ibis.connect URL format

Install Ibis in Python and connect to Snowflake for working with in a pandas-like dataframe library

Snowflake

https://www.snowflake.com

Install

Install Ibis and dependencies for the Snowflake backend:

Install with the snowflake extra:

pip install 'ibis-framework[snowflake]'

And connect:

import ibis

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

Install for Snowflake:

conda install -c conda-forge ibis-snowflake

And connect:

import ibis

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

Install for Snowflake:

mamba install -c conda-forge ibis-snowflake

And connect:

import ibis

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

Connect

ibis.snowflake.connect

con = ibis.snowflake.connect(
    user="user",
    password="password",
    account="safpqpq-sq55555",
    database="my_database",
    schema="my_schema",
)
Note

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

Connection Parameters

do_connect

do_connect(['self', 'create_object_udfs=True', '**kwargs'])

Connect to Snowflake.

Parameters
Name Type Description Default
user Username required
account A Snowflake organization ID and a Snowflake user ID, separated by a hyphen. Note that a Snowflake user ID is a separate identifier from a username. See https://ibis-project.org/backends/Snowflake/ for details required
database A Snowflake database and a Snowflake schema, separated by a /. See https://ibis-project.org/backends/Snowflake/ for details required
password Password. If empty or None then authenticator must be passed. required
authenticator String indicating authentication method. See https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example#connecting-with-oauth for details. Note that the authentication flow will not take place until a database connection is made. This means that ibis.snowflake.connect(...) can succeed, while subsequent API calls fail if the authentication fails for any reason. required
create_object_udfs bool Enable object UDF extensions defined by Ibis on the first connection to the database. True
kwargs Any Additional arguments passed to the DBAPI connection call. {}

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

con = ibis.connect(f"snowflake://{user}:{password}@{account}/{database}")

Authenticating with SSO

Ibis supports connecting to SSO-enabled Snowflake warehouses using the authenticator parameter.

You can use it in the explicit-parameters-style or in the URL-style connection APIs. All values of authenticator are supported.

Explicit

con = ibis.snowflake.connect(
    user="user",
    account="safpqpq-sq55555",
    database="my_database",
    schema="my_schema",
    warehouse="my_warehouse",
    authenticator="externalbrowser",
)

URL

con = ibis.connect(
    f"snowflake://{user}@{account}/{database}/{schema}?warehouse={warehouse}",
    authenticator="externalbrowser",
)

Authenticating with Key Pair Authentication

Ibis supports connecting to Snowflake warehouses using private keys.

You can use it in the explicit-parameters-style or in the URL-style connection APIs.

Explicit

con = ibis.snowflake.connect(
    user="user",
    account="safpqpq-sq55555",
    database="my_database",
    schema="my_schema",
    warehouse="my_warehouse",
    # extracted private key from .p8 file
    private_key=os.getenv(SNOWFLAKE_PKEY),
)

URL

con = ibis.connect(
    f"snowflake://{user}@{account}/{database}/{schema}?warehouse={warehouse}",
    private_key=os.getenv(SNOWFLAKE_PKEY),
)

Looking up your Snowflake organization ID and user ID

A Snowflake account identifier consists of an organization ID and a user ID, separated by a hyphen.

Note

This user ID is not the same as the username you log in with.

To find your organization ID and user ID, log in to the Snowflake web app, then click on the text just to the right of the Snowflake logo (in the lower-left-hand corner of the screen).

The bold text at the top of the little pop-up window is your organization ID. The bold blue text with a checkmark next to it is your user ID.

Snowflake Organization and User ID

Choosing a value for database

Snowflake refers to a collection of tables as a schema, and a collection of schema as a database.

You must choose a database and a schema to connect to. You can refer to the available databases and schema in the “Data” sidebar item in the Snowflake web app.

Snowflake Database

snowflake.Backend

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.

Ibis 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 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=False', 'overwrite=False', 'comment=None'])

Create a table in Snowflake.

