ibis.connect URL format

Connect to DuckDB with Ibis, the portable dataframe library

DuckDB

https://duckdb.org

Install

Install Ibis and dependencies for the DuckDB backend:

Install with the duckdb extra:

pip install 'ibis-framework[duckdb]'

And connect:

import ibis

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

Install for DuckDB:

conda install -c conda-forge ibis-duckdb

And connect:

import ibis

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

Install for DuckDB:

mamba install -c conda-forge ibis-duckdb

And connect:

import ibis

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

Connect

ibis.duckdb.connect

Connect to an in-memory database:

con = ibis.duckdb.connect()

Connect to, or create, a local DuckDB file

con = ibis.duckdb.connect("mydb.duckdb")
Note

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

Connection Parameters

do_connect

do_connect(self, database=':memory:', read_only=False, extensions=None, **config)

Create an Ibis client connected to a DuckDB database.

NoteChanged in version 10.0.0

Before, we had special handling if the user passed the temp_directory parameter, setting a custom default, and creating intermediate directories if necessary. Now, we do nothing, and just pass the value directly to DuckDB. You may need to add Path(your_temp_dir).mkdir(exists_ok=True, parents=True) to your code to maintain the old behavior.

Parameters
Name Type Description Default
database str | Path Path to a duckdb database. ':memory:'
read_only bool Whether the database is read-only. False
extensions Sequence[str] | None A list of duckdb extensions to install/load upon connection. None
config Any DuckDB configuration parameters. See the DuckDB configuration documentation for possible configuration values. {}
Examples
>>> import ibis
>>> ibis.duckdb.connect(threads=4, memory_limit="1GB")
<ibis.backends.duckdb.Backend object at 0x...>

In addition to ibis.duckdb.connect, you can also connect to DuckDB by passing a properly-formatted DuckDB connection URL to ibis.connect:

import ibis

con = ibis.connect("duckdb://local.ddb")

Given an empty path, ibis.connect will connect to an ephemeral, in-memory database.

con = ibis.connect("duckdb://")

Cloud bucket reads

DuckDB has a secret management system that is designed to support reading data from both public and private cloud blob storage systems like Amazon’s S3.

To make your life easier, you should probably start with the CREDENTIAL_CHAIN provider, which mimics the default behavior of the aws CLI and SDKs.

Ibis doesn’t have an Ibis-native API for dealing with DuckDB’s secrets, but you can of course run raw_sql to set them up:

con.raw_sql("CREATE SECRET s3 (TYPE S3, PROVIDER CREDENTIAL_CHAIN)")

Assuming you’ve got the appropriate authorizations in AWS, this should allow DuckDB to read from any bucket you’re authorized to access.

MotherDuck

The DuckDB backend supports MotherDuck. If you have an account, you can connect to MotherDuck by passing in the string md: or motherduck:. ibis will trigger the authentication prompt in-browser.

import ibis

con = ibis.duckdb.connect("md:")
Note

Authentication to MotherDuck will trigger on the first call that requires retrieving information (in this case list_tables)

con.list_tables()
Attempting to automatically open the SSO authorization page in your default browser.
1. Please open this link to login into your account: https://auth.motherduck.com/activate
2. Enter the following code: ZSRQ-GJQS


Token successfully retrieved ✅
You can store it as an environment variable to avoid having to log in again:
  $ export motherduck_token='****************'

['penguins']

Geospatial

The DuckDB backend has experimental support for geospatial operations.

To enable geospatial operations, install the geospatial extra or otherwise install the additional required dependencies:

See read_geo for some tips on reading in geospatial data.

pip install 'ibis-framework[geospatial]'
conda install -c conda-forge ibis-framework geopandas 'shapely>=2,<3'
mamba install -c conda-forge ibis-framework geopandas 'shapely>=2,<3'

duckdb.Backend

attach

attach(self, path, name=None, read_only=False)

Attach another DuckDB database to the current DuckDB session.

Parameters

Name Type Description Default
path str | Path Path to the database to attach. required
name str | None Name to attach the database as. Defaults to the basename of path. None
read_only bool Whether to attach the database as read-only. False

attach_sqlite

attach_sqlite(self, path, overwrite=False, all_varchar=False)

Attach a SQLite database to the current DuckDB session.

