On March 14, join ~150 devs at SF Python's presentation night and learn more about new language features and a new language :) Our generous sponsor Yelp will also provide pizza and beer for the evening.
Please register via ti.to (https://ti.to/sf-python/New-Language-Features), not Meetup RSVP. Those without a registration from ti.to by Wed 9a will need to wait till 6:45p to enter and risk not having any pizza left.
If you'd like to give a 5 mins lightning talk or 10-15 mins short talk at this or upcoming meetups, please submit your talk idea here (https://goo.gl/forms/ICpqIMunLo3ZgsrC3).
— Lightning talks (5m)
- Lessons learned from migrating to Python 3 at CMB, by Ann Paul
- Narrative Logging with Eliot, by Stephan Fitzpatrick
- Packaging a flask + gunicorn app with Docker and deploying on Hasura, by Tanmai Gopal
- importlib.resources, by Barry Warsaw
— Short talk (15m + Q&A)
Nim for Python programmers, by Abhishek Kapatkar
Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org
Bio: Abhishek Kapatkar works at Netflix on Machine learning infrastructure team, whose mission is to make using data easy and efficient. He and his team are responsible for envisioning how the data platform allows data scientists to make Netflix's service even better. He enjoys product development, programming language design, and is passionate about the usage of technology for the social good and currently serves as a San Francisco chapter leader for Datakind.org.
— Main talk (~40 mins + Q&A)
Trio: Async concurrency for mere mortals, by Nathan Smith
Concurrent programs are super useful: think of web apps juggling lots of simultaneous downloads and websocket connections, chatbots tracking multiple concurrent conversations, or web spiders fetching pages in parallel. But *writing* concurrent programs is complicated, intimidating to newcomers, and often challenging even for experts.
Does it have to be? Python is famous for being simple and straightforward; can Python make concurrent programming simple and straightforward too? I think so. By carefully analyzing usability pitfalls in other libraries, and taking advantage of new Python 3 features, I've come up with a new set of primitives that make it dramatically easier to write correct concurrent programs, and implemented them in a new library called [Trio](https://trio.readthedocs.io). In this talk, I'll describe these primitives, and demonstrate how to use them to implement a basic algorithm for speeding up
Bio: Nathaniel J. Smith is a cognitive scientist and open-source developer, currently at the UC Berkeley Institute for Data Science. He's a core developer on NumPy and CPython, brought the '@' operator to Python, co-designed matplotlib's "viridis" colormap, instigated the creation of "manylinux" wheels, and writes too many PEPs. He won't be talking about any of that.
6:00p - Check-in and mingle, with food provided by our generous sponsor Yelp!
7:05p - Welcome
7:10p - Announcements, lightning talks, and main talk
7:30p - Doors Close
8:20p - More mingling
9:30p - Hard Stop
**SF Python is run by volunteers aiming to foster the Python Community in the bay area. Please consider making a donation (https://secure.meetup.com/sfpython/contribute/) to SF Python and saying a big thank you to Yelp for providing pizza, beer and the venue for this Wed's meetup.
**Yelp sees 89 million mobile users and 79 million desktop users every month. Keeping everything running smoothly requires the best and brightest in the industry. Their engineers come from diverse technical backgrounds and value digital craftsmanship, open-source, and creative problem-solving. They write tests, review code, and push multiple times a day. Come out and talk to them.
140 New Montgomery