Stephen Simmons
where else to find them
what they talk about
all 4 in the filters
where they keep going back
- PyData London2 editions2016–2018
on a stage with
- Neil Slingeronce
who talks about the same things
- Jeff Reback5 talks
- Christopher Ariza7 talks
- Matt Harrison16 talks
- Tom Augspurger5 talks
- Patrick Hoefler11 talks
- Han Wang13 talks
| title | conference | date |
|---|---|---|
| Python at Massive Scale | PyData London 2018 | 2018-04-26 |
Athena runs a mono repo of 35m LOC/150k modules served from a custom Hydra object DB with import hooks and continuous deployment, supporting about 1,600 active… | ||
| Pandas from the Inside / "Big Pandas" | PyData Berlin 2017 | 2017-06-23 |
Pandas internals get examined: DataFrames are blocks of homogeneous numpy arrays managed by a block manager, so pulling a Series is often microsecond-fast… | ||
| Pandas from the Inside | PyData DC 2016 | 2016-10-07 |
Slides and code dig into pandas internals using numpy arrays and real AFL game data and build a season ladder that matches the AFL website. Concrete claims… | ||
| Pandas from the inside | PyData London 2016 | 2016-05-06 |
Shows how DataFrames are implemented: data lives in numpy-backed block manager chunks, not as boxed Python objects, so single-column access is cheap —… | ||
| nothing matches | ||