Pre-release

This release is a pre-release and may not be stable for production use.

Ibis

What is Ibis?

Ibis is the portable Python dataframe library:

Fast local dataframes (via DuckDB by default)
Lazy dataframe expressions
Interactive mode for iterative data exploration
Compose Python dataframe and SQL code
Use the same dataframe API for nearly 20 backends
Iterate locally and deploy remotely by changing a single line of code

See the documentation on "Why Ibis?" to learn more.

Getting started

You can pip install Ibis with a backend and example data:

pip install 'ibis-framework[duckdb,examples]'

💡 Tip

See the installation guide for more installation options.

Then use Ibis:

>>> import ibis
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┓
┃ species ┃ island    ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ body_mass_g ┃ sex    ┃ year  ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━┩
│ string  │ string    │ float64        │ float64       │ int64             │ int64       │ string │ int64 │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼─────────────┼────────┼───────┤
│ Adelie  │ Torgersen │           39.1 │          18.7 │               181 │        3750 │ male   │  2007 │
│ Adelie  │ Torgersen │           39.5 │          17.4 │               186 │        3800 │ female │  2007 │
│ Adelie  │ Torgersen │           40.3 │          18.0 │               195 │        3250 │ female │  2007 │
│ Adelie  │ Torgersen │           NULL │          NULL │              NULL │        NULL │ NULL   │  2007 │
│ Adelie  │ Torgersen │           36.7 │          19.3 │               193 │        3450 │ female │  2007 │
│ Adelie  │ Torgersen │           39.3 │          20.6 │               190 │        3650 │ male   │  2007 │
│ Adelie  │ Torgersen │           38.9 │          17.8 │               181 │        3625 │ female │  2007 │
│ Adelie  │ Torgersen │           39.2 │          19.6 │               195 │        4675 │ male   │  2007 │
│ Adelie  │ Torgersen │           34.1 │          18.1 │               193 │        3475 │ NULL   │  2007 │
│ Adelie  │ Torgersen │           42.0 │          20.2 │               190 │        4250 │ NULL   │  2007 │
│ …       │ …         │              … │             … │                 … │           … │ …      │     … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴─────────────┴────────┴───────┘
>>> g = t.group_by("species", "island").agg(count=t.count()).order_by("count")
>>> g
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━┓
┃ species   ┃ island    ┃ count ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━┩
│ string    │ string    │ int64 │
├───────────┼───────────┼───────┤
│ Adelie    │ Biscoe    │    44 │
│ Adelie    │ Torgersen │    52 │
│ Adelie    │ Dream     │    56 │
│ Chinstrap │ Dream     │    68 │
│ Gentoo    │ Biscoe    │   124 │
└───────────┴───────────┴───────┘

💡 Tip

See the getting started tutorial for a full introduction to Ibis.

Python + SQL: better together

For most backends, Ibis works by compiling its dataframe expressions into SQL:

>>> ibis.to_sql(g)
SELECT
  "t1"."species",
  "t1"."island",
  "t1"."count"
FROM (
  SELECT
    "t0"."species",
    "t0"."island",
    COUNT(*) AS "count"
  FROM "penguins" AS "t0"
  GROUP BY
    1,
    2
) AS "t1"
ORDER BY
  "t1"."count" ASC

You can mix SQL and Python code:

>>> a = t.sql("SELECT species, island, count(*) AS count FROM penguins GROUP BY 1, 2")
>>> a
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━┓
┃ species   ┃ island    ┃ count ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━┩
│ string    │ string    │ int64 │
├───────────┼───────────┼───────┤
│ Adelie    │ Torgersen │    52 │
│ Adelie    │ Biscoe    │    44 │
│ Adelie    │ Dream     │    56 │
│ Gentoo    │ Biscoe    │   124 │
│ Chinstrap │ Dream     │    68 │
└───────────┴───────────┴───────┘
>>> b = a.order_by("count")
>>> b
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━┓
┃ species   ┃ island    ┃ count ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━┩
│ string    │ string    │ int64 │
├───────────┼───────────┼───────┤
│ Adelie    │ Biscoe    │    44 │
│ Adelie    │ Torgersen │    52 │
│ Adelie    │ Dream     │    56 │
│ Chinstrap │ Dream     │    68 │
│ Gentoo    │ Biscoe    │   124 │
└───────────┴───────────┴───────┘

This allows you to combine the flexibility of Python with the scale and performance of modern SQL.

