Great! Now that we have reviewed some basics, let's talk about some useful aspects of the programming language.

Creating Functions

You may already be aware of built-in functions. Built-in functions are specified by the programming language directly via reserved keywords-- terms taken by the language itself. Such functions are available for the user to freely use in their programs. An example of one such very common built-in function in Python is print().

But what if you wanted to create a custom function to perform a task of your choice? You can create a user-defined function in that case, and Python fully supports this.

Let's now see how user-defined functions in Python work. A function definition starts with a def keyword, followed by the function name, parenthesis, and a colon. You can also provide function parameters within the parenthesis. However, they are entirely optional, and functions exist without parameters as well.

To use this custom function in a program, it needs to be called, or invoked, within your code. This is shown in the code block below, where the function is now utilized. As output, "Hello World!" is printed on the console.

Functions help modularize code, as the program gets divided into different blocks (or "subroutines") which can be reused. Suppose you have a program that performs file writing when triggered by a certain condition. Instead of writing the same lines of code repeatedly, a function can be made which performs this specific task. This function is then called whenever this task is required.

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function myFunction() {

    console.log("Hello World!");

}

​

myFunction();

Lists

So far, you've seen variables in Python. The problem with variables is that they can only store one value of a single data type.

Lists solve this problem for us. They can store a collection of data-- that is, multiple values of the same or different data types in a single variable.

Lists in Python are defined with square brackets. Let's look at some examples of lists.

What if we want to access any of its elements? This is done using indexing. In indexing, each value in a list is given a number (starting from 0, not 1!). To access a certain element, this number is specified inside the square bracket with the list name. For example, "w" from the list below can be accessed using lst[5].

Lists are very powerful, and many useful operations are defined with them. These list methods make it easier to manipulate and perform operations on lists. Some of these common methods are in the table below.

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// Array with items of single type

let fruits = ["orange", "apple", "banana", "strawberry"];

​

// Array with items of multiple types

let lst = ["a", 1, "c", ["x", "y"], 5, 7, [1,2]];

Dictionaries

A collection of data can also be stored in the form of dictionaries in Python. Unlike lists, dictionaries store data values in what's known as key: value pairs. These key: value pairs are also called items. This means that in a dictionary, values are assigned to keys, and the values of these items can be obtained using key names.

In Python, dictionaries are declared using curly braces {}, separated by a comma. A key is specified within the curly braces, which is followed by a colon and its corresponding value.

Let's look at an example dictionary.

But in what cases can dictionaries be helpful?

Suppose you want to store distances of all cities from a chosen starting point. In such a case, it would be helpful if you could store distance values for each city from the starting city. Using a list would be a tedious task as you would have difficulty representing which city has what distance. Dictionaries make it easier to represent such problems. In this example, using a dictionary, cities can be represented as keys and their distances as values.

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let distances = {"A": 421, "B": 234, "C": 127, "D": 184};

Working with Files

Analyzing or working with data from a local file in a program is called file handling. Suppose you have student academic records in a file and want to calculate percentages of each student. Calculating it one by one in a file is a tiring task. This work would be easier if the file could be loaded to a program, and you could directly apply the operation on all the data in the file.

To work with files in Python, you need to open the file (within the program), perform an operation on it (read or write), and then close the file. Simple, right? Let's see how it looks in code.

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var fs = require('fs');

fs.readFile('filename.txt', 'utf8', function(err,data) {

    if (err) {

        return console.log(err);

    }

    console.log(data);

});

Python provides an in-built function open() which opens the file inside the program. You need to specify the name of the file which needs to be opened in a string within the parenthesis. By default, the file opens in reading mode. You can specify different modes according to how you want to use the file in your program.

If you want to write to a file, you'd do something like this.

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var fs = require('fs');

fs.writeFile("filename.txt", "Writing in file", function(err) {

  if (err) {

    return console.log(err);

  }

});

However, this would overwrite the file if there was any previous information in it. To avoid that, we can append to a file using a different mode like this.

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const fs = require('fs');

fs.appendFile('filename.txt', 'Appending to existing file', function (err) {

  if (err) throw err;

});