This week we welcome Draga Doncila Pop as our PyDev of the Week! Draga is a core developer of the napari package, which is a multi-dimensional image viewer for Python. Draga also speaks at Python conferences about Python and data visualization.
You can see what else Draga is up to by visiting Draga’s GitHub profile.
Let’s spend some time getting to know Draga better!
Can you tell us a little about yourself (hobbies, education, etc):
I am a Romanian born Kiwi living in Australia. I’m currently studying towards my PhD in computer science and working part time as a software engineer. In my spare time I like to read a lot of fantasy and science fiction – I’m currently re-reading the Red Rising saga while I wait for Brandon Sanderson’s next novel. I also love baking, mostly sweet treats – but I really want to conquer yeasted doughs next.
Why did you start using Python?
Python was the second programming language I learned. The first was Borland Delphi, when I was 14. I love Python because it’s so accessible. It’s so easy to spin up something quickly, but it has all the flexibility you need for more complex applications. It used to be that it was way too slow for many applications, but these days even getting C-esque speedups isn’t that bad.
What other programming languages do you know and which is your favorite?
I know Python best, but I’ve dabbled in Java, C#, C, javascript (and its many frameworks), typescript and even a little bit of Haskell. I think Python is my favourite, but I work so much with Python that it’s hard to make this a fair comparison. I love the ethos of Python, its community, and the difference it’s made to scientific computing. I do love Haskell a lot too, just because it’s a totally different paradigm – I wish I knew it better.
What projects are you working on now?
I mostly work on napari now, and its associated bits and pieces. I’m also working on some packages as part of my PhD, mostly utilities for cell tracking, and eventually a napari plugin. I contribute here and there to other projects as well, but napari is my main focus.
Which Python libraries are your favorite (core or 3rd party)?
I’m a sucker for the array-likes. Zarr, NumPy, dask.array, SciPy sparse… I love the (often…) seamless abstraction of the array interface despite the very different backends and use cases. I love the scientific Python stack in general.
How did you get involved with the napari project?
I worked with napari during my Honours year research project, analyzing high resolution satellite images. I really loved the community and the project itself, so I continued working on it while taking a break from study. Now I’m a core developer, and it’s part of my PhD work as well, and I think I’m very privileged to get to work on something so cool almost full time.
What are the top three things you love about napari?
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- Seeing people’s cool demos and interesting data. It’s just so neat! People have all sorts of fascinating applications, and the results are often absolutely beautiful.
- The fact that it makes research easier for people. I love that software/computer science can help accelerate research in all sorts of fields, and working with something where I can see the real world impact is very satisfying.
- It’s open source. This one’s pretty self explanatory, but I just think it’s fantastic that it’s free, anyone can use it, anyone can contribute to it – I think that’s how it should be. Especially for a project that’s meant to support research.
Thanks for doing the interview, Draga!
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