.save_metadata(job)


class DlgDataIOImportPopulation(DlgDataIOImportBase, Ui_DlgDataIOImportPopulation):
    def __init__(self, parent=None):
        super().__init__(parent)

    def validate_input(self, value):
        max_max = 10000000  # Maximum value for population
        if (
            self.input_widget.spinBox_data_year.text()
            == self.input_widget.spinBox_data_year.specialValueText()
        ):
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr("Enter the year of the input data."),
            )

            return

        ret = self._validate_base_input(value)

        if not ret:
            return

        if self.input_widget.radio_raster_input.isChecked():
            in_file = self.input_widget.lineEdit_raster_file.text()
            stats = get_raster_stats(
                in_file,
                int(self.input_widget.comboBox_bandnumber.currentText()),
                max_max=max_max,
            )
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            layer = self.input_widget.get_vector_layer()
            field = self.input_widget.comboBox_fieldname.currentText()
            idx = layer.fields().lookupField(field)

            if not layer.fields().field(idx).isNumeric():
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "The chosen field ({}) is not numeric. Choose a numeric field.".format(
                            field
                        )
                    ),
                )

                return
            else:
                stats = get_vector_stats(
                    self.input_widget.get_vector_layer(), field, max_max=max_max
                )
        log("Stats are: {}".format(stats))

        if not stats:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid population "
                    "input file. The file should contain values of soil "
                    "organic carbon in tonnes / hectare.".format(in_file)
                ),
            )

            return

        if stats[0] < 0:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid population "
                    "input file. The minimum value in this file is {}. The no "
                    "data value should be -32768, and all other values should be >= 0.".format(
                        in_file, stats[0]
                    )
                ),
            )

            return

        if stats[1] > 10000000:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid soil organic "
                    "carbon input file. The maximum value in this file is {}. "
                    "The maximum value allowed is {} tonnes / hectare.".format(
                        in_file, stats[1], max_max
                    )
                ),
            )

            return

        super().done(value)

        self.ok_clicked()

    def ok_clicked(self):
        out_file = self._output_raster_path

        if self.input_widget.radio_raster_input.isChecked():
            ret = self.warp_raster(out_file)
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            attribute = self.input_widget.comboBox_fieldname.currentText()
            ret = self.rasterize_vector(in_file, out_file, attribute)

        if not ret:
            return False

        layer_name = self.get_layer_name(
            tr_data_io.tr(
                "Population "
                f"({int(self.input_widget.spinBox_data_year.text())}, imported)"
            )
        )
        job = job_manager.create_job_from_dataset(
            dataset_path=Path(out_file),
            band_name="Population (number of people)",
            band_metadata={
                "year": int(self.input_widget.spinBox_data_year.text()),
                "source": "custom data",
                "type": "total",
            },
            task_name=layer_name,
            task_notes=self.get_task_notes(),
        )
        self.finalize_import(job)


class DlgDataIOImportSOC(DlgDataIOImportBase, Ui_DlgDataIOImportSOC):
    def __init__(self, parent=None):
        super().__init__(parent)
        self.datatype = "continuous"

    def validate_input(self, value):
        if (
            self.input_widget.spinBox_data_year.text()
            == self.input_widget.spinBox_data_year.specialValueText()
        ):
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr("Enter the year of the input data."),
            )

            return

        ret = self._validate_base_input(value)

        if not ret:
            return

        if self.input_widget.radio_raster_input.isChecked():
            in_file = self.input_widget.lineEdit_raster_file.text()
            stats = get_raster_stats(
                in_file, int(self.input_widget.comboBox_bandnumber.currentText())
            )
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            layer = self.input_widget.get_vector_layer()
            field = self.input_widget.comboBox_fieldname.currentText()
            idx = layer.fields().lookupField(field)

            if not layer.fields().field(idx).isNumeric():
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "The chosen field ({}) is not numeric. Choose a numeric field.".format(
                            field
                        )
                    ),
                )

                return
            else:
                stats = get_vector_stats(self.input_widget.get_vector_layer(), field)
        log("Stats are: {}".format(stats))

        if not stats:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid soil organic "
                    "carbon input file. The file should contain values of soil "
                    "organic carbon in tonnes / hectare.".format(in_file)
                ),
            )

            return

        if stats[0] < 0:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid soil organic "
                    "carbon input file. The minimum value in this file is {}. The no "
                    "data value should be -32768, and all other values should be >= 0.".format(
                        in_file, stats[0]
                    )
                ),
            )

            return

        if stats[1] > 1000:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid soil organic "
                    "carbon input file. The maximum value in this file is {}. "
                    "The maximum value allowed is 1000 tonnes / hectare.".format(
                        in_file, stats[1]
                    )
                ),
            )

            return

        super().done(value)

        self.ok_clicked()

