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
Seattle Weather

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-0.4.2a6.tar.gz (174.9 kB view details)

Uploaded Source

Built Distribution

lumen-0.4.2a6-py2.py3-none-any.whl (55.4 kB view details)

Uploaded Python 2Python 3

File details

Details for the file lumen-0.4.2a6.tar.gz.

File metadata

  • Download URL: lumen-0.4.2a6.tar.gz
  • Upload date:
  • Size: 174.9 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-0.4.2a6.tar.gz
Algorithm Hash digest
SHA256 4bfaf67c5c95c3d1c89fd7431cbf2845e775318f7a29c754dd8f26e56574aa7a
MD5 d42f564bb39e40d2b9e35eae3f7765c4
BLAKE2b-256 b9e97c00c6986707c93ef1c1f3419b50c77ea755731a305c1fefda537ef4dee3

See more details on using hashes here.

File details

Details for the file lumen-0.4.2a6-py2.py3-none-any.whl.

File metadata

  • Download URL: lumen-0.4.2a6-py2.py3-none-any.whl
  • Upload date:
  • Size: 55.4 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-0.4.2a6-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 066c223110bd0252c0bd0d4f94d46201cca2c20c98fd9614a86b752556b62705
MD5 26718928b8b67a967c54b0438f5c240a
BLAKE2b-256 09feaf4359084ef528be8ff69209fe65ad0300bcf2547b80637f56c2fc5d2e6c

See more details on using hashes here.

Supported by

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