LCDP for rapid web application development and sharing of machine learning models.
A low-code development platform (LCDP) provides a development environment used to create application software through a graphical user interface instead of traditional hand-coded computer programming.
In this article, let’s go through some of the open-source low code development platforms or frameworks for web application development, business intelligence, and sharing of machine learning models. If you find yourself tired of writing CRUD operations and APIs repeatedly, you may want to try out these platforms or frameworks.
Some of them may not necessarily have a graphical user interface, but they provide a framework that makes it very easy to develop a full-fledged web application.
LCDP for Web Application Development
- UI Components: Table, Chart, Form, Map, Image, Video, and many more.
- API Support: REST APIs, OAuth 2.0, CURL
- Database Support: PostgreSQL, MongoDB, MySQL, Firestore, S3, Redshift, Elastic Search, DynamoDB, Redis, and MSFT SQL Server
- Hosting: Cloud-hosted & On-premise
Lowdefy is an open-source (Apache-2.0) low-code framework that lets you build web apps with YAML configuration files. It is great for building admin panels, BI dashboards, workflows, and CRUD apps.
User interfaces in Lowdefy are built using blocks, which are React components. Lowdefy provides a set of default block types with the essentials needed to build an app, but you can also create your own custom blocks. Lowdefy uses webpack module federation to import these blocks as micro front-ends.
- Automatic menu generation.
- Automatic CRUD generation.
- Multiple actions on database records.
- Big variety of filters for your lists.
- Various view widgets: lists, master-detail, list of thumbnails, etc
- Select2, Datepicker, DateTimePicker
- Google charts with an automatic group by or direct values and filters.
Django is a high-level Python Web framework that makes it very easy for rapid web development. Django is definitely one of the most widely used frameworks for Python developers.
With some Python basics, you should be able to create a full-fledged app using Django.
react-admin + strapi
strapi is an open-source headless CMS to build powerful APIs with no effort.
With these 2 combined, you can quickly build your front-end and back-end easily.
ToolJet is an open-source low-code framework to build and deploy internal tools quickly.
You can connect to your data sources such as databases ( PostgreSQL, MongoDB, MySQL, Elasticsearch, Firestore, DynamoDB, and more ), API endpoints ( ToolJet supports importing OpenAPI spec & OAuth2 authorization), and external services ( Stripe, Slack, Google Sheets, etc ) and use pre-built UI widgets to build internal tools.
It provides a visual app builder with widgets and supports mobile and desktop layouts. For deployment, you can deploy it using Docker, Kubernetes, Heroku, and more.
LCDP for Machine Learning
For data scientists or machine learning engineers, Dash is definitely no stranger to them. It abstracts away all of the technologies and protocols that are required to build an interactive web-based analytics application. Dash is simple enough that you can bind a user interface around your Python code in an afternoon.
Built on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical Python code.
Gradio allows you to quickly create customizable UI components around your TensorFlow or PyTorch models, or even arbitrary Python functions.
With just a few lines of code, you can generate a user interface for your machine learning model.
import gradio as gr
# ... implement digit recognition model on input array
# ... return dictionary of labels and confidences
gr.Interface(fn=recognize_digit, inputs="sketchpad", outputs="label").launch()
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.
With just a few lines of code, you can create an impressive application to share your machine learning model.
LCDP for Business Intelligence
Using Metabase, you can easily develop beautiful dashboards which provide meaningful insights into your data.
Apache Superset is a data visualization and data exploration platform.
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 an SQLAlchemy dialect.
It provides an intuitive interface for data visualization, ready-to-use visualizations, the ability to custom develop plugins, and many more features.
And lastly, let’s also look into NocoDB which is an interesting application to turn any MySQL, PostgreSQL, SQL Server, SQLite & MariaDB into a smart spreadsheet.
It provides a rich spreadsheet interface for you to search, sort filter table columns, display images and create customized views for the tables.
You can even create and automate workflow using MS Teams, Slack, Discord, Email, SMS, Whatsapp, or using any 3rd party APIs. Programmatic API access is also provided using REST or GraphQL APIs.
You may also want to check out these articles!
Serving Machine Learning Models (DCGAN, PGAN, ResNext) using FastAPI and Streamlit