Python has many other additional features for working with various data types and files, networking, cryptography, multithreading and more. We have seen only the most commonly used Python features. To complete our knowledge of basic Python, let’s learn a few more features that you may find useful in your future projects.

Iterable Unpacking

As you are already aware, you can assign multiple variables using multiple values and variable names. For instance,

x, y = 42, "abc"

assigns x and y. This type of assignment is called tuple unpacking as the right-hand side of the assignment creates a tuple using comma-separated values, 42, "abc".

Similarly, tuples and other iterables can be unpacked into other tuples using the star (*) notation, where “*” groups the remaining values into a list.

You can also use _ to ignore a value (or *_ to ignore multiple values) during assignment.

Lambda Functions

Lambda function is a term used for anonymous functions in Python. Anonymous functions do not have names like a usual function that you define with def. They are generally short convenience functions, defined and used on the fly and then thrown away.

  • lambda var1, ...: code: defines a lambda function. The function takes in variables var1, …, and executes a given single line of short code.

You may find lambda functions useful as inputs to other functions. See below for more examples.

Comprehensions

Python comprehensions are a concise and efficient method for creating new sequences. For example, instead of writing a for loop to create a list:

l = []
for i in items:
    l.append(i)

You could use a list comprehension:

  • List comprehension : [i for i in items]

Similarly, Python also offers methods for building dict and set iterables.

  • Dictionary comprehension: {k: v for k, v in iterable}
  • Set comprehension: {k for k in items}

Comprehensions can be used with ifclause to build filtered sequences.

  • Conditional filter: [i for i in items if condition]

You can create tuples by converting lists that you build using the list comprehension.

Sorting

Python has two related functions for sorting, list.sort and sorted. The first is a list instance method that sorts the values of a list and hence used only with the list objects. The latter is a more general sorting function that takes in an input iterable and outputs a sorted list of values.

  • list.sort(): sorts the items’ values of the list in place. sort uses < comparison, so the list items must support this operation. This is straightforward when it comes to the numerical types.

Strings also implement comparison based on order of the characters’ alphabetical (and numerical values).

  • sorted(iterable): produces a list of sorted items taken from an iterable object.

Both .sort and sorted accept two optional keyword arguments.

  • key: a function with one input argument. Key is applied to each item before comparing them. The default is None.
  • reverse: a Boolean, reverses the sorting order if equal to True. The default value is False.

Map and Filter

Python’s built-in map and filter functions allow working with iterables without using loops or if statements.

  • map: accepts a function and at least one iterable. map applies the input function on each item of an iterable. The function’s inputs must match the number of input iterables, e.g., in map(func, iterable), func must accept a single argument, and for map(func, iterable1, iterable2), func must accept two inputs.

map returns a map object instead of the original iterable type and uses a “lazy” evaluation. Use list, tuple, dict, etc. to convert the output to your desired type of iterable. You can use any function with any number of outputs.

  • filter: accepts a function and an iterable. The function should return either True or False (and None) and it works as a filter over the items in the iterable. All the elements of the input iterable that produce False are removed.

Getting Help

You will most likely forget about the commands you have learned so far. It could be a name, or number or type of inputs, or usage of a command. This is completely fine and you should expect it.

I forget commands’ inputs and usage details all the time.

So what do you do if you forget a command or its usage? You will need a way to find commands that you need together with their usage details, a.k.a. documentation. Below is my “method”, feel free to modify and adapt it to your own working style.

  • Somewhat familiar with the command: use help function to lookup its documentation. help is useful when you want to remind youself on the usage details.
  • Know the name but not familiar: use the command and observe its outputs and errors. Then, use help and search engine for the command’s documentation and examples.
  • Forgot the command or not familiar with it: use your preferred search engine for command’s name and documentation, usage examples, and tutorials. E.g., “format float in python”.
  • You have defined a clear goal but don’t know where to start: use AI (chat) agent, AI search, etc., to draft your code. Then, use help or Python documentation to explore and edit your draft. Start small with a few lines of code and build on it.

AI is very useful when you get stuck while coding. Be careful not to generate very long code (e.g., >>10-20 lines). Code with too many lines is difficult to read and debug. Try to build your code line by line.

Exercises

E1: Complete the code below so that it prints a string with sorted characters 123ABCabc. Use the list’s .sort() method. You may find list(...) and string’s "".join(...) useful for this task.

E2: Please write a key using a lambda function that returns the last letter of an input word. The sorted function below should return sorted list of words based on the last letter of each word.

You may also find the included inspect function useful to check what sorted “sees” when applying the key to the elements of the list.

E3: Use sorted, abs, map, and filter to complete the code below. The final print should print a sorted sequence of numbers that excludes all numbers with absolute values (abs(x)) between 3-7, including 3 and 7. For example, an original sequence

original: 8, -9, 3, 5, 8, -10, -4, 7, 5, -2

should look like this after processing it:

filtered: -10, -9, -2, 8, 8

Comment out the random.seed(0) to try out your code with random sequences.

E4: Use help to lookup help on sum, max, and min. Apply these commands on range(10).