Backends

Ibis supports nearly 20 backends:

How it works

Most Python dataframes are tightly coupled to their execution engine. And many databases only support SQL, with no Python API. Ibis solves this problem by providing a common API for data manipulation in Python, and compiling that API into the backend’s native language. This means you can learn a single API and use it across any supported backend (execution engine).

Ibis broadly supports two types of backend:

SQL-generating backends
DataFrame-generating backends

Ibis backend types

Portability

To use different backends, you can set the backend Ibis uses:

>>> ibis.set_backend("duckdb")
>>> ibis.set_backend("polars")
>>> ibis.set_backend("datafusion")

Typically, you'll create a connection object:

>>> con = ibis.duckdb.connect()
>>> con = ibis.polars.connect()
>>> con = ibis.datafusion.connect()

And work with tables in that backend:

>>> con.list_tables()
['penguins']
>>> t = con.table("penguins")

You can also read from common file formats like CSV or Apache Parquet:

>>> t = con.read_csv("penguins.csv")
>>> t = con.read_parquet("penguins.parquet")

This allows you to iterate locally and deploy remotely by changing a single line of code.

💡 Tip

Check out the blog on backend agnostic arrays for one example using the same code across DuckDB and BigQuery.

Community and contributing

Ibis is an open source project and welcomes contributions from anyone in the community.

Read the contributing guide.
We care about keeping the community welcoming for all. Check out the code of conduct.
The Ibis project is open sourced under the Apache License.

Join our community by interacting on GitHub or chatting with us on Zulip.

For more information visit https://ibis-project.org/.

Governance

The Ibis project is an independently governed open source community project to build and maintain the portable Python dataframe library. Ibis has contributors across a range of data companies and institutions.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ibis_framework-10.0.0.dev415.tar.gz (1.2 MB view details)

Uploaded Dec 29, 2024 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

ibis_framework-10.0.0.dev415-py3-none-any.whl (1.9 MB view details)

Uploaded Dec 29, 2024 Python 3

File details

Details for the file ibis_framework-10.0.0.dev415.tar.gz.

File metadata

Download URL: ibis_framework-10.0.0.dev415.tar.gz
Upload date: Dec 29, 2024
Size: 1.2 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: uv/0.5.13

File hashes

Hashes for ibis_framework-10.0.0.dev415.tar.gz
Algorithm	Hash digest
SHA256	`973e4530b8c1813caf861c18d9e110b2dcb49ff1af3c79ba4f60a0681517f2fa`
MD5	`e31ff092390add5c0807ec56efde617f`
BLAKE2b-256	`e6ff536c627f0f1a8628d1d977e4351786f5bf7d084a619d0eb5cda5cd9b5e6b`

See more details on using hashes here.

File details

Details for the file ibis_framework-10.0.0.dev415-py3-none-any.whl.

File metadata

Download URL: ibis_framework-10.0.0.dev415-py3-none-any.whl
Upload date: Dec 29, 2024
Size: 1.9 MB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: uv/0.5.13

File hashes

Hashes for ibis_framework-10.0.0.dev415-py3-none-any.whl
Algorithm	Hash digest
SHA256	`62ccf3b6b36829a06fdc49a6dd3ad7a0721a719e8ae1d71665c41b916de37f0c`
MD5	`4653c88745b7e1268ecf70a1b3e81810`
BLAKE2b-256	`f32989ce596b6bbe92f50f6e94929f6b770b73f948adcf55c1c5b0f984b1c454`