Metadata-Version: 2.1
Name: databand
Version: 0.30.6
Summary: Machine Learning Orchestration
Home-page: https://github.com/databand-ai/dbnd
Author: Evgeny Shulman
Author-email: evgeny.shulman@databand.ai
Maintainer: Evgeny Shulman
Maintainer-email: evgeny.shulman@databand.ai
License: UNKNOWN
Project-URL: Documentation, https://dbnd.readme.io/
Project-URL: Bug-Tracker, https://github.com/databand-ai/dbnd/issues
Project-URL: Source-Code, https://github.com/databand-ai/dbnd
Description: [![pipeline status](https://gitlab.com/databand-ai/dbnd/badges/master/pipeline.svg)](https://gitlab.com/databand-ai/dbnd/pipelines)
        
        ![PyPI - Downloads](https://img.shields.io/pypi/dm/dbnd) ![PyPI](https://img.shields.io/pypi/v/dbnd)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/dbnd) ![PyPI - License](https://img.shields.io/pypi/l/dbnd)
        ![Code style: ](https://img.shields.io/badge/code%20style-black-000000.svg)
        
        # 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
        
        ```python
        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
        
        ```python
        from dbnd import log_metric, log_dataframe
        
        log_dataframe("my_dataset", my_dataset)
        log_metric("r2", r2)
        ```
        
        ## Getting Started
        
        See our [documentation](https://dbnd.readme.io/) 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](https://virtualenv.pypa.io/en/latest/) or [Conda](https://docs.conda.io/en/latest/). Update to the latest and greatest:
        
        ```shell script
        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
        
Keywords: orchestration,data,machinelearning
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
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