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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.loc[1000:3000, "float_with_nan"] = np.nan
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", "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.loc[1000:3000, "float_with_nan"] = np.nan
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.loc[1000:3000, "float_with_nan"] = np.nan
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", "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.loc[1000:3000, "float_with_nan"] = np.nan
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
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