    def ok_clicked(self):
        out_file = self._output_raster_path

        if self.input_widget.radio_raster_input.isChecked():
            ret = self.warp_raster(out_file)
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            attribute = self.input_widget.comboBox_fieldname.currentText()
            ret = self.rasterize_vector(in_file, out_file, attribute)

        if not ret:
            return False

        layer_name = self.get_layer_name(
            tr_data_io.tr(
                "Soil organic carbon "
                f"({int(self.input_widget.spinBox_data_year.text())}, imported)"
            )
        )
        job = job_manager.create_job_from_dataset(
            dataset_path=Path(out_file),
            band_name="Soil organic carbon",
            band_metadata={
                "year": int(self.input_widget.spinBox_data_year.text()),
                "source": "custom data",
            },
            task_name=layer_name,
            task_notes=self.get_task_notes(),
        )
        self.finalize_import(job)


class DlgDataIOImportProd(DlgDataIOImportBase, Ui_DlgDataIOImportProd):
    def __init__(self, parent=None):
        super().__init__(parent)
        self.input_widget.groupBox_year.hide()
        self.populate_data_types()

        # Ensure the special value text (set to " ") is displayed by default
        self.spinBox_year_initial.setSpecialValueText(" ")
        self.spinBox_year_initial.setValue(int(self.spinBox_year_initial.minimum()))
        self.spinBox_year_final.setSpecialValueText(" ")
        self.spinBox_year_final.setValue(int(self.spinBox_year_final.minimum()))

    def _move_dialog_settings_to_tab(self):
        """Move Prod-specific settings to the Settings tab."""
        # Move year spinboxes (groupBox_2)
        if hasattr(self, "groupBox_2") and self.groupBox_2:
            self.groupBox_2.setParent(None)
            self.tab_settings_layout.addWidget(self.groupBox_2)
        # Move data type combo (groupBox_datatype)
        if hasattr(self, "groupBox_datatype") and self.groupBox_datatype:
            self.groupBox_datatype.setParent(None)
            self.tab_settings_layout.addWidget(self.groupBox_datatype)
        # Move productivity class definition (groupBox_lc_agg)
        if hasattr(self, "groupBox_lc_agg") and self.groupBox_lc_agg:
            self.groupBox_lc_agg.setParent(None)
            self.tab_settings_layout.addWidget(self.groupBox_lc_agg)

    def validate_input(self, value):
        try:
            _ = int(self.spinBox_year_initial.text())
            _ = int(self.spinBox_year_final.text())
        except ValueError:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "On the settings tab, enter the intial and final year applying to this input data."
                ),
            )

            return
        ret = self._validate_base_input(value)

        if not ret:
            return

        if self.input_widget.radio_raster_input.isChecked():
            in_file = self.input_widget.lineEdit_raster_file.text()
            values = get_unique_values_raster(
                in_file,
                int(self.input_widget.comboBox_bandnumber.currentText()),
                max_unique=7,
            )
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            layer = self.input_widget.get_vector_layer()
            field = self.input_widget.comboBox_fieldname.currentText()
            idx = layer.fields().lookupField(field)

            if not layer.fields().field(idx).isNumeric():
                QtWidgets.QMessageBox.critical(
                    self,
                    tr_data_io.tr("Error"),
                    tr_data_io.tr(
                        "The chosen field ({}) is not numeric. Choose a field that "
                        "contains numbers.".format(field)
                    ),
                )

                return
            else:
                values = get_unique_values_vector(layer, field, max_unique=7)

        if not values:
            QtWidgets.QMessageBox.critical(
                self,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid productivity "
                    "input file.".format(in_file)
                ),
            )

            return
        invalid_values = [v for v in values if v not in [-32768, 0, 1, 2, 3, 4, 5]]

        if len(invalid_values) > 0:
            QtWidgets.QMessageBox.warning(
                self,
                tr_data_io.tr("Warning"),
                tr_data_io.tr(
                    "The input file ({}) does not appear to be a valid productivity "
                    "input file. Trends.Earth will load the file anyway, but review "
                    "the map once it has loaded to ensure the values make sense. The "
                    "only values allowed in a productivity input file are -32768, 1, "
                    "2, 3, 4 and 5. There are {} value(s) in the input file "
                    "that were not recognized.".format(in_file, len(invalid_values))
                ),
            )

        super().done(value)

        self.ok_clicked()

    def populate_data_types(self):
        for datatype in [
            ld_conf.CUSTOM_LPD_BAND_NAME,
            ld_conf.JRC_LPD_BAND_NAME,
            ld_conf.FAO_WOCAT_LPD_BAND_NAME,
            ld_conf.TE_LPD_BAND_NAME,
        ]:
            self.datatype_cb.addItem(datatype)

