Using Python

When running a Python file, you can use flags on the command line to inspect your code further. Here are a few that will come in handy. If you want to learn more about other Python flags, take a look at the documentation.

• Using no flags will run the code in the file you provide and return you to the command line.

  python3 lab01.py

• -i: The -i option runs your Python script first, then opens an interactive session. To exit, type exit() into the interpreter prompt. You can also use the keyboard shortcut Ctrl-D on Linux/Mac machines or Ctrl-Z Enter on Windows.

  If you edit the Python file while running it interactively, you will need to exit and restart the interpreter in order for those changes to take effect.

  python3 -i lab01.py

• -m doctest: Runs doctests in a particular file. If there is no output, it means all doctests passed. Doctests are marked by triple quotes (""") and are usually located within functions. DO NOT DELETE DOCTESTS ON YOUR LABS AND HOMEWORKS. The autograder (OK) will not run properly without them.

  python3 -m doctest lab01.py

Using OK

In CS 88, we use a program called OK for autograding labs, homeworks, and projects. You should have OK in the starter files downloaded at the start of this lab. For more information on using OK commands, learn more here. To use OK to run doctests for a specified function, run the following command:

python3 ok -q <specified function>

By default, only tests that did not pass will show up. You can use the -v option to show all tests, including tests you have passed:

python3 ok -v

Sometimes it's helpful to debug using print statements, but that may also interfere with OK's grading system. If you would like to print and have OK ignore the output, you can use the debug printing feature in OK by writing:

print("DEBUG:", x)

Where x is the content you would like to print. Finally, when you have finished all the questions in lab01.py, you must submit the assignment using the --submit option:

python3 ok --submit

For more OK commands, visit here.

Division

Let's compare the different division-related operators in Python:

>>> 1 / 5
0.2

>>> 25 / 4
6.25

>>> 5 / 0
ZeroDivisionError

>>> 1 // 5
0

>>> 25 // 4
6

>>> 5 // 0
ZeroDivisionError

>>> 1 % 5
1

>>> 25 % 4
1

>>> 5 % 0
ZeroDivisionError

Note that floor division and modulo both return an integer while true division always returns a floating point number.
For now, the only difference you need to understand between integers and floats is that integers are positive or negative whole numbers, while floats are positive or negative decimals.

One useful technique involving the % operator is to check whether a number x is divisible by another number y:

x % y == 0

For example, in order to check if x is an even number:

x % 2 == 0

Functions

If we want to execute a series of statements over and over, we can abstract them away into a function to avoid repeating code.

For example, let's say we want to know the results of multiplying the numbers 1-3 by 3 and then adding 2 to it. Here's one way to do it:

>>> 1 * 3 + 2
5
>>> 2 * 3 + 2
8
>>> 3 * 3 + 2
11

If we wanted to do this with a larger set of numbers, that'd be a lot of repeated code! Let's write a function to capture this operation given any input number.

def foo(x):
    return x * 3 + 2

This function, called foo, takes in a single argument and will return the result of multiplying that argument by 3 and adding 2.

Now we can call this function whenever we want this operation to be done:

>>> foo(1)
5
>>> foo(2)
8
>>> foo(1000)
3002

Applying a function to some arguments is done with a call expression.

Call expressions

A call expression applies a function, which may or may not accept arguments. The call expression evaluates to the function's return value. It has a familiar notation borrowed from Math.

The syntax of a function call:

  add   (    2   ,    3   )
   |         |        |
operator  operand  operand

Every call expression requires a set of parentheses delimiting its comma-separated operands.

To evaluate a function call:

1. Evaluate the operator
2. Evaluate the operands (from left to right).
3. Apply the operator to the operands (the values of the operands).

If an operand is a nested call expression, then these two steps are applied to that operand in order to evaluate it.

return and print

Most functions that you define will contain a return statement. The return statement will give the result of some computation back to the caller of the function and exit the function. For example, the function square below takes in a number x and returns its square.

def square(x):
    """
    >>> square(4)
    16
    """
    return x * x

When Python executes a return statement, the function terminates immediately. If Python reaches the end of the function body without executing a return statement, it will automatically return None.

