"""
# The core API of TF.

It provides methods to navigate nodes and edges and lookup features.
"""

from .helpers import flattenToSet, console
from .nodes import Nodes
from .locality import Locality
from .nodefeature import NodeFeatures
from .edgefeature import EdgeFeatures
from .computed import Computeds
from .text import Text
from ..search.search import Search

API_REFS = dict(
    AllComputeds=("Computed", "computedall", "computed-data"),
    AllEdges=("Features", "edgeall", "edge-features"),
    AllFeatures=("Features", "nodeall", "node-features"),
    C=("Computed", "computed", "computed-data"),
    Call=("Computed", "computedall", "computed-data"),
    Computed=("Computed", "computed", "computed-data"),
    ComputedString=("Computed", "computedstr", "computed-data"),
    Cs=("Computed", "computedstr", "computed-data"),
    E=("Features", "edge", "edge-features"),
    Eall=("Features", "edgeall", "edge-features"),
    Edge=("Features", "edge", "edge-features"),
    EdgeString=("Features", "edgestr", "edge-features"),
    Es=("Features", "edgestr", "edge-features"),
    F=("Features", "node", "node-features"),
    Fall=("Features", "nodeall", "node-features"),
    Feature=("Features", "node", "node-features"),
    FeatureString=("Features", "nodestr", "node-features"),
    Fs=("Features", "nodestr", "node-features"),
    L=("Locality", "locality", "locality"),
    Locality=("Locality", "locality", "locality"),
    N=("Nodes", "nodes", "navigating-nodes"),
    Nodes=("Nodes", "nodes", "navigating-nodes"),
    S=("Search", "search", "search"),
    Search=("Search", "search", "search"),
    T=("Text", "text", "text"),
    TF=("Fabric", "fabric", "loading"),
    Text=("Text", "text", "text"),
)


class Api(object):
    def __init__(self, TF):
        self.TF = TF
        self.ignored = tuple(sorted(TF.featuresIgnored))
        """Which features were found but ignored.

        Features are ignored if the feature is also present in another location
        that is loaded later.
        """
        TF.ignored = self.ignored

        self.F = NodeFeatures()
        self.Feature = self.F
        self.E = EdgeFeatures()
        self.Edge = self.E
        self.C = Computeds()
        self.Computed = self.C
        tmObj = TF.tmObj
        TF.silentOn = tmObj.silentOn
        TF.silentOff = tmObj.silentOff
        TF.isSilent = tmObj.isSilent
        TF.setSilent = tmObj.setSilent
        TF.info = tmObj.info
        TF.warning = tmObj.warning
        TF.error = tmObj.error
        TF.cache = tmObj.cache
        TF.reset = tmObj.reset
        TF.indent = tmObj.indent
        TF.loadLog = tmObj.cache

        """All messages produced during the feature loading process.

        It also shows the messages that have been suppressed due to the `silent`
        parameter.
        """

        TF.ensureLoaded = self.ensureLoaded
        TF.makeAvailableIn = self.makeAvailableIn

        setattr(self, "FeatureString", self.Fs)
        setattr(self, "EdgeString", self.Es)
        setattr(self, "ComputedString", self.Cs)
        setattr(self, "AllFeatures", self.Fall)
        setattr(self, "AllEdges", self.Eall)
        setattr(self, "AllComputeds", self.Call)

    def Fs(self, fName):
        """Get the node feature sub API.

        If feature name is not a valid python identifier,
        or if you do not know its name in advance,
        you can not use `F.feature`, but you should use
        `Fs(feature)`.
        """

        if not hasattr(self.F, fName):
            self.TF.error(f'Node feature "{fName}" not loaded')
            return None
        return getattr(self.F, fName)

    def Es(self, fName):
        """Get the edge feature sub API.

        If feature name is not a valid python identifier,
        or if you do not know its name in advance,
        you can not use `E.feature`, but you should use
        `Es(feature)`.
        """

        if not hasattr(self.E, fName):
            self.TF.error(f'Edge feature "{fName}" not loaded')
            return None
        return getattr(self.E, fName)

    def Cs(self, fName):
        """Get the computed data sub API.