    def ok_clicked(self):
        out_file = self._output_raster_path

        if self.input_widget.radio_raster_input.isChecked():
            ret = self.warp_raster(out_file)
        else:
            in_file = self.input_widget.lineEdit_vector_file.text()
            attribute = self.input_widget.comboBox_fieldname.currentText()
            ret = self.rasterize_vector(in_file, out_file, attribute)

        if not ret:
            return False

        layer_name = self.get_layer_name(
            self.tr(f"Land productivity (imported - {self.datatype_cb.currentText()})")
        )
        job = job_manager.create_job_from_dataset(
            dataset_path=Path(out_file),
            band_name=self.datatype_cb.currentText(),
            band_metadata={
                "year_initial": int(self.spinBox_year_initial.text()),
                "year_final": int(self.spinBox_year_final.text()),
            },
            task_name=layer_name,
            task_notes=self.get_task_notes(),
        )
        self.finalize_import(job)


def _get_layers(node):
    layer = []

    if isinstance(node, qgis.core.QgsLayerTreeGroup):
        for child in node.children():
            if isinstance(child, qgis.core.QgsLayerTreeLayer):
                layer.append(child.layer())
            else:
                layer.extend(_get_layers(child))
    else:
        layer = node

    return layer


PROD_MODE_FOR_BAND = {
    ld_conf.FAO_WOCAT_LPD_BAND_NAME: ProductivityMode.FAO_WOCAT_5_CLASS_LPD.value,
    ld_conf.JRC_LPD_BAND_NAME: ProductivityMode.JRC_5_CLASS_LPD.value,
    ld_conf.TE_LPD_BAND_NAME: ProductivityMode.TRENDS_EARTH_5_CLASS_LPD.value,
    ld_conf.CUSTOM_LPD_BAND_NAME: ProductivityMode.CUSTOM_5_CLASS_LPD.value,
    ld_conf.FWV2_LPD_BAND_NAME: ProductivityMode.FWV2_5_CLASS_LPD.value,
}


@functools.lru_cache(
    maxsize=None
)  # not using functools.cache, as it was only introduced in Python 3.9
def _get_usable_bands(
    band_name: typing.Optional[typing.Union[str, typing.Tuple[str, ...]]] = "any",
    selected_job_id: uuid.UUID = None,
    filter_field: str = None,
    filter_value: str = None,
    aoi=None,
    prod_mode=None,
) -> typing.List[Band]:
    result = []

    for job in job_manager.relevant_jobs:
        job: Job
        is_available = job.status in (JobStatus.DOWNLOADED, JobStatus.GENERATED_LOCALLY)
        is_of_interest = (selected_job_id is None) or (job.id == selected_job_id)
        is_valid_type = job.is_raster()

        if not (is_available and is_of_interest and is_valid_type):
            continue

        # Quick bbox pre-filter using cached extent — avoids loading
        # results for jobs outside the selected region.
        if aoi is not None and _cached_extent_overlaps_aoi(job, aoi) is False:
            continue

        # Skip jobs whose bands don't match - without loading the results
        if band_name != "any":
            cached_bands = getattr(job, "_cached_band_names", None)
            if cached_bands is not None:
                if isinstance(band_name, tuple):
                    if not any(b in cached_bands for b in band_name):
                        continue
                else:
                    if band_name not in cached_bands:
                        continue

        # When the caller requests a specific productivity mode, use the
        # cached value to skip non-matching jobs without loading params.
        expected_mode = prod_mode
        if expected_mode is not None:
            cached_pm = getattr(job, "_cached_prod_mode", None)
            if cached_pm is not None:
                # Custom LPD always passes
                if (
                    cached_pm != ProductivityMode.CUSTOM_5_CLASS_LPD.value
                    and cached_pm != expected_mode
                ):
                    continue

        # Load data only after all the pre-filtering
        job_manager.ensure_params_loaded(job)
        job_manager.ensure_results_loaded(job)

        # Full prod_mode check (handles edge cases the cache can't cover)
        params = job.params or {}
        job_mode = None
        if "prod_mode" in params:
            job_mode = params.get("prod_mode")
        elif "productivity" in params:
            job_mode = params.get("productivity", {}).get("mode")

        # For imported datasets, infer productivity mode from band name
        # if not explicitly set in params. This handles backward compatibility
        # with datasets imported before prod_mode was stored in job params.
        # Get the first raster result if available for band info
        raster_result = job.get_first_result_by_type(RasterResults)
        if job_mode is None and raster_result:
            for band_info in raster_result.get_bands():
                if band_info.name in PROD_MODE_FOR_BAND:
                    job_mode = PROD_MODE_FOR_BAND[band_info.name]
                    break

        # Normalize enums to raw values
        if isinstance(job_mode, ProductivityMode):
            job_mode_value = job_mode.value
        else:
            job_mode_value = job_mode

