Skip to main content

Amphi is a no-code ETL extension for Jupyterlab.

Project description

Micro ETL for Jupyterlab

jupyter-lab-amph-screenshot

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.

Requirements

  • JupyterLab >= 4.0

Install Jupyterlab + Amphi

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.

Install Amphi on an existing Jupyterlab instance

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.

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

jupyterlab_amphi-0.5.4.tar.gz (9.5 MB view details)

Uploaded Source

Built Distribution

jupyterlab_amphi-0.5.4-py3-none-any.whl (4.7 MB view details)

Uploaded Python 3

File details

Details for the file jupyterlab_amphi-0.5.4.tar.gz.

File metadata

  • Download URL: jupyterlab_amphi-0.5.4.tar.gz
  • Upload date:
  • Size: 9.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for jupyterlab_amphi-0.5.4.tar.gz
Algorithm Hash digest
SHA256 650d5f2efd448970f6f5dd50197a5e1cff5ae1b4f2a53dffe5d77fac6a0145b1
MD5 b570518ed22d61d126a2ada65d7ed351
BLAKE2b-256 c2185b64be2102727523a9bfd9226facedcf0d2d8894495519140e14ad938fa6

See more details on using hashes here.

File details

Details for the file jupyterlab_amphi-0.5.4-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyterlab_amphi-0.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 5d4ae29e02904aeed503ffa10c66070c4fcb2e437b96739523592754a6b53489
MD5 3428ccd92302e6bc08b359da9a8b5321
BLAKE2b-256 6f2b0269b0e78b368694d1757c8800893853e81bb706f56c6a996412b825814f

See more details on using hashes here.

Supported by

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