Parameters

Name Type Description Default
path str | Path The path to the SQLite database. required
overwrite bool Allow overwriting any tables or views that already exist in your current session with the contents of the SQLite database. False
all_varchar bool Set all SQLite columns to type VARCHAR to avoid type errors on ingestion. False

Examples

>>> import ibis
>>> import sqlite3
>>> con = sqlite3.connect("/tmp/attach_sqlite.db")
>>> with con:
...     con.execute("DROP TABLE IF EXISTS t")
...     con.execute("CREATE TABLE t (a INT, b TEXT)")
...     con.execute(
...         "INSERT INTO t VALUES (1, 'a'), (2, 'b'), (3, 'c')"
...     )
<...>
>>> con.close()
>>> con = ibis.connect("duckdb://")
>>> con.list_tables()
[]
>>> con.attach_sqlite("/tmp/attach_sqlite.db")
>>> con.list_tables()
['t']

compile

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

Compile an expression to a SQL string.

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. None
params Mapping[ir.Expr, Any] | None Mapping of scalar parameter expressions to value. None
pretty bool Pretty print the SQL query during compilation. False

Returns

Name Type Description
str Compiled 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_database

create_database(self, name, /, *, catalog=None, force=False)

Create a database named name in catalog.

NoteIbis does not use the word 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 the terminology the backend uses.

See the Table Hierarchy Concepts Guide for more info.

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=False, overwrite=False)

Create a table in DuckDB.

Parameters

Name Type Description Default
name str Name of the table to create required
obj ir.Table | pd.DataFrame | pa.Table | pl.DataFrame | pl.LazyFrame | None The data with which to populate the table; optional, but at least one of obj or schema must be specified None
schema SchemaLike | None The schema of the table to create; optional, but at least one of obj or schema must be specified None
database str | None The name of the database in which to create the table; if not passed, the current database is used. For multi-level table hierarchies, you can pass in a dotted string path like "catalog.database" or a tuple of strings like ("catalog", "database"). None
temp bool Create a temporary table False
overwrite bool If True, replace the table if it already exists, otherwise fail if the table exists False

create_view

create_view(self, name, /, obj, *, database=None, overwrite=False)

Create a view from an Ibis expression.

Parameters

Name Type Description Default
name str The name of the view to create. required
obj ir.Table The Ibis expression to create the view from. required
database str | None The database that the view should be created in. None
overwrite bool If True, replace an existing view with the same name. False

Returns

Name Type Description
ir.Table A table expression representing the view.

detach

detach(self, name)

Detach a database from the current DuckDB session.

Parameters

Name Type Description Default
name str The name of the database to detach. required

disconnect

disconnect(self)

Disconnect from the backend.

drop_database

drop_database(self, name, /, *, catalog=None, force=False)

Drop the database with name in catalog.

NoteIbis does not use the word 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 the terminology the backend uses.

See the Table Hierarchy Concepts Guide for more info.

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 from the backend.

Parameters

Name Type Description Default
name str The name of the table to drop required
database tuple[str, str] | str | None The database that the table is located in. None
force bool If True, do not raise an error if the table does not exist. False

drop_view

drop_view(self, name, /, *, database=None, force=False)

Drop a view from the backend.

Parameters

Name Type Description Default
name str The name of the view to drop. required
database str | None The database that the view is located in. None
force bool If True, do not raise an error if the view does not exist. False

execute

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

Execute an expression.

from_connection

from_connection(cls, con, /, *, extensions=None)

Create an Ibis client from an existing connection to a DuckDB database.

Parameters

Name Type Description Default
con duckdb.DuckDBPyConnection An existing connection to a DuckDB database. required
extensions Sequence[str] | None A list of duckdb extensions to install/load upon connection. None

get_schema

get_schema(self, table_name, *, catalog=None, database=None)

Compute the schema of a table.

Parameters

Name Type Description Default
table_name str May not be fully qualified. Use database if you want to qualify the identifier. required
catalog str | None Catalog name None
database str | None Database name None

Returns

Name Type Description
sch.Schema Ibis schema

has_operation

has_operation(cls, operation, /)

Return whether the backend supports the given operation.

