Fly with Python

[Subscribed members would be given preference in case of over attendance]

PyData Salamanca is proud to announce a new meetup!

What is PyData? PyData is a group for users and developers of data analysis tools to share ideas and learn from each other. We gather to discuss best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. We approach data science using many languages, including (but not limited to) Python, Julia, and R.

https://www.youtube.com/watch?v=J8cVPXnafos&t=6s

LOCATION

This meetup will be held at the Main Hall of Edificio I+D+i (C/ Espejo 12 , 37007).
Thanks to Medialab USAL (http://medialab.usal.es/) for letting us use the space!

You can find us at:

https://goo.gl/maps/bC7k6e3otZn

AGENDA

6:50pm - Doors open and networking

7:05pm - Community announcements (Spanish)

News and information about the community.

7:15pm - Keynote I - Q&A (Spanish)

"Using Jupyter: From simple personal notebooks to large deployments with thousands of users" (Spanish) - Juan Cruz-Benito (Ph.D.) - Senior Software Engineer @ IBM Research

The project Jupyter (https://jupyter.org/) has revolutionized the world of research and data science in the last years. It comprises a lot of different subprojects, including the Jupyter Notebook web app, the kernels, the Docker images including modern data science software, JupyterHub, etc.

A lot of people, researchers, and developers use software from this project each day, but, do we know how to take advantage of its full potential?

In this talk, we will give a practical overview of the different features of Jupyter-related applications and environments, ranging the contents from the regular personal use to explain how to enable cooperative Jupyter environments for thousands of users.

7:50pm - Keynote II + Q&A (Spanish)

"Is it a bird? Is it a plane? Accelerating Python with numba" (Spanish) - Juan Luis Cano Rodríguez (MS) - Mission Planning & Execution Engineer @ Satellogic

We are lucky there are very diverse solutions to make Python faster
that have been in use for a while: from wrapping compiled languages
(NumPy), to altering the Python syntax to make it more suitable to
compilers (Cython), to using a subset of it which can in turn be
accelerated (numba), and many many more. However, each of these
options has a tradeoff, and there is no silver bullet.

Some years ago I chose numba for poliastro, my personal project,
because of its simplicity, effectiveness, and not having to learn a
hybrid dialect of Python. numba compiles numerical Python code on the
fly using the LLVM machinery, producing extremely performant code...
when it works!

On the other hand, even though it is quite mature as a library and
most of the Python syntax and NumPy functions are supported, there are
still some limitations that affect its usage. In particular, I strive
to offer a high-level API with support for physical units (extensions
of NumPy) and reusable functions which can be passed as arguments,
which sometimes require using complex objects or introspective Python
behavior which is not available.

In this talk we will introduce numba, describe its basic usage, and
then discuss the strategies and workarounds we have developed to
overcome its limitations, as well as some advanced numba features we
can leverage. We will focus mostly on CPUs, and mention very briefly
its GPU capabilities.

8:25pm - Refreshments and networking

FUTURE SPEAKERS

Would you like to speak at this meetup or a future one? Please submit your proposal at (coordinaciondatalab [at] gmail [dot] com ).