I’m Not Asking you This Python Interview Question Because I Want to Know. I’m Asking Because I Want to Know if YOU Know!
It Starts with a Python Interview
Last week we interviewed a candidate for a data engineering position. In this case, a fairly strong knowledge of Python was required. One Python interview question I like to ask explores the difference between lists, dictionaries, and tuples. It’s a pretty good question if you want to know how much a candidate understands Python data structures.
So, we asked the candidate. He hemmed and hawed for a few seconds and, while we couldn’t see his hands, we did see that they seemed busy and his gaze seemed to turn to a second monitor. Then, suddenly, he said something like, “A Python list is an ordered and changeable collection of data objects. Unlike an array, which can contain objects of a single type, a list can contain a mixture of objects.” (BTW, this definition was taken from edspresso). He continued on with similar, detailed definitions of dictionaries and tuples.
Both Katie and I were on the call, and we both noticed it. This guy was looking up the answers as he was interviewing!
What He Didn’t Get (Besides the Job)
So, while we really appreciated his researching and imparting knowledge, it seems that this guy didn’t get the point of our question. We weren’t asking because we had burning desire for the textbook definitions, we were asking because we wanted to know if HE knew. It appears that he didn’t.
BTW, in basic terms:
- list – An ordered set of elements, somewhat akin to an array although the elements can be of different data types
- dictionary – A set of key value pairs
- tuple – Like a list but unchangeable once it’s created
What do you think? Have you ever experienced a situation where your interviewee took advantage of the fact that they were remote to look up answers during the interview? I’d love to hear about it! Leave your comments on this post or send me an email at Benjamin.Taub@Dataspace.com.
And, if you’re looking for contract or permanent talent in analytics, data engineering, or related technologies (like Python), check us out. We’d love to help!
Thanks for reading!