===========================
PY4E - Python for Everybody
===========================

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Chapter 1: Introduction Chapter 2: Variables Chapter 3: Conditionals
Chapter 4: Functions Chapter 5: Iterations Chapter 6: Strings Chapter 7:
Files Chapter 8: Lists Chapter 9: Dictionaries Chapter 10: Tuples
Chapter 11: Regex Chapter 12: Networked Programs Chapter 13: Python and
Web Services Chapter 14: Python Objects Chapter 15: Python and Databases
Chapter 16: Data Vizualization

Conditional execution
=====================

Boolean expressions
-------------------

A *boolean expression* is an expression that is either true or false.
The following examples use the operator ``==``, which compares two
operands and produces ``True`` if they are equal and ``False``
otherwise:

.. code:: python

    >>> 5 == 5
    True
    >>> 5 == 6
    False

``True`` and ``False`` are special values that belong to the class
``bool``; they are not strings:

.. code:: python

    >>> type(True)
    <class 'bool'>
    >>> type(False)
    <class 'bool'>

The ``==`` operator is one of the *comparison operators*; the others
are:

.. code:: python

    x != y               # x is not equal to y
    x > y                # x is greater than y
    x < y                # x is less than y
    x >= y               # x is greater than or equal to y
    x <= y               # x is less than or equal to y
    x is y               # x is the same as y
    x is not y           # x is not the same as y

Although these operations are probably familiar to you, the Python
symbols are different from the mathematical symbols for the same
operations. A common error is to use a single equal sign (``=``) instead
of a double equal sign (``==``). Remember that ``=`` is an assignment
operator and ``==`` is a comparison operator. There is no such thing as
``=<`` or ``=>``.

Logical operators
-----------------

There are three *logical operators*: ``and``, ``or``, and ``not``. The
semantics (meaning) of these operators is similar to their meaning in
English. For example,

``x > 0 and x < 10``

is true only if ``x`` is greater than 0 *and* less than 10.

``n%2 == 0 or n%3 == 0`` is true if *either* of the conditions is true,
that is, if the number is divisible by 2 *or* 3.

Finally, the ``not`` operator negates a boolean expression, so
``not (x > y)`` is true if ``x > y`` is false; that is, if ``x`` is less
than or equal to ``y``.

Strictly speaking, the operands of the logical operators should be
boolean expressions, but Python is not very strict. Any nonzero number
is interpreted as “true.”

.. code:: python

    >>> 17 and True
    True

This flexibility can be useful, but there are some subtleties to it that
might be confusing. You might want to avoid it until you are sure you
know what you are doing.

Conditional execution
---------------------

In order to write useful programs, we almost always need the ability to
check conditions and change the behavior of the program accordingly.
*Conditional statements* give us this ability. The simplest form is the
``if`` statement:

.. code:: python

    if x > 0 :
        print('x is positive')

The boolean expression after the ``if`` statement is called the
*condition*. We end the ``if`` statement with a colon character (:) and
the line(s) after the if statement are indented.

|If Logic|

If Logic

If the logical condition is true, then the indented statement gets
executed. If the logical condition is false, the indented statement is
skipped.

``if`` statements have the same structure as function definitions or
``for``
loops\ `:sup:`1` <https://www.py4e.com/html3/03-conditional#fn1>`__. The
statement consists of a header line that ends with the colon character
(:) followed by an indented block. Statements like this are called
*compound statements* because they stretch across more than one line.

There is no limit on the number of statements that can appear in the
body, but there must be at least one. Occasionally, it is useful to have
a body with no statements (usually as a place holder for code you
haven’t written yet). In that case, you can use the ``pass`` statement,
which does nothing.

.. code:: python

    if x < 0 :
        pass          # need to handle negative values!

