Polars

https://www.pola.rs

Install

Install Ibis and dependencies for the Polars backend:

Install with the polars extra:

pip install 'ibis-framework[polars]'

And connect:

import ibis

con = ibis.polars.connect()
1
Adjust connection parameters as needed.

Install for Polars:

conda install -c conda-forge ibis-polars

And connect:

import ibis

con = ibis.polars.connect()
1
Adjust connection parameters as needed.

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', 'params=None', '**_'])

Compile an expression.

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
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', 'streaming=False', "engine='cpu'", '**kwargs'])

Execute an expression.

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] 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

register(['self', 'source', 'table_name=None', '**kwargs'])

Register a data source as a table in the current database.

Parameters

Name Type Description Default
source str | Path | Any The data source(s). May be a path to a file, a parquet directory, or a pandas dataframe. 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 functions for CSV or parquet. See https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_csv.html and https://pola-rs.github.io/polars/py-polars/html/reference/api/polars.scan_parquet.html for more information {}

Returns

Name Type Description
ir.Table The just-registered table

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'])

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_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', 'streaming=False', "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 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', '**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.
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