How to turn my data processing code into a pipeline?

This page summarizes the projects mentioned and recommended in the original post on /r/dataengineering

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  • ploomber

    The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

    If you're working with .py or .ipynb I recommend ploomber, there's lots of flexibility on the input/output formats and you can interactively check out your data and work with Git. There's also an automatic tool that converts it to a pipeline for you via the H2 headings.

  • soorgeon

    Convert monolithic Jupyter notebooks 📙 into maintainable Ploomber pipelines. 📊

    If you're working with .py or .ipynb I recommend ploomber, there's lots of flexibility on the input/output formats and you can interactively check out your data and work with Git. There's also an automatic tool that converts it to a pipeline for you via the H2 headings.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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