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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
Lists
=====
A list is a sequence
--------------------
Like a string, a *list* is a sequence of values. In a string, the values
are characters; in a list, they can be any type. The values in list are
called *elements* or sometimes *items*.
There are several ways to create a new list; the simplest is to enclose
the elements in square brackets (“[” and ”]”):
.. code:: python
[10, 20, 30, 40]
['crunchy frog', 'ram bladder', 'lark vomit']
The first example is a list of four integers. The second is a list of
three strings. The elements of a list don’t have to be the same type.
The following list contains a string, a float, an integer, and (lo!)
another list:
.. code:: python
['spam', 2.0, 5, [10, 20]]
A list within another list is *nested*.
A list that contains no elements is called an empty list; you can create
one with empty brackets, ``[]``.
As you might expect, you can assign list values to variables:
.. code:: python
>>> cheeses = ['Cheddar', 'Edam', 'Gouda']
>>> numbers = [17, 123]
>>> empty = []
>>> print(cheeses, numbers, empty)
['Cheddar', 'Edam', 'Gouda'] [17, 123] []
Lists are mutable
-----------------
The syntax for accessing the elements of a list is the same as for
accessing the characters of a string: the bracket operator. The
expression inside the brackets specifies the index. Remember that the
indices start at 0:
.. code:: python
>>> print(cheeses[0])
Cheddar
Unlike strings, lists are mutable because you can change the order of
items in a list or reassign an item in a list. When the bracket operator
appears on the left side of an assignment, it identifies the element of
the list that will be assigned.
.. code:: python
>>> numbers = [17, 123]
>>> numbers[1] = 5
>>> print(numbers)
[17, 5]
The one-th element of ``numbers``, which used to be 123, is now 5.
You can think of a list as a relationship between indices and elements.
This relationship is called a *mapping*; each index “maps to” one of the
elements.
List indices work the same way as string indices:
- Any integer expression can be used as an index.
- If you try to read or write an element that does not exist, you get
an ``IndexError``.
- If an index has a negative value, it counts backward from the end of
the list.
The ``in`` operator also works on lists.
.. code:: python
>>> cheeses = ['Cheddar', 'Edam', 'Gouda']
>>> 'Edam' in cheeses
True
>>> 'Brie' in cheeses
False
Traversing a list
-----------------
The most common way to traverse the elements of a list is with a ``for``
loop. The syntax is the same as for strings:
.. code:: python
for cheese in cheeses:
print(cheese)
This works well if you only need to read the elements of the list. But
if you want to write or update the elements, you need the indices. A
common way to do that is to combine the functions ``range`` and ``len``:
.. code:: python
for i in range(len(numbers)):
numbers[i] = numbers[i] * 2
This loop traverses the list and updates each element. ``len`` returns
the number of elements in the list. ``range`` returns a list of indices
from 0 to *n* − 1, where *n* is the length of the list. Each time
through the loop, ``i`` gets the index of the next element. The
assignment statement in the body uses ``i`` to read the old value of the
element and to assign the new value.
A ``for`` loop over an empty list never executes the body:
.. code:: python
for x in empty:
print('This never happens.')
Although a list can contain another list, the nested list still counts
as a single element. The length of this list is four:
.. code:: python
['spam', 1, ['Brie', 'Roquefort', 'Pol le Veq'], [1, 2, 3]]
List operations
---------------
The ``+`` operator concatenates lists:
.. code:: python
>>> a = [1, 2, 3]
>>> b = [4, 5, 6]
>>> c = a + b
>>> print(c)
[1, 2, 3, 4, 5, 6]
Similarly, the ``*`` operator repeats a list a given number of times:
.. code:: python
>>> [0] * 4
[0, 0, 0, 0]
>>> [1, 2, 3] * 3
[1, 2, 3, 1, 2, 3, 1, 2, 3]
The first example repeats four times. The second example repeats the
list three times.
List slices
-----------
The slice operator also works on lists:
.. code:: python
>>> t = ['a', 'b', 'c', 'd', 'e', 'f']
>>> t[1:3]
['b', 'c']
>>> t[:4]
['a', 'b', 'c', 'd']
>>> t[3:]
['d', 'e', 'f']
If you omit the first index, the slice starts at the beginning. If you
omit the second, the slice goes to the end. So if you omit both, the
slice is a copy of the whole list.