        # Check if productivity mode matches (or if no filtering is needed)
        # Custom LPD datasets are always included when filtering by any
        # productivity mode, since they represent user-imported data that can
        # be used in place of any LPD source
        if expected_mode is None:
            is_valid_prod_mode = True
        elif job_mode_value == ProductivityMode.CUSTOM_5_CLASS_LPD.value:
            is_valid_prod_mode = True
        else:
            is_valid_prod_mode = job_mode_value == expected_mode

        if not is_valid_prod_mode:
            continue

        # Get the first RasterResults from the job (handles both single and list results)
        raster_result = job.get_first_result_by_type(RasterResults)
        if raster_result is None:
            continue

        for band_index, band_info in enumerate(raster_result.get_bands(), start=1):
            if raster_result.uri is None:
                continue
            # Handle band_name as either a string or tuple of strings
            if isinstance(band_name, tuple):
                matches_name = band_info.name in band_name
            else:
                matches_name = band_info.name == band_name or band_name == "any"
            if not matches_name:
                continue
            if aoi is not None and not _check_dataset_overlap_raster(
                aoi, raster_result, job.visible_name, job
            ):
                continue
            if (
                filter_field
                and filter_value
                and band_info.metadata.get(filter_field) != filter_value
            ):
                continue

            result.append(
                Band(
                    job=job,
                    path=raster_result.uri.uri,
                    band_index=band_index,
                    band_info=band_info,
                )
            )

    result.sort(key=lambda ub: ub.job.start_date, reverse=True)
    return result


class WidgetDataIOSelectTELayerBase(QtWidgets.QWidget):
    comboBox_layers: QtWidgets.QComboBox
    layer_list: typing.Optional[typing.List[Band]]

    def set_layer_type(self, layer_type: str):
        self.setProperty("layer_type", layer_type)
        self.populate()

    def set_prod_mode(self, prod_mode: str):
        self.setProperty("prod_mode", prod_mode)

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setupUi(self)

        self.layer_list = None

        self.NO_LAYERS_MESSAGE = _get_no_layers_message()
        self.NO_REGION_MESSAGE = _get_no_region_message()

    def populate(self, selected_job_id=None):
        aoi = try_prepare_area_of_interest()

        if aoi is None:
            # No valid region selected - show message and disable selection
            self.layer_list = []
            self.comboBox_layers.clear()
            self.comboBox_layers.addItem(self.NO_REGION_MESSAGE)
            return

        layer_types = self.property("layer_type").split(";")
        prod_mode = self.property("prod_mode")
        usable_bands = []
        for layer_type in layer_types:
            usable_bands.extend(
                _get_usable_bands(
                    band_name=layer_type,
                    selected_job_id=selected_job_id,
                    filter_field=self.property("layer_filter_field"),
                    filter_value=self.property("layer_filter_value"),
                    aoi=aoi,
                    prod_mode=prod_mode,
                )
            )
        self.layer_list = usable_bands
        old_text = self.currentText()
        self.comboBox_layers.clear()

        if len(usable_bands) == 0:
            self.comboBox_layers.addItem(self.NO_LAYERS_MESSAGE)
        else:
            for i, usable_band in enumerate(usable_bands):
                self.comboBox_layers.addItem(usable_band.get_name_info())
                self.comboBox_layers.setItemData(
                    i, usable_band.get_hover_info(), QtCore.Qt.ToolTipRole
                )
        if not self.set_index_from_text(old_text):
            self.comboBox_layers.setCurrentIndex(0)

    def has_valid_selection(self) -> bool:
        """Check if a valid layer is currently selected.

        Returns False if no region is selected, no layers are available,
        or the current selection is a placeholder message.
        """
        return self.get_validation_status() == LayerValidationStatus.VALID

    def get_validation_status(self) -> "LayerValidationStatus":
        """Get the current validation status of the layer selection.

        Returns:
            LayerValidationStatus indicating why selection is invalid or VALID if OK.
        """
        if not self.layer_list:
            return LayerValidationStatus.NO_REGION
        current_text = self.comboBox_layers.currentText()
        if current_text == self.NO_REGION_MESSAGE:
            return LayerValidationStatus.NO_REGION
        if current_text == self.NO_LAYERS_MESSAGE:
            return LayerValidationStatus.NO_LAYERS
        return LayerValidationStatus.VALID

    def show_validation_error(
        self,
        parent: QtWidgets.QWidget,
        layer_name: str,
        tool_name: str = "this tool",
    ) -> bool:
        """Show an appropriate error message if the layer selection is invalid.

        Args:
            parent: Parent widget for the message box.
            layer_name: Human-readable name for the layer type (e.g., "land cover").
            tool_name: Name of the tool requiring the layer (e.g., "SDG calculation tool").

