Must Know Things to Clear Your Python Coding Interview
Python is not only one of the most loved languages but rather it is used in various different domains. Due to its high dependency and usage in a lot of fields, there has suddenly been an increase in the job openings in Python programming language and related frameworks. Python developers are in high demand as it solves problems effortlessly in areas like web development, data science, artificial intelligence, cloud computing, and cybersecurity. 2021 saw a substantial rise in job openings for Python developers.
Therefore, acing for a Python role does not only mean you have to be good at Python libraries, modules, data structures but also be able to write clean code without redundant code. This means Python already provides a lot of in-built methods and libraries so that you don’t have to write long redundant codes. Let us look at this by one so that you can clear your Python interview flawlessly!
1. String Formatting in Python
Python uses string formatting similar to that of C-language to create new, formatted strings. To inculcate string formatting in your code, there are three ways you can implement it: with the help of placeholders, using the format() method, and formatting using string literals i.e., f-strings. When using the placeholder method, we need to use the modulo (%) operator along with s, d, f or b characters, where s means inserting a string, d means inserting decimal values, f means floating-point values and b means inserting binary value. When using the format() method, we need to pass in the string values as arguments that are to be replaced in the original string. It can also insert multiple values using indexes in the actual string. The final method, by using f-strings, was introduced in Python 3.6 and above. Here, we append the original string to the character f and then place variables inside the string in curly braces.
To learn more about it, must read: String Formatting in Python
2. Using Generators as Opposed to List Comprehension
Using list comprehensions is great when working with smaller lists. If list comprehension is used for larger lists, it often ends up consuming a lot of time thereby slowing down your program. Therefore, Python provides generators that help to create your own iterator functions. It is a special type of Python function which rather than providing a single value, provides an iterator object with a sequence of values. In normal functions, we use a return keyword, but in generator functions, we use yield keyword. The return statement terminates the function whereas yield only pauses the execution while maintaining an internal state of the function.
To learn more about it, must read: Generators in Python
3. Magic of the enumerate() Method
We all use Python iterables but what if we need a counter to keep a track of all the items in the current iterable? Python provides a method called enumerate() which adds a counter to an iterable and after that returns it in a form of an enumerate object. It can also be used in loop constructs where having a counter to every item in the iterable is needed.
To learn more about it, must read: Enumerate Method in Python
4. Python’s Collection Module
Python has an amazing module called collection which is used to implement container data types, namely lists, dict, set, tuple to get rid of their shortcomings. It provides specialized data structures: namedtuple(), UserList, UserDict, UserString, deque, Chainmap, Counter, OrderedDict and defaultdict. Using these in your code increases its performance to a great extent and also makes day-to-day programming easier for Python developers.
To learn more about it, must read: Python Collections Module
5. Passing Arguments to sort() Method
Python provides a built-in function called sort() which sorts the list, by default, in ascending order. But it not just limited to sorting lists, rather, we can pass various arguments to this function to customize the results as per our needs. Firstly, we can pass reverse=True in the sort method so we can receive the list in descending order. Secondly, we can pass a value to the key which is a function and serves as a key for the sorting comparison. For example, if we have a list of strings and we want to sort them based on their height, we will follow this syntax: list_input.sort(key=len).
To read more about it, must read: sort() in Python
6. Debugging Code with breakpoint()
We all admit to use print() while debugging our Python codes and passing all sorts of weird strings to check until which line the print executes. But, that is a bad approach and should not be used when Python provides a function called breakpoint() to test the code at lines where we think there can be potential bugs or errors. There are a few statements that are used for purposes like continuing execution, quitting debugger, going to the next line within the same or the called function.
To read more about it, must read: Debugging in Python
7. Knowing Mysterious **kwargs
**kwargs in Python is used in function definitions and is generally used to pass a keyworded argument list which could be of variable length. The double wildcard indicates that there is no restriction to the number of keyword of arguments that can be passed (variable-length). To use this, we need to provide names to the arguments that we are passing and they can eventually be retrieved just like dictionaries, without any particular order.
To learn more about it, must read: **kwargs in Python
8. Using all or any Keywords
These are one of the most used AND/OS built-in that Python provides and definitely reduce your code to a great extent. The keyword any is used when we need to check if even any single item is True. To easily visualize it, we can think of it as a successive OR operation on the iterable on which it is called. Whereas, all is used to check if each and every item in the iterable is true. Both of these are short circuit operators and stop as soon as a false is encountered in all or a true is encountered in any.
To learn more about it, must read: All Any in Python
We have seen various Python tips and tricks that you must know as a developer and will help you keep an edge over candidates in your Python coding interviews!