Python Decision Control Structures: Python while And for Loops Part 2

The last post discussed on the use of the python if else, and elif statements as part of a selection control structure. Today, the second part, we will discuss on repetition control structures using python while and for loops. These control flows are used when we want to reuse parts of some code a number of times based on a condition.

The looping constructs provided by python, the while and for loops, are distinct, yet sometimes they can be interchanged except in some cases. First, we will discuss the python while loop.

The python while loop.

A while loop helps one to carry out repeated execution of a block of code based on repeated testing of a Boolean condition.

The syntax of a while loop is as follows:


while condition:
    body

Just similar to the python if statement, the condition is a Boolean expression that evaluates to True or False, and the body is a block of code. The block of code can even be nested with other control structures. The while loops starts its execution by testing the Boolean condition. If the condition evaluates to True, the body of the loop is executed. After the execution of the body, the condition is retested again. If the condition evaluates to True again, another iteration of the body is done. This iteration is repeated as long as the condition evaluates to True. The moment it evaluates to False, the loop is exited and the flow of control transfers to the statement outside the python while loop.

To make sure that the while loop doesn’t run forever, it should come to a point where the condition will evaluate to False. To do this effectively, use a counter that you initialize before the loop and that is incremented or decremented inside the loop. If on the other hand you find that you didn’t do so and your loop runs forever, just press Ctrl+C to interrupt the process.

Here is a code that loops through a list of fruits and tells us whether our favorite fruit, which we have to input, is in the list of fruits. Please, pardon me that the list of recommended fruits is short.

Notice in line 5 that the python while loop is based on two Boolean expressions:

while j < len(fruits) and fruits[j] != fav_fruit:

The first Boolean expression checks to make sure we have not gone to the end of the list and the second checks by the index, j, to see if we have the fruit in our list. After the Boolean expressions, the body of the loop is just a one-liner that increments the index to the list, j. j is being used here as an index to the list to iterate through the list whenever the Boolean expressions evaluates to True; that means we have not found a match for favorite fruit in the list. There is some python if else statements after the while loop that is used as confirmation whether a match was found or not. You can see the post on python if else statements.

This code does not run forever; it terminates no matter what the user enters. Because either we will not find a favorite fruit on the list and get to the end of the list where the loop terminates or we will find a favorite fruit on the list and the loop then terminates.

Now, let’s go to the second looping structure: python’s for loop with some examples.

The python for loop.

When you want to iterate through a sequence of elements in an iterable, the for loop is more preferred to the while loop. It can be used on any structure that is iterable, whether a sequence or collection. Sequences are python strings, tuples, range, and bytes while collections are python dictionaries, sets, and frozensets. The syntax of a python for loop is:


for element in iterable:
    body

You often use the element variable in the body code; the reason why we are iterating through the iterable in the first place is to access the elements. Readers who are familiar with java programming language would realize that the python for loop is in some sense similar to the java “for each” loop.

To illustrate the way a for loop works, let us take a list of numbers, iterate through each of the numbers in the list and add them together to get a total sum.

In the code above, the variable num iterates through each of the numbers in the list of numbers in the for loop and then at the body code, it adds the numbers to total variable to give the total sum.

Let’s take another python for loop example of getting the biggest number in the list of numbers.

We first assigned biggest variable to an arbitrary number, this time 0, and then in the for loop num iterates through each of the numbers. Each time num gets the value of one of the numbers in the list. In the body of the for loop we compare num to the biggest each time and if num is bigger than the biggest, we assign that num to the biggest variable. This comparison happens each iteration through the list in the for loop.

We could achieve the above code using a while loop but we would need to use an indexing method. Indexing with for loops will be described below. But note that some collections like sets cannot be done using while loops because they cannot be indexed.

Now let’s implement a for loop using an index into the elements of the iterable.

Python for loops using an index

There are occasions where we might want to know where an element resides within an iterable. The traditional application of the for loop does not give us that benefit of location. But we can get that effect by indexing into the iterable using a python range function. The range function will generate a sequence of numbers that serve as the indices into the iterable or sequence. The syntax for the for loop is:


for element in range(len(iterable)):
    body

Note how the python length function provides the number that range will use to generate the indices for looping through the iterable. I have a post on the python length function. You can check it out to further understand the syntax above. Now, let’s take some illustrative example. Suppose we want to get the biggest number like we did above but using the indices in the loop, we could implement the code this way:

We eventually implemented the same code like before but instead of iterating directly through the numbers in the list, we used the indexing method to iterate through the numbers.

Note that the index variable above is an integer which is derived from the range of values generated by the range function.

I think we have basically covered the essential points for python while and for loops. But we will not close the chapter without talking about two important statements that have an influence on the iteration of a while and for loop – the python break and continue statements.

The python break and continue statements

Both of these statements interrupt the operation of a while or for loop but in different ways.

The break statement terminates the execution of the loop and transfers control to the next statement in the code. It is usually used to check for the trigger of a condition in the loop and when that condition is satisfied, the loop is terminated.

