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

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`PY4E <https://www.py4e.com/>`__

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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

Variables, expressions, and statements
======================================

Values and types
----------------

A *value* is one of the basic things a program works with, like a letter
or a number. The values we have seen so far are 1, 2, and “Hello,
World!”

These values belong to different *types*: 2 is an integer, and “Hello,
World!” is a *string*, so called because it contains a “string” of
letters. You (and the interpreter) can identify strings because they are
enclosed in quotation marks.

The ``print`` statement also works for integers. We use the ``python``
command to start the interpreter.

.. code:: python

    python
    >>> print(4)
    4

If you are not sure what type a value has, the interpreter can tell you.

.. code:: python

    >>> type('Hello, World!')
    <class 'str'>
    >>> type(17)
    <class 'int'>

Not surprisingly, strings belong to the type ``str`` and integers belong
to the type ``int``. Less obviously, numbers with a decimal point belong
to a type called ``float``, because these numbers are represented in a
format called *floating point*.

.. code:: python

    >>> type(3.2)
    <class 'float'>

What about values like “17” and “3.2”? They look like numbers, but they
are in quotation marks like strings.

.. code:: python

    >>> type('17')
    <class 'str'>
    >>> type('3.2')
    <class 'str'>

They’re strings.

When you type a large integer, you might be tempted to use commas
between groups of three digits, as in 1,000,000. This is not a legal
integer in Python, but it is legal:

.. code:: python

    >>> print(1,000,000)
    1 0 0

Well, that’s not what we expected at all! Python interprets 1,000,000 as
a comma-separated sequence of integers, which it prints with spaces
between.

This is the first example we have seen of a semantic error: the code
runs without producing an error message, but it doesn’t do the “right”
thing.

Variables
---------

One of the most powerful features of a programming language is the
ability to manipulate *variables*. A variable is a name that refers to a
value.

An *assignment statement* creates new variables and gives them values:

.. code:: python

    >>> message = 'And now for something completely different'
    >>> n = 17
    >>> pi = 3.1415926535897931

This example makes three assignments. The first assigns a string to a
new variable named ``message``; the second assigns the integer 17 to
``n``; the third assigns the (approximate) value of *π* to ``pi``.

To display the value of a variable, you can use a print statement:

.. code:: python

    >>> print(n)
    17
    >>> print(pi)
    3.141592653589793

The type of a variable is the type of the value it refers to.

.. code:: python

    >>> type(message)
    <class 'str'>
    >>> type(n)
    <class 'int'>
    >>> type(pi)
    <class 'float'>

Variable names and keywords
---------------------------

Programmers generally choose names for their variables that are
meaningful and document what the variable is used for.

Variable names can be arbitrarily long. They can contain both letters
and numbers, but they cannot start with a number. It is legal to use
uppercase letters, but it is a good idea to begin variable names with a
lowercase letter (you’ll see why later).

The underscore character ( \_ ) can appear in a name. It is often used
in names with multiple words, such as ``my_name`` or
``airspeed_of_unladen_swallow``. Variable names can start with an
underscore character, but we generally avoid doing this unless we are
writing library code for others to use.

If you give a variable an illegal name, you get a syntax error:

.. code:: python

    >>> 76trombones = 'big parade'
    SyntaxError: invalid syntax
    >>> more@ = 1000000
    SyntaxError: invalid syntax
    >>> class = 'Advanced Theoretical Zymurgy'
    SyntaxError: invalid syntax

``76trombones`` is illegal because it begins with a number. ``more@`` is
illegal because it contains an illegal character, @. But what’s wrong
with ``class``?

It turns out that ``class`` is one of Python’s *keywords*. The
interpreter uses keywords to recognize the structure of the program, and
they cannot be used as variable names.

Python reserves 35 keywords:

::

    and       del       from      None      True
    as        elif      global    nonlocal  try
    assert    else      if        not       while
    break     except    import    or        with
    class     False     in        pass      yield
    continue  finally   is        raise     async
    def       for       lambda    return    await

You might want to keep this list handy. If the interpreter complains
about one of your variable names and you don’t know why, see if it is on
this list.

Statements
----------

A *statement* is a unit of code that the Python interpreter can execute.
We have seen two kinds of statements: print being an expression
statement and assignment.

When you type a statement in interactive mode, the interpreter executes
it and displays the result, if there is one.

A script usually contains a sequence of statements. If there is more
than one statement, the results appear one at a time as the statements
execute.

For example, the script

.. code:: python

    print(1)
    x = 2
    print(x)

produces the output

::

    1
    2

The assignment statement produces no output.

Operators and operands
----------------------

*Operators* are special symbols that represent computations like
addition and multiplication. The values the operator is applied to are
called *operands*.

