"""Database and utility functions for phenotypes."""
from typing import Optional
from functools import reduce
from datetime import datetime

import MySQLdb as mdb
from MySQLdb.cursors import Cursor, DictCursor
from flask import current_app as app

from gn_libs.mysqldb import debug_query

def datasets_by_population(
        conn: mdb.Connection,
        species_id: int,
        population_id: int
) -> tuple[dict, ...]:
    """Retrieve all of a population's phenotype studies."""
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            "SELECT s.SpeciesId, pf.* FROM Species AS s "
            "INNER JOIN InbredSet AS iset ON s.Id=iset.SpeciesId "
            "INNER JOIN PublishFreeze AS pf ON iset.Id=pf.InbredSetId "
            "WHERE s.Id=%s AND iset.Id=%s;",
                       (species_id, population_id))
        return tuple(dict(row) for row in cursor.fetchall())


def dataset_by_id(conn: mdb.Connection,
                  species_id: int,
                  population_id: int,
                  dataset_id: int) -> dict:
    """Fetch dataset details by identifier"""
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            "SELECT s.SpeciesId, pf.* FROM Species AS s "
            "INNER JOIN InbredSet AS iset ON s.Id=iset.SpeciesId "
            "INNER JOIN PublishFreeze AS pf ON iset.Id=pf.InbredSetId "
            "WHERE s.Id=%s AND iset.Id=%s AND pf.Id=%s",
            (species_id, population_id, dataset_id))
        return dict(cursor.fetchone())


def phenotypes_count(conn: mdb.Connection,
                     population_id: int,
                     dataset_id: int) -> int:
    """Count the number of phenotypes in the dataset."""
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            "SELECT COUNT(*) AS total_phenos FROM Phenotype AS pheno "
            "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId "
            "INNER JOIN PublishFreeze AS pf ON pxr.InbredSetId=pf.InbredSetId "
            "WHERE pxr.InbredSetId=%s AND pf.Id=%s",
        (population_id, dataset_id))
        return int(cursor.fetchone()["total_phenos"])


def phenotype_publication_data(conn, phenotype_id) -> Optional[dict]:
    """Retrieve the publication data for a phenotype if it exists."""
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(
            "SELECT DISTINCT pxr.PhenotypeId, pub.* FROM PublishXRef AS pxr "
            "INNER JOIN Publication as pub ON pxr.PublicationId=pub.Id "
            "WHERE pxr.PhenotypeId=%s",
            (phenotype_id,))
        res = cursor.fetchone()
        if res is None:
            return res
        return dict(res)


def dataset_phenotypes(conn: mdb.Connection,
                       population_id: int,
                       dataset_id: int,
                       offset: int = 0,
                       limit: Optional[int] = None) -> tuple[dict, ...]:
    """Fetch the actual phenotypes."""
    _query = (
        "SELECT pheno.*, pxr.Id AS xref_id, ist.InbredSetCode FROM Phenotype AS pheno "
        "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId "
        "INNER JOIN PublishFreeze AS pf ON pxr.InbredSetId=pf.InbredSetId "
        "INNER JOIN InbredSet AS ist ON pf.InbredSetId=ist.Id "
        "WHERE pxr.InbredSetId=%s AND pf.Id=%s") + (
            f" LIMIT {limit} OFFSET {offset}" if bool(limit) else "")
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(_query, (population_id, dataset_id))
        debug_query(cursor, app.logger)
        return tuple(dict(row) for row in cursor.fetchall())


def __phenotype_se__(cursor: Cursor, xref_id, dataids_and_strainids):
    """Fetch standard-error values (if they exist) for a phenotype."""
    paramstr = ", ".join(["(%s, %s)"] * len(dataids_and_strainids))
    flat = tuple(item for sublist in dataids_and_strainids for item in sublist)
    cursor.execute("SELECT * FROM PublishSE WHERE (DataId, StrainId) IN "
                   f"({paramstr})",
                   flat)
    debug_query(cursor, app.logger)
    _se = {
        (row["DataId"], row["StrainId"]): {
            "DataId": row["DataId"],
            "StrainId": row["StrainId"],
            "error": row["error"]
        }
        for row in cursor.fetchall()
    }

    cursor.execute("SELECT * FROM NStrain WHERE (DataId, StrainId) IN "
                   f"({paramstr})",
                   flat)
    debug_query(cursor, app.logger)
    _n = {
        (row["DataId"], row["StrainId"]): {
            "DataId": row["DataId"],
            "StrainId": row["StrainId"],
            "count": row["count"]
        }
        for row in cursor.fetchall()
    }

    keys = set(tuple(_se.keys()) + tuple(_n.keys()))
    return {
        key: {"xref_id": xref_id, **_se.get(key,{}), **_n.get(key,{})}
        for key in keys
    }

