MSSQL
https://www.microsoft.com/sql-server
Install
Install Ibis and dependencies for the MSSQL backend:
Install with the mssql
extra:
pip install 'ibis-framework[mssql]'
And connect:
import ibis
= ibis.mssql.connect() con
- 1
- Adjust connection parameters as needed.
Install for MSSQL:
conda install -c conda-forge ibis-mssql
And connect:
import ibis
= ibis.mssql.connect() con
- 1
- Adjust connection parameters as needed.
Install for MSSQL:
mamba install -c conda-forge ibis-mssql
And connect:
import ibis
= ibis.mssql.connect() con
- 1
- Adjust connection parameters as needed.
Connect
ibis.mssql.connect
= ibis.mssql.connect(
con ="username",
user="password",
password="hostname",
host="SQL Server",
driver )
= ibis.mssql.connect(
con ="username",
user="password",
password="hostname",
host="FreeTDS", # if you are using unixODBC
driver )
ibis.mssql.connect
is a thin wrapper around ibis.backends.mssql.Backend.do_connect
.
Connection Parameters
do_connect
do_connect(['self', "host='localhost'", 'user=None', 'password=None', 'port=1433', 'database=None', 'driver=None', '**kwargs'])
Connect to MSSQL database.
Parameters
Name | Type | Description | Default |
---|---|---|---|
host | str | Address of MSSQL server to connect to. | 'localhost' |
user | str | None | Username. Leave blank to use Integrated Authentication. | None |
password | str | None | Password. Leave blank to use Integrated Authentication. | None |
port | int | Port of MSSQL server to connect to. | 1433 |
database | str | None | The MSSQL database to connect to. | None |
driver | str | None | ODBC Driver to use. On Mac and Linux this is usually ‘FreeTDS’. On Windows, it is usually one of: - ODBC Driver 11 for SQL Server - ODBC Driver 13 for SQL Server (for both 13 and 13.1) - ODBC Driver 17 for SQL Server - ODBC Driver 18 for SQL Server See https://learn.microsoft.com/en-us/sql/connect/odbc/windows/system-requirements-installation-and-driver-files | None |
kwargs | Any | Additional keyword arguments to pass to PyODBC. | {} |
Examples
>>> import os
>>> import ibis
>>> host = os.environ.get("IBIS_TEST_MSSQL_HOST", "localhost")
>>> user = os.environ.get("IBIS_TEST_MSSQL_USER", "sa")
>>> password = os.environ.get("IBIS_TEST_MSSQL_PASSWORD", "1bis_Testing!")
>>> database = os.environ.get("IBIS_TEST_MSSQL_DATABASE", "ibis_testing")
>>> driver = os.environ.get("IBIS_TEST_MSSQL_PYODBC_DRIVER", "FreeTDS")
>>> con = ibis.mssql.connect(
=database,
... database=host,
... host=user,
... user=password,
... password=driver,
... driver
... )>>> con.list_tables()
[...]>>> t = con.table("functional_alltypes")
>>> t
DatabaseTable: functional_alltypesid int32
bool_col boolean
tinyint_col int16
smallint_col int16
int_col int32
bigint_col int64
float_col float32
double_col float64
date_string_col string
string_col string7)
timestamp_col timestamp(
year int32 month int32
ibis.connect
URL format
In addition to ibis.mssql.connect
, you can also connect to MSSQL by passing a properly-formatted MSSQL connection URL to ibis.connect
:
= ibis.connect(f"mssql://{user}:{password}@{host}:{port}") con
Using Integrated Authentication
Integrated Authentication allows users to log in via NTLM or Kerberos. To make use of integrated authentication, use ibis.mssql.connect
as documented above, but do not specify values for user
or password
. The PyODBC driver will then default to Integrated Authentication.
Some environments may require you to set additional keywords to connect. Additional information is available at the following pages:
- https://learn.microsoft.com/en-us/aspnet/web-api/overview/security/integrated-windows-authentication
- https://learn.microsoft.com/en-us/sql/connect/odbc/linux-mac/using-integrated-authentication
mssql.Backend
begin
begin(['self'])
compile
compile(['self', 'expr', 'limit=None', 'params=None', 'pretty=False'])
Compile an Ibis expression to a SQL string.
connect
connect(['self', '*args', '**kwargs'])
Connect to the database.
Parameters
Name | Type | Description | Default |
---|---|---|---|
*args | Mandatory connection parameters, see the docstring of do_connect for details. |
() |
|
**kwargs | Extra connection parameters, see the docstring of do_connect for details. |
{} |
Notes
This creates a new backend instance with saved args
and kwargs
, then calls reconnect
and finally returns the newly created and connected backend instance.
