RRP Defence (RRP Group), through its entity Vimananu, has entered into a strategic partnership with the Franco-American firm CYGR to establish an advanced drone manufacturing facility in India. 

The project, based in Navi Mumbai, aims to support India’s ‘Make in India’ initiative by developing unmanned aerial vehicles (UAVs) for defence, surveillance, and industrial applications.

The collaboration will manufacture three categories of drones: hand-launched fixed-wing drones for field operations, compact nano drones for close-range use, and ISR drones tailored for intelligence, surveillance, and reconnaissance missions. 

Production is expected to start with hundreds of units annually, with an initial contract valued at over $20 million.

Rajendra Chodankar, chairman of RRP Defence, said, “This collaboration is a defining moment for India’s UAV ecosystem. By combining our local manufacturing strength and field understanding with CYGR’s world-class drone technologies, we’re building systems that meet India’s unique operational needs.”

The facility will also contribute to high-skill employment and export-focused manufacturing, further positioning India as a key player in the global UAV supply chain.

The initiative strengthens India’s self-reliance in aerospace and defence technology. Zaynah, the global advisor in Make in India global exports in defence for the collaboration, confirmed that an immediate Letter of Intent (LoI) is being released as part of the $20 million contract for global defence exports.

George El Aily, director of CYGR France, added, “India is a key strategic partner for us. Through this collaboration with RRP Defence Ltd, we are not only transferring technology but also co-developing future-ready solutions that support India’s defence and surveillance landscape.”

The project will focus on sectors including defence, homeland security, and industrial monitoring. The companies aim to deliver solutions customised for India’s operational environments while expanding global market access through technology localisation.

This joint venture marks a step forward in India’s ambition to become a global drone hub through international cooperation and indigenous expertise.

Figure AI, a California-based robotics company, introduced its third-generation battery for its latest F03 humanoid robot, marking a significant step in its in-house hardware development. 

The new battery offers 2.3 kWh of energy, supports five hours of peak performance runtime, and includes built-in safety systems to prevent thermal runaway. The battery is manufactured entirely in-house at Figure’s BotQ facility, which is now ramping up production capabilities.

Today we’re introducing our next generation humanoid battery for F.03

Like our actuators, vertically integrating our battery system is critical to Figure’s success

Engineered in-house and manufactured at BotQ pic.twitter.com/lw81dXZ9qO

— Figure (@Figure_robot) July 17, 2025

Founder Brett Adcock said in a LinkedIn post that Figure “succeeds when we own the full stack,” with every core system, including actuators and batteries, engineered and built internally. 

The battery is the first in the humanoid robotics space to be in the process of securing both UN38.3 and UL2271 safety certifications.

The F03 battery is directly integrated into the robot’s torso, unlike the earlier external battery packs of the F01. It utilises structural components such as stamped steel and die-cast aluminium, allowing it to act as a load-bearing part of the robot and saving space and weight.

The company claims a 94% increase in energy density over its first-generation battery and a 78% cost reduction compared to the previous F.02 model. The battery’s structural and thermal design features active cooling, a flame arrestor vent, and a custom Battery Management System (BMS) that helps prevent fault conditions, such as overheating or short circuits.

The battery is manufactured using mass production techniques, including stamping, injection moulding, and die casting, which enables Figure to target production volumes of up to 12,000 humanoid units per year.

To support manufacturing scale-up at its BotQ facility, Figure has opened roles across several verticals, including software test engineering, electrical testing, manufacturing engineering, and equipment handling.

Recently, Adcock had also said that the company has tripled the team to 293 people to support manufacturing, supply chain, and fleet operations.

According to the company’s blog, Figure has collaborated with OSHA-accredited testing labs to establish safety standards for humanoid robots, as these standards did not previously exist. “We specified that the battery system of F.03 must not emit flames should a catastrophic failure of a single cell occur,” Figure said.

Image by Author | Canva

Python is widely known for its popularity among engineers and data scientists, but it’s also a favorite choice for web developers. In fact, many developers prefer Python over JavaScript for building web applications because of its simple syntax, readability, and the vast ecosystem of powerful frameworks and tools available.