.. code:: python
>>> t[:]
['a', 'b', 'c', 'd', 'e', 'f']
Since lists are mutable, it is often useful to make a copy before
performing operations that fold, spindle, or mutilate lists.
A slice operator on the left side of an assignment can update multiple
elements:
.. code:: python
>>> t = ['a', 'b', 'c', 'd', 'e', 'f']
>>> t[1:3] = ['x', 'y']
>>> print(t)
['a', 'x', 'y', 'd', 'e', 'f']
List methods
------------
Python provides methods that operate on lists. For example, ``append``
adds a new element to the end of a list:
.. code:: python
>>> t = ['a', 'b', 'c']
>>> t.append('d')
>>> print(t)
['a', 'b', 'c', 'd']
``extend`` takes a list as an argument and appends all of the elements:
.. code:: python
>>> t1 = ['a', 'b', 'c']
>>> t2 = ['d', 'e']
>>> t1.extend(t2)
>>> print(t1)
['a', 'b', 'c', 'd', 'e']
This example leaves ``t2`` unmodified.
``sort`` arranges the elements of the list from low to high:
.. code:: python
>>> t = ['d', 'c', 'e', 'b', 'a']
>>> t.sort()
>>> print(t)
['a', 'b', 'c', 'd', 'e']
Most list methods are void; they modify the list and return ``None``. If
you accidentally write ``t = t.sort()``, you will be disappointed with
the result.
Deleting elements
-----------------
There are several ways to delete elements from a list. If you know the
index of the element you want, you can use ``pop``:
.. code:: python
>>> t = ['a', 'b', 'c']
>>> x = t.pop(1)
>>> print(t)
['a', 'c']
>>> print(x)
b
``pop`` modifies the list and returns the element that was removed. If
you don’t provide an index, it deletes and returns the last element.
If you don’t need the removed value, you can use the ``del`` statement:
.. code:: python
>>> t = ['a', 'b', 'c']
>>> del t[1]
>>> print(t)
['a', 'c']
If you know the element you want to remove (but not the index), you can
use ``remove``:
.. code:: python
>>> t = ['a', 'b', 'c']
>>> t.remove('b')
>>> print(t)
['a', 'c']
The return value from ``remove`` is ``None``.
To remove more than one element, you can use ``del`` with a slice index:
.. code:: python
>>> t = ['a', 'b', 'c', 'd', 'e', 'f']
>>> del t[1:5]
>>> print(t)
['a', 'f']
As usual, the slice selects all the elements up to, but not including,
the second index.
Lists and functions
-------------------
There are a number of built-in functions that can be used on lists that
allow you to quickly look through a list without writing your own loops:
.. code:: python
>>> nums = [3, 41, 12, 9, 74, 15]
>>> print(len(nums))
6
>>> print(max(nums))
74
>>> print(min(nums))
3
>>> print(sum(nums))
154
>>> print(sum(nums)/len(nums))
25
The ``sum()`` function only works when the list elements are numbers.
The other functions (``max()``, ``len()``, etc.) work with lists of
strings and other types that can be comparable.
We could rewrite an earlier program that computed the average of a list
of numbers entered by the user using a list.
First, the program to compute an average without a list:
.. code:: python
total = 0
count = 0
while (True):
inp = input('Enter a number: ')
if inp == 'done': break
value = float(inp)
total = total + value
count = count + 1
average = total / count
print('Average:', average)
# Code: http://www.py4e.com/code3/avenum.py
In this program, we have ``count`` and ``total`` variables to keep the
number and running total of the user’s numbers as we repeatedly prompt
the user for a number.
We could simply remember each number as the user entered it and use
built-in functions to compute the sum and count at the end.
.. code:: python
numlist = list()
while (True):
inp = input('Enter a number: ')
if inp == 'done': break
value = float(inp)
numlist.append(value)
average = sum(numlist) / len(numlist)
print('Average:', average)
# Code: http://www.py4e.com/code3/avelist.py
We make an empty list before the loop starts, and then each time we have
a number, we append it to the list. At the end of the program, we simply
compute the sum of the numbers in the list and divide it by the count of
the numbers in the list to come up with the average.
