Using Python

When running a Python file, you can use options 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 command-line options, take a look at the documentation.

• Using no command-line options will run the code in the file you provide and return you to the command line. For example, if we want to run lab00.py this way, we would write in the terminal:

  python3 lab00.py

• -i: The -i option runs your Python script, then opens an interactive session. In an interactive session, you run Python code line by line and get immediate feedback instead of running an entire file all at once. 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.

  Here's how we can run lab00.py interactively:

  python3 -i lab00.py

• -m doctest: Runs doctests in a particular file. Doctests are surrounded by triple quotes (""") within functions.

  Each test in the file consists of >>> followed by some Python code and the expected output (though the >>> are not seen in the output of the doctest command).

  To run doctests for lab00.py, we can run:

  python3 -m doctest lab00.py

Using OK

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.

You can quickly generate most ok commands at ok-help.

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

You can also use the debug printing feature in OK by writing

print("DEBUG:", x)

Pair programming

You can use this lab as a way to try out pair programming. Check out the pair programming page.

Division, Floor Div, and Modulo

Let's compare the different division-related operators in Python 3:

>>> 1 / 5
0.2

>>> 25 / 4
6.25

>>> 4 / 2
2.0

>>> 5 / 0
ZeroDivisionError

>>> 1 // 5
0

>>> 25 // 4
6

>>> 4 // 2
2

>>> 5 // 0
ZeroDivisionError

>>> 1 % 5
1

>>> 25 % 4
1

>>> 4 % 2
0

Notice that Python outputs ZeroDivisionError for certain cases. We will go over this later in this lab under Error Messages.

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.

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, and then the operands (from left to right).
2. 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 inner operand first in order to evaluate the outer operand.

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('61A is awesome!')

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

Notice also that print will display text without the quotes, but return will preserve the quotes.

Control

Boolean Operators

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 both operands are False, then or evaluates to False.
• not evaluates to True if its operand evaluates to False. It evaluates to False if its operand evalutes to True.

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. 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

Truthy and Falsey Values: It turns out and and or work on more than just booleans (True, False). Python values such as 0, None, '' (the empty string), and [] (the empty list) are considered false values. All other values are considered true values.

Short Circuiting

What do you think will happen if we type the following into 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.

Short-circuiting happens when the operator reaches an operand that allows them to make a conclusion about the expression. For example, and will short-circuit as soon as it reaches the first false value because it then knows that not all the values are true.

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!

While Loops

You can review the syntax of while loops in Section 1.5.5 of Composing Programs.

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 the error. In the example above, TypeError occurred at line 1.