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https://github.com/ibis-project/ibis

the portable Python dataframe library
https://github.com/ibis-project/ibis

bigquery clickhouse database datafusion duckdb impala mssql mysql pandas polars postgresql pyarrow pyspark python snowflake sql sqlite trino

Last synced: 3 days ago
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the portable Python dataframe library

Host: GitHub
URL: https://github.com/ibis-project/ibis
Owner: ibis-project
License: apache-2.0
Created: 2015-04-17T20:43:46.000Z (over 9 years ago)
Default Branch: main
Last Pushed: 2024-10-29T10:33:17.000Z (about 1 month ago)
Last Synced: 2024-10-29T12:13:03.516Z (about 1 month ago)
Topics: bigquery, clickhouse, database, datafusion, duckdb, impala, mssql, mysql, pandas, polars, postgresql, pyarrow, pyspark, python, snowflake, sql, sqlite, trino
Language: Python
Homepage: https://ibis-project.org
Size: 133 MB
Stars: 5,240
Watchers: 85
Forks: 591
Open Issues: 241
Metadata Files:
- Readme: README.md
- Contributing: docs/CONTRIBUTING.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md

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my-awesome-starred - ibis - Productivity-centric Python data analysis framework for SQL systems and the Hadoop platform. Co-founded by the creator of pandas (Python)
best-of-python - GitHub - 9% open · ⏱️ 05.06.2024): (Database Clients)
awesome-dataframes - Ibis - A pandas-like deferred expression system, with first-class SQL support. (Libraries)
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pytrade.org - ibis

README

        # Ibis

[![Documentation status](https://img.shields.io/badge/docs-docs.ibis--project.org-blue.svg)](http://ibis-project.org)

[![Project chat](https://img.shields.io/badge/zulip-join_chat-purple.svg?logo=zulip)](https://ibis-project.zulipchat.com)

[![Anaconda badge](https://anaconda.org/conda-forge/ibis-framework/badges/version.svg)](https://anaconda.org/conda-forge/ibis-framework)

[![PyPI](https://img.shields.io/pypi/v/ibis-framework.svg)](https://pypi.org/project/ibis-framework)

[![Build status](https://github.com/ibis-project/ibis/actions/workflows/ibis-main.yml/badge.svg)](https://github.com/ibis-project/ibis/actions/workflows/ibis-main.yml?query=branch%3Amain)

[![Build status](https://github.com/ibis-project/ibis/actions/workflows/ibis-backends.yml/badge.svg)](https://github.com/ibis-project/ibis/actions/workflows/ibis-backends.yml?query=branch%3Amain)

[![Codecov branch](https://img.shields.io/codecov/c/github/ibis-project/ibis/main.svg)](https://codecov.io/gh/ibis-project/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](#python--sql-better-together)

- Use the same dataframe API for [nearly 20 backends](#backends)

- Iterate locally and deploy remotely by [changing a single line of code](#portability)

See the documentation on ["Why Ibis?"](https://ibis-project.org/why) to learn more.

## Getting started

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

```bash

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

```

> 💡 **Tip**

>

> See the [installation guide](https://ibis-project.org/install) for more installation options.

Then use Ibis:

```python

>>> 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](https://ibis-project.org/tutorials/getting_started) for a full introduction to Ibis.

## Python + SQL: better together

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

```python

>>> 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:

```python

>>> 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:

- [Apache DataFusion](https://ibis-project.org/backends/datafusion/)

- [Apache Druid](https://ibis-project.org/backends/druid/)

- [Apache Flink](https://ibis-project.org/backends/flink)

- [Apache Impala](https://ibis-project.org/backends/impala/)

- [Apache PySpark](https://ibis-project.org/backends/pyspark/)

- [BigQuery](https://ibis-project.org/backends/bigquery/)

- [ClickHouse](https://ibis-project.org/backends/clickhouse/)

- [DuckDB](https://ibis-project.org/backends/duckdb/)

- [Exasol](https://ibis-project.org/backends/exasol)

- [MySQL](https://ibis-project.org/backends/mysql/)

- [Oracle](https://ibis-project.org/backends/oracle/)

- [Polars](https://ibis-project.org/backends/polars/)

- [PostgreSQL](https://ibis-project.org/backends/postgresql/)

- [RisingWave](https://ibis-project.org/backends/risingwave/)

- [SQL Server](https://ibis-project.org/backends/mssql/)

- [SQLite](https://ibis-project.org/backends/sqlite/)

- [Snowflake](https://ibis-project.org/backends/snowflake)

- [Trino](https://ibis-project.org/backends/trino/)

## 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:

1. SQL-generating backends

2. DataFrame-generating backends

![Ibis backend types](./docs/images/backends.png)

## Portability

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

```python

>>> ibis.set_backend("duckdb")

>>> ibis.set_backend("polars")

>>> ibis.set_backend("datafusion")

```

Typically, you'll create a connection object:

```python

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

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

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

```

And work with tables in that backend:

```python

>>> con.list_tables()

['penguins']

>>> t = con.table("penguins")

```

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

```python

>>> 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](https://ibis-project.org/posts/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](https://github.com/ibis-project/ibis/blob/main/docs/CONTRIBUTING.md).

- We care about keeping the community welcoming for all. Check out [the code of conduct](https://github.com/ibis-project/ibis/blob/main/CODE_OF_CONDUCT.md).

- The Ibis project is open sourced under the [Apache License](https://github.com/ibis-project/ibis/blob/main/LICENSE.txt).

Join our community by interacting on GitHub or chatting with us on [Zulip](https://ibis-project.zulipchat.com/).

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

## Governance

The Ibis project is an [independently governed](https://github.com/ibis-project/governance/blob/main/governance.md) open source community project to build and maintain the portable Python dataframe library. Ibis has contributors across a range of data companies and institutions.