Returns
Name | Type | Description |
---|---|---|
BaseBackend | An instance of the backend |
create_catalog
create_catalog(['self', 'name', 'force=False'])
Create a new catalog.
schema
to refer to database hierarchy.
A collection of table
is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the new catalog. | required |
force | bool | If False , an exception is raised if the catalog already exists. |
False |
create_database
create_database(['self', 'name', 'catalog=None', 'force=False'])
Create a database named name
in catalog
.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the database to create. | required |
catalog | str | None | Name of the catalog in which to create the database. If None , the current catalog is used. |
None |
force | bool | If False , an exception is raised if the database exists. |
False |
create_table
create_table(['self', 'name', 'obj=None', '*', 'schema=None', 'database=None', 'temp=None', 'overwrite=False'])
Create a new table.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the new table. | required |
obj | ir.Table | pd.DataFrame | pa.Table | pl.DataFrame | pl.LazyFrame | None | An Ibis table expression or pandas table that will be used to extract the schema and the data of the new table. If not provided, schema must be given. |
None |
schema | sch.SchemaLike | None | The schema for the new table. Only one of schema or obj can be provided. |
None |
database | str | None | Name of the database where the table will be created, if not the default. To specify a location in a separate catalog, you can pass in the catalog and database as a string "catalog.database" , or as a tuple of strings ("catalog", "database") . |
None |
temp | bool | None | Whether a table is temporary or not. All created temp tables are “Global Temporary Tables”. They will be created in “tempdb.dbo” and will be prefixed with “##”. | None |
overwrite | bool | Whether to clobber existing data. overwrite and temp cannot be used together with MSSQL. |
False |
Returns
Name | Type | Description |
---|---|---|
Table | The table that was created. |
create_view
create_view(['self', 'name', 'obj', '*', 'database=None', 'overwrite=False'])
Create a new view from an expression.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the new view. | required |
obj | ir.Table | An Ibis table expression that will be used to create the view. | required |
database | str | None | Name of the database where the view will be created, if not provided the database’s default is used. | None |
overwrite | bool | Whether to clobber an existing view with the same name | False |
Returns
Name | Type | Description |
---|---|---|
Table | The view that was created. |
disconnect
disconnect(['self'])
Close the connection to the backend.
drop_catalog
drop_catalog(['self', 'name', 'force=False'])
Drop a catalog with name name
.
schema
to refer to database hierarchy.
A collection of table
is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Catalog to drop. | required |
force | bool | If False , an exception is raised if the catalog does not exist. |
False |
drop_database
drop_database(['self', 'name', 'catalog=None', 'force=False'])
Drop the database with name
in catalog
.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the schema to drop. | required |
catalog | str | None | Name of the catalog to drop the database from. If None , the current catalog is used. |
None |
force | bool | If False , an exception is raised if the database does not exist. |
False |
drop_table
drop_table(['self', 'name', 'database=None', 'force=False'])
Drop a table.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the table to drop. | required |
database | str | None | Name of the database where the table exists, if not the default. | None |
force | bool | If False , an exception is raised if the table does not exist. |
False |
drop_view
drop_view(['self', 'name', '*', 'database=None', 'force=False'])
Drop a view.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Name of the view to drop. | required |
database | str | None | Name of the database where the view exists, if not the default. | None |
force | bool | If False , an exception is raised if the view does not exist. |
False |
execute
execute(['self', 'expr', 'params=None', "limit='default'", '**kwargs'])
Execute an expression.
from_connection
from_connection(['cls', 'con'])
Create an Ibis client from an existing connection to a MSSQL database.
Parameters
Name | Type | Description | Default |
---|---|---|---|
con | pyodbc.Connection | An existing connection to a MSSQL database. | required |
get_schema
get_schema(['self', 'name', '*', 'catalog=None', 'database=None'])
has_operation
has_operation(['cls', 'operation'])
Return whether the backend implements support for operation
.
Parameters
Name | Type | Description | Default |
---|---|---|---|
operation | type[ops.Value] | A class corresponding to an operation. | required |
Returns
Name | Type | Description |
---|---|---|
bool | Whether the backend implements the operation. |
Examples
>>> import ibis
>>> import ibis.expr.operations as ops
>>> ibis.sqlite.has_operation(ops.ArrayIndex)
False
>>> ibis.postgres.has_operation(ops.ArrayIndex)
True
insert
insert(['self', 'table_name', 'obj', 'database=None', 'overwrite=False'])
Insert data into a table.
schema
to refer to database hierarchy.