        Returns:
            True if an error was shown (selection invalid), False if selection is valid.
        """
        status = self.get_validation_status()
        if status == LayerValidationStatus.VALID:
            return False

        if status == LayerValidationStatus.NO_REGION:
            QtWidgets.QMessageBox.critical(
                parent,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    "Please select a region in the Trends.Earth settings "
                    f"before using {tool_name}."
                ),
            )
        else:  # NO_LAYERS
            QtWidgets.QMessageBox.critical(
                parent,
                tr_data_io.tr("Error"),
                tr_data_io.tr(
                    f"You must select a {layer_name} layer "
                    f"before you can use {tool_name}."
                ),
            )
        return True

    def get_current_extent(self):
        band = self.get_current_band()
        if band is None:
            return None

        return qgis.core.QgsRasterLayer(str(band.path), "raster file", "gdal").extent()

    def get_current_data_file(self) -> Path:
        band = self.get_current_band()
        if band is None:
            return None
        return band.path

    def get_layer(self) -> qgis.core.QgsRasterLayer:
        data_file = self.get_current_data_file()
        if data_file is None:
            return None
        return qgis.core.QgsRasterLayer(str(data_file), "raster file", "gdal")

    def get_current_band(self) -> typing.Optional[Band]:
        """Get the currently selected band.

        Returns None if no valid selection exists (no region selected,
        no layers available, or placeholder message selected).
        """
        if not self.has_valid_selection():
            return None
        return self.layer_list[self.comboBox_layers.currentIndex()]

    def set_index_from_job_id(self, job_id):
        if self.layer_list:
            for i in range(len(self.layer_list)):
                if self.layer_list[i].job.id == job_id:
                    self.comboBox_layers.setCurrentIndex(i)

                    return True

        return False

    def set_index_from_text(self, text):
        if self.layer_list:
            for i, layer in enumerate(self.layer_list):
                if text == layer.get_name_info():
                    self.comboBox_layers.setCurrentIndex(i)
                    return True

        return False

    def get_vrt(self):
        band = self.get_current_band()
        if band is None:
            return None
        f = GetTempFilename(".vrt")
        ds = gdal.BuildVRT(f, str(band.path), bandList=[band.band_index])
        if ds is not None:
            ds.FlushCache()
        ds = None

        return f

    def currentText(self):
        return self.comboBox_layers.currentText()


class WidgetDataIOSelectTELayerExisting(
    WidgetDataIOSelectTELayerBase, Ui_WidgetDataIOSelectTELayerExisting
):
    def __init__(self, parent=None):
        super().__init__(parent)


class WidgetDataIOSelectTELayerImport(
    WidgetDataIOSelectTELayerBase, Ui_WidgetDataIOSelectTELayerImport
):
    pass


def _cached_extent_overlaps_aoi(job, aoi) -> typing.Optional[bool]:
    """Quick bbox overlap pre-filter using the cached extent on the job.

    Returns True if the cached extent overlaps the AOI bounding box,
    False if they are disjoint, or None if no cached extent is available
    (caller should fall through to the full check).
    """
    extent = getattr(job, "_cached_extent", None)
    if extent is None or aoi is None:
        return None
    # extent is (west, south, east, north) = (minx, miny, maxx, maxy)
    west, south, east, north = extent
    aoi_rect = aoi.l.extent()
    # Pure arithmetic disjoint check
    if (
        east < aoi_rect.xMinimum()
        or west > aoi_rect.xMaximum()
        or north < aoi_rect.yMinimum()
        or south > aoi_rect.yMaximum()
    ):
        return False
    return True


@functools.lru_cache(
    maxsize=None
)  # not using functools.cache, as it was only introduced in Python 3.9
def _extent_as_geom(extent: typing.Tuple[float, float, float, float]):
    if extent is None:
        return None
    # Validate that extent is a tuple/list with valid numeric values
    try:
        if not extent or len(extent) != 4:
            return None
        # Check for None, NaN, or Inf values in extent
        if any(
            v is None or (isinstance(v, float) and (math.isnan(v) or math.isinf(v)))
            for v in extent
        ):
            return None
        return qgis.core.QgsGeometry.fromRect(qgis.core.QgsRectangle(*extent))
    except (TypeError, ValueError):
        return None


def _check_band_overlap(aoi, raster):
    if raster.type == RasterType.ONE_FILE_RASTER:
        extent_geom = _extent_as_geom(raster.extent)
        if extent_geom is not None and aoi.calc_frac_overlap(extent_geom) >= 0.99:
            return True
    elif raster.type == RasterType.TILED_RASTER:
        # Sum overlap fractions for tiled rasters
        # Note: This can sum to >1.0 if tiles overlap, but ensures coverage check passes
        # even if individual tiles don't fully cover AOI
        frac = 0
        for extent in raster.extents:
            extent_geom = _extent_as_geom(extent)
            if extent_geom is not None:
                frac += aoi.calc_frac_overlap(extent_geom)
        if frac >= 0.99:
            return True
    else:
        return False


def _check_dataset_overlap_raster(aoi, raster_results, dataset_name=None, job=None):
    dataset_label = f" for dataset '{dataset_name}'" if dataset_name else ""
    extents = raster_results.get_extents()

