Is Python good for data structures and algorithms?
Yes, and for learning it is arguably the best choice: the code is short, so what you read is the algorithm, not the syntax around it. Two trade-offs are worth knowing. Python runs slower than Java or C++, which matters on tight competitive programming time limits but rarely in an interview, and its built-ins hide the costs you are learning to reason about, which is why this path has you build them first.
Which Python data structures should I know for coding interviews?
list (a dynamic array), dict and set (hash tables), tuple, collections.deque (a queue that is fast at both ends), heapq (a binary min-heap on a list) and collections.Counter. Know what each operation costs, not just its name. Python has no built-in linked list, tree, trie or graph, so those you write yourself, in steps one and two.
Why implement a stack or a queue when Python already has them?
Because interviews rarely ask you to use a queue and often ask why your solution is slow. A queue built on a list pays for every pop(0), because every remaining element shifts one place; deque.popleft() does not. Implementing each structure once is how you learn the costs well enough to pick the right one without thinking.
Is Python fast enough for competitive programming?
For most problems, yes. On tight time limits C++ is the safer choice, which is why most competitive programmers use it, and many judges offer PyPy, which runs the same Python code much faster. In an interview, how fast you write matters far more than how fast the code runs, and there Python wins.
What is Python's recursion limit, and does it matter for DSA?
CPython stops at a depth of 1,000 calls by default, so a recursive depth-first search over a long chain can raise RecursionError. You can raise the limit with sys.setrecursionlimit, but the better habit, and the one interviewers like to see, is knowing how to replace the recursion with a loop and an explicit stack: the structure you build in step one.
Do I need to know Python before starting this path?
You should be comfortable with functions, loops, lists and dictionaries, and ideally classes, since every structure here is written as one. If you are not there yet, Coddy's Python course takes you there first, free, and this path picks up where it ends.