Parameters

Name Type Description Default
operation type[ops.Value] Operation type, a Python class object. required

insert

insert(self, name, /, obj, *, database=None, overwrite=False)

Insert data into a table.

NoteIbis does not use the word 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 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.

NoteIbis does not use the word 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 the terminology the backend uses.

See the Table Hierarchy Concepts Guide for more info.

Parameters

Name Type Description Default
like str | None A pattern in Python’s regex format to filter returned catalog 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.

NoteIbis does not use the word 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 the terminology the backend uses.

See the Table Hierarchy Concepts Guide for more info.

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)

The table names that match like in the given database.

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

Parameters

Name Type Description Default
like str | None A pattern in Python’s regex format. None
database tuple[str, str] | str | None The database, or (catalog, database) from which to list tables. For backends that support a single-level table hierarchy, you can pass in a string like "bar". 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"). If not provided, the current database (and catalog, if applicable for this backend) is used. See the Table Hierarchy Concepts Guide for more info. None

Returns

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

Examples

This example uses the DuckDB backend, but the list_tables API works the same for other backends.

>>> import ibis
>>> con = ibis.duckdb.connect()
>>> foo = con.create_table("foo", schema=ibis.schema(dict(a="int")))
>>> con.list_tables()
['foo']
>>> bar = con.create_view("bar", foo)
>>> con.list_tables()
['bar', 'foo']
>>> con.create_database("my_database")
>>> con.list_tables(database="my_database")
[]
>>> con.raw_sql("CREATE TABLE my_database.baz (a INTEGER)")
<duckdb.duckdb.DuckDBPyConnection object at 0x...>
>>> con.list_tables(database="my_database")
['baz']

load_extension

load_extension(self, extension, force_install=False)

Install and load a duckdb extension by name or path.

Parameters

Name Type Description Default
extension str The extension name or path. required
force_install bool Force reinstallation of the extension. False

raw_sql

raw_sql(self, query, **kwargs)

read_csv

read_csv(self, paths, /, *, table_name=None, columns=None, types=None, **kwargs)

Register a CSV file as a table in the current database.

Parameters

Name Type Description Default
paths str | list[str] | tuple[str] The data source(s). May be a path to a file or directory of CSV files, or an iterable of CSV files. required
table_name str | None An optional name to use for the created table. This defaults to a sequentially generated name. None
columns Mapping[str, str | dt.DataType] | None An optional mapping of all column names to their types. None
types Mapping[str, str | dt.DataType] | None An optional mapping of a subset of column names to their types. None
**kwargs Any Additional keyword arguments passed to DuckDB loading function. See https://duckdb.org/docs/data/csv for more information. {}

Returns

Name Type Description
ir.Table The just-registered table

Examples

Generate some data

>>> import tempfile
>>> data = b'''
... lat,lon,geom
... 1.0,2.0,POINT (1 2)
... 2.0,3.0,POINT (2 3)
... '''
>>> with tempfile.NamedTemporaryFile(delete=False) as f:
...     nbytes = f.write(data)

Import Ibis

>>> import ibis
>>> from ibis import _
>>> ibis.options.interactive = True
>>> con = ibis.duckdb.connect()

Read the raw CSV file

>>> t = con.read_csv(f.name)
>>> t
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ lat     ┃ lon     ┃ geom        ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━┩
│ float64 │ float64 │ string      │
├─────────┼─────────┼─────────────┤
│     1.0 │     2.0 │ POINT (1 2) │
│     2.0 │     3.0 │ POINT (2 3) │
└─────────┴─────────┴─────────────┘

Load the spatial extension and read the CSV file again, using specific column types

>>> con.load_extension("spatial")
>>> t = con.read_csv(f.name, types={"geom": "geometry"})
>>> t
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
┃ lat     ┃ lon     ┃ geom                 ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│ float64 │ float64 │ geospatial:geometry  │
├─────────┼─────────┼──────────────────────┤
│     1.0 │     2.0 │ <POINT (1 2)>        │
│     2.0 │     3.0 │ <POINT (2 3)>        │
└─────────┴─────────┴──────────────────────┘

read_delta

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

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

Parameters

Name Type Description Default
path 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 deltalake.DeltaTable. {}

Returns

Name Type Description
ir.Table The just-registered table.

read_geo

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

Register a geospatial data file as a table in the current database.

