Amphi for JupyterLab is a Micro ETL designed for ingesting, cleansing, and processing data from files and databases. Amphi addresses use cases such as data extraction from structured and unstructured data, data preparation and enrichment, and data processing for LLMs-based systems. Use Amphi within the Jupyterlab environment to design your data pipelines with a graphical user-interface and generate native Python code you can deploy anywhere.
📣 Beta release
Amphi for Jupyterlab is currently in beta. To start with Amphi, see below for install instructions.
As Amphi is in beta version, we welcome feedback and suggestions. Join the Slack community or reach out directly at hello@amphi.ai.
If you want to launch Jupyterlab + Amphi, you can run the following commands. It is recommended to a virtual environment (venv or conda for example).
To install perform the following steps, with pip:
pip install --upgrade jupyterlab jupyterlab-amphi
For more installation instructions, visit the docs.
If you already have a Jupyterlab instance, just install the amphi package:
pip install --upgrade jupyterlab-amphi
Alternatively, you can search in the Extension Manager for Amphi.
For more information, see docs.
FAQs
Amphi is a no-code ETL extension for Jupyterlab.
We found that jupyterlab-amphi demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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