"""
# Fabric

The main class that works the core API is `tf.fabric.Fabric`.

It is responsible for feature data loading and saving.

!!! note "Tutorial"
    The tutorials for specific annotated corpora (see `tf.about.corpora`)
    put the Text-Fabric API on show for vastly different corpora.

!!! note "Generic API versus apps"
    This is the API of Text-Fabric in general.
    Text-Fabric has no baked in knowledge of particular corpora.

    However, Text-Fabric comes with several *apps* that make working
    with specific `tf.about.corpora` easier.
    Such an app may be as simple as a *config.yaml* file, even an empty one.
    The extra functions of those apps
    are available through the advanced API: `A`, see `tf.app`.

Fabric has built-in volume support: it can load volumes of a work and it can
collect volumes into a new work.

Fabric is an extension of `tf.core.fabric` where volume support is added.
"""

import os

from .parameters import LOCATIONS, LOCAL, OTYPE
from .core.helpers import itemize, setDir, expandDir, normpath, unexpanduser as ux
from .core.fabric import FabricCore
from .core.timestamp import Timestamp, SILENT_D, silentConvert
from .volumes import extract, collect, getVolumes


class Fabric(FabricCore):
    """Initialize the core API for a corpus.

    !!! note "Implementation"
        Fabric is implemented as a subclass of `tf.core.fabric.FabricCore`

    See `tf.core.fabric.FabricCore for most of the functionality.
    Here we document the volume support only.

    Parameters
    ----------
    collection: string, optional `None`
        If the collection exists, it will be loaded instead of the whole corpus.
        If the collection does not exist an error will be generated.

    volume: string, optional `None`
        If the volume exists, it will be loaded instead of the whole corpus.
        If the volume does not exist an error will be generated.

    When determining whether the volume exists, only the first members of `locations`
    and `modules` will be used.
    There the volumes reside under a directory `_local`.
    You may want to add `_local` to your `.gitignore`, so that volumes generated
    in a backend directory will not be pushed.

    !!! caution "Volumes and collections"
        It is an error to load a volume as a collection and vice-versa

        You get a warning if you pass both a volume and a collection.
        The collection takes precedence, and the volume is ignored in that case.
    """

    def __init__(
        self,
        locations=None,
        modules=None,
        silent=SILENT_D,
        volume=None,
        collection=None,
        **kwargs,
    ):

        if modules is None:
            module = [""]
        elif type(modules) is str:
            module = [normpath(x.strip()) for x in itemize(modules, "\n")]
        else:
            module = [normpath(str(x)) for x in modules]
        module = module[0] if module else ""
        module = module.strip("/")

        if locations is None:
            location = LOCATIONS if LOCATIONS else [""]
        elif type(locations) is str:
            location = [normpath(x.strip()) for x in itemize(locations, "\n")]
        else:
            location = [normpath(str(x)) for x in locations]
        location = location[0] if location else ""
        location = location.rstrip("/")

        setDir(self)
        location = expandDir(self, location)
        sep = "/" if location and module else ""

        location = f"{location}{sep}{module}"
        sep = "/" if location else ""
        volumeBase = f"{location}{sep}{LOCAL}"
        collectionBase = f"{location}{sep}{LOCAL}"

        TM = Timestamp(silent=silent)

        if collection:
            collectionLoc = f"{collectionBase}/{collection}"
            self.collectionLoc = collectionLoc
            locations = collectionLoc
            modules = [""]
            if not os.path.exists(locations):
                TM = Timestamp(silent=silent)
                TM.error(
                    f"Collection {collection} not found under {ux(collectionLoc)}"
                )
        elif volume:
            volumeLoc = f"{volumeBase}/{volume}"
            self.volumeLoc = volumeLoc
            locations = volumeLoc
            modules = [""]
            if not os.path.exists(locations):
                TM.error(f"Volume {volume} not found under {ux(volumeLoc)}")

        if collection and volume:
            TM.warning(
                f"Both collection={collection} and volume={volume} specified.", tm=False
            )
            TM.warning("Ignoring the volume", tm=False)

        super().__init__(locations=locations, modules=modules, silent=silent, **kwargs)
        self.volumeBase = volumeBase
        self.collectionBase = collectionBase
        self.collection = collection
        self.volume = None if collection else volume

    def _makeApi(self):
        api = super()._makeApi()

        if self.collection:
            self.collectionInfo = self.features[OTYPE].metaData.get("collection", None)
            if self.collectionInfo is None:
                self.error("This is not a collection!")
                self.good = False
                return None

        elif self.volume:
            self.volumeInfo = self.features[OTYPE].metaData.get("volume", None)
            if self.volumeInfo is None:
                self.error("This is not a volume!")
                self.good = False
                return None
        return api

    def getVolumes(self):
        """Lists available volumes within the dataset.

        See `tf.volumes.extract.getVolumes`.
        """

        volumeBase = self.volumeBase
        return getVolumes(volumeBase)

    def extract(self, volumes=True, byTitle=True, silent=SILENT_D, overwrite=None, show=False):
        """Extract volumes from the currently loaded work.

        This function is only provided if the dataset is a work,
        i.e. it is loaded as a whole.
        When a single volume of a work is loaded, there is no `extract` method.

        See `tf.volumes.extract` and note that parameters
        `workLocation`, `volumesLocation`, `api`
        will be supplied automatically.
        """

        silent = silentConvert(silent)
        volume = self.volume
        volumeBase = self.volumeBase
        api = self.api

        if volume:
            self.error("Cannot extract volumes from a single volume of a work")
            return

        return extract(
            None,
            volumeBase,
            volumes=volumes,
            byTitle=byTitle,
            silent=silent,
            api=api,
            overwrite=overwrite,
            checkOnly=False,
            show=show,
        )

    def collect(
        self,
        volumes,
        collection,
        volumeType=None,
        volumeFeature=None,
        mergeTypes=None,
        featureMeta=None,
        silent=SILENT_D,
        overwrite=None,
    ):
        """Creates a work out of a number of volumes.

        Parameters
        ----------

        volumes: tuple
            Just the names of the volumes that you want to collect.

        collection: string
            The name of the new collection

        See `tf.volumes.collect` for the other parameters and note that parameter
        `workLocation` will be supplied automatically from `collection`.
        """

        volumeBase = self.volumeBase

        return collect(
            tuple(f"{volumeBase}/{name}" for name in volumes),
            f"{volumeBase}/{collection}",
            volumeType=volumeType,
            volumeFeature=volumeFeature,
            mergeTypes=mergeTypes,
            featureMeta=featureMeta,
            silent=silent,
            overwrite=overwrite,
        )