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Ordeq integration for Google BigQuery

Project description

Welcome to Ordeq!

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Ordeq is a framework for developing data pipelines. It simplifies IO and modularizes pipeline logic. Ordeq elevates your proof-of-concept to a production-grade pipelines. See the introduction for an easy-to-follow example of how Ordeq can help.

Installation

Ordeq is lightweight with 0 dependencies.

To install Ordeq, run:

uv pip install ordeq

Integrations

Ordeq integrates seamlessly with existing tooling. It provides out-of-the-box integrations with 25+ popular libraries. In total, Ordeq offers over 100 IOs via these integrations.

You can install them as needed. For example, for reading and writing data with Pandas, install the ordeq-pandas package:

uv pip install ordeq-pandas

Some of the available integrations:

Data processing

Pandas
Pandas
Spark
Spark
NumPy
Numpy
Polars
Polars
Ibis
Ibis
Joblib
Joblib
HuggingFace
HuggingFace
Pillow
Pillow
SentenceTransformers
st
Requests
Requests
Pydantic
Pydantic
DuckDB
DuckDB
Networkx
NetworkX
TOML
TOML
PyMuPDF
PyMuPDF
ChromaDB
ChromaDB

Plotting

Matplotlib
Matplotlib
Altair
Altair
Plotly Express
Plotly Express

Cloud storage

Google Cloud Storage
Google Cloud Storage
Azure
Azure Storage Blob
AWS S3
AWS S3
Boto3
Boto3
Bigquery
Bigquery

Have a look at the package overview and API reference for a list of available packages.

Documentation

Documentation is available at https://ing-bank.github.io/ordeq/.

Why consider Ordeq?

  • Ordeq is the GenAI companion: it gives your project structure and consistency, such that GenAI can thrive
  • It offers seamless integrations with existing data & ML tooling, such as Spark, Pandas, Pydantic and PyMuPDF, and adding new integrations is trivial
  • It's actively developed and trusted by data scientists, engineers, analysts and machine learning engineers at ING

Learning Ordeq

To learn more about Ordeq, check out the following resources:

Visualizing pipelines

Ordeq makes it easy to visualize your pipelines like this with a single line of code. Read more in the documentation.

The following figure shows an example Ordeq pipeline of a Retrieval-Augmented Generation (RAG) pipeline visualized with Mermaid:

RAG pipeline

Acknowledgements

Ordeq builds upon design choices and ideas from Kedro and other frameworks. It has been developed at ING, with contributions from various individuals. Please refer to the acknowledgements section in the documentation for more details.

License

Ordeq is available under the MIT license. Please refer to the license and notice for more details.

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