    # Check if we have any extents at all - if missing, try to recalculate them
    if not extents:
        if job is not None:
            from . import jobs

            try:
                jobs.manager.set_results_extents(job, force=True)
                extents = raster_results.get_extents()
            except Exception as e:
                log(
                    f"Failed to recalculate extents{dataset_label}: {type(e).__name__}: {e}"
                )

        if not extents:
            log(
                f"Warning: No valid extents found for raster results{dataset_label}. "
                "This job will be excluded from the dataset dropdown."
            )
            return False

    # Sum overlap fractions across all extents
    # Note: This can sum to >1.0 if extents overlap, which is intentional to ensure
    # jobs pass the filter even if individual extents don't fully cover the AOI
    frac = 0
    valid_extent_count = 0
    for extent in extents:
        extent_geom = _extent_as_geom(extent)
        if extent_geom is not None:
            this_frac = aoi.calc_frac_overlap(extent_geom)
            frac += this_frac
            valid_extent_count += 1

    if valid_extent_count == 0:
        log(
            f"Warning: All {len(extents)} extent(s) resulted in None geometry{dataset_label}. "
            "This may indicate invalid extent values (None, NaN, or Inf)."
        )
        return False

    if frac >= 0.99:
        return True
    else:
        return False


def _check_dataset_overlap_vector(aoi, vector_results):
    "Checks to see if the vector results are NOT disjoint with the aoi"
    extent = vector_results.extent
    log(f"vector extent is {extent}")
    if extent is not None:
        log(f"vector calc_disjoint is {aoi.calc_disjoint(_extent_as_geom(extent))}")
        return not aoi.calc_disjoint(_extent_as_geom(extent))
    else:
        return False


@functools.lru_cache(
    maxsize=None
)  # not using functools.cache, as it was only introduced in Python 3.9
def get_usable_datasets(
    dataset_name: typing.Optional[str] = "any",
    aoi=None,
    productivity_mode: typing.Optional[str] = None,
) -> typing.List[Dataset]:
    result = []

    for job in job_manager.relevant_jobs:
        job: Job
        is_available = job.status in (JobStatus.DOWNLOADED, JobStatus.GENERATED_LOCALLY)
        try:
            # Use cache-aware type checks which work without results loaded
            is_valid_type = job.is_raster() or job.is_vector()
        except AttributeError:
            # Catch case of an invalid type

            continue

        if not (is_available and is_valid_type):
            continue

        if dataset_name != "any":
            script = getattr(job, "script", None)
            if script is not None and hasattr(script, "name"):
                if not _script_name_matches_dataset(script.name, dataset_name):
                    # For vectors, also check vector.type which is matched
                    # differently — we can't exclude here.  Only skip if
                    # the job is purely raster (no vector results possible).
                    if not job.is_vector():
                        continue

        # Quick bbox pre-filter using cached extent — avoids loading
        # heavy results pickle for jobs outside the selected region.
        if aoi is not None and _cached_extent_overlaps_aoi(job, aoi) is False:
            continue

        expected_mode = productivity_mode
        if expected_mode is not None:
            cached_pm = getattr(job, "_cached_prod_mode", None)
            if cached_pm is not None:
                if (
                    cached_pm != ProductivityMode.CUSTOM_5_CLASS_LPD.value
                    and cached_pm != expected_mode
                ):
                    continue

        job_manager.ensure_params_loaded(job)
        job_manager.ensure_results_loaded(job)

        # Full prod_mode check (handles edge cases the cache can't cover)
        params = job.params or {}
        job_mode = None
        if "prod_mode" in params:
            job_mode = params.get("prod_mode")
        elif "productivity" in params:
            job_mode = params.get("productivity", {}).get("mode")

        # For imported datasets, infer productivity mode from band name
        # if not explicitly set in params. This handles backward compatibility
        # with datasets imported before prod_mode was stored in job params.
        # Get the first raster result if available for band info
        raster_result = job.get_first_result_by_type(RasterResults)
        if job_mode is None and raster_result:
            for band_info in raster_result.get_bands():
                if band_info.name in PROD_MODE_FOR_BAND:
                    job_mode = PROD_MODE_FOR_BAND[band_info.name]
                    break

        # Normalize enums to raw values
        if isinstance(job_mode, ProductivityMode):
            job_mode_value = job_mode.value
        else:
            job_mode_value = job_mode