Parameters

Name Type Description Default
path str The data source(s). Path to a file of geospatial files supported by duckdb. See https://duckdb.org/docs/extensions/spatial.html#st_read—read-spatial-data-from-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 DuckDB loading function. See https://duckdb.org/docs/extensions/spatial.html#st_read—read-spatial-data-from-files for more information. {}

Returns

Name Type Description
ir.Table The just-registered table

read_json

read_json(self, paths, /, *, table_name=None, columns=None, **kwargs)

Read newline-delimited JSON into an ibis table.

NoteThis feature requires duckdb>=0.7.0

Parameters

Name Type Description Default
paths str | list[str] | tuple[str] File or list of files required
table_name str | None Optional table name None
columns Mapping[str, str] | None Optional mapping from string column name to duckdb type string. None
**kwargs Additional keyword arguments passed to DuckDB’s read_json_auto function. See https://duckdb.org/docs/data/json/overview.html#json-loading for parameters and more information about reading JSON. {}

Returns

Name Type Description
Table An ibis table expression

read_mysql

read_mysql(self, uri, /, *, catalog, table_name=None)

Register a table from a MySQL instance into a DuckDB table.

Parameters

Name Type Description Default
uri str A mysql URI of the form mysql://user:password@host:port/database required
catalog str User-defined alias given to the MySQL database that is being attached to DuckDB required
table_name str | None The table to read None

Returns

Name Type Description
ir.Table The just-registered table.

read_parquet

read_parquet(self, paths, /, *, table_name=None, **kwargs)

Register a parquet file as a table in the current database.

Parameters

Name Type Description Default
paths 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 DuckDB loading function. See https://duckdb.org/docs/data/parquet for more information. {}

Returns

Name Type Description
ir.Table The just-registered table

read_postgres

read_postgres(self, uri, /, *, table_name=None, database='public')

Register a table from a postgres instance into a DuckDB table.

NoteIbis does not use the word 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
uri str A postgres URI of the form postgres://user:password@host:port required
table_name str | None The table to read None
database str PostgreSQL database (schema) where table_name resides 'public'

Returns

Name Type Description
ir.Table The just-registered table.

read_sqlite

read_sqlite(self, path, /, *, table_name=None)

Register a table from a SQLite database into a DuckDB table.

Parameters

Name Type Description Default
path str | Path The path to the SQLite database required
table_name str | None The table to read None

Returns

Name Type Description
ir.Table The just-registered table.

Examples

>>> import ibis
>>> import sqlite3
>>> ibis.options.interactive = True
>>> con = sqlite3.connect("/tmp/sqlite.db")
>>> with con:
...     con.execute("DROP TABLE IF EXISTS t")
...     con.execute("CREATE TABLE t (a INT, b TEXT)")
...     con.execute(
...         "INSERT INTO t VALUES (1, 'a'), (2, 'b'), (3, 'c')"
...     )
<...>
>>> con.close()
>>> con = ibis.connect("duckdb://")
>>> t = con.read_sqlite("/tmp/sqlite.db", table_name="t")
>>> t
┏━━━━━━━┳━━━━━━━━┓
┃ a     ┃ b      ┃
┡━━━━━━━╇━━━━━━━━┩
│ int64 │ string │
├───────┼────────┤
│     1 │ a      │
│     2 │ b      │
│     3 │ c      │
└───────┴────────┘

read_xlsx

read_xlsx(self, path, /, *, sheet=None, range=None, **kwargs)

Read an Excel file into a DuckDB table. This requires duckdb>=1.2.0.

Parameters

Name Type Description Default
path str | Path The path to the Excel file. required
sheet str | None The name of the sheet to read, eg ‘Sheet3’. None
range str | None The range of cells to read, eg ‘A5:Z’. None
kwargs Additional args passed to the backend’s read function. {}

Returns

Name Type Description
ir.Table The just-registered table.

