How to Stand Out in a Python Coding Interview (Summary)
You can now feel comfortable using some of Python’s less common, but more powerful, standard features in your next coding interview. There’s a lot to learn about the language as a whole, but this article should have given you a starting point to go deeper while letting you use Python more effectively when you interview.
In this course, you learned different types of standard tools to supercharge your coding interview skills:
- Powerful built-in functions
- Data structures built to handle common scenarios with barely any code
- Standard library packages that have feature-rich solutions for specific problems, letting you write better code faster
Interviewing may not be the best approximation of real software development, but it’s worth knowing how to succeed in any programming environment, even interviews. Thankfully, learning how to use Python during coding interviews can help you understand the language more deeply, which will pay dividends during day-to-day development.
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.
00:00 Let’s go through what you learned in this course. You learned a bunch of different concepts, and it’s always good to revisit what you learned. It’s also good to go through them and maybe make a cheat sheet or put them somewhere so you don’t forget.
I have an interview prep document where I’ve written a lot of this down, just so I don’t forget. In Section 1, you learned about built-in functions—for example,
enumerate(), you can loop through the indexes and the element, while
range()—you just loop through the numbers. List comprehensions, where you were able to construct lists in a very Pythonic way and also find the min and max, and do some other aggregates on lists.
Sorting, where you could sort using the
sorted() function, and then pass in a key to sort based on some function. In Section 2, you leveraged different data structures—for example, sets, where you’re able to check membership in constant time, generators, where you could iterate through a sequence using constant memory, dictionaries and
defaultdict, where you could set default values for dictionaries,
collections.Counter, where you could count the number of times a element appeared in an iterable,
collections.deque, where you could pop and push both on the left and right side of the iterable, and
collections.namedtuple, where you could basically create immutable classes. In Section 3, you learned about different built-in modules: the
string module, which helped you get all the digits and lowercase letters which you could use in the interview question,
itertools module, which helped you iterate over sequences effectively,
functools module, which had higher order functions and properties where you could cache different values, and then
assert, where you could test your code and also make sure that certain conditions were always met in a very easy way. In Section 4, you used all those concepts to solve an easy, medium, and a hard interview question. You also learned about the
PriorityQueue, which helped you get the minimum value in logarithmic time.
02:02 Hopefully, you can see that everything in Section 1, 2, and 3 can really be applied to real-world problems and can show the interviewer that you really know Python. And then, of course, this video, which is the conclusion and course overview.
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