        # Check if productivity mode matches (or if no filtering is needed)
        # Custom LPD datasets are always included when filtering by any
        # productivity mode, since they represent user-imported data that can
        # be used in place of any LPD source
        if expected_mode is None:
            is_valid_prod_mode = True
        elif job_mode_value == ProductivityMode.CUSTOM_5_CLASS_LPD.value:
            is_valid_prod_mode = True
        else:
            is_valid_prod_mode = job_mode_value == expected_mode

        if not is_valid_prod_mode:
            continue

        # Check for raster results
        if raster_result is not None:
            if (
                (
                    aoi is None
                    or _check_dataset_overlap_raster(
                        aoi, raster_result, job.visible_name, job
                    )
                )
                and _script_name_matches_dataset(job.script.name, dataset_name)
                and raster_result.uri is not None
            ):
                result.append(
                    Dataset(
                        job=job,
                        path=raster_result.uri.uri,
                    )
                )

        # Check for vector results
        vector_result = job.get_first_result_by_type(VectorResults)
        if vector_result is not None:
            # Check vector.type for the vector category, or use name for matching
            vector_type_matches = False
            if vector_result.vector is not None:
                vector_type_matches = vector_result.vector.type.value == dataset_name
            elif vector_result.name == dataset_name:
                vector_type_matches = True

            if (
                (aoi is None or _check_dataset_overlap_vector(aoi, vector_result))
                and vector_type_matches
                and vector_result.uri is not None
            ):
                result.append(Dataset(job=job, path=vector_result.uri.uri))
    result.sort(key=lambda ub: ub.job.start_date, reverse=True)

    return result


def invalidate_usable_data_caches(*args, **kwargs):
    """Clear the cached usable dataset/band lookups.

    ``_get_usable_bands`` and ``get_usable_datasets`` scan every local job, so
    their results are memoized. They must be cleared whenever the set of local
    jobs changes (jobs added, removed, downloaded, refreshed, or imported) so
    the dropdowns reflect the new state.

    Accepts and ignores arbitrary arguments so it can be connected directly to
    Qt signals that emit a ``Job`` payload.
    """
    _get_usable_bands.cache_clear()
    get_usable_datasets.cache_clear()


_usable_data_cache_invalidation_connected = False


def _connect_usable_data_cache_invalidation():
    """Connect cache invalidation to job_manager signals (idempotent)."""
    global _usable_data_cache_invalidation_connected
    if _usable_data_cache_invalidation_connected:
        return
    for signal_name in (
        "refreshed_local_state",
        "refreshed_from_remote",
        "downloaded_job_results",
        "deleted_job",
        "imported_job",
        "processed_local_job",
    ):
        signal = getattr(job_manager, signal_name, None)
        if signal is not None:
            try:
                signal.connect(invalidate_usable_data_caches)
            except Exception:  # pragma: no cover - defensive
                pass
    _usable_data_cache_invalidation_connected = True


_connect_usable_data_cache_invalidation()


class DlgDataIOAddLayersToMap(QtWidgets.QDialog, Ui_DlgDataIOAddLayersToMap):
    layers_view: QtWidgets.QListView
    layers_model: QtCore.QStringListModel

    def __init__(self, parent, job):
        super().__init__(parent)
        self.setupUi(self)

        self.layers_model = QtCore.QStringListModel()
        self.layers_view.setModel(self.layers_model)
        self.layers_model.setStringList([])

        self.buttonBox.accepted.connect(self.ok_clicked)
        self.buttonBox.rejected.connect(self.reject)

        self.job = job

        self.layers_model.setStringList([])

        self.update_band_list()

    def ok_clicked(self):
        band_numbers = []

        for i in self.layers_view.selectionModel().selectedRows():
            band_numbers.append(i.row() + 1)  # band numbers start at 1

        if len(band_numbers) > 0:
            job_manager.display_selected_job_results(self.job, band_numbers)
            self.close()

            # QtWidgets.QMessageBox.critical(
            #     None,
            #     tr_data_io.tr("Error"),
            #     tr_data_io.tr(f'Unable to automatically add "{band.name}". '
            #             'No style is defined for this type of layer.')
            # )
        else:
            QtWidgets.QMessageBox.critical(
                None, tr_data_io.tr("Error"), tr_data_io.tr("Select a layer to load.")
            )

    def update_band_list(self):
        # Get bands from the first raster result
        raster_result = self.job.get_first_result_by_type(RasterResults)
        self.layer_list = raster_result.get_bands() if raster_result else []

        band_strings = [
            f"Band {n}: {layers.get_band_title(JobBand.Schema().dump(band))}"
            for n, band in enumerate(self.layer_list, start=1)
        ]
        self.layers_model.setStringList(band_strings)
        self.layers_view.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers)

