As Python experts we worked with a global asset manager who needed a Python agency to build innovative asset management solutions.
We produced specialist applications allowing advisors to show investment simulations to their clients. This allowed their customers to select different asset allocations and see the impact in real-time.
The whole backend of these applications was built with Python microservices, each specialised on a certain job, allowing several development teams to work on them at the same time. One team could build the microservice handling the huge database and exposing data whilst another developed the email management service.
Using Python let us develop modules rapidly and 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.
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).
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.