MSSQL.read_columns

MSSQL.read_columns(table_name, column_names, dtype=None, schema_name=None, chunk_size=None, **kwargs)[source]

Read data of specific columns of a table.

Parameters:

table_name (str) – name of a table in the currently-connected database
column_names (list | tuple) – column name(s) of the specified table
dtype (str | None) – data type, defaults to None; options include 'hierarchyid', 'varbinary' and 'geometry'
schema_name (str | None) – name of a schema, defaults to DEFAULT_SCHEMA when schema_name=None
chunk_size (int | None) – number of rows to include in each chunk (if specified), defaults to None
kwargs – [optional] parameters of pandas.read_sql

Returns:

data of specific columns of the queried table

Return type:

pandas.DataFrame

Examples:

>>> from pyhelpers.dbms import MSSQL
>>> from pyhelpers._cache import example_dataframe

>>> mssql = MSSQL()
Connecting <server_name>@localhost:1433/master ... Successfully.

>>> mssql.get_table_names()
{'dbo': ['MSreplication_options',
  'spt_fallback_db',
  'spt_fallback_dev',
  'spt_fallback_usg',
  'spt_monitor']}

>>> mssql.read_columns('MSreplication_options', column_names=['optname', 'value'])
          optname  value
0   transactional   True
1           merge   True
2  security_model   True