In contrast, the print function is used to display values in the Terminal. This can lead to some confusion between print and return because calling a function in the Python interpreter will print out the function's return value.

However, unlike a return statement, when Python evaluates a print expression, the function does not terminate immediately.

def what_prints():
    print('Hello World!')
    return 'Exiting this function.'
    print('CS 88 is awesome!')

>>> what_prints()
Hello World!
'Exiting this function.'

Notice also that print will display text (Python strings) without the quotes, but return will preserve the quotes.

Another thing to remember is that print is a function itself, so it also has a return value. The return value of print is None.

>>> print(print("Hello World!"))
Hello World!
None

Control

Boolean Operators

You briefly encountered Boolean operators last week, but here you will see there is a close connection between them and conditionals.

Python supports three boolean operators: and, or, and not:

>>> a = 4
>>> a < 2 and a > 0
False
>>> a < 2 or a > 0
True
>>> not (a > 0)
False

• and evaluates to True only if both operands evaluate to True. If at least one operand is False, then and evaluates to False.
• or evaluates to True if at least one operand evaluates to True. If all operands are False, then or evaluates to False.

What do you think the following expression evaluates to? Try it out in the Python interpreter.

>>> True and not False or not True and False

It is difficult to read complex expressions, like the one above, and understand how a program will behave. Using parentheses can make your code easier to understand. Just so you know, Python interprets that expression in the following way:

>>> (True and (not False)) or ((not True) and False)

This is because boolean operators, like arithmetic operators, have an order of operation:

• not has the highest priority
• and
• or has the lowest priority

To make your code more readable, and and or work on more than just booleans (True, False). Other Python values can be considered "false-y," including 0, None, '' (the empty string), etc. (see here for a complete list of false-y values in Python). All other values are considered "truth-y."

Short Circuiting

What do you think will happen if we evaluate the following in Python?

1 / 0

Try it out in Python! You should see a ZeroDivisionError. But what about this expression?

True or 1 / 0

It evaluates to True because Python's and and or operators short-circuit. That is, they don't necessarily evaluate every operand.

If and and or do not short-circuit, they just return the last value. Another way to remember this is that and and or always return the last thing they evaluate, whether they short circuit or not. Keep in mind that and and or don't always return booleans when using values other than True and False.

If Statements

You can review the syntax of if statements in Section 1.5.4 of Composing Programs.

Tip: We sometimes see code that looks like this:

if x > 3:
    return True
else:
    return False

This can be written more concisely as return x > 3. If your code looks like the code above, see if you can rewrite it more clearly!

Iteration

There are two main types of loops, the while and for loop. They are both used to run a block of code an arbitrary number of times, however, they have different ways of doing it. Take a look at the differences in the table below.

...
while <predicate expression>:
    <body statements>
...

>>> i = 0
>>> while i <= 2:
...     print(i)
...     i = i + 1
0
1
2

...
for <variables> in <sequence expression>:
    <body statements>
...

>>> x = [0, 1, 2]
>>> for i in x:
...     print(i)
0
1
2

Error Messages

By now, you've probably seen a couple of error messages. They might look intimidating, but error messages are very helpful for debugging code. The following are some common types of errors:

Using these descriptions of error messages, you should be able to get a better idea of what went wrong with your code. If you run into error messages, try to identify the problem before asking for help. You can often Google unfamiliar error messages to see if others have made similar mistakes to help you debug.

For example:

>>> square(3, 3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: square() takes 1 positional argument but 2 were given

Note:

• The last line of an error message tells us the type of the error. In the example above, we have a TypeError.
• The error message tells us what we did wrong — we gave square 2 arguments when it can only take in 1 argument. In general, the last line is the most helpful.
• The second to last line of the error message tells us on which line the error occurred. This helps us track down he error. In the example above, TypeError occurred at line 1.