Python sqlalchemy.sql.sqltypes.Float() Examples

The following are 15 code examples of sqlalchemy.sql.sqltypes.Float(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module sqlalchemy.sql.sqltypes , or try the search function .
Example #1
Source File: test_sql.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_notna_dtype(self):
        if self.flavor == 'mysql':
            pytest.skip('Not applicable to MySQL legacy')

        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)

        assert self._get_sqlite_column_type(tbl, 'Bool') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Date') == 'TIMESTAMP'
        assert self._get_sqlite_column_type(tbl, 'Int') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Float') == 'REAL'
Example #2
Source File: test_sql.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_notna_dtype(self):
        if self.flavor == 'mysql':
            pytest.skip('Not applicable to MySQL legacy')

        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)

        assert self._get_sqlite_column_type(tbl, 'Bool') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Date') == 'TIMESTAMP'
        assert self._get_sqlite_column_type(tbl, 'Int') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Float') == 'REAL'
Example #3
Source File: test_sql.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_notna_dtype(self):
        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)
        returned_df = sql.read_sql_table(tbl, self.conn)  # noqa
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        if self.flavor == 'mysql':
            my_type = sqltypes.Integer
        else:
            my_type = sqltypes.Boolean

        col_dict = meta.tables[tbl].columns

        assert isinstance(col_dict['Bool'].type, my_type)
        assert isinstance(col_dict['Date'].type, sqltypes.DateTime)
        assert isinstance(col_dict['Int'].type, sqltypes.Integer)
        assert isinstance(col_dict['Float'].type, sqltypes.Float)
Example #4
Source File: test_sql.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_notna_dtype(self):
        if self.flavor == 'mysql':
            pytest.skip('Not applicable to MySQL legacy')

        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)

        assert self._get_sqlite_column_type(tbl, 'Bool') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Date') == 'TIMESTAMP'
        assert self._get_sqlite_column_type(tbl, 'Int') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Float') == 'REAL'
Example #5
Source File: test_sql.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_notna_dtype(self):
        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)
        returned_df = sql.read_sql_table(tbl, self.conn)  # noqa
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        if self.flavor == 'mysql':
            my_type = sqltypes.Integer
        else:
            my_type = sqltypes.Boolean

        col_dict = meta.tables[tbl].columns

        assert isinstance(col_dict['Bool'].type, my_type)
        assert isinstance(col_dict['Date'].type, sqltypes.DateTime)
        assert isinstance(col_dict['Int'].type, sqltypes.Integer)
        assert isinstance(col_dict['Float'].type, sqltypes.Float)
Example #6
Source File: test_sql.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_notna_dtype(self):
        if self.flavor == 'mysql':
            pytest.skip('Not applicable to MySQL legacy')

        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)

        assert self._get_sqlite_column_type(tbl, 'Bool') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Date') == 'TIMESTAMP'
        assert self._get_sqlite_column_type(tbl, 'Int') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Float') == 'REAL'
Example #7
Source File: test_sql.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def test_notna_dtype(self):
        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)
        returned_df = sql.read_sql_table(tbl, self.conn)  # noqa
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        if self.flavor == 'mysql':
            my_type = sqltypes.Integer
        else:
            my_type = sqltypes.Boolean

        col_dict = meta.tables[tbl].columns

        assert isinstance(col_dict['Bool'].type, my_type)
        assert isinstance(col_dict['Date'].type, sqltypes.DateTime)
        assert isinstance(col_dict['Int'].type, sqltypes.Integer)
        assert isinstance(col_dict['Float'].type, sqltypes.Float)
Example #8
Source File: test_sql.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def test_notna_dtype(self):
        if self.flavor == 'mysql':
            pytest.skip('Not applicable to MySQL legacy')