Lists and strings
-----------------
A string is a sequence of characters and a list is a sequence of values,
but a list of characters is not the same as a string. To convert from a
string to a list of characters, you can use ``list``:
.. code:: python
>>> s = 'spam'
>>> t = list(s)
>>> print(t)
['s', 'p', 'a', 'm']
Because ``list`` is the name of a built-in function, you should avoid
using it as a variable name. I also avoid the letter “l” because it
looks too much like the number “1”. So that’s why I use “t”.
The ``list`` function breaks a string into individual letters. If you
want to break a string into words, you can use the ``split`` method:
.. code:: python
>>> s = 'pining for the fjords'
>>> t = s.split()
>>> print(t)
['pining', 'for', 'the', 'fjords']
>>> print(t[2])
the
Once you have used ``split`` to break the string into a list of words,
you can use the index operator (square bracket) to look at a particular
word in the list.
You can call ``split`` with an optional argument called a *delimiter*
that specifies which characters to use as word boundaries. The following
example uses a hyphen as a delimiter:
.. code:: python
>>> s = 'spam-spam-spam'
>>> delimiter = '-'
>>> s.split(delimiter)
['spam', 'spam', 'spam']
``join`` is the inverse of ``split``. It takes a list of strings and
concatenates the elements. ``join`` is a string method, so you have to
invoke it on the delimiter and pass the list as a parameter:
.. code:: python
>>> t = ['pining', 'for', 'the', 'fjords']
>>> delimiter = ' '
>>> delimiter.join(t)
'pining for the fjords'
In this case the delimiter is a space character, so ``join`` puts a
space between words. To concatenate strings without spaces, you can use
the empty string, ““, as a delimiter.
Parsing lines
-------------
Usually when we are reading a file we want to do something to the lines
other than just printing the whole line. Often we want to find the
“interesting lines” and then *parse* the line to find some interesting
*part* of the line. What if we wanted to print out the day of the week
from those lines that start with “From”?
::
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008
The ``split`` method is very effective when faced with this kind of
problem. We can write a small program that looks for lines where the
line starts with “From”, ``split`` those lines, and then print out the
third word in the line:
.. code:: python
fhand = open('mbox-short.txt')
for line in fhand:
line = line.rstrip()
if not line.startswith('From '): continue
words = line.split()
print(words[2])
# Code: http://www.py4e.com/code3/search5.py
The program produces the following output:
::
Sat
Fri
Fri
Fri
...
Later, we will learn increasingly sophisticated techniques for picking
the lines to work on and how we pull those lines apart to find the exact
bit of information we are looking for.
Objects and values
------------------
If we execute these assignment statements:
.. code:: python
a = 'banana'
b = 'banana'
we know that ``a`` and ``b`` both refer to a string, but we don’t know
whether they refer to the *same* string. There are two possible states:
|Variables and Objects|
Variables and Objects
In one case, ``a`` and ``b`` refer to two different objects that have
the same value. In the second case, they refer to the same object.
To check whether two variables refer to the same object, you can use the
``is`` operator.
.. code:: python
>>> a = 'banana'
>>> b = 'banana'
>>> a is b
True
In this example, Python only created one string object, and both ``a``
and ``b`` refer to it.
But when you create two lists, you get two objects:
.. code:: python
>>> a = [1, 2, 3]
>>> b = [1, 2, 3]
>>> a is b
False
In this case we would say that the two lists are *equivalent*, because
they have the same elements, but not *identical*, because they are not
the same object. If two objects are identical, they are also equivalent,
but if they are equivalent, they are not necessarily identical.
Until now, we have been using “object” and “value” interchangeably, but
it is more precise to say that an object has a value. If you execute
``a = [1,2,3]``, ``a`` refers to a list object whose value is a
particular sequence of elements. If another list has the same elements,
we would say it has the same value.