The operators ``+``, ``-``, ``*``, ``/``, and ``**`` perform addition,
subtraction, multiplication, division, and exponentiation, as in the
following examples:

.. code:: python

    20+32
    hour-1
    hour*60+minute
    minute/60
    5**2
    (5+9)*(15-7)

There has been a change in the division operator between Python 2.x and
Python 3.x. In Python 3.x, the result of this division is a floating
point result:

.. code:: python

    >>> minute = 59
    >>> minute/60
    0.9833333333333333

The division operator in Python 2.0 would divide two integers and
truncate the result to an integer:

.. code:: python

    >>> minute = 59
    >>> minute/60
    0

To obtain the same answer in Python 3.0 use floored ( ``//`` integer)
division.

.. code:: python

    >>> minute = 59
    >>> minute//60
    0

In Python 3.0 integer division functions much more as you would expect
if you entered the expression on a calculator.

Expressions
-----------

An *expression* is a combination of values, variables, and operators. A
value all by itself is considered an expression, and so is a variable,
so the following are all legal expressions (assuming that the variable
``x`` has been assigned a value):

.. code:: python

    17
    x
    x + 17

If you type an expression in interactive mode, the interpreter
*evaluates* it and displays the result:

.. code:: python

    >>> 1 + 1
    2

But in a script, an expression all by itself doesn’t do anything! This
is a common source of confusion for beginners.

**Exercise 1: Type the following statements in the Python interpreter to
see what they do:**

.. code:: python

    5
    x = 5
    x + 1

Order of operations
-------------------

When more than one operator appears in an expression, the order of
evaluation depends on the *rules of precedence*. For mathematical
operators, Python follows mathematical convention. The acronym *PEMDAS*
is a useful way to remember the rules:

-  *P*\ arentheses have the highest precedence and can be used to force
   an expression to evaluate in the order you want. Since expressions in
   parentheses are evaluated first, ``2 *     (3-1)`` is 4, and
   ``(1+1)**(5-2)`` is 8. You can also use parentheses to make an
   expression easier to read, as in ``(minute * 100) / 60``, even if it
   doesn’t change the result.

-  *E*\ xponentiation has the next highest precedence, so ``2**1+1`` is
   3, not 4, and ``3*1**3`` is 3, not 27.

-  *M*\ ultiplication and *D*\ ivision have the same precedence, which
   is higher than *A*\ ddition and *S*\ ubtraction, which also have the
   same precedence. So ``2*3-1`` is 5, not 4, and ``6+4/2`` is 8, not 5.

-  Operators with the same precedence are evaluated from left to right.
   So the expression ``5-3-1`` is 1, not 3, because the ``5-3`` happens
   first and then ``1`` is subtracted from 2.

When in doubt, always put parentheses in your expressions to make sure
the computations are performed in the order you intend.

Modulus operator
----------------

The *modulus operator* works on integers and yields the remainder when
the first operand is divided by the second. In Python, the modulus
operator is a percent sign (``%``). The syntax is the same as for other
operators:

.. code:: python

    >>> quotient = 7 // 3
    >>> print(quotient)
    2
    >>> remainder = 7 % 3
    >>> print(remainder)
    1

So 7 divided by 3 is 2 with 1 left over.

The modulus operator turns out to be surprisingly useful. For example,
you can check whether one number is divisible by another: if ``x % y``
is zero, then ``x`` is divisible by ``y``.

You can also extract the right-most digit or digits from a number. For
example, ``x % 10`` yields the right-most digit of ``x`` (in base 10).
Similarly, ``x % 100`` yields the last two digits.

String operations
-----------------

The ``+`` operator works with strings, but it is not addition in the
mathematical sense. Instead it performs *concatenation*, which means
joining the strings by linking them end to end. For example:

.. code:: python

    >>> first = 10
    >>> second = 15
    >>> print(first+second)
    25
    >>> first = '100'
    >>> second = '150'
    >>> print(first + second)
    100150

The ``*`` operator also works with strings by multiplying the content of
a string by an integer. For example:

.. code:: python

    >>> first = 'Test '
    >>> second = 3
    >>> print(first * second)
    Test Test Test

Asking the user for input
-------------------------

Sometimes we would like to take the value for a variable from the user
via their keyboard. Python provides a built-in function called ``input``
that gets input from the
keyboard\ `:sup:`1` <https://www.py4e.com/html3/02-variables#fn1>`__.
When this function is called, the program stops and waits for the user
to type something. When the user presses ``Return`` or ``Enter``, the
program resumes and ``input`` returns what the user typed as a string.