Whether you are a beginner or an experienced developer, Python offers frameworks that cater to every need, from lightweight micro-frameworks that require just a few lines of code, to robust full-stack solutions packed with built-in features. Some frameworks are designed for rapid prototyping, while others focus on security, scalability, or lightning-fast performance. 

In this article, we will review seven of the most popular Python web frameworks. You will discover which ones are best suited for building anything from simple websites to complex, high-traffic web applications. No matter your experience level, there is a Python framework that can help you bring your web project to life efficiently and effectively.

Python Web Development Frameworks

1. Django: The Full-Stack Powerhouse for Scalable Web Apps

Django is a robust, open-source Python framework designed for rapid development of secure and scalable web applications. With its built-in ORM, admin interface, authentication, and a vast ecosystem of reusable components, Django is ideal for building everything from simple websites to complex enterprise solutions. 

Learn more: https://www.djangoproject.com/

2. Flask: The Lightweight and Flexible Microframework

Flask is a minimalist Python web framework that gives you the essentials to get started, while letting you add only what you need. It’s perfect for small to medium-sized applications, APIs, and rapid prototyping. Flask’s simplicity, flexibility, and extensive documentation make it a top choice for developers who want full control over their project’s architecture.

Learn more: https://flask.palletsprojects.com/

3. FastAPI: Modern, High-Performance APIs with Ease

FastAPI is best known for building high-performance APIs, but with Jinja templates (v2), you can also create fully-featured websites that combine both backend and frontend functionality within the same framework. Built on top of Starlette and Pydantic, FastAPI offers asynchronous support, automatic interactive documentation, and exceptional speed, making it one of the fastest Python web frameworks available.

Learn more: https://fastapi.tiangolo.com/

4. Gradio: Effortless Web Interfaces for Machine Learning

Gradio is an open-source Python framework that allows you to rapidly build and share web-based interfaces for machine learning models. It is highly popular among the machine learning community, as you can build, test, and deploy your ML web demos on Hugging Face for free in just minutes. You don’t need front-end or back-end experience; just basic Python knowledge is enough to create high-performance web demos and APIs.

Learn more: https://www.gradio.app/

5. Streamlit: Instantly Build Data Web Apps

Streamlit is designed for data scientists and engineers who want to create beautiful, interactive web apps directly from Python scripts. With its intuitive API, you can build dashboards, data visualizations, and ML model demos in minutes.No need for HTML, CSS, or JavaScript. Streamlit is perfect for rapid prototyping and sharing insights with stakeholders.

Learn more: https://streamlit.io/

6. Tornado: Scalable, Non-Blocking Web Server and Framework

Tornado is a powerful Python web framework and asynchronous networking library, designed for building scalable and high-performance web applications. Unlike traditional frameworks, Tornado uses a non-blocking network I/O, which makes it ideal for handling thousands of simultaneous connections, perfect for real-time web services like chat applications, live updates, and long polling.

Learn more: https://www.tornadoweb.org/en/stable/guide.html 

7. Reflex: Pure Python Web Apps, Simplified

Reflex (formerly Pynecone) lets you build full-stack web applications using only Python, no JavaScript required. It compiles your Python code into modern web apps, handling both the frontend and backend seamlessly. Reflex is perfect for Python developers who want to create interactive, production-ready web apps without switching languages.

Learn more: https://reflex.dev/ 

Conclusion

 
FastAPI is my go-to framework for creating REST API endpoints for machine learning applications, thanks to its speed, simplicity, and production-ready features. 

For sharing machine learning demos with non-technical stakeholders, Gradio is incredibly useful, allowing you to build interactive web interfaces with minimal effort.

Django stands out as a robust, full-featured framework that lets you build any web-related application with complete control and scalability.

If you need something lightweight and quick to set up, Flask is an excellent choice for simple web apps and prototype.

Streamlit shines when it comes to building interactive user interfaces for data apps in just minutes, making it perfect for rapid prototyping and visualization.

For real-time web applications that require handling thousands of simultaneous connections, Tornado is a strong option due to its non-blocking, asynchronous architecture.

Finally, Reflex is a modern framework designed for building production-ready applications that are both simple to develop and easy to deploy.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.