        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)

        assert self._get_sqlite_column_type(tbl, 'Bool') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Date') == 'TIMESTAMP'
        assert self._get_sqlite_column_type(tbl, 'Int') == 'INTEGER'
        assert self._get_sqlite_column_type(tbl, 'Float') == 'REAL'
Example #9
Source File: test_sql.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_notna_dtype(self):
        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)
        returned_df = sql.read_sql_table(tbl, self.conn)  # noqa
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        if self.flavor == 'mysql':
            my_type = sqltypes.Integer
        else:
            my_type = sqltypes.Boolean

        col_dict = meta.tables[tbl].columns

        assert isinstance(col_dict['Bool'].type, my_type)
        assert isinstance(col_dict['Date'].type, sqltypes.DateTime)
        assert isinstance(col_dict['Int'].type, sqltypes.Integer)
        assert isinstance(col_dict['Float'].type, sqltypes.Float)
Example #10
Source File: test_sql.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_notna_dtype(self):
        cols = {'Bool': Series([True, None]),
                'Date': Series([datetime(2012, 5, 1), None]),
                'Int': Series([1, None], dtype='object'),
                'Float': Series([1.1, None])
                }
        df = DataFrame(cols)

        tbl = 'notna_dtype_test'
        df.to_sql(tbl, self.conn)
        returned_df = sql.read_sql_table(tbl, self.conn)  # noqa
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        if self.flavor == 'mysql':
            my_type = sqltypes.Integer
        else:
            my_type = sqltypes.Boolean

        col_dict = meta.tables[tbl].columns

        assert isinstance(col_dict['Bool'].type, my_type)
        assert isinstance(col_dict['Date'].type, sqltypes.DateTime)
        assert isinstance(col_dict['Int'].type, sqltypes.Integer)
        assert isinstance(col_dict['Float'].type, sqltypes.Float)
Example #11
Source File: test_sql.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_double_precision(self):
        V = 1.23456789101112131415

        df = DataFrame({'f32': Series([V, ], dtype='float32'),
                        'f64': Series([V, ], dtype='float64'),
                        'f64_as_f32': Series([V, ], dtype='float64'),
                        'i32': Series([5, ], dtype='int32'),
                        'i64': Series([5, ], dtype='int64'),
                        })

        df.to_sql('test_dtypes', self.conn, index=False, if_exists='replace',
                  dtype={'f64_as_f32': sqlalchemy.Float(precision=23)})
        res = sql.read_sql_table('test_dtypes', self.conn)

        # check precision of float64
        assert (np.round(df['f64'].iloc[0], 14) ==
                np.round(res['f64'].iloc[0], 14))

        # check sql types
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        col_dict = meta.tables['test_dtypes'].columns
        assert str(col_dict['f32'].type) == str(col_dict['f64_as_f32'].type)
        assert isinstance(col_dict['f32'].type, sqltypes.Float)
        assert isinstance(col_dict['f64'].type, sqltypes.Float)
        assert isinstance(col_dict['i32'].type, sqltypes.Integer)
        assert isinstance(col_dict['i64'].type, sqltypes.BigInteger)
Example #12
Source File: test_sql.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_double_precision(self):
        V = 1.23456789101112131415

        df = DataFrame({'f32': Series([V, ], dtype='float32'),
                        'f64': Series([V, ], dtype='float64'),
                        'f64_as_f32': Series([V, ], dtype='float64'),
                        'i32': Series([5, ], dtype='int32'),
                        'i64': Series([5, ], dtype='int64'),
                        })

        df.to_sql('test_dtypes', self.conn, index=False, if_exists='replace',
                  dtype={'f64_as_f32': sqlalchemy.Float(precision=23)})
        res = sql.read_sql_table('test_dtypes', self.conn)

        # check precision of float64
        assert (np.round(df['f64'].iloc[0], 14) ==
                np.round(res['f64'].iloc[0], 14))