.. code:: python

    >>> inp = input()
    Some silly stuff
    >>> print(inp)
    Some silly stuff

Before getting input from the user, it is a good idea to print a prompt
telling the user what to input. You can pass a string to ``input`` to be
displayed to the user before pausing for input:

.. code:: python

    >>> name = input('What is your name?\n')
    What is your name?
    Chuck
    >>> print(name)
    Chuck

The sequence ``\n`` at the end of the prompt represents a *newline*,
which is a special character that causes a line break. That’s why the
user’s input appears below the prompt.

If you expect the user to type an integer, you can try to convert the
return value to ``int`` using the ``int()`` function:

.. code:: python

    >>> prompt = 'What...is the airspeed velocity of an unladen swallow?\n'
    >>> speed = input(prompt)
    What...is the airspeed velocity of an unladen swallow?
    17
    >>> int(speed)
    17
    >>> int(speed) + 5
    22

But if the user types something other than a string of digits, you get
an error:

.. code:: python

    >>> speed = input(prompt)
    What...is the airspeed 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:

We will see how to handle this kind of error later.

Comments
--------

As programs get bigger and more complicated, they get more difficult to
read. Formal languages are dense, and it is often difficult to look at a
piece of code and figure out what it is doing, or why.

For this reason, it is a good idea to add notes to your programs to
explain in natural language what the program is doing. These notes are
called *comments*, and in Python they start with the ``#`` symbol:

.. code:: python

    # compute the percentage of the hour that has elapsed
    percentage = (minute * 100) / 60

In this case, the comment appears on a line by itself. You can also put
comments at the end of a line:

.. code:: python

    percentage = (minute * 100) / 60     # percentage of an hour

Everything from the ``#`` to the end of the line is ignored; it has no
effect on the program.

Comments are most useful when they document non-obvious features of the
code. It is reasonable to assume that the reader can figure out *what*
the code does; it is much more useful to explain *why*.

This comment is redundant with the code and useless:

.. code:: python

    v = 5     # assign 5 to v

This comment contains useful information that is not in the code:

.. code:: python

    v = 5     # velocity in meters/second.

Good variable names can reduce the need for comments, but long names can
make complex expressions hard to read, so there is a trade-off.

Choosing mnemonic variable names
--------------------------------

As long as you follow the simple rules of variable naming, and avoid
reserved words, you have a lot of choice when you name your variables.
In the beginning, this choice can be confusing both when you read a
program and when you write your own programs. For example, the following
three programs are identical in terms of what they accomplish, but very
different when you read them and try to understand them.

.. code:: python

    a = 35.0
    b = 12.50
    c = a * b
    print(c)

.. code:: python

    hours = 35.0
    rate = 12.50
    pay = hours * rate
    print(pay)

.. code:: python

    x1q3z9ahd = 35.0
    x1q3z9afd = 12.50
    x1q3p9afd = x1q3z9ahd * x1q3z9afd
    print(x1q3p9afd)

The Python interpreter sees all three of these programs as *exactly the
same* but humans see and understand these programs quite differently.
Humans will most quickly understand the *intent* of the second program
because the programmer has chosen variable names that reflect their
intent regarding what data will be stored in each variable.

We call these wisely chosen variable names “mnemonic variable names”.
The word
*mnemonic*\ `:sup:`2` <https://www.py4e.com/html3/02-variables#fn2>`__
means “memory aid”. We choose mnemonic variable names to help us
remember why we created the variable in the first place.

While this all sounds great, and it is a very good idea to use mnemonic
variable names, mnemonic variable names can get in the way of a
beginning programmer’s ability to parse and understand code. This is
because beginning programmers have not yet memorized the reserved words
(there are only 33 of them) and sometimes variables with names that are
too descriptive start to look like part of the language and not just
well-chosen variable names.

Take a quick look at the following Python sample code which loops
through some data. We will cover loops soon, but for now try to just
puzzle through what this means:

.. code:: python

    for word in words:
        print(word)

What is happening here? Which of the tokens (for, word, in, etc.) are
reserved words and which are just variable names? Does Python understand
at a fundamental level the notion of words? Beginning programmers have
trouble separating what parts of the code *must* be the same as this
example and what parts of the code are simply choices made by the
programmer.

The following code is equivalent to the above code:

.. code:: python

    for slice in pizza:
        print(slice)

It is easier for the beginning programmer to look at this code and know
which parts are reserved words defined by Python and which parts are
simply variable names chosen by the programmer. It is pretty clear that
Python has no fundamental understanding of pizza and slices and the fact
that a pizza consists of a set of one or more slices.

But if our program is truly about reading data and looking for words in
the data, ``pizza`` and ``slice`` are very un-mnemonic variable names.
Choosing them as variable names distracts from the meaning of the
program.