A collection of table
is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
table_name | str | The name of the table to which data needs will be inserted | required |
obj | pd.DataFrame | ir.Table | list | dict | The source data or expression to insert | required |
database | str | None | Name of the attached database that the table is located in. For backends that support multi-level table hierarchies, you can pass in a dotted string path like "catalog.database" or a tuple of strings like ("catalog", "database") . |
None |
overwrite | bool | If True then replace existing contents of table |
False |
list_catalogs
list_catalogs(['self', 'like=None'])
List existing catalogs in the current connection.
schema
to refer to database hierarchy.
A collection of table
is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
like | str | None | A pattern in Python’s regex format to filter returned database names. | None |
Returns
Name | Type | Description |
---|---|---|
list[str] | The catalog names that exist in the current connection, that match the like pattern if provided. |
list_databases
list_databases(['self', 'like=None', 'catalog=None'])
List existing databases in the current connection.
schema
to refer to database hierarchy.
A collection of table
is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
like | str | None | A pattern in Python’s regex format to filter returned database names. | None |
catalog | str | None | The catalog to list databases from. If None , the current catalog is searched. |
None |
Returns
Name | Type | Description |
---|---|---|
list[str] | The database names that exist in the current connection, that match the like pattern if provided. |
list_tables
list_tables(['self', 'like=None', 'database=None'])
List the tables in the database.
schema
to refer to database hierarchy.
A collection of tables is referred to as a database
. A collection of database
is referred to as a catalog
.
These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
like | str | None | A pattern to use for listing tables. | None |
database | tuple[str, str] | str | None | Table location. If not passed, uses the current catalog and database. To specify a table in a separate catalog, you can pass in the catalog and database as a string "catalog.database" , or as a tuple of strings ("catalog", "database") . |
None |
raw_sql
raw_sql(['self', 'query', '**kwargs'])
read_csv
read_csv(['self', 'path', 'table_name=None', '**kwargs'])
Register a CSV file as a table in the current backend.
Parameters
Name | Type | Description | Default |
---|---|---|---|
path | str | Path | The data source. A string or Path to the CSV file. | required |
table_name | str | None | An optional name to use for the created table. This defaults to a sequentially generated name. | None |
**kwargs | Any | Additional keyword arguments passed to the backend loading function. | {} |
Returns
Name | Type | Description |
---|---|---|
ir.Table | The just-registered table |
read_delta
read_delta(['self', 'source', 'table_name=None', '**kwargs'])
Register a Delta Lake table in the current database.
Parameters
Name | Type | Description | Default |
---|---|---|---|
source | str | Path | The data source. Must be a directory containing a Delta Lake table. | required |
table_name | str | None | An optional name to use for the created table. This defaults to a sequentially generated name. | None |
**kwargs | Any | Additional keyword arguments passed to the underlying backend or library. | {} |
Returns
Name | Type | Description |
---|---|---|
ir.Table | The just-registered table. |
read_json
read_json(['self', 'path', 'table_name=None', '**kwargs'])
Register a JSON file as a table in the current backend.
Parameters
Name | Type | Description | Default |
---|---|---|---|
path | str | Path | The data source. A string or Path to the JSON file. | required |
table_name | str | None | An optional name to use for the created table. This defaults to a sequentially generated name. | None |
**kwargs | Any | Additional keyword arguments passed to the backend loading function. | {} |
Returns
Name | Type | Description |
---|---|---|
ir.Table | The just-registered table |
read_parquet
read_parquet(['self', 'path', 'table_name=None', '**kwargs'])
Register a parquet file as a table in the current backend.
Parameters
Name | Type | Description | Default |
---|---|---|---|
path | str | Path | The data source. | required |
table_name | str | None | An optional name to use for the created table. This defaults to a sequentially generated name. | None |
**kwargs | Any | Additional keyword arguments passed to the backend loading function. | {} |
Returns
Name | Type | Description |
---|---|---|
ir.Table | The just-registered table |
reconnect
reconnect(['self'])
Reconnect to the database already configured with connect.
register_options
register_options(['cls'])
Register custom backend options.
rename_table
rename_table(['self', 'old_name', 'new_name'])
Rename an existing table.