If you enter an ``if`` statement in the Python interpreter, the prompt
will change from three chevrons to three dots to indicate you are in the
middle of a block of statements, as shown below:

.. code:: python

    >>> x = 3
    >>> if x < 10:
    ...    print('Small')
    ...
    Small
    >>>

When using the Python interpreter, you must leave a blank line at the
end of a block, otherwise Python will return an error:

.. code:: python

    >>> x = 3
    >>> if x < 10:
    ...    print('Small')
    ... print('Done')
      File "<stdin>", line 3
        print('Done')
            ^
    SyntaxError: invalid syntax

A blank line at the end of a block of statements is not necessary when
writing and executing a script, but it may improve readability of your
code.

Alternative execution
---------------------

A second form of the ``if`` statement is *alternative execution*, in
which there are two possibilities and the condition determines which one
gets executed. The syntax looks like this:

.. code:: python

    if x%2 == 0 :
        print('x is even')
    else :
        print('x is odd')

If the remainder when ``x`` is divided by 2 is 0, then we know that
``x`` is even, and the program displays a message to that effect. If the
condition is false, the second set of statements is executed.

|If-Then-Else Logic|

If-Then-Else Logic

Since the condition must either be true or false, exactly one of the
alternatives will be executed. The alternatives are called *branches*,
because they are branches in the flow of execution.

Chained conditionals
--------------------

Sometimes there are more than two possibilities and we need more than
two branches. One way to express a computation like that is a *chained
conditional*:

.. code:: python

    if x < y:
        print('x is less than y')
    elif x > y:
        print('x is greater than y')
    else:
        print('x and y are equal')

``elif`` is an abbreviation of “else if.” Again, exactly one branch will
be executed.

|If-Then-ElseIf Logic|

If-Then-ElseIf Logic

There is no limit on the number of ``elif`` statements. If there is an
``else`` clause, it has to be at the end, but there doesn’t have to be
one.

.. code:: python

    if choice == 'a':
        print('Bad guess')
    elif choice == 'b':
        print('Good guess')
    elif choice == 'c':
        print('Close, but not correct')

Each condition is checked in order. If the first is false, the next is
checked, and so on. If one of them is true, the corresponding branch
executes, and the statement ends. Even if more than one condition is
true, only the first true branch executes.

Nested conditionals
-------------------

One conditional can also be nested within another. We could have written
the three-branch example like this:

.. code:: python

    if x == y:
        print('x and y are equal')
    else:
        if x < y:
            print('x is less than y')
        else:
            print('x is greater than y')

The outer conditional contains two branches. The first branch contains a
simple statement. The second branch contains another ``if`` statement,
which has two branches of its own. Those two branches are both simple
statements, although they could have been conditional statements as
well.

|Nested If Statements|

Nested If Statements

Although the indentation of the statements makes the structure apparent,
*nested conditionals* become difficult to read very quickly. In general,
it is a good idea to avoid them when you can.

Logical operators often provide a way to simplify nested conditional
statements. For example, we can rewrite the following code using a
single conditional:

.. code:: python

    if 0 < x:
        if x < 10:
            print('x is a positive single-digit number.')

The ``print`` statement is executed only if we make it past both
conditionals, so we can get the same effect with the ``and`` operator:

.. code:: python

    if 0 < x and x < 10:
        print('x is a positive single-digit number.')

Catching exceptions using try and except
----------------------------------------

Earlier we saw a code segment where we used the ``input`` and ``int``
functions to read and parse an integer number entered by the user. We
also saw how treacherous doing this could be:

.. code:: python

    >>> prompt = "What is the air velocity of an unladen swallow?\n"
    >>> speed = input(prompt)
    What is the air velocity of an unladen swallow?
    What do you mean, an African or a European swallow?
    >>> int(speed)
    ValueError: invalid literal for int() with base 10:
    >>>

When we are executing these statements in the Python interpreter, we get
a new prompt from the interpreter, think “oops”, and move on to our next
statement.

However if you place this code in a Python script and this error occurs,
your script immediately stops in its tracks with a traceback. It does
not execute the following statement.