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 sch.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. 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
comment str | None Add a comment to the table None

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.

Ibis 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 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_object_udfs=True'])

Create an Ibis Snowflake backend from an existing connection.

Parameters

Name Type Description Default
con snowflake.connector.SnowflakeConnection | snowflake.snowpark.Session A Snowflake Connector for Python connection or a Snowpark session instance. required
create_object_udfs bool Enable object UDF extensions defined by Ibis on the first connection to the database. True

Returns

Name Type Description
Backend An Ibis Snowflake backend instance.

Examples

>>> import ibis
>>> ibis.options.interactive = True
>>> import snowflake.snowpark as sp
>>> session = sp.Session.builder.configs(...).create()
>>> con = ibis.snowflake.from_connection(session)
>>> batting = con.tables.BATTING
>>> batting[["playerID", "RBI"]].head()
┏━━━━━━━━━━━┳━━━━━━━┓
┃ playerID  ┃ RBI   ┃
┡━━━━━━━━━━━╇━━━━━━━┩
│ string    │ int64 │
├───────────┼───────┤
│ abercda01 │     0 │
│ addybo01  │    13 │
│ allisar01 │    19 │
│ allisdo01 │    27 │
│ ansonca01 │    16 │
└───────────┴───────┘

from_snowpark

from_snowpark(['cls', 'session', '*', 'create_object_udfs=True'])

Create an Ibis Snowflake backend from a Snowpark session.

Parameters

Name Type Description Default
session snowflake.snowpark.Session A Snowpark session instance. required
create_object_udfs bool Enable object UDF extensions defined by Ibis on the first connection to the database. True

Returns

Name Type Description
Backend An Ibis Snowflake backend instance.

Examples

>>> import ibis
>>> ibis.options.interactive = True
>>> import snowflake.snowpark as sp
>>> session = sp.Session.builder.configs(...).create()
>>> con = ibis.snowflake.from_snowpark(session)
>>> batting = con.tables.BATTING
>>> batting[["playerID", "RBI"]].head()
┏━━━━━━━━━━━┳━━━━━━━┓
┃ playerID  ┃ RBI   ┃
┡━━━━━━━━━━━╇━━━━━━━┩
│ string    │ int64 │
├───────────┼───────┤
│ abercda01 │     0 │
│ addybo01  │    13 │
│ allisar01 │    19 │
│ allisdo01 │    27 │
│ ansonca01 │    16 │
└───────────┴───────┘

get_schema

get_schema(['self', 'table_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.

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
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 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.

Ibis 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
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.

Ibis 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
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.

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 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 Snowflake 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 Snowflake backend.

Parameters

Name Type Description Default
path str | Path A string or Path to a CSV file; globs are supported required
table_name str | None Optional name for the table; if not passed, a random name will be generated None
kwargs Any Snowflake-specific file format configuration arguments. See the documentation for the full list of options: https://docs.snowflake.com/en/sql-reference/sql/create-file-format#type-csv {}

Returns

Name Type Description
Table The table that was read from the CSV file

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'])

Read newline-delimited JSON into an ibis table, using Snowflake.

Parameters

Name Type Description Default
path str | Path A string or Path to a JSON file; globs are supported required
table_name str | None Optional table name None
kwargs Any Additional keyword arguments. See https://docs.snowflake.com/en/sql-reference/sql/create-file-format#type-json for the full list of options. {}

Returns

Name Type Description
Table An ibis table expression

read_parquet

read_parquet(['self', 'path', 'table_name=None', '**kwargs'])

Read a Parquet file into an ibis table, using Snowflake.

Parameters

Name Type Description Default
path str | Path A string or Path to a Parquet file; globs are supported required
table_name str | None Optional table name None
kwargs Any Additional keyword arguments. See https://docs.snowflake.com/en/sql-reference/sql/create-file-format#type-parquet for the full list of options. {}

Returns

Name Type Description
Table An ibis table expression

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.

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'])

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', '**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 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 RecordBatchs.

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.

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 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
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