For example, let us say we want to loop through the list of numbers above to stop when we get a 9. This is how the code could be written. Watch how the python break statement was inserted into a control flow block.

If you run the code above, you will notice that the loop is iterating through each of the numbers until it gets triggered when num is 9. When this condition is reached, the loop terminates and the rest of the numbers are not referenced.

Use the break statement sparingly. It has great power.

The companion loop interruption statement is the python continue statement. The continue statement is usually employed when we don’t want a set of statements in the body of the loop to be executed when a condition is triggered. When triggered, control passes to the next item in the loop; the loop is not terminated.

An example will suffice.

I used a python while loop this time around. The Boolean expression in the while loop checks for when we have looped through all the elements in the numbers list. For each num we are looping, we first check if the number at that index is 0, if it is not zero, we use it to divide the numerator and print out the result, but if it is zero, we tell the program to ignore that number, don’t use it to divide the numerator, and move on to the next number in the loop using the continue statement. This is a very convenient way to program. That is why I love python.

Notice on line 6 and 10 that each time I increase the index by 1 so that the loop can proceed. This makes sure we do not find ourselves in an infinite loop that doesn’t end.

Take your knowledge to new heights. Experiment with the looping constructs introduced here. It’s a joyful thing programming in python.

Python Decision Control Structures: The Python if else Statement - Part 1

decision making in programming in python

We all need to make decisions. We decide on what to eat, what to wear, what to learn, or where to work. Computers also make decisions; at least, the decisions we code. You designate what decision you want a program to make using control structures in your code.

A control structure is a block of programming that analyses one or more variables and then decides on what to do next based on the parameters given by the variables. Another word for control structures is flow of control. Given conditions and parameters, this is the decision making construct in any program.

There are three types of control structures or control flow. They are the sequential, the selection, and repetition control structures.

Sequential control Flow

This is when you execute statements one after the other in the order they appear in the program. Provided there are no syntax or semantic errors, the statement will run from the first to the last statement.

Here is the flow chart for the sequential control flow.

Selection Control Flow

This involves choosing between two or more alternative paths, based on the evaluation of the conditional statement.

Here is a typical flowchart.

python if else statement control flowchart

Selection control flows are usually implemented as python conditional statements and could be a python if statement, python if else statement, or python if elif else statement.

Repetition control flow

This involves repeating a series of statements several times based on the evaluation of a conditional statement.

Here is a typical flowchart.

Repetition control, or sometimes called iteration control, flows are usually implemented in python using the while and for loops.

Apart from the sequential control flow, the selection control flow which makes use of conditional and the repetition control flow which makes use of loops all consist of a condition to be evaluated and a body of statements. You use the python syntax for defining blocks of code to help python interpret your statements appropriately. This involves using the colon character to delimit the beginning of a block of code that acts as the body for a control structure. If the body is just a one-line statement, you can place it on the same line with the condition being evaluated and just after the colon. Or you could decide to place it on a separate line. But if the body is more than one line, you use python’s principles of indentation to place it on a separate line after the colon. Using indented blocks to designate the body helps python to interpret the code as a group of statements belonging to the same control flow. You should already be familiar with python’s principle of indentation. But let me just give some examples with a python while loop.


# using a while loop to show block indentation
while n < 5:  #use colon to show block of code comes next
    # indent the block of code in body by 4 spaces
    print(n)
    n += 1

In any program, you could end up using one, two or all of the control flows. In this post, we will discuss about the selection control flow, while in the next part we will discuss the repetition control flow.

Python implements the selection control flow using conditionals.

Conditonal statements.

Conditional statements in python, also known as the python if statement, if else statement, or if elif else statement, are a way for one to execute a chosen block of code based on the run-time evaluation of one or more Boolean expressions. You usually write the conditional or python if statement in the following way:


if first_condition:
    first_body
elif second_condition:
    second_body
elif third_condition:
    third_body
else:
    fourth_body

Each condition is a Boolean expression that evaluates to True or False, and each body consists of one or more statements that are executed conditionally. On the success of the first condition, the body is executed and no other condition is evaluated after that. But if it fails, the next condition is evaluated for whether it will succeed or fail. When any condition succeeds, all other conditions are discarded and only the body of the condition that succeeds is executed. If none of the conditions succeed, the else body is executed. Note that precisely only the body following a successful conditional will be executed, and sometimes none at all if there is no else statement.

In the example code above, I used two elif statements. You can use any number of elif statements, including zero.

Note that when you want to evaluate a conditional in the if statement, you are evaluating it based on whether it resolves to True or False. In some cases, if you are not evaluating the Boolean expression based on a specific value but on whether the variable has value, you don’t need to evaluate for True or False because every variable is already True when it has a value. You only write out the variable name.

For example, don’t do this:


if fruits == 'True':
    print('Fruits variable has a value')

Rather you produce more optimized code if you write it like this, omitting the test for True:


#I removed the test for True
if fruits: 
    print('Fruits variable has a value')

The elif and else statements in conditional constructs are optional. Let’s illustrate all with examples.

Where only the python if statement is used.


if hungry:
    eat_food()

Where the python if else statements are used.