Aliasing
--------
If ``a`` refers to an object and you assign ``b = a``, then both
variables refer to the same object:
.. code:: python
>>> a = [1, 2, 3]
>>> b = a
>>> b is a
True
The association of a variable with an object is called a *reference*. In
this example, there are two references to the same object.
An object with more than one reference has more than one name, so we say
that the object is *aliased*.
If the aliased object is mutable, changes made with one alias affect the
other:
.. code:: python
>>> b[0] = 17
>>> print(a)
[17, 2, 3]
Although this behavior can be useful, it is error-prone. In general, it
is safer to avoid aliasing when you are working with mutable objects.
For immutable objects like strings, aliasing is not as much of a
problem. In this example:
.. code:: python
a = 'banana'
b = 'banana'
it almost never makes a difference whether ``a`` and ``b`` refer to the
same string or not.
List arguments
--------------
When you pass a list to a function, the function gets a reference to the
list. If the function modifies a list parameter, the caller sees the
change. For example, ``delete_head`` removes the first element from a
list:
.. code:: python
def delete_head(t):
del t[0]
Here’s how it is used:
.. code:: python
>>> letters = ['a', 'b', 'c']
>>> delete_head(letters)
>>> print(letters)
['b', 'c']
The parameter ``t`` and the variable ``letters`` are aliases for the
same object.
It is important to distinguish between operations that modify lists and
operations that create new lists. For example, the ``append`` method
modifies a list, but the ``+`` operator creates a new list:
.. code:: python
>>> t1 = [1, 2]
>>> t2 = t1.append(3)
>>> print(t1)
[1, 2, 3]
>>> print(t2)
None
>>> t3 = t1 + [3]
>>> print(t3)
[1, 2, 3]
>>> t2 is t3
False
This difference is important when you write functions that are supposed
to modify lists. For example, this function *does not* delete the head
of a list:
.. code:: python
def bad_delete_head(t):
t = t[1:] # WRONG!
The slice operator creates a new list and the assignment makes ``t``
refer to it, but none of that has any effect on the list that was passed
as an argument.
An alternative is to write a function that creates and returns a new
list. For example, ``tail`` returns all but the first element of a list:
.. code:: python
def tail(t):
return t[1:]
This function leaves the original list unmodified. Here’s how it is
used:
.. code:: python
>>> letters = ['a', 'b', 'c']
>>> rest = tail(letters)
>>> print(rest)
['b', 'c']
**Exercise 1: Write a function called ``chop`` that takes a list and
modifies it, removing the first and last elements, and returns ``None``.
Then write a function called ``middle`` that takes a list and returns a
new list that contains all but the first and last elements.**
Debugging
---------
Careless use of lists (and other mutable objects) can lead to long hours
of debugging. Here are some common pitfalls and ways to avoid them:
#. Don’t forget that most list methods modify the argument and return
``None``. This is the opposite of the string methods, which return a
new string and leave the original alone.
If you are used to writing string code like this:
.. code:: python
word = word.strip()
It is tempting to write list code like this:
.. code:: python
t = t.sort() # WRONG!
Because ``sort`` returns ``None``, the next operation you perform
with ``t`` is likely to fail.
Before using list methods and operators, you should read the
documentation carefully and then test them in interactive mode. The
methods and operators that lists share with other sequences (like
strings) are documented at:
`docs.python.org/library/stdtypes.html#common-sequence-operations `__
The methods and operators that only apply to mutable sequences are
documented at:
`docs.python.org/library/stdtypes.html#mutable-sequence-types `__
#. Pick an idiom and stick with it.
Part of the problem with lists is that there are too many ways to do
things. For example, to remove an element from a list, you can use
``pop``, ``remove``, ``del``, or even a slice assignment.
To add an element, you can use the ``append`` method or the ``+``
operator. But don’t forget that these are right:
.. code:: python
t.append(x)
t = t + [x]
And these are wrong:
.. code:: python
t.append([x]) # WRONG!
t = t.append(x) # WRONG!
t + [x] # WRONG!
t = t + x # WRONG!
Try out each of these examples in interactive mode to make sure you
understand what they do. Notice that only the last one causes a
runtime error; the other three are legal, but they do the wrong
thing.
