17 best Python Dasboard libraries in 2024

Python Dashboard library offers graphs, maps, charts, and tables. Dashboards can be interactive by adding sliders, drop-down lists and buttons. 

It can update the visualizations dynamically. These libraries often offer options for customizing the dashboard's layout, styles, and colors to match specific design requirements. Dashboards can be deployed locally or on the web using a cloud-based platform or a built-in server. These dashboards can integrate with different data sources like APIs, spreadsheets, and databases, making it easier to update the data in real-time. Different users can share and access it through password-protected logins or public URLs. These libraries can come with extensive documentation and community support making it easier to get started and troubleshoot any issues.   

Here is the list of the top 17 Python Dashboard libraries that are handpicked to help developers: 

redash: 

• Is an open source visualization and dashboard platform which will allow users to connect and visualize the data from different sources, like APIs, third-party services, and databases.  
• Is a web-based platform that can be accessed through a browser and is built using JavaScript and Python.  
• Offers a simple and intuitive interface to create and share data visualization, which can be customized to be suitable for individual requirements.   

plotly.py: 

• Is a Python Data visualization that can be used for creating interactive, publication-quality graphs and charts.   
• Allows the creation of interactive visualizations with hover, zoom, and click events, making it easy to explore and analyze data in real time.  
• Allows customization of each aspect of a chart, like fonts, titles, colors, and axis labels.   

flask_jsondash: 

• Is a flask extension to create dashboards and visualizations in Python designed to be customizable, allowing developers to create their own dashboard layouts and widgets.  
• Create custom widgets that interact with the data in real-time, like drop-down lists, buttons, and sliders.  
• Is a good choice for developers creating simple, lightweight dashboards, and visualizations in Python, without learning a more complex framework.   

wave: 

• Is a Python library to build and deploy interactive, web-based dashboards for data exploration and visualization.   
• Integrates seamlessly with H2O.ai's machine learning platform, allowing users to visualize and explore machine learning models.  
• Offers features for sharing and collaboration, like the ability to share dashboards with others and collaborate on projects. 

psdash: 

• Is a Python-based web dashboard for real-time monitoring of process statistics, system resource utilization, and other system-related information.   
• Can be used for identifying and troubleshooting issues, optimizing system performance, and performance bottlenecks.  
• Offers real-time updates of process and system statistics with the ability to refresh data at a customizable interval.   

panel: 

• Is a Python library to create interactive web dashboards and applications and offers a high-level API.  
• Supports different backends like Matplotlib, Holoviews, Bokeh, and Plotly, allowing developers to use their preferred plotting library.  
• Offers reactive widgets that can update in real-time based on user input, allowing interactive and dynamic applications to be created. 

stashboard: 

• Offers a user-friendly interface to monitor system health, uptime, and other key metrics, which can be used to notify users of system issues in real-time.  
• Can be used for monitoring APIs, web services, and other software systems with support for SOAP, REST, and other protocols.  
• Offers custom metrics support, allowing users to monitor system performance using their analytics tools and metrics.   

pygraphistry: 

• Is a Python-based library to visualize large and complex datasets in interactive and visually appealing methods. 
• Offers a graph-based visualization of data which is useful for visualizing connections and relationships between data points.  
• Can be deployed to the cloud, allowing users to access their visualizations from anywhere.   

grafanalib: 

• Is a Python library for programmatically creating dashboards in Grafana, an open source platform for monitoring and analytics.   
• Allows developers to create and manage dashboards using Python code which can be version-controlled and automated.  
• Supports macros and templates, allowing developers to create reusable components for their dashboards. 

flow-dashboard: 

• Is designed to be used with the Flow framework, a web-based platform to build and deploy machine learning models.  
• Can display data from various sources like APIs, streaming services, and databases.  
• Offers built-in user management features allowing administrators to control access to data and dashboards. 

horizon: 

• Is a Python library to build real-time monitoring systems and scalable dashboards.  
• Offers real-time data processing capabilities, allowing users to filter, collect, and process data in real-time.   
• Is designed to be highly scalable with support for distributed processing and horizontal scaling.   

graph-explorer: 

• Is a Python-based library to build a dashboard to display data from different sources, like Prometheus, Elasticsearch, and Graphite.  
• Allows users to create customizable dashboards with the support of various data sources and visualizations.  
• Offers advanced querying capabilities, allowing users to filter and search data.   

django-controlcenter: 

• Is a Python-based library to build reusable and customizable dashboards in Django-based web applications.  
• Allows developers to create dashboards that display data from different sources like APIs, Django models, and other data sources.  
• Offers integration with Django models, allowing developers to display data from their database in their dashboards.   

changes: 

• Is a Python library that offers an easy-to-use interface to monitor file system events like creation, editing, and deletion.  
• Allows developers to create applications that monitor directories and respond to real-time changes.  
• Is a useful tool for creating applications that can monitor file system events in real-time with various integrations and features, making it suited for various use cases. 

bowtie: 

• Is a bioinformatics software tool to align short DNA sequences to large reference genomes.   
• Allows developers to easily create dashboards that display data from different sources like SQL databases, APIs, and CSV files.  
• Offers support for interactive visualizations, like graphs, maps, and charts.   

socialsentiment: 

• Is designed for sentiment analysis of social media data like comments or tweets on online platforms. 
• Uses machine learning algorithms for classifying text as negative, positive, and neutral based on the sentiment expressed in the text. 
• Offers a pre-trained sentiment analysis model which can be trained on a larger corpus of social media data.  

dashboard-api-python: 

• Is a Python library for the Google Analytics Dashboard API which will allow developers to access and retrieve Google Analytics data programmatically using Python. 
• Is designed to make it easier for developers to question and manipulate data in Google Analytics without requiring the API details or how to construct API calls. 
• Includes creating and updating dashboards, managing data sources, and functions for querying data.