        # check sql types
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        col_dict = meta.tables['test_dtypes'].columns
        assert str(col_dict['f32'].type) == str(col_dict['f64_as_f32'].type)
        assert isinstance(col_dict['f32'].type, sqltypes.Float)
        assert isinstance(col_dict['f64'].type, sqltypes.Float)
        assert isinstance(col_dict['i32'].type, sqltypes.Integer)
        assert isinstance(col_dict['i64'].type, sqltypes.BigInteger)
Example #13
Source File: test_sql.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_double_precision(self):
        V = 1.23456789101112131415

        df = DataFrame({'f32': Series([V, ], dtype='float32'),
                        'f64': Series([V, ], dtype='float64'),
                        'f64_as_f32': Series([V, ], dtype='float64'),
                        'i32': Series([5, ], dtype='int32'),
                        'i64': Series([5, ], dtype='int64'),
                        })

        df.to_sql('test_dtypes', self.conn, index=False, if_exists='replace',
                  dtype={'f64_as_f32': sqlalchemy.Float(precision=23)})
        res = sql.read_sql_table('test_dtypes', self.conn)

        # check precision of float64
        assert (np.round(df['f64'].iloc[0], 14) ==
                np.round(res['f64'].iloc[0], 14))

        # check sql types
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        col_dict = meta.tables['test_dtypes'].columns
        assert str(col_dict['f32'].type) == str(col_dict['f64_as_f32'].type)
        assert isinstance(col_dict['f32'].type, sqltypes.Float)
        assert isinstance(col_dict['f64'].type, sqltypes.Float)
        assert isinstance(col_dict['i32'].type, sqltypes.Integer)
        assert isinstance(col_dict['i64'].type, sqltypes.BigInteger)
Example #14
Source File: test_sql.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_double_precision(self):
        V = 1.23456789101112131415

        df = DataFrame({'f32': Series([V, ], dtype='float32'),
                        'f64': Series([V, ], dtype='float64'),
                        'f64_as_f32': Series([V, ], dtype='float64'),
                        'i32': Series([5, ], dtype='int32'),
                        'i64': Series([5, ], dtype='int64'),
                        })

        df.to_sql('test_dtypes', self.conn, index=False, if_exists='replace',
                  dtype={'f64_as_f32': sqlalchemy.Float(precision=23)})
        res = sql.read_sql_table('test_dtypes', self.conn)

        # check precision of float64
        assert (np.round(df['f64'].iloc[0], 14) ==
                np.round(res['f64'].iloc[0], 14))

        # check sql types
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        col_dict = meta.tables['test_dtypes'].columns
        assert str(col_dict['f32'].type) == str(col_dict['f64_as_f32'].type)
        assert isinstance(col_dict['f32'].type, sqltypes.Float)
        assert isinstance(col_dict['f64'].type, sqltypes.Float)
        assert isinstance(col_dict['i32'].type, sqltypes.Integer)
        assert isinstance(col_dict['i64'].type, sqltypes.BigInteger)
Example #15
Source File: test_sql.py    From recruit with Apache License 2.0 4 votes vote down vote up 
def test_double_precision(self):
        V = 1.23456789101112131415

        df = DataFrame({'f32': Series([V, ], dtype='float32'),
                        'f64': Series([V, ], dtype='float64'),
                        'f64_as_f32': Series([V, ], dtype='float64'),
                        'i32': Series([5, ], dtype='int32'),
                        'i64': Series([5, ], dtype='int64'),
                        })

        df.to_sql('test_dtypes', self.conn, index=False, if_exists='replace',
                  dtype={'f64_as_f32': sqlalchemy.Float(precision=23)})
        res = sql.read_sql_table('test_dtypes', self.conn)

        # check precision of float64
        assert (np.round(df['f64'].iloc[0], 14) ==
                np.round(res['f64'].iloc[0], 14))

        # check sql types
        meta = sqlalchemy.schema.MetaData(bind=self.conn)
        meta.reflect()
        col_dict = meta.tables['test_dtypes'].columns
        assert str(col_dict['f32'].type) == str(col_dict['f64_as_f32'].type)
        assert isinstance(col_dict['f32'].type, sqltypes.Float)
        assert isinstance(col_dict['f64'].type, sqltypes.Float)
        assert isinstance(col_dict['i32'].type, sqltypes.Integer)
        assert isinstance(col_dict['i64'].type, sqltypes.BigInteger)