Skip to main content

Welcome to Ordeq!

Release Docs PyPI PyPI - Downloads License: MIT

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

To install Ordeq, run:

uv pip install ordeq

Integrations

Ordeq integrates seamlessly with existing tooling. It provides integrations with many popular libraries out of the box. 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
Matplotlib
Matplotlib
Joblib
Joblib
HuggingFace
HuggingFace
SentenceTransformers
st
Requests
Requests
Pydantic
Pydantic
DuckDB
DuckDB
Altair
Altair
Networkx
NetworkX
TOML
TOML
PyMuPDF
PyMuPDF

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

Cloud storage

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

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:

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.

Metadata

Release files for ordeq_args 1.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ordeq_args 1.0.2
File Size Uploaded Provenance Actions
ordeq_args-1.0.2.tar.gz 9.3 kB Without provenance Details for ordeq_args-1.0.2.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for ordeq_args 1.0.2
File Interpreter ABI Platform Actions
ordeq_args-1.0.2-py3-none-any.whl Python 3 none any Details for ordeq_args-1.0.2-py3-none-any.whl

Total release size: 17.0 kB

Release files / ordeq_args-1.0.2.tar.gz

Download URL ordeq_args-1.0.2.tar.gz
Size 9.3 kB
Tags Source
SHA-256 checksum
How to use checksums
181cac2181bd6f89a27e5f4f76c0ec92517489e48ec08070ee3052d74c6853b4
BLAKE2b-256 checksum
How to use checksums
18ccf56560f9c86f99250ad1dc9c07f62517d325051e5b36d5688209b091cfbc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.9.3

Release files / ordeq_args-1.0.2-py3-none-any.whl

Download URL ordeq_args-1.0.2-py3-none-any.whl
Size 7.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8d7c41339da80c3ca6caa7e4b8476010ea53e4d6efec7077865b32aa872c63f8
BLAKE2b-256 checksum
How to use checksums
39503f636027f7cce9b2d661bd93c7a2fd404cfc2a77f00d181f922aaf44bbd8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.9.3

Security for ordeq_args 1.0.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page