Here is a sample program to convert a Fahrenheit temperature to a
Celsius temperature:

.. code:: python

    inp = input('Enter Fahrenheit Temperature: ')
    fahr = float(inp)
    cel = (fahr - 32.0) * 5.0 / 9.0
    print(cel)

    # Code: http://www.py4e.com/code3/fahren.py

If we execute this code and give it invalid input, it simply fails with
an unfriendly error message:

::

    python fahren.py
    Enter Fahrenheit Temperature:72
    22.22222222222222

::

    python fahren.py
    Enter Fahrenheit Temperature:fred
    Traceback (most recent call last):
      File "fahren.py", line 2, in <module>
        fahr = float(inp)
    ValueError: could not convert string to float: 'fred'

There is a conditional execution structure built into Python to handle
these types of expected and unexpected errors called “try / except”. The
idea of ``try`` and ``except`` is that you know that some sequence of
instruction(s) may have a problem and you want to add some statements to
be executed if an error occurs. These extra statements (the except
block) are ignored if there is no error.

You can think of the ``try`` and ``except`` feature in Python as an
“insurance policy” on a sequence of statements.

We can rewrite our temperature converter as follows:

.. code:: python

    inp = input('Enter Fahrenheit Temperature:')
    try:
        fahr = float(inp)
        cel = (fahr - 32.0) * 5.0 / 9.0
        print(cel)
    except:
        print('Please enter a number')

    # Code: http://www.py4e.com/code3/fahren2.py

Python starts by executing the sequence of statements in the ``try``
block. If all goes well, it skips the ``except`` block and proceeds. If
an exception occurs in the ``try`` block, Python jumps out of the
``try`` block and executes the sequence of statements in the ``except``
block.

::

    python fahren2.py
    Enter Fahrenheit Temperature:72
    22.22222222222222

::

    python fahren2.py
    Enter Fahrenheit Temperature:fred
    Please enter a number

Handling an exception with a ``try`` statement is called *catching* an
exception. In this example, the ``except`` clause prints an error
message. In general, catching an exception gives you a chance to fix the
problem, or try again, or at least end the program gracefully.

Short-circuit evaluation of logical expressions
-----------------------------------------------

When Python is processing a logical expression such as
``x >= 2 and (x/y) > 2``, it evaluates the expression from left to
right. Because of the definition of ``and``, if ``x`` is less than 2,
the expression ``x >= 2`` is ``False`` and so the whole expression is
``False`` regardless of whether ``(x/y) > 2`` evaluates to ``True`` or
``False``.

When Python detects that there is nothing to be gained by evaluating the
rest of a logical expression, it stops its evaluation and does not do
the computations in the rest of the logical expression. When the
evaluation of a logical expression stops because the overall value is
already known, it is called *short-circuiting* the evaluation.

While this may seem like a fine point, the short-circuit behavior leads
to a clever technique called the *guardian pattern*. Consider the
following code sequence in the Python interpreter:

.. code:: python

    >>> x = 6
    >>> y = 2
    >>> x >= 2 and (x/y) > 2
    True
    >>> x = 1
    >>> y = 0
    >>> x >= 2 and (x/y) > 2
    False
    >>> x = 6
    >>> y = 0
    >>> x >= 2 and (x/y) > 2
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    ZeroDivisionError: division by zero
    >>>

The third calculation failed because Python was evaluating ``(x/y)`` and
``y`` was zero, which causes a runtime error. But the first and the
second examples did *not* fail because in the first calculation ``y``
was non zero and in the second one the first part of these expressions
``x >= 2`` evaluated to ``False`` so the ``(x/y)`` was not ever executed
due to the *short-circuit* rule and there was no error.

We can construct the logical expression to strategically place a *guard*
evaluation just before the evaluation that might cause an error as
follows:

.. code:: python

    >>> x = 1
    >>> y = 0
    >>> x >= 2 and y != 0 and (x/y) > 2
    False
    >>> x = 6
    >>> y = 0
    >>> x >= 2 and y != 0 and (x/y) > 2
    False
    >>> x >= 2 and (x/y) > 2 and y != 0
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    ZeroDivisionError: division by zero
    >>>

In the first logical expression, ``x >= 2`` is ``False`` so the
evaluation stops at the ``and``. In the second logical expression,
``x >= 2`` is ``True`` but ``y != 0`` is ``False`` so we never reach
``(x/y)``.

