pip install DataSpyre==0.2.8

Spyre makes it easy to build interactive web applications,and requires no knowledge of HTML, CSS, or Javascript.

Source
Among top 10% packages on PyPI.
Over 10.2K downloads in the last 90 days.

Commonly used with DataSpyre

Based on how often these packages appear together in public requirements.txt files on GitHub.

bhtsne

Python module for Barnes-Hut implementation of t-SNE (Cython)

jupyterlab-git

A server extension for JupyterLab's git extension

jupyter-alabaster-theme

Jupyter Alabaster Theme

jupyterlab-widgets

A JupyterLab extension.

liveplots

Real-time live plot server

Mesa

Agent-based modeling (ABM) in Python 3+

ipysankeywidget

Display Sankey diagrams in Jupyter

jupyter_dashboards

Extension for Jupyter Notebook for laying out, viewing, and deploying notebooks as dynamic dashboards

jupyter_cms

Extension for Jupyter Notebook 4.0.x with experimental content management features

jupyter_declarativewidgets

Jupyter extensions for supporting declarative widgets

pyconsensus

Standalone implementation of Augur's consensus mechanism

sphinx-last-updated-by-git

Get the "last updated" time for each Sphinx page from Git

pygeogrids

Module for creation and handling of discrete global grids

pymining

Small collection of data mining algorithms

matminer

matminer is a library that contains tools for data mining in Materials Science

dHydra

A framework for saving & data mining Chinese Stocks

cmdstanpy

Python interface to CmdStan

fanova

Functional ANOVA: an implementation of the ICML 2014 paper 'An Efficient Approach for Assessing Hyperparameter Importance' by Frank Hutter, Holger Hoos and Kevin Leyton-Brown.

arviz

Exploratory analysis of Bayesian models

Version usage of DataSpyre

Proportion of downloaded versions in the last 3 months (only versions over 1%).

0.2.8

5.77%

0.2.7

3.94%

0.2.6

3.87%

0.2.4

3.61%

0.2.5

3.59%

0.1.8

3.57%

0.2.2

3.57%

0.1.9

3.57%

0.2.3

3.56%

0.1.7

3.56%

0.2.1

3.56%

0.1.1

3.52%

0.1.4

3.52%

0.1.0

3.52%

0.1.6

3.51%

0.1.5

3.51%

0.1.2

3.51%

0.0.1

3.51%

0.0.5

3.51%

0.0.9

3.51%

0.0.2

3.50%

0.0.3

3.50%

0.0.8

3.50%

0.1.3

3.50%

0.0.6

3.50%

0.0.7

3.50%

0.0.4

3.47%

0.2.0

1.80%