Polars

https://www.pola.rs

Install

Install Ibis and dependencies for the Polars backend:

pip

Install with the polars extra:

pip install 'ibis-framework[polars]'

And connect:

import ibis

con = ibis.polars.connect()

1

Adjust connection parameters as needed.

conda

Install for Polars:

conda install -c conda-forge ibis-polars

And connect:

import ibis

con = ibis.polars.connect()

1

Adjust connection parameters as needed.

mamba

Install for Polars:

mamba install -c conda-forge ibis-polars

And connect:

import ibis

con = ibis.polars.connect()

1

Adjust connection parameters as needed.

Connect

ibis.polars.connect

con = ibis.polars.connect()

Note

ibis.polars.connect is a thin wrapper around ibis.backends.polars.Backend.do_connect.

Connection Parameters

do_connect

do_connect(self, tables=None)

Construct a client from a dictionary of polars LazyFrames and/or DataFrames.

Parameters

Name	Type	Description	Default
tables	Mapping[str, pl.LazyFrame | pl.DataFrame] | None	An optional mapping of string table names to polars LazyFrames.	None

Examples

>>> import ibis
>>> import polars as pl
>>> ibis.options.interactive = True
>>> lazy_frame = pl.LazyFrame(
...     {"name": ["Jimmy", "Keith"], "band": ["Led Zeppelin", "Stones"]}
... )
>>> con = ibis.polars.connect(tables={"band_members": lazy_frame})
>>> t = con.table("band_members")
>>> t
┏━━━━━━━━┳━━━━━━━━━━━━━━┓
┃ name   ┃ band         ┃
┡━━━━━━━━╇━━━━━━━━━━━━━━┩
│ string │ string       │
├────────┼──────────────┤
│ Jimmy  │ Led Zeppelin │
│ Keith  │ Stones       │
└────────┴──────────────┘

polars.Backend

compile

compile(self, expr, /, *, limit=None, params=None, **_)

Compile an expression.

Parameters

Name	Type	Description	Default
expr	ir.Expr	An ibis expression to compile.	required
limit	str | int | 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.Expr, Any] | None	Mapping of scalar parameter expressions to value.	None
kwargs	Any	Additional keyword arguments	{}

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_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	pd.DataFrame | pa.Table | ir.Table | 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	ibis.Schema | 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.	None
temp	bool	Whether a table is temporary or not	False
overwrite	bool	Whether to clobber existing data	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
	ir.Table	The view that was created.

disconnect

disconnect(self)

Close the connection to the backend.

drop_table

drop_table(self, name, /, *, 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, /, *, 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=None, engine='cpu', **kwargs)

Execute an Ibis expression and return a pandas DataFrame, Series, or scalar.

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	{}

get_schema

get_schema(self, table_name)

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

list_tables

list_tables(self, *, like=None, database=None)

Return the list of table names in the current database.

For some backends, the tables may be files in a directory, or other equivalent entities in a SQL database.

Ibis does not use the word 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 in Python’s regex format.	None
database	tuple[str, str] | str | None	The database from which to list tables. If not provided, the current database is used. 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

Returns

Name	Type	Description
	list[str]	The list of the table names that match the pattern like.

read_csv

read_csv(self, path, /, *, table_name=None, **kwargs)

Register a CSV file as a table.

Parameters

Name	Type	Description	Default
path	str | Path | list[str | Path] | tuple[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 Polars loading function. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_csv.html for more information.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_delta

read_delta(self, path, /, *, table_name=None, **kwargs)

Register a Delta Lake as a table in the current database.

Parameters

Name	Type	Description	Default
path	str | Path	The data source(s). Path to a Delta Lake table directory.	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 Polars loading function. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_delta.html for more information.	{}

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.

Parameters

Name	Type	Description	Default
path	str | Path	A string or Path to a JSON file; globs are supported	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 Polars loading function. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_ndjson.html for more information.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_pandas

read_pandas(self, source, /, *, table_name=None, **kwargs)

Register a Pandas DataFrame or pyarrow Table a table in the current database.

Parameters

Name	Type	Description	Default
source	pd.DataFrame	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 Polars loading function. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.from_pandas.html for more information.	{}

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 database.

Parameters

Name	Type	Description	Default
path	str | Path | Iterable[str | Path]	The data source(s). May be a path to a file, an iterable of files, or directory of parquet files.	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 Polars loading function. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_parquet.html for more information (if loading a single file or glob; when loading multiple files polars’ scan_pyarrow_dataset method is used instead).	{}

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.

Ibis does not use the word 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	tuple[str, str] | str | None	Database name If not provided, the current database is used. 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

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_json

to_json(self, expr, /, path, **kwargs)

Write the results of expr to a json file of [{column -> value}, …] objects.

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
kwargs	Any	Additional, backend-specifc keyword arguments.	{}

to_pandas

to_pandas(self, expr, /, *, params=None, limit=None, **kwargs)

Execute an Ibis expression and return a pandas DataFrame, Series, or scalar.

Note

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 DataFrames.

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 DataFrames.

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, engine='cpu', **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 to a pyarrow object.

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
	result	If the passed expression is a Table, a pyarrow table is returned. If the passed expression is a Column, a pyarrow array is returned. If the passed expression is a Scalar, a pyarrow scalar is returned.

to_pyarrow_batches

to_pyarrow_batches(self, expr, /, *, params=None, limit=None, chunk_size=1000000, **kwargs)

Execute expression and return a RecordBatchReader.

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
kwargs	Any	Keyword arguments	{}

Returns

Name	Type	Description
	results	RecordBatchReader

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.