#. Make copies to avoid aliasing.
If you want to use a method like ``sort`` that modifies the argument,
but you need to keep the original list as well, you can make a copy.
.. code:: python
orig = t[:]
t.sort()
In this example you could also use the built-in function ``sorted``,
which returns a new, sorted list and leaves the original alone. But
in that case you should avoid using ``sorted`` as a variable name!
#. Lists, ``split``, and files
When we read and parse files, there are many opportunities to
encounter input that can crash our program so it is a good idea to
revisit the *guardian* pattern when it comes writing programs that
read through a file and look for a “needle in the haystack”.
Let’s revisit our program that is looking for the day of the week on
the from lines of our file:
::
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008
Since we are breaking this line into words, we could dispense with
the use of ``startswith`` and simply look at the first word of the
line to determine if we are interested in the line at all. We can use
``continue`` to skip lines that don’t have “From” as the first word
as follows:
.. code:: python
fhand = open('mbox-short.txt')
for line in fhand:
words = line.split()
if words[0] != 'From' : continue
print(words[2])
This looks much simpler and we don’t even need to do the ``rstrip``
to remove the newline at the end of the file. But is it better?
::
python search8.py
Sat
Traceback (most recent call last):
File "search8.py", line 5, in
if words[0] != 'From' : continue
IndexError: list index out of range
It kind of works and we see the day from the first line (Sat), but
then the program fails with a traceback error. What went wrong? What
messed-up data caused our elegant, clever, and very Pythonic program
to fail?
You could stare at it for a long time and puzzle through it or ask
someone for help, but the quicker and smarter approach is to add a
``print`` statement. The best place to add the print statement is
right before the line where the program failed and print out the data
that seems to be causing the failure.
Now this approach may generate a lot of lines of output, but at least
you will immediately have some clue as to the problem at hand. So we
add a print of the variable ``words`` right before line five. We even
add a prefix “Debug:” to the line so we can keep our regular output
separate from our debug output.
.. code:: python
for line in fhand:
words = line.split()
print('Debug:', words)
if words[0] != 'From' : continue
print(words[2])
When we run the program, a lot of output scrolls off the screen but
at the end, we see our debug output and the traceback so we know what
happened just before the traceback.
::
Debug: ['X-DSPAM-Confidence:', '0.8475']
Debug: ['X-DSPAM-Probability:', '0.0000']
Debug: []
Traceback (most recent call last):
File "search9.py", line 6, in
if words[0] != 'From' : continue
IndexError: list index out of range
Each debug line is printing the list of words which we get when we
``split`` the line into words. When the program fails, the list of
words is empty ``[]``. If we open the file in a text editor and look
at the file, at that point it looks as follows:
::
X-DSPAM-Result: Innocent
X-DSPAM-Processed: Sat Jan 5 09:14:16 2008
X-DSPAM-Confidence: 0.8475
X-DSPAM-Probability: 0.0000
Details: http://source.sakaiproject.org/viewsvn/?view=rev&rev=39772
The error occurs when our program encounters a blank line! Of course
there are “zero words” on a blank line. Why didn’t we think of that
when we were writing the code? When the code looks for the first word
(``word[0]``) to check to see if it matches “From”, we get an “index
out of range” error.
This of course is the perfect place to add some *guardian* code to
avoid checking the first word if the first word is not there. There
are many ways to protect this code; we will choose to check the
number of words we have before we look at the first word:
.. code:: python
fhand = open('mbox-short.txt')
count = 0
for line in fhand:
words = line.split()
# print('Debug:', words)
if len(words) == 0 : continue
if words[0] != 'From' : continue
print(words[2])
First we commented out the debug print statement instead of removing
it, in case our modification fails and we need to debug again. Then
we added a guardian statement that checks to see if we have zero
words, and if so, we use ``continue`` to skip to the next line in the
file.
We can think of the two ``continue`` statements as helping us refine
the set of lines which are “interesting” to us and which we want to
process some more. A line which has no words is “uninteresting” to us
so we skip to the next line. A line which does not have “From” as its
first word is uninteresting to us so we skip it.
The program as modified runs successfully, so perhaps it is correct.
