Skip to main content

A monitoring solution built on Panel.

Project description

Lumen

Illuminate your data

Build Status Linux/MacOS/Windows Build Status
Coverage codecov
Latest dev release Github tag dev-site
Latest release Github release PyPI version lumen version conda-forge version defaults version
Docs gh-pages site
Support Discourse

Why Lumen?

The Lumen project provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification. The power of Lumen comes from the ability to leverage the powerful data intake, data processing and data visualization libraries available in the PyData ecosystem.

  • Data Intake: A flexible system for declaring data sources with strong integration with Intake, allows Lumen to query data from a wide range of sources including many file formats such as CSV or Parquet but also SQL and many others.
  • Data Proccessing: Internally Lumen stores data as DataFrame objects, allowing users to leverage familiar APIs for filtering and transforming data using Pandas while also providing the ability to scale these transformations out to a cluster thanks to Dask.
  • Data Visualization: Since Lumen is built on Panel all the most popular plotting libraries and many other components such as powerful datagrids and BI indicators are supported.

The core strengths of Lumen include:

  • Flexibility: The design of Lumen allows flexibly combining data intake, data processing and data visualization into a simple declarative pipeline.
  • Extensibility: Every part of Lumen is designed to be extended letting you define custom Source, Filter, Transform and View components.
  • Scalability: Lumen is designed with performance in mind and supports scalable Dask DataFrames out of the box, letting you scale to datasets larger than memory or even scale out to a cluster.
  • Security: Lumen ships with a wide range of OAuth providers out of the box, making it a breeze to add authentication to your applications.

Examples

London Bike Points
NYC Taxi
Palmer Penguins
Precipitation

Getting started

Lumen works with Python 3 and above on Linux, Windows, or Mac. The recommended way to install Lumen is using the conda command provided by Anaconda or Miniconda:

conda install -c pyviz lumen

or using PyPI:

pip install lumen

Once installed you will be able to start a Lumen server by running:

lumen serve dashboard.yaml --show

This will open a browser serving the application or dashboard declared by your yaml file in a browser window. During development it is very helpful to use the --autoreload flag, which will automatically refresh and update the application in your browser window, whenever you make an edit to the dashboard yaml specification. In this way you can quickly iterate on your dashboard.

Try it out! Click on one of the examples below, copy the yaml specification and launch your first Lumen application.

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

lumen-0.3.3a2.tar.gz (45.2 kB view details)

Uploaded Source

Built Distribution

lumen-0.3.3a2-py2.py3-none-any.whl (50.1 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file lumen-0.3.3a2.tar.gz.

File metadata

  • Download URL: lumen-0.3.3a2.tar.gz
  • Upload date:
  • Size: 45.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.7.10

File hashes

Hashes for lumen-0.3.3a2.tar.gz
Algorithm Hash digest
SHA256 4a1d3d21657e0effc317e8b087fd3f7997777aa31de8def361e0d8b1f6b338f2
MD5 0bf5bfe47d421c0820b7c48f521b1e8c
BLAKE2b-256 60ce0273e55aa5cd87c3b2750c04fba8a8b9dbff9aa05be29069f8ee0d3d1387

See more details on using hashes here.

Provenance

File details

Details for the file lumen-0.3.3a2-py2.py3-none-any.whl.

File metadata

  • Download URL: lumen-0.3.3a2-py2.py3-none-any.whl
  • Upload date:
  • Size: 50.1 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.7.10

File hashes

Hashes for lumen-0.3.3a2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 848caf7f3568a7ac49ba917d7af978b25cfbbedad584e7df9a0c2f49500d3f57
MD5 c156a7c48a370b2b056751777395b784
BLAKE2b-256 59b9aabf4cc2e7aae757e3ffe95b5818a88f68e5f9b1ac4dfb3a046103e346f7

See more details on using hashes here.

Provenance

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