        for n in range(len(self.layer_list)):
            if self.layer_list[n].add_to_map:
                self.layers_view.selectionModel().select(
                    self.layers_model.createIndex(n, 0),
                    QtCore.QItemSelectionModel.Select,
                )


class WidgetDataIOSelectTEDatasetExisting(
    QtWidgets.QWidget, Ui_WidgetDataIOSelectTEDatasetExisting
):
    comboBox_datasets: QtWidgets.QComboBox
    dataset_list: typing.Optional[typing.List[Dataset]]
    job_selected = QtCore.pyqtSignal(uuid.UUID)

    def __init__(self, parent=None):
        super().__init__(parent)
        self.setupUi(self)

        self.dataset_list = None

        self.comboBox_datasets.currentIndexChanged.connect(self.selected_job_changed)

        self.NO_DATASETS_MESSAGE = _get_no_datasets_message()
        self.NO_REGION_MESSAGE = _get_no_region_message()

    def set_prod_mode(self, prod_mode: str):
        """Set the productivity mode filter and repopulate the dataset list"""
        self.setProperty("productivity_mode", prod_mode)
        self.populate()

    def populate(self):
        aoi = try_prepare_area_of_interest()

        # Handle case where no region is selected
        if aoi is None:
            self.dataset_list = []
            self.comboBox_datasets.currentIndexChanged.disconnect(
                self.selected_job_changed
            )
            self.comboBox_datasets.clear()
            self.comboBox_datasets.addItem(self.NO_REGION_MESSAGE)
            self.comboBox_datasets.setCurrentIndex(0)
            self.comboBox_datasets.currentIndexChanged.connect(
                self.selected_job_changed
            )
            return

        productivity_mode = self.property("productivity_mode")
        usable_datasets = get_usable_datasets(
            self.property("dataset_type"), aoi=aoi, productivity_mode=productivity_mode
        )
        self.dataset_list = usable_datasets
        # Ensure selected_job_changed is called only once when adding items to
        # combobox
        self.comboBox_datasets.currentIndexChanged.disconnect(self.selected_job_changed)
        old_text = self.currentText()
        self.comboBox_datasets.clear()

        if len(usable_datasets) == 0:
            self.comboBox_datasets.addItem(self.NO_DATASETS_MESSAGE)
        else:
            for i, usable_dataset in enumerate(usable_datasets):
                self.comboBox_datasets.addItem(usable_dataset.get_name_info())
                self.comboBox_datasets.setItemData(
                    i, usable_dataset.get_hover_info(), QtCore.Qt.ToolTipRole
                )

        if not self.set_index_from_text(old_text):
            self.comboBox_datasets.setCurrentIndex(0)
        self.selected_job_changed()
        # Reconnect function to fire on selected dataset change
        self.comboBox_datasets.currentIndexChanged.connect(self.selected_job_changed)

    def get_current_data_file(self) -> Path:
        return self.get_current_dataset().path

    def currentText(self):
        return self.comboBox_datasets.currentText()

    def get_current_dataset(self):
        current_dataset = self.dataset_list[self.comboBox_datasets.currentIndex()]
        if current_dataset != self.NO_DATASETS_MESSAGE:
            return current_dataset
        else:
            return None

    def get_current_extent(self):
        job = self.get_current_job()
        if job:
            if job.is_raster():
                band = self.get_bands("any")[0]
                return qgis.core.QgsRasterLayer(
                    str(band.path), "raster file", "gdal"
                ).extent()
            elif job.is_vector():
                rect = qgis.core.QgsVectorLayer(
                    str(self.get_current_data_file()), "vector file", "ogr"
                ).extent()
                return (
                    rect.xMinimum(),
                    rect.yMinimum(),
                    rect.yMaximum(),
                    rect.yMaximum(),
                )

    def get_bands(self, band_name) -> Band:
        aoi = try_prepare_area_of_interest()
        if aoi is None:
            return []

        current_dataset = self.get_current_dataset()
        if current_dataset is None:
            return []

        # Convert list to tuple for lru_cache compatibility
        if isinstance(band_name, list):
            band_name = tuple(band_name)

        return _get_usable_bands(band_name, current_dataset.job.id, aoi=aoi)

    def set_index_from_text(self, text):
        if self.dataset_list:
            for i in range(len(self.dataset_list)):
                if self.dataset_list[i].get_name_info() == text:
                    self.comboBox_datasets.setCurrentIndex(i)

                    return True

        return False

    def get_current_job(self):
        current_dataset = self.get_current_dataset()
        if current_dataset:
            return current_dataset.job
        else:
            return None

    def selected_job_changed(self):
        if len(self.dataset_list) >= 1:
            current_job = self.get_current_job()
            if current_job:
                job_id = current_job.id
            else:
                job_id = None
            self.job_selected.emit(job_id)