See Also

DuckDB’s excel extension docs for reading

Examples

>>> import os
>>> import ibis
>>> t = ibis.memtable({"a": [1, 2, 3], "b": ["a", "b", "c"]})
>>> con = ibis.duckdb.connect()
>>> con.to_xlsx(t, "/tmp/test.xlsx", header=True)
>>> assert os.path.exists("/tmp/test.xlsx")
>>> t = con.read_xlsx("/tmp/test.xlsx")
>>> t.columns
('a', 'b')

reconnect

reconnect(self)

Reconnect to the database already configured with connect.

register_filesystem

register_filesystem(self, filesystem)

Register an fsspec filesystem object with DuckDB.

This allow a user to read from any fsspec compatible filesystem using read_csv, read_parquet, read_json, etc.

Note

Creating an fsspec filesystem requires that the corresponding backend-specific fsspec helper library is installed.

e.g. to connect to Google Cloud Storage, gcsfs must be installed.

Parameters

Name Type Description Default
filesystem AbstractFileSystem The fsspec filesystem object to register with DuckDB. See https://duckdb.org/docs/guides/python/filesystems for details. required

Examples

>>> import ibis
>>> import fsspec
>>> ibis.options.interactive = True
>>> gcs = fsspec.filesystem("gcs")
>>> con = ibis.duckdb.connect()
>>> con.register_filesystem(gcs)
>>> t = con.read_csv(
...     "gcs://ibis-examples/data/band_members.csv.gz",
...     table_name="band_members",
... )
>>> t
┏━━━━━━━━┳━━━━━━━━━┓
┃ name   ┃ band    ┃
┡━━━━━━━━╇━━━━━━━━━┩
│ string │ string  │
├────────┼─────────┤
│ Mick   │ Stones  │
│ John   │ Beatles │
│ Paul   │ Beatles │
└────────┴─────────┘

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)

Create an Ibis table expression from a SQL query.

Parameters

Name Type Description Default
query str A SQL query string required
schema SchemaLike | None The schema of the query. If not provided, Ibis will try to infer the schema of the query. None
dialect str | None The SQL dialect of the query. If not provided, the backend’s dialect is assumed. This argument can be useful when the query is written in a different dialect from the backend. None

Returns

Name Type Description
ir.Table The table expression representing the query

table

table(self, name, /, *, database=None)

to_csv

to_csv(self, expr, /, path, *, params=None, header=True, **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
header bool Whether to write the column names as the first line of the CSV file. True
kwargs Any DuckDB CSV writer arguments. https://duckdb.org/docs/data/csv/overview.html#parameters {}

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_geo

to_geo(self, expr, /, path, *, format, layer_creation_options=None, params=None, limit=None, **kwargs)

Write the results of executing expr to a geospatial output.

Parameters

Name Type Description Default
expr ir.Table Ibis expression to execute and persist to geospatial output. required
path str | Path A string or Path to the desired output file location. required
format str The format of the geospatial output. One of GDAL’s supported vector formats. The list of vector formats is located here: https://gdal.org/en/latest/drivers/vector/index.html required
layer_creation_options Mapping[str, Any] | None A mapping of layer creation options. None
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. None
kwargs Any Additional keyword arguments passed to the DuckDB COPY command. {}

Examples

>>> import os
>>> import tempfile
>>> import ibis
>>> ibis.options.interactive = True
>>> from ibis import _

Load some geospatial data

>>> con = ibis.duckdb.connect()
>>> zones = ibis.examples.zones.fetch(backend=con)
>>> zones[["zone", "geom"]].head()
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ zone                                  ┃ geom                                 ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ string                                │ geospatial:geometry                  │
├───────────────────────────────────────┼──────────────────────────────────────┤
│                                       │ <POLYGON ((933100.918 192536.086,    │
│ Newark Airport                        │ 933091.011 192572.175, 933088.585    │
│                                       │ 192604.9...>                         │
│                                       │ <MULTIPOLYGON (((1033269.244         │
│ Jamaica Bay                           │ 172126.008, 1033439.643 170883.946,  │
│                                       │ 1033473.265...>                      │
│                                       │ <POLYGON ((1026308.77 256767.698,    │
│ Allerton/Pelham Gardens               │ 1026495.593 256638.616, 1026567.23   │
│                                       │ 256589....>                          │
│                                       │ <POLYGON ((992073.467 203714.076,    │
│ Alphabet City                         │ 992068.667 203711.502, 992061.716    │
│                                       │ 203711.7...>                         │
│                                       │ <POLYGON ((935843.31 144283.336,     │
│ Arden Heights                         │ 936046.565 144173.418, 936387.922    │
│                                       │ 143967.75...>                        │
└───────────────────────────────────────┴──────────────────────────────────────┘