        If component name is not a valid python identifier,
        or if you do not know its name in advance,
        you can not use `C.component`, but you should use
        `Cs(component)`.
        """

        if not hasattr(self.C, fName):
            self.TF.error(f'Computed feature "{fName}" not loaded')
            return None
        return getattr(self.C, fName)

    def Fall(self):
        """Returns a sorted list of all usable, loaded node feature names.
        """

        return sorted(x[0] for x in self.F.__dict__.items())

    def Eall(self):
        """Returns a sorted list of all usable, loaded edge feature names.
        """

        return sorted(x[0] for x in self.E.__dict__.items())

    def Call(self):
        """Returns a sorted list of all usable, loaded computed data names.
        """

        return sorted(x[0] for x in self.C.__dict__.items())

    def makeAvailableIn(self, scope):
        """Exports members of the API to the global namespace.

        Only the members whose names start with a capital are exported.

        If you are working with a single data source in your program, it is a bit
        tedious to write the initial `TF.api.` or `A.api` all the time.
        By this method you can avoid that.

        !!! explanation "Longer names"
            There are also longer names which can be used as aliases
            to the single capital letters.
            This might or might not improve the readability of your program.

            short name | long name
            --- | ---
            `N` | `Nodes`
            `F` | `Feature`
            `Fs` | `FeatureString`
            `Fall`  `AllFeatures`
            `E` | `Edge`
            `Es` | `EdgeString`
            `Eall`  `AllEdges`
            `C` | `Computed`
            `Cs`  `ComputedString`
            `Call`  `AllComputeds`
            `L` | `Locality`
            `T` | `Text`
            `S` | `Search`

        Parameters
        ----------
        scope: dict
            A dictionary into which the members of the core API will be inserted.
            The only sensible choice is: `globals()`.

        Returns
        -------
        tuple
            A grouped list of API members that has been hoisted to the global
            scope.

        Notes
        -----
        !!! explanation "Why pass `globals()`?"
            Although we know it should always be `globals()`, we cannot
            define a function that looks into the `globals()` of its caller.
            So we have to pass it on.
        """

        for member in dir(self):
            if "_" not in member and member[0].isupper():
                scope[member] = getattr(self, member)
                if member not in API_REFS:
                    console(f'WARNING: API member "{member}" not documented')

        grouped = {}
        for (member, (head, sub, ref)) in API_REFS.items():
            grouped.setdefault(ref, {}).setdefault((head, sub), []).append(member)

        # grouped
        # node-features=>(Features, node)=>[F, ...]

        docs = []
        for (ref, groups) in sorted(grouped.items()):
            chunks = []
            for ((head, sub), members) in sorted(groups.items()):
                chunks.append(" ".join(sorted(members, key=lambda x: (len(x), x))))
            docs.append((head, ref, tuple(chunks)))
        return docs

    # docs
    # (Features, node-features, ('F ...', ...))

    def ensureLoaded(self, features):
        """Checks if features are loaded and if not loads them.

        All features in question will be made available to the core API.

        Parameters
        ----------
        features: string | iterable of strings
            It is a string containing space separated feature names,
            or an iterable of feature names.
            The feature names are just the names of `.tf` files
            without directory information and without extension.

        Returns
        -------
        set
            The names of the features in question as a set of strings.
        """

        F = self.F
        E = self.E
        TF = self.TF
        warning = TF.warning

        needToLoad = set()
        loadedFeatures = set()

        for fName in sorted(flattenToSet(features)):
            fObj = TF.features.get(fName, None)
            if not fObj:
                warning(f'Cannot load feature "{fName}": not in dataset')
                continue
            if fObj.dataLoaded and (hasattr(F, fName) or hasattr(E, fName)):
                loadedFeatures.add(fName)
            else:
                needToLoad.add(fName)
        if len(needToLoad):
            TF.load(
                needToLoad, add=True, silent="deep",
            )
            loadedFeatures |= needToLoad
        return loadedFeatures


def addOtype(api):
    setattr(api.F.otype, "all", tuple(o[0] for o in api.C.levels.data))
    setattr(
        api.F.otype, "support", dict(((o[0], (o[2], o[3])) for o in api.C.levels.data))
    )


def addLocality(api):
    api.L = Locality(api)
    api.Locality = api.L


def addNodes(api):
    api.N = Nodes(api)
    api.Nodes = api.N


def addText(api):
    api.T = Text(api)
    api.Text = api.T


def addSearch(api, silent):
    api.S = Search(api, silent)
    api.Search = api.S