def test_is_dataframe(self): df = pd.DataFrame({ 'category': ['a', 'b', 'c'], 'gender': ['F', 'M', 'F'], 'age': [1, 5, 4] }) self.assertTrue(filters.is_dataframe(df))
def test_is_dataframe(self): df = pd.DataFrame({ 'category': ['a', 'b', 'c'], 'gender': ['F', 'M', 'F'], 'age': [1, 5, 4] }) self.assertTrue(filters.is_dataframe(df))
def test_is_not_dataframe(self): junk_inputs = [ 'foo', 42, [1, 2, 3], [[1, 2, 3], [1, 2, 3], [1, 2, 3], ], {'a': 1} ] for junk in junk_inputs: self.assertFalse(filters.is_dataframe(junk))
def test_is_not_dataframe(self): junk_inputs = [ 'foo', 42, [1, 2, 3], [[1, 2, 3], [1, 2, 3], [1, 2, 3], ], {'a': 1} ] for junk in junk_inputs: self.assertFalse(filters.is_dataframe(junk))
def write_to_db_agnostic(engine, table, dataframe, schema=None): """ Given an sqlalchemy engine or sqlite connection, writes a dataframe to a table Args: engine (sqlalchemy.engine.base.Engine, sqlite3.Connection): the database engine or connection object table (str): destination table dataframe (pandas.DataFrame): the data to write schema (str): the optional database schema """ # Validate inputs is_engine = isinstance(engine, sqlalchemy.engine.base.Engine) if sqlite3_is_loaded: is_sqlite_connection = isinstance(engine, sqlite3.Connection) else: is_sqlite_connection = False if not is_engine and not is_sqlite_connection: raise HealthcareAIError('sqlalchemy engine or sqlite connection required, a {} was given'.format(type(engine))) if not is_dataframe(dataframe): raise HealthcareAIError('Dataframe required, a {} was given'.format(type(dataframe))) if not isinstance(table, str): raise HealthcareAIError('Table name required, a {} was given'.format(type(table))) # Verify that tables exist for databases if is_engine and not healthcareai.common.database_validators.does_table_exist(engine, table, schema): raise HealthcareAIError('Destination table ({}) does not exist. Please create it.'.format(table)) elif is_sqlite_connection: healthcareai.common.database_validators.verify_sqlite_table_exists(engine, table) try: # Count before before_count = pd.read_sql('select count(*) from {}'.format(table), engine).iloc[0][0] # Insert into database dataframe.to_sql(table, engine, if_exists='append', index=False) # Count after after_count = pd.read_sql('select count(*) from {}'.format(table), engine).iloc[0][0] delta = after_count - before_count print('\nSuccessfully inserted {} rows. Dataframe contained {} rows'.format(delta, len(dataframe))) # TODO catch other errors here: except (sqlalchemy.exc.SQLAlchemyError, sqlite3.Error, pd.io.sql.DatabaseError): raise HealthcareAIError("""Failed to insert values into {}.\n Please verify that the table [{}] exists.\n Was your test insert successful earlier?\n If so, what has changed with your database/table/entity since then?""".format(table, table))
def write_to_db_agnostic(engine, table, dataframe, schema=None): """ Given an sqlalchemy engine or sqlite connection, writes a dataframe to a table Args: engine (sqlalchemy.engine.base.Engine, sqlite3.Connection): the database engine or connection object table (str): destination table dataframe (pandas.DataFrame): the data to write schema (str): the optional database schema """ # Validate inputs is_engine = isinstance(engine, sqlalchemy.engine.base.Engine) if sqlite3_is_loaded: is_sqlite_connection = isinstance(engine, sqlite3.Connection) else: is_sqlite_connection = False if not is_engine and not is_sqlite_connection: raise HealthcareAIError( 'sqlalchemy engine or sqlite connection required, a {} was given'. format(type(engine))) if not is_dataframe(dataframe): raise HealthcareAIError('Dataframe required, a {} was given'.format( type(dataframe))) if not isinstance(table, str): raise HealthcareAIError('Table name required, a {} was given'.format( type(table))) # Verify that tables exist for databases if is_engine and not healthcareai.common.database_validators.does_table_exist( engine, table, schema): raise HealthcareAIError( 'Destination table ({}) does not exist. Please create it.'.format( table)) elif is_sqlite_connection: healthcareai.common.database_validators.verify_sqlite_table_exists( engine, table) try: # Count before before_count = pd.read_sql('select count(*) from {}'.format(table), engine).iloc[0][0] # Insert into database dataframe.to_sql(table, engine, if_exists='append', index=False) # Count after after_count = pd.read_sql('select count(*) from {}'.format(table), engine).iloc[0][0] delta = after_count - before_count print('\nSuccessfully inserted {} rows. Dataframe contained {} rows'. format(delta, len(dataframe))) # TODO catch other errors here: except (sqlalchemy.exc.SQLAlchemyError, sqlite3.Error, pd.io.sql.DatabaseError): raise HealthcareAIError("""Failed to insert values into {}.\n Please verify that the table [{}] exists.\n Was your test insert successful earlier?\n If so, what has changed with your database/table/entity since then?""". format(table, table))