Parameters
Name | Type | Description | Default |
---|---|---|---|
old_name | str | The old name of the table. | required |
new_name | str | The new name of the table. | required |
sql
sql(['self', 'query', 'schema=None', 'dialect=None'])
table
table(['self', 'name', 'database=None'])
Construct a table expression.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Table name | required |
database | tuple[str, str] | str | None | Database name | None |
Returns
Name | Type | Description |
---|---|---|
Table | Table expression |
to_csv
to_csv(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])
Write the results of executing the given expression to a CSV file.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Table | The ibis expression to execute and persist to CSV. | required |
path | str | Path | The data source. A string or Path to the CSV file. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
kwargs | Any | Additional keyword arguments passed to pyarrow.csv.CSVWriter | {} |
https | required |
to_delta
to_delta(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])
Write the results of executing the given expression to a Delta Lake table.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Table | The ibis expression to execute and persist to Delta Lake table. | required |
path | str | Path | The data source. A string or Path to the Delta Lake table. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
kwargs | Any | Additional keyword arguments passed to deltalake.writer.write_deltalake method | {} |
to_pandas
to_pandas(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])
Execute an Ibis expression and return a pandas DataFrame
, Series
, or scalar.
This method is a wrapper around execute
.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to execute. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
limit | int | str | None | An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py . |
None |
kwargs | Any | Keyword arguments | {} |
to_pandas_batches
to_pandas_batches(['self', 'expr', '*', 'params=None', 'limit=None', 'chunk_size=1000000', '**kwargs'])
Execute an Ibis expression and return an iterator of pandas DataFrame
s.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to execute. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
limit | int | str | None | An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py . |
None |
chunk_size | int | Maximum number of rows in each returned DataFrame batch. This may have no effect depending on the backend. |
1000000 |
kwargs | Any | Keyword arguments | {} |
Returns
Name | Type | Description |
---|---|---|
Iterator[pd.DataFrame] | An iterator of pandas DataFrame s. |
to_parquet
to_parquet(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])
Write the results of executing the given expression to a parquet file.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Table | The ibis expression to execute and persist to parquet. | required |
path | str | Path | The data source. A string or Path to the parquet file. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
**kwargs | Any | Additional keyword arguments passed to pyarrow.parquet.ParquetWriter | {} |
https | required |
to_parquet_dir
to_parquet_dir(['self', 'expr', 'directory', '*', 'params=None', '**kwargs'])
Write the results of executing the given expression to a parquet file in a directory.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Table | The ibis expression to execute and persist to parquet. | required |
directory | str | Path | The data source. A string or Path to the directory where the parquet file will be written. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
**kwargs | Any | Additional keyword arguments passed to pyarrow.dataset.write_dataset | {} |
https | required |
to_polars
to_polars(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])
Execute expression and return results in as a polars DataFrame.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to export to polars. | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
limit | int | str | None | An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py . |
None |
kwargs | Any | Keyword arguments | {} |
Returns
Name | Type | Description |
---|---|---|
dataframe | A polars DataFrame holding the results of the executed expression. |
to_pyarrow
to_pyarrow(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])
Execute expression and return results in as a pyarrow table.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to export to pyarrow | required |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
limit | int | str | None | An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py . |
None |
kwargs | Any | Keyword arguments | {} |
Returns
Name | Type | Description |
---|---|---|
Table | A pyarrow table holding the results of the executed expression. |
to_pyarrow_batches
to_pyarrow_batches(['self', 'expr', '*', 'params=None', 'limit=None', 'chunk_size=1000000', '**_'])
Execute expression and return an iterator of pyarrow record batches.
This method is eager and will execute the associated expression immediately.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to export to pyarrow | required |
limit | int | str | None | An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py . |
None |
params | Mapping[ir.Scalar, Any] | None | Mapping of scalar parameter expressions to value. | None |
chunk_size | int | Maximum number of rows in each returned record batch. | 1000000 |
Returns
Name | Type | Description |
---|---|---|
RecordBatchReader | Collection of pyarrow RecordBatch s. |
to_torch
to_torch(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])
Execute an expression and return results as a dictionary of torch tensors.
Parameters
Name | Type | Description | Default |
---|---|---|---|
expr | ir.Expr | Ibis expression to execute. | required |
params | Mapping[ir.Scalar, Any] | None | Parameters to substitute into the expression. | None |
limit | int | str | None | An integer to effect a specific row limit. A value of None means no limit. |
None |
kwargs | Any | Keyword arguments passed into the backend’s to_torch implementation. |
{} |
Returns
Name | Type | Description |
---|---|---|
dict[str, torch.Tensor] | A dictionary of torch tensors, keyed by column name. |
truncate_table
truncate_table(['self', 'name', 'database=None'])
Delete all rows from a table.
schema
to refer to database hierarchy.
A collection of tables is referred to as a database
. A collection of database
is referred to as a catalog
. These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.
Parameters
Name | Type | Description | Default |
---|---|---|---|
name | str | Table name | required |
database | str | None | Name of the attached database that the table is located in. For backends that support multi-level table hierarchies, you can pass in a dotted string path like "catalog.database" or a tuple of strings like ("catalog", "database") . |
None |