As Python experts, we worked with a major French asset manager, who needed a Python agency to innovative asset management solutions.
We produced several specialist applications, allowing advisors to show investment simulations to their clients, and let them play with it. The whole backend of these applications is built upon several Python microservices, each specialised on a certain job, keeping them really simple and easy to work on for several teams. As an example, we got a microservice only handling the huge database and exposing data. Another one is taking care of sending emails for all the apps.
Using Python let us develop these modules rapidly and made it easy to create new backends on the fly. Furthermore, thanks to SQLAlchemy (an open source database library) we had no issue handling the massive database of our clients.
Django has a very large online community, constantly improving existing modules and producing exciting new ones. As developers, this means we can access component libraries and a community of support to accelerate development for our clients.
Widely used by the scientific community for the past decade, Python is one of the best high-level language for mathematical computation and machine learning. Which means if you are into Big Data, it is probably what you are looking for.
The Django framework takes care of all the hassle of setting up a web project and provides developers with specialist tools for many use cases (authentication, localization, geographic data handling).