Our guardian statement does make sure that the ``words[0]`` will
never fail, but perhaps it is not enough. When we are programming, we
must always be thinking, “What might go wrong?”
**Exercise 2: Figure out which line of the above program is still not
properly guarded. See if you can construct a text file which causes the
program to fail and then modify the program so that the line is properly
guarded and test it to make sure it handles your new text file.**
**Exercise 3: Rewrite the guardian code in the above example without two
``if`` statements. Instead, use a compound logical expression using the
``or`` logical operator with a single ``if`` statement.**
Glossary
--------
aliasing
A circumstance where two or more variables refer to the same object.
delimiter
A character or string used to indicate where a string should be
split.
element
One of the values in a list (or other sequence); also called items.
equivalent
Having the same value.
index
An integer value that indicates an element in a list.
identical
Being the same object (which implies equivalence).
list
A sequence of values.
list traversal
The sequential accessing of each element in a list.
nested list
A list that is an element of another list.
object
Something a variable can refer to. An object has a type and a value.
reference
The association between a variable and its value.
Exercises
---------
**Exercise 4: Find all unique words in a file**
**Shakespeare used over 20,000 words in his works. But how would you
determine that? How would you produce the list of all the words that
Shakespeare used? Would you download all his work, read it and track all
unique words by hand?**
**Let’s use Python to achieve that instead. List all unique words,
sorted in alphabetical order, that are stored in a file ``romeo.txt``
containing a subset of Shakespeare’s work.**
**To get started, download a copy of the file**
`**www.py4e.com/code3/romeo.txt** `__\ **.
Create a list of unique words, which will contain the final result.
Write a program to open the file ``romeo.txt`` and read it line by line.
For each line, split the line into a list of words using the ``split``
function. For each word, check to see if the word is already in the list
of unique words. If the word is not in the list of unique words, add it
to the list. When the program completes, sort and print the list of
unique words in alphabetical order.**
::
Enter file: romeo.txt
['Arise', 'But', 'It', 'Juliet', 'Who', 'already',
'and', 'breaks', 'east', 'envious', 'fair', 'grief',
'is', 'kill', 'light', 'moon', 'pale', 'sick', 'soft',
'sun', 'the', 'through', 'what', 'window',
'with', 'yonder']
**Exercise 5: Minimalist Email Client.**
**MBOX (mail box) is a popular file format to store and share a
collection of emails. This was used by early email servers and desktop
apps. Without getting into too many details, MBOX is a text file, which
stores emails consecutively. Emails are separated by a special line
which starts with ``From`` (notice the space). Importantly, lines
starting with ``From:`` (notice the colon) describes the email itself
and does not act as a separator. Imagine you wrote a minimalist email
app, that lists the email of the senders in the user’s Inbox and counts
the number of emails.**
**Write a program to read through the mail box data and when you find
line that starts with “From”, you will split the line into words using
the ``split`` function. We are interested in who sent the message, which
is the second word on the From line.**
::
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008
**You will parse the From line and print out the second word for each
From line, then you will also count the number of From (not From:) lines
and print out a count at the end. This is a good sample output with a
few lines removed:**
::
python fromcount.py
Enter a file name: mbox-short.txt
stephen.marquard@uct.ac.za
louis@media.berkeley.edu
zqian@umich.edu
[...some output removed...]
ray@media.berkeley.edu
cwen@iupui.edu
cwen@iupui.edu
cwen@iupui.edu
There were 27 lines in the file with From as the first word
**Exercise 6: Rewrite the program that prompts the user for a list of
numbers and prints out the maximum and minimum of the numbers at the end
when the user enters “done”. Write the program to store the numbers the
user enters in a list and use the ``max()`` and ``min()`` functions to
compute the maximum and minimum numbers after the loop completes.**
::
Enter a number: 6
Enter a number: 2
Enter a number: 9
Enter a number: 3
Enter a number: 5
Enter a number: done
Maximum: 9.0
Minimum: 2.0
--------------
If you find a mistake in this book, feel free to send me a fix using
`Github `__.
.. |Variables and Objects| image:: ./chap8_files/list1.svg