Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science. Build an app in a few lines of code with magically simple API. Adding a widget is the same as declaring a variable. No need to write a backend, define routes etc. Effortlessly share, manage, and collaborate on your apps directly from Streamlit. Apps are deployed directly from Github repo.

Streamlit - The fastest way to build data apps in Python

Mesa is an Apache2 licensed agent-based modeling (or ABM) framework in Python.It allows users to quickly create agent-based models using built-in core components (such as spatial grids and agent schedulers) or customized implementations; visualize them using a browser-based interface; and analyze their results using Python's data analysis tools. Its goal is to be the Python 3-based alternative to NetLogo, Repast, or MASON.

Mesa is a agent-based modeling framework in Python

Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. It easily integrates your data, using either our simple no-code viz builder or state of the art SQL IDE. Superset can query data from any SQL-speaking datastore or data engine (e.g. Presto or Athena) that has a Python DB-API driver and a SQLAlchemy dialect.
 
Superset provides: 
<ul>
<li>An intuitive interface for visualizing datasets and
crafting interactive dashboards</li>
<li>A wide array of beautiful visualizations to showcase your data</li>
<li>Code-free visualization builder to extract and present datasets</li>
<li>A world-class SQL IDE for preparing data for visualization, including a rich metadata browser</li>
<li>A lightweight semantic layer which empowers data analysts to quickly define custom dimensions and metrics</li>
<li>Out-of-the-box support for most SQL-speaking databases</li>
<li>Seamless, in-memory asynchronous caching and queries</li>
<li>An extensible security model that allows configuration of very intricate rules on
on who can access which product features and datasets.</li>
<li>Integration with major
authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, etc)</li>
<li>The ability to add custom visualization plugins</li>
<li>An API for programmatic customization</li>
<li>A cloud-native architecture designed from the ground up for scale</li>
</ul>

Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. It easily integrates your data, using either our simple no-code viz builder or state of the art SQL IDE. Superset can query data from any SQL-speaking datastore or data engine (e.g. Presto or Athena) that has a Python DB-API driver and a SQLAlchemy dialect.

Apache Superset is a Data Visualization and Data Exploration Platform 

Elementary was built out of the need to effortlessly and immediately gain visibility into the data stack, starting with tracing the actual upstream & downstream dependencies in the data warehouse, without any implementation efforts, security risks or compromises on accuracy.
 
Features:
<ul><li>Lineage visualization: Visual map of data flow and dependencies in the data warehouse.&nbsp;</li><li>Dataset status: Present data about freshness and volume on the lineage graph.</li><li>Accuracy: Reflects the actual state in the DWH based on logs.</li><li>Plug-and-play: No need for code changes.</li><li>Graph filters: Filter the graph by dataset, dates, direction and depth.</li></ul>

Elementary was built out of the need to effortlessly and immediately gain visibility into the data stack, starting with tracing the actual upstream & downstream dependencies in the data warehouse, without any implementation efforts, security risks or compromises on accuracy.

Elementary - Data observability platform for modern data teams that is open and transparent

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Streamlit - The fastest way to build data apps in Python

Mesa is a agent-based modeling framework in Python

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Streamlit - The fastest way to build data apps in Python

Mesa is a agent-based modeling framework in Python

Apache Superset is a Data Visualization and Data Exploration Platform

Elementary - Data observability platform for modern data teams that is open and transparent

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