Some call this the python if then else statement which is a correspondence to other programming languages like java.


if hungry:
    eat_food()
else:
    sleep()

Where only the python if elif statements are used.


if hungry:
    eat_food()
elif tired:
    rest()

Where all three statements, if elif else statements, are used.

This looks like a case switch statement in python; a throwback from java.

 
if hungry:
    eat_food()
elif tired:
    rest()
elif bored:
    watch_tv()
else:
    sleep()

So I have outlined four different ways the conditional construct can be used. Note that only the if statement is required; the others are optional.

One other thing I need you to know about the block indentation so you don’t run into problems. When you have code you want to specify that is not included in the body of the conditional construct, you need to take back your indentation by 4 steps. For example, if after the else block below I want my program to shift control to another activity which does not lie in the conditional construct, i.e do_next_activity(), my indentation goes back 4 steps.


if hungry:
    eat_food()
else:
    sleep()
# this is not part of the conditional construct
# it goes back 4 steps in indentation    
do_next_activity()

From above, do_next_acitivity() goes back 4 steps and is not part of the indentation for the conditional constructs. It does not participate in the indentation.

Lastly, we have python nested if statements.

Python nested if statements.

We may nest one control structure within another, and to do this successfully, we rely on the indentation to make our intent clear to python. Let’s take our if statement a bit further and nest it.


if hungry:
    if food_exists:
        cook_food()
    else:
        buy_food()
    eat_food()
do_next_activity()

You can now see that we have a nested if statement within another if statement. All you need to do is to be careful about making sure your indentation is correct.

We can illustrate the nested conditional construct above with a traditional flowchart. That makes for easy understanding.

In the next post, I will discuss on the repetition control flow which consists of the while and for loops.

The Python Length Function: A Quintessential Size Measuring Tool

There is a built-in function in python that is versatile. It can be used to measure the number of items or length of any object. That function is the python length function. It is denoted as len(s). It is a quintessential tool. I have found it useful on so many occasion and I believe you have been using it without giving a second thought to how important it is to your programming work. In this post, I will describe the objects it can be used for and some of the benefits of the python length function.

The syntax of the python length function.

The syntax of the built-in python length function is len(s) where s, the argument, can be any sequence or a collection. A sequence as you must know is any object that is either a string, byte, tuple, list, or range. A collection can be either a dictionary, set, or frozen set. We will be showing how the length function can be used for each of these. As we already are aware, the function returns the number of items of an object passed to it, but if you fail to pass it an object or you pass it an invalid argument, it will return a TypeError.

I have noticed that many beginners associate a sequence with python lists and so they think that the python length function only calculates python list size. Well, in these examples, I want you to think of other objects as sequences.

Examples of its use on sequences.

Here are some examples of its use on sequences and collections.

First, on strings and byte objects.

Notice that they correctly returned the same number of items when the len function was called on them.

Also, on lists, tuples, and range, see how it works.

And finally on collections like python dictionaries, sets, and frozensets.

You will notice that I was converting from the dictionary to set and frozensets. I wanted the examples to be correspondent. Note that frozensets are immutable while sets are mutable.

Now, let’s go to the application of the python length function. That’s the fun part.

Application of the python length function.

There are several uses of the python length function. As we have already described, it gives the length of an object. But its usefulness gives performance optimization when you are writing code. In the examples above, I give instances where the object length is extremely useful and how the len function is used in those instance.

Used as argument to the range function.

When using the range function you need to pass it an integer argument for it to compute a range. When you want to iterate over the items in a sequence and this is based on the length of the sequence, then the len function comes in handy to provide the integer argument that the range needs. The range items can then be used as indices to the sequence. Let’s show with an example:

When object length is required for conditionals.

There are times you want to compare objects based on their length. The python length function comes in handy in this case. Here is an example.

These are two common examples I have seen in code where the python length function is widely used.

Using the python length function in user defined objects.

Often, we might want to use the len function to find out the number of items a user defined object contains, especially when the underlying data structure of the user defined object is a sequence. You need to implement the __len()__ special method to be able to do this. When you call len(sequence) on an object, under the hood, it calls the __len__() special method of that object. So, this gives us the ability to just define a __len__() method for our user defined objects and they would behave like sequences and collections when it comes to using the python length function.

So, here is some code.

In the Fruits class, I set the initial items to be the empty list, that is, when a fruit object is instantiated, it does not contain any fruit. Then, we need to add fruits to the basket. Before adding fruits, I defined an add_fruit method which first checks that the fruit you are adding is an instance of a string. All fruit names are strings by default. Then if that comes through, I add the fruit to the list of items. Then, we implemented the __len__() special method in order to calculate the length of the list after fruits are added. Without implementing this special method, we could not use the python length function with the f1 object which is an instance of the Fruits class.

One way of thinking about the built-in python length function is that it is calling on the implementation of the __len__() special method of the object passed as argument. You could think of it as acting as this:


def len(x):
    return x.__len__()

I believe you have all you need to use the quintessential python length function. Be creative. Go write some code using this python length function.

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