Write to a GeoJSON file

>>> with tempfile.TemporaryDirectory() as tmpdir:
...     con.to_geo(
...         zones,
...         path=os.path.join(tmpdir, "zones.geojson"),
...         format="geojson",
...     )

Write to a Shapefile

>>> with tempfile.TemporaryDirectory() as tmpdir:
...     con.to_geo(
...         zones,
...         path=os.path.join(tmpdir, "zones.shp"),
...         format="ESRI Shapefile",
...     )

to_json

to_json(self, expr, /, path, *, compression='auto', dateformat=None, timestampformat=None)

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

This method is eager and will execute the associated expression immediately. See https://duckdb.org/docs/sql/statements/copy.html#json-options for more info.

Parameters

Name Type Description Default
expr ir.Table The ibis expression to execute and persist to Delta Lake table. required
path str | Path URLs such as S3 buckets are supported. required
compression Literal['auto', 'none', 'gzip', 'zstd'] Compression codec to use. One of “auto”, “none”, “gzip”, “zstd”. 'auto'
dateformat str | None Date format string. None
timestampformat str | None Timestamp format string. None

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 DuckDB Parquet writer arguments. See https://duckdb.org/docs/data/parquet/overview.html#writing-to-parquet-files for details. {}

Examples

Write out an expression to a single parquet file.

>>> import ibis
>>> penguins = ibis.examples.penguins.fetch()
>>> con = ibis.get_backend(penguins)
>>> con.to_parquet(penguins, "/tmp/penguins.parquet")

Write out an expression to a hive-partitioned parquet file.

>>> import tempfile
>>> penguins = ibis.examples.penguins.fetch()
>>> con = ibis.get_backend(penguins)

Partition on a single column.

>>> con.to_parquet(penguins, tempfile.mkdtemp(), partition_by="year")

Partition on multiple columns.

>>> con.to_parquet(penguins, tempfile.mkdtemp(), partition_by=("year", "island"))

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 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, **_)

Return a stream of record batches.

The returned RecordBatchReader contains a cursor with an unbounded lifetime.

For analytics use cases this is usually nothing to fret about. In some cases you may need to explicit release the cursor.

Parameters

Name Type Description Default
expr ir.Expr Ibis expression required
params Mapping[ir.Scalar, Any] | None Bound parameters None
limit int | str | None Limit the result to this number of rows None
chunk_size int The number of rows to fetch per batch 1000000

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.

to_xlsx

to_xlsx(self, expr, /, path, *, sheet='Sheet1', header=False, params=None, **kwargs)

Write a table to an Excel file.

Parameters

Name Type Description Default
expr ir.Table Ibis table expression to write to an excel file. required
path str | Path Excel output path. required
sheet str The name of the sheet to write to, eg ‘Sheet3’. 'Sheet1'
header bool Whether to include the column names as the first row. False
params Mapping[ir.Scalar, Any] | None Additional Ibis expression parameters to pass to the backend’s write function. None
kwargs Any Additional arguments passed to the backend’s write function. {}

Notes

Requires DuckDB >= 1.2.0.

See Also

DuckDB’s excel extension docs for writing

Examples

>>> import os
>>> import ibis
>>> t = ibis.memtable({"a": [1, 2, 3], "b": ["a", "b", "c"]})
>>> con = ibis.duckdb.connect()
>>> con.to_xlsx(t, "/tmp/test.xlsx")
>>> os.path.exists("/tmp/test.xlsx")
True

truncate_table

truncate_table(self, name, /, *, database=None)

Delete all rows from a table.

NoteIbis 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 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
Back to top