import sqlite3

import numpy as np
from sqlalchemy import create_engine

from pandas import (
    DataFrame,
    date_range,
    read_sql_query,
    read_sql_table,
)

from ..pandas_vb_common import tm


class SQL:
    params = ["sqlalchemy", "sqlite"]
    param_names = ["connection"]

    def setup(self, connection):
        N = 10000
        con = {
            "sqlalchemy": create_engine("sqlite:///:memory:"),
            "sqlite": sqlite3.connect(":memory:"),
        }
        self.table_name = "test_type"
        self.query_all = f"SELECT * FROM {self.table_name}"
        self.con = con[connection]
        self.df = DataFrame(
            {
                "float": np.random.randn(N),
                "float_with_nan": np.random.randn(N),
                "string": ["foo"] * N,
                "bool": [True] * N,
                "int": np.random.randint(0, N, size=N),
                "datetime": date_range("2000-01-01", periods=N, freq="s"),
            },
            index=tm.makeStringIndex(N),
        )
        self.df.iloc[1000:3000, 1] = np.nan
        self.df["date"] = self.df["datetime"].dt.date
        self.df["time"] = self.df["datetime"].dt.time
        self.df["datetime_string"] = self.df["datetime"].astype(str)
        self.df.to_sql(self.table_name, self.con, if_exists="replace")

    def time_to_sql_dataframe(self, connection):
        self.df.to_sql("test1", self.con, if_exists="replace")

    def time_read_sql_query(self, connection):
        read_sql_query(self.query_all, self.con)


class WriteSQLDtypes:
    params = (
        ["sqlalchemy", "sqlite"],
        [
            "float",
            "float_with_nan",
            "string",
            "bool",
            "int",
            "date",
            "time",
            "datetime",
        ],
    )
    param_names = ["connection", "dtype"]

    def setup(self, connection, dtype):
        N = 10000
        con = {
            "sqlalchemy": create_engine("sqlite:///:memory:"),
            "sqlite": sqlite3.connect(":memory:"),
        }
        self.table_name = "test_type"
        self.query_col = f"SELECT {dtype} FROM {self.table_name}"
        self.con = con[connection]
        self.df = DataFrame(
            {
                "float": np.random.randn(N),
                "float_with_nan": np.random.randn(N),
                "string": ["foo"] * N,
                "bool": [True] * N,
                "int": np.random.randint(0, N, size=N),
                "datetime": date_range("2000-01-01", periods=N, freq="s"),
            },
            index=tm.makeStringIndex(N),
        )
        self.df.iloc[1000:3000, 1] = np.nan
        self.df["date"] = self.df["datetime"].dt.date
        self.df["time"] = self.df["datetime"].dt.time
        self.df["datetime_string"] = self.df["datetime"].astype(str)
        self.df.to_sql(self.table_name, self.con, if_exists="replace")

    def time_to_sql_dataframe_column(self, connection, dtype):
        self.df[[dtype]].to_sql("test1", self.con, if_exists="replace")

    def time_read_sql_query_select_column(self, connection, dtype):
        read_sql_query(self.query_col, self.con)


class ReadSQLTable:
    def setup(self):
        N = 10000
        self.table_name = "test"
        self.con = create_engine("sqlite:///:memory:")
        self.df = DataFrame(
            {
                "float": np.random.randn(N),
                "float_with_nan": np.random.randn(N),
                "string": ["foo"] * N,
                "bool": [True] * N,
                "int": np.random.randint(0, N, size=N),
                "datetime": date_range("2000-01-01", periods=N, freq="s"),
            },
            index=tm.makeStringIndex(N),
        )
        self.df.iloc[1000:3000, 1] = np.nan
        self.df["date"] = self.df["datetime"].dt.date
        self.df["time"] = self.df["datetime"].dt.time
        self.df["datetime_string"] = self.df["datetime"].astype(str)
        self.df.to_sql(self.table_name, self.con, if_exists="replace")

    def time_read_sql_table_all(self):
        read_sql_table(self.table_name, self.con)

    def time_read_sql_table_parse_dates(self):
        read_sql_table(
            self.table_name,
            self.con,
            columns=["datetime_string"],
            parse_dates=["datetime_string"],
        )


class ReadSQLTableDtypes:
    params = [
        "float",
        "float_with_nan",
        "string",
        "bool",
        "int",
        "date",
        "time",
        "datetime",
    ]
    param_names = ["dtype"]

    def setup(self, dtype):
        N = 10000
        self.table_name = "test"
        self.con = create_engine("sqlite:///:memory:")
        self.df = DataFrame(
            {
                "float": np.random.randn(N),
                "float_with_nan": np.random.randn(N),
                "string": ["foo"] * N,
                "bool": [True] * N,
                "int": np.random.randint(0, N, size=N),
                "datetime": date_range("2000-01-01", periods=N, freq="s"),
            },
            index=tm.makeStringIndex(N),
        )
        self.df.iloc[1000:3000, 1] = np.nan
        self.df["date"] = self.df["datetime"].dt.date
        self.df["time"] = self.df["datetime"].dt.time
        self.df["datetime_string"] = self.df["datetime"].astype(str)
        self.df.to_sql(self.table_name, self.con, if_exists="replace")

    def time_read_sql_table_column(self, dtype):
        read_sql_table(self.table_name, self.con, columns=[dtype])


from ..pandas_vb_common import setup  # noqa: F401 isort:skip
