PyQL and Quantlib in Python

Earlier this month at the first New York Finance Python User’s Group (NY FPUG) meetup, Kelsey Jordahl talked about how PyQL streamlines the development of Python-based finance applications using QuantLib. There were about 30 people attending the talk at the Cornell Club in New York City. We have a recording of the presentation below.

QuantLib is a free, open-source (BSD-licensed) quantitative finance package. It provides tools for financial instruments, yield curves, pricing engines, creating simulations, and date / time management. There is a lot more detail on the QuantLib website along with the latest downloads. Kelsey refers to a really useful blog / open-source book by one of the core QuantLib developers on implementing QuantLib. Quantlib also comes with different language bindings, including Python.

So why use PyQL if there are already Python bindings in QuantLib? Well, PyQL provides a much more Pythonic set of APIs, in short. Kelsey discusses some of the differences between the original QuantLib Python API and the PyQL API and how PyQL streamlines the resulting Python code. You get better integration with other packages like NumPy, better namespace usage and better documentation. PyQL is available up on GitHub in the PyQL repo. Kelsey uses the IPython Notebooks in the examples directory to explore PyQL and QuantLib and compares the use of PyQL versus the standard (SWIG) QuantLib Python APIs.

PyQL remains a work in progress, with goals to make its QuantLib coverage more complete, the API even more Pythonic, and getting a successful build on Windows (works on Mac OS and Linux now). It’s open source, so feel free to step up and contribute!

For the details, check out the video of Kelsey’s presentation (44 minutes).

And here are the slides online if you want to check the links in the presentation.

If you are interested in working on either QuantLib or PyQL, let the maintainers know!

Share this article:

Related Content

Prospecting for Data on the Web

Introduction At Enthought we teach a lot of scientists and engineers about using Python and the ecosystem of scientific Python packages for processing, analyzing, and…

Read More

Configuring a Neural Network Output Layer

Introduction If you have used TensorFlow before, you know how easy it is to create a simple neural network model using the Keras API. Just…

Read More

No Zero Padding with strftime()

One of the best features of Python is that it is platform independent. You can write code on Linux, Windows, and MacOS and it works…

Read More

Got Data?

Introduction So, you have data and want to get started with machine learning. You’ve heard that machine learning will help you make sense of that…

Read More

Sorting Out .sort() and sorted()

Sorting Out .sort() and sorted() Sometimes sorting a Python list can make it mysteriously disappear.  This happens even to experienced Python programmers who use .sort()…

Read More

A Beginner’s Guide to Deep Learning

Deep learning. By this point, we’ve all heard of it. It’s the magic silver bullet that can fix any complex problem. It’s the special ingredient…

Read More

Giving Visibility to Renewable Energy

The ultimate project goal of EnergizAIR Infrastructure was to raise individual awareness of the contribution of renewable energy sources, and ultimately change behaviors. Now ten…

Read More

Introducing Enthought Edge: Unlocking the Value of R&D Data

While the value of R&D data is clear, finding a way to sort through it can be daunting given the special handling required to extract…

Read More

Machine Learning in Materials Science

The process of materials discovery is complex and iterative, requiring a level of expertise to be done effectively. Materials workflows that require human judgement present…

Read More

AI Needs the ‘Applied Sciences’ Treatment

As industries rapidly advance in AI/machine learning, a key to unlocking the power of these approaches for companies is an enabling environment. Domain experts need…

Read More

Join Our Mailing List!

Sign up below to receive email updates including the latest news, insights, and case studies from our team.