After a pretty short period of time, you will know the most common
reserved words and you will start to see the reserved words jumping out
at you:

::

    for word in words:
        print(word)

The parts of the code that are defined by Python (``for``, ``in``,
``print``, and ``:``) are in bold and the programmer-chosen variables
(``word`` and ``words``) are not in bold. Many text editors are aware of
Python syntax and will color reserved words differently to give you
clues to keep your variables and reserved words separate. After a while
you will begin to read Python and quickly determine what is a variable
and what is a reserved word.

Debugging
---------

At this point, the syntax error you are most likely to make is an
illegal variable name, like ``class`` and ``yield``, which are keywords,
or ``odd~job`` and ``US$``, which contain illegal characters.

If you put a space in a variable name, Python thinks it is two operands
without an operator:

.. code:: python

    >>> bad name = 5
    SyntaxError: invalid syntax

.. code:: python

    >>> month = 09
      File "<stdin>", line 1
        month = 09
                 ^
    SyntaxError: invalid token

For syntax errors, the error messages don’t help much. The most common
messages are ``SyntaxError: invalid syntax`` and
``SyntaxError: invalid token``, neither of which is very informative.

The runtime error you are most likely to make is a “use before def;”
that is, trying to use a variable before you have assigned a value. This
can happen if you spell a variable name wrong:

.. code:: python

    >>> principal = 327.68
    >>> interest = principle * rate
    NameError: name 'principle' is not defined

Variables names are case sensitive, so ``LaTeX`` is not the same as
``latex``.

At this point, the most likely cause of a semantic error is the order of
operations. For example, to evaluate 1/2\ *π*, you might be tempted to
write

.. code:: python

    >>> 1.0 / 2.0 * pi

But the division happens first, so you would get *π*/2, which is not the
same thing! There is no way for Python to know what you meant to write,
so in this case you don’t get an error message; you just get the wrong
answer.

Glossary
--------

assignment
    A statement that assigns a value to a variable.
concatenate
    To join two operands end to end.
comment
    Information in a program that is meant for other programmers (or
    anyone reading the source code) and has no effect on the execution
    of the program.
evaluate
    To simplify an expression by performing the operations in order to
    yield a single value.
expression
    A combination of variables, operators, and values that represents a
    single result value.
floating point
    A type that represents numbers with fractional parts.
integer
    A type that represents whole numbers.
keyword
    A reserved word that is used by the compiler to parse a program; you
    cannot use keywords like ``if``, ``def``, and ``while`` as variable
    names.
mnemonic
    A memory aid. We often give variables mnemonic names to help us
    remember what is stored in the variable.
modulus operator
    An operator, denoted with a percent sign (``%``), that works on
    integers and yields the remainder when one number is divided by
    another.
operand
    One of the values on which an operator operates.
operator
    A special symbol that represents a simple computation like addition,
    multiplication, or string concatenation.
rules of precedence
    The set of rules governing the order in which expressions involving
    multiple operators and operands are evaluated.
statement
    A section of code that represents a command or action. So far, the
    statements we have seen are assignments and print expression
    statement.
string
    A type that represents sequences of characters.
type
    A category of values. The types we have seen so far are integers
    (type ``int``), floating-point numbers (type ``float``), and strings
    (type ``str``).
value
    One of the basic units of data, like a number or string, that a
    program manipulates.
variable
    A name that refers to a value.

Exercises
---------

**Exercise 2: Write a program that uses ``input`` to prompt a user for
their name and then welcomes them.**

::

    Enter your name: Chuck
    Hello Chuck

**Exercise 3: Write a program to prompt the user for hours and rate per
hour to compute gross pay.**

::

    Enter Hours: 35
    Enter Rate: 2.75
    Pay: 96.25

We won’t worry about making sure our pay has exactly two digits after
the decimal place for now. If you want, you can play with the built-in
Python ``round`` function to properly round the resulting pay to two
decimal places.

**Exercise 4: Assume that we execute the following assignment
statements:**

::

    width = 17
    height = 12.0

For each of the following expressions, write the value of the expression
and the type (of the value of the expression).

#. ``width//2``

#. ``width/2.0``

#. ``height/3``

#. ``1 + 2 * 5``

Use the Python interpreter to check your answers.

**Exercise 5: Write a program which prompts the user for a Celsius
temperature, convert the temperature to Fahrenheit, and print out the
converted temperature.**

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

#. In Python 2.0, this function was named
   ``raw_input``.\ `↩︎ <https://www.py4e.com/html3/02-variables#fnref1>`__

#. See https://en.wikipedia.org/wiki/Mnemonic for an extended
   description of the word
   “mnemonic”.\ `↩︎ <https://www.py4e.com/html3/02-variables#fnref2>`__

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

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>`__.