def __organise_by_phenotype__(pheno, row):
    """Organise disparate data rows into phenotype 'objects'."""
    _pheno = pheno.get(row["Id"])
    return {
        **pheno,
        row["Id"]: {
            "Id": row["Id"],
            "Pre_publication_description": row["Pre_publication_description"],
            "Post_publication_description": row["Post_publication_description"],
            "Original_description": row["Original_description"],
            "Units": row["Units"],
            "Pre_publication_abbreviation": row["Pre_publication_abbreviation"],
            "Post_publication_abbreviation": row["Post_publication_abbreviation"],
            "xref_id": row["pxr.Id"],
            "data": {
                **(_pheno["data"] if bool(_pheno) else {}),
                (row["DataId"], row["StrainId"]): {
                    "DataId": row["DataId"],
                    "StrainId": row["StrainId"],
                    "mean": row["mean"],
                    "Locus": row["Locus"],
                    "LRS": row["LRS"],
                    "additive": row["additive"],
                    "Sequence": row["Sequence"],
                    "comments": row["comments"],
                    "value": row["value"],
                    "StrainName": row["Name"],
                    "StrainName2": row["Name2"],
                    "StrainSymbol": row["Symbol"],
                    "StrainAlias": row["Alias"]
                }
            }
        }
    }


def __merge_pheno_data_and_se__(data, sedata) -> dict:
    """Merge phenotype data with the standard errors."""
    return {
        key: {**value, **sedata.get(key, {})}
        for key, value in data.items()
    }


def phenotype_by_id(
        conn: mdb.Connection,
        species_id: int,
        population_id: int,
        dataset_id: int,
        xref_id
) -> Optional[dict]:
    """Fetch a specific phenotype."""
    _dataquery = ("SELECT pheno.*, pxr.*, pd.*, str.*, iset.InbredSetCode "
                  "FROM Phenotype AS pheno "
                  "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId "
                  "INNER JOIN PublishData AS pd ON pxr.DataId=pd.Id "
                  "INNER JOIN Strain AS str ON pd.StrainId=str.Id "
                  "INNER JOIN StrainXRef AS sxr ON str.Id=sxr.StrainId "
                  "INNER JOIN PublishFreeze AS pf ON sxr.InbredSetId=pf.InbredSetId "
                  "INNER JOIN InbredSet AS iset ON pf.InbredSetId=iset.InbredSetId "
                  "WHERE "
                  "(str.SpeciesId, pxr.InbredSetId, pf.Id, pxr.Id)=(%s, %s, %s, %s)")
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(_dataquery,
                       (species_id, population_id, dataset_id, xref_id))
        _pheno: dict = reduce(__organise_by_phenotype__, cursor.fetchall(), {})
        if bool(_pheno) and len(_pheno.keys()) == 1:
            _pheno = tuple(_pheno.values())[0]
            return {
                **_pheno,
                "data": tuple(__merge_pheno_data_and_se__(
                    _pheno["data"],
                    __phenotype_se__(
                        cursor, xref_id, tuple(_pheno["data"].keys()))
                ).values())
            }
        if bool(_pheno) and len(_pheno.keys()) > 1:
            raise Exception(
                "We found more than one phenotype with the same identifier!")

    return None


def phenotypes_data(conn: mdb.Connection,
                    population_id: int,
                    dataset_id: int,
                    offset: int = 0,
                    limit: Optional[int] = None) -> tuple[dict, ...]:
    """Fetch the data for the phenotypes."""
    # — Phenotype -> PublishXRef -> PublishData -> Strain -> StrainXRef -> PublishFreeze
    _query = ("SELECT pheno.*, pxr.*, pd.*, str.*, iset.InbredSetCode "
              "FROM Phenotype AS pheno "
              "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId "
              "INNER JOIN PublishData AS pd ON pxr.DataId=pd.Id "
              "INNER JOIN Strain AS str ON pd.StrainId=str.Id "
              "INNER JOIN StrainXRef AS sxr ON str.Id=sxr.StrainId "
              "INNER JOIN PublishFreeze AS pf ON sxr.InbredSetId=pf.InbredSetId "
              "INNER JOIN InbredSet AS iset ON pf.InbredSetId=iset.InbredSetId "
              "WHERE pxr.InbredSetId=%s AND pf.Id=%s") + (
                  f" LIMIT {limit} OFFSET {offset}" if bool(limit) else "")
    with conn.cursor(cursorclass=DictCursor) as cursor:
        cursor.execute(_query, (population_id, dataset_id))
        debug_query(cursor, app.logger)
        return tuple(dict(row) for row in cursor.fetchall())


def save_new_dataset(cursor: Cursor,
                     population_id: int,
                     dataset_name: str,
                     dataset_fullname: str,
                     dataset_shortname: str) -> dict:
    """Create a new phenotype dataset."""
    params = {
        "population_id": population_id,
        "dataset_name": dataset_name,
        "dataset_fullname": dataset_fullname,
        "dataset_shortname": dataset_shortname,
        "created": datetime.now().date().isoformat(),
        "public": 2,
        "confidentiality": 0,
        "users": None
    }
    cursor.execute(
        "INSERT INTO PublishFreeze(Name, FullName, ShortName, CreateTime, "
        "public, InbredSetId, confidentiality, AuthorisedUsers) "
        "VALUES(%(dataset_name)s, %(dataset_fullname)s, %(dataset_shortname)s, "
        "%(created)s, %(public)s, %(population_id)s, %(confidentiality)s, "
        "%(users)s)",
        params)
    debug_query(cursor, app.logger)
    return {**params, "Id": cursor.lastrowid}