Skip to main content

Machine Learning Orchestration

Project description

pipeline status

PyPI - Downloads PyPI PyPI - Python Version PyPI - License Code style:

DBND

DBND an open source framework for building and tracking data pipelines. DBND is used for processes ranging from data ingestion, preparation, machine learning model training and production.

DBND includes a Python library, set of APIs, and CLI that enables you to collect metadata from your workflows, create a system of record for runs, and easily orchestrate complex processes.

DBND simplifies the process of building and running data pipelines from dbnd import task

from dbnd import task

@task
def say_hello(name: str = "databand.ai") -> str:
    value = "Hello %s!" % name
    return value

And makes it easy to track your critical pipeline metadata

from dbnd import log_metric, log_dataframe

log_dataframe("my_dataset", my_dataset)
log_metric("r2", r2)

Getting Started

See our documentation with examples and quickstart guides to get up and running with DBND.

The Latest and Greatest

For using DBND, we recommend that you work with a virtual environment like Virtualenv or Conda. Update to the latest and greatest:

pip install dbnd

If you would like access to our latest features, or have any questions, feedback, or contributions we would love to here from you! Get in touch through contact@databand.ai

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

databand-0.76.1.tar.gz (11.1 kB view details)

Uploaded Source

Built Distribution

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

databand-0.76.1-py2.py3-none-any.whl (6.8 kB view details)

Uploaded Python 2Python 3

File details

Details for the file databand-0.76.1.tar.gz.

File metadata

  • Download URL: databand-0.76.1.tar.gz
  • Upload date:
  • Size: 11.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.3 CPython/3.9.11

File hashes

Hashes for databand-0.76.1.tar.gz
Algorithm Hash digest
SHA256 7051146664bc0a3c0670f13ca4ec83f6259f7d36b4cf6946ff8b925916218128
MD5 5f926b9b625932b31facd082fda94166
BLAKE2b-256 b61d119e78b893f062426d4627300b4d29545170bc9d0df0b6c9a4b86784e4eb

See more details on using hashes here.

File details

Details for the file databand-0.76.1-py2.py3-none-any.whl.

File metadata

  • Download URL: databand-0.76.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 6.8 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.3 CPython/3.9.11

File hashes

Hashes for databand-0.76.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 7d2837aeda04099b30c73cb415d9fb4862e467ab755013804a5f3e7d4465c1d2
MD5 bf0ac1b8ff355691ddf3146b3670d501
BLAKE2b-256 56efb9af61a89070159f8943cd92f15c54cec8e0f19e8150a5456317ff32feb6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page