In the third logical expression, the ``y != 0`` is *after* the ``(x/y)``
calculation so the expression fails with an error.

In the second expression, we say that ``y != 0`` acts as a *guard* to
insure that we only execute ``(x/y)`` if ``y`` is non-zero.

Debugging
---------

The traceback Python displays when an error occurs contains a lot of
information, but it can be overwhelming. The most useful parts are
usually:

-  What kind of error it was, and

-  Where it occurred.

Syntax errors are usually easy to find, but there are a few gotchas.
Whitespace errors can be tricky because spaces and tabs are invisible
and we are used to ignoring them.

.. code:: python

    >>> x = 5
    >>>  y = 6
      File "<stdin>", line 1
        y = 6
        ^
    IndentationError: unexpected indent

In this example, the problem is that the second line is indented by one
space. But the error message points to ``y``, which is misleading. In
general, error messages indicate where the problem was discovered, but
the actual error might be earlier in the code, sometimes on a previous
line.

In general, error messages tell you where the problem was discovered,
but that is often not where it was caused.

Glossary
--------

body
    The sequence of statements within a compound statement.
boolean expression
    An expression whose value is either ``True`` or ``False``.
branch
    One of the alternative sequences of statements in a conditional
    statement.
chained conditional
    A conditional statement with a series of alternative branches.
comparison operator
    One of the operators that compares its operands: ``==``, ``!=``,
    ``>``, ``<``, ``>=``, and ``<=``.
conditional statement
    A statement that controls the flow of execution depending on some
    condition.
condition
    The boolean expression in a conditional statement that determines
    which branch is executed.
compound statement
    A statement that consists of a header and a body. The header ends
    with a colon (:). The body is indented relative to the header.
guardian pattern
    Where we construct a logical expression with additional comparisons
    to take advantage of the short-circuit behavior.
logical operator
    One of the operators that combines boolean expressions: ``and``,
    ``or``, and ``not``.
nested conditional
    A conditional statement that appears in one of the branches of
    another conditional statement.
traceback
    A list of the functions that are executing, printed when an
    exception occurs.
short circuit
    When Python is part-way through evaluating a logical expression and
    stops the evaluation because Python knows the final value for the
    expression without needing to evaluate the rest of the expression.

Exercises
---------

**Exercise 1: Rewrite your pay computation to give the employee 1.5
times the hourly rate for hours worked above 40 hours.**

::

    Enter Hours: 45
    Enter Rate: 10
    Pay: 475.0

**Exercise 2: Rewrite your pay program using ``try`` and ``except`` so
that your program handles non-numeric input gracefully by printing a
message and exiting the program. The following shows two executions of
the program:**

::

    Enter Hours: 20
    Enter Rate: nine
    Error, please enter numeric input

::

    Enter Hours: forty
    Error, please enter numeric input

**Exercise 3: Write a program to prompt for a score between 0.0 and 1.0.
If the score is out of range, print an error message. If the score is
between 0.0 and 1.0, print a grade using the following table:**

::

     Score   Grade
    >= 0.9     A
    >= 0.8     B
    >= 0.7     C
    >= 0.6     D
     < 0.6     F

::

    Enter score: 0.95
    A

::

    Enter score: perfect
    Bad score

::

    Enter score: 10.0
    Bad score

::

    Enter score: 0.75
    C

::

    Enter score: 0.5
    F

Run the program repeatedly as shown above to test the various different
values for input.

--------------

#. We will learn about functions in Chapter 4 and loops in Chapter
   5.\ `↩︎ <https://www.py4e.com/html3/03-conditional#fnref1>`__

--------------

If you find a mistake in this book, feel free to send me a fix using
`Github <https://github.com/csev/py4e/tree/master/book3>`__.

.. |If Logic| image:: ./chap3_files/if.svg
.. |If-Then-Else Logic| image:: ./chap3_files/if-else.svg
.. |If-Then-ElseIf Logic| image:: ./chap3_files/elif.svg
.. |Nested If Statements| image:: ./chap3_files/nested.svg