# Think Python/Files



## Persistence

Most of the programs we have seen so far are transient in the sense that
they run for a short time and produce some output, but when they end,
their data disappears. If you run the program again, it starts with a
clean slate.

Other programs are **persistent**: they run for a long time (or all the
time); they keep at least some of their data in permanent storage (a
hard drive, for example); and if they shut down and restart, they pick
up where they left off.

Examples of persistent programs are operating systems, which run pretty
much whenever a computer is on, and web servers, which run all the time,
waiting for requests to come in on the network.

One of the simplest ways for programs to maintain their data is by
reading and writing text files. We have already seen programs that read
text files; in this chapters we will see programs that write them.

An alternative is to store the state of the program in a database. In
this chapter I will present a simple database and a module, `pickle`,
that makes it easy to store program data.

## Reading and writing

A text file is a sequence of characters stored on a permanent medium
like a hard drive, flash memory, or CD-ROM. We saw how to open and read
a file in Section 9.1.

To write a file, you have to open it with mode `'w'` as a second
parameter:

``` python
>>> fout = open('output.txt', 'w')
>>> print fout
&lt;open file 'output.txt', mode 'w' at 0xb7eb2410>
```

If the file already exists, opening it in write mode clears out the old
data and starts fresh, so be careful! If the file doesn't exist, a new
one is created.

The `write` method puts data into the file.

``` python
>>> line1 = "This here's the wattle,\n"
>>> fout.write(line1)
```

Again, the file object keeps track of where it is, so if you call
`write` again, it adds the new data to the end.

``` python
>>> line2 = "the emblem of our land.\n"
>>> fout.write(line2)
```

When you are done writing, you have to close the file.

``` python
>>> fout.close()
```

## Format operator

The argument of `write` has to be a string, so if we want to put other
values in a file, we have to convert them to strings. The easiest way to
do that is with `str`:

``` python
>>> x = 52
>>> f.write(str(x))
```

An alternative is to use the **format operator**, `%`. When applied to
integers, `%` is the modulus operator. But when the first operand is a
string, `%` is the format operator.

The first operand is the **format string**, and the second operand is a
tuple of expressions. The result is a string that contains the values of
the expressions, formatted according to the format string.

As an example, the **format sequence** `'%d'` means that the first
expression in the tuple should be formatted as an integer (`d` stands
for "decimal"):

``` python
>>> camels = 42
>>> '%d' % camels
'42'
```

The result is the string `'42'`, which is not to be confused with the
integer value `42`.

A format sequence can appear anywhere in the format string, so you can
embed a value in a sentence:

``` python
>>> camels = 42
>>> 'I have spotted %d camels.' % camels
'I have spotted 42 camels.'
```

The format sequence `'%g'` formats the next element in the tuple as a
floating-point number (don't ask why), and `'%s'` formats the next item
as a string:

``` python
>>> 'In %d years I have spotted %g %s.' % (3, 0.1, 'camels')
'In 3 years I have spotted 0.1 camels.'
```

The number of elements in the tuple has to match the number of format
sequences in the string. Also, the types of the elements have to match
the format sequences:

``` python
>>> '%d %d %d' % (1, 2)
TypeError: not enough arguments for format string
>>> '%d' % 'dollars'
TypeError: illegal argument type for built-in operation
```

In the first example, there aren't enough elements; in the second, the
element is the wrong type.

The format operator is powerful but difficult to use. You can read more
about it at `docs.python.org/lib/typesseq-strings.html`.

## Filenames and paths

Files are organized into **directories** (also called "folders"). Every
running program has a "current directory," which is the default
directory for most operations. For example, when you open a file for
reading, Python looks for it in the current directory.

The `os` module provides functions for working with files and
directories ("os" stands for "operating system"). `os.getcwd` returns
the name of the current directory:

``` python
>>> import os
>>> cwd = os.getcwd()
>>> print cwd
/home/dinsdale
```

`cwd` stands for "current working directory." The result in this example
is `/home/dinsdale`, which is the home directory of a user named
`dinsdale`.

A string like `cwd` that identifies a file is called a **path**. A
**relative path** starts from the current directory; an **absolute
path** starts from the topmost directory in the file system.

The paths we have seen so far are simple filenames, so they are relative
to the current directory. To find the absolute path to a file, you can
use `os.path.abspath`:

``` python
>>> os.path.abspath('memo.txt')
'/home/dinsdale/memo.txt'
```

`os.path.exists` checks whether a file or directory exists:

``` python
>>> os.path.exists('memo.txt')
True
```

If it exists, `os.path.isdir` checks whether it's a directory:

``` python
>>> os.path.isdir('memo.txt')
False
>>> os.path.isdir('music')
True
```

Similarly, `os.path.isfile` checks whether it's a file.

`os.listdir` returns a list of the files (and other directories) in the
given directory:

``` python
>>> os.listdir(cwd)
['music', 'photos', 'memo.txt']
```

To demonstrate these functions, the following example "walks" through a
directory, prints the names of all the files, and calls itself
recursively on all the directories.

``` python
def walk(dir):
    for name in os.listdir(dir):
        path = os.path.join(dir, name)

        if os.path.isfile(path):
            print path
        else:
            walk(path)
```

`os.path.join` takes a directory and a file name and joins them into a
complete path.

### Exercise 1

Modify **\'`walk`**\' so that instead of printing the names of the
files, it returns a list of names. \'\'

```{=html}
</DIV>
```
```{=html}
<DIV CLASS="theorem">
```
**Exercise 2**  \'\' The **\'`os`**\' module provides a function called
**\'`walk`**\' that is similar to this one but more versatile. Read the
documentation and use it to print the names of the files in a given
directory and its subdirectories.

## Catching exceptions

A lot of things can go wrong when you try to read and write files. If
you try to open a file that doesn't exist, you get an `IOError`:

``` python
>>> fin = open('bad_file')
IOError: [Errno 2] No such file or directory: 'bad_file'
```

If you don't have permission to access a file:

``` python
>>> fout = open('/etc/passwd', 'w')
IOError: [Errno 13] Permission denied: '/etc/passwd'
```

And if you try to open a directory for reading, you get

``` python
>>> fin = open('/home')
IOError: [Errno 21] Is a directory
```

To avoid these errors, you could use functions like `os.path.exists` and
`os.path.isfile`, but it would take a lot of time and code to check all
the possibilities (if "`Errno 21`" is any indication, there are at least
21 things that can go wrong).

It is better to go ahead and try, and deal with problems if they happen,
which is exactly what the `try` statement does. The syntax is similar to
an `if` statement:

``` python
try:    
    fin = open('bad_file')
    for line in fin:
        print line
    fin.close()
except:
    print 'Something went wrong.'
```

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

Handling an exception with a `try` statement is called **catching** an
exception. In this example, the `except` clause prints an error message
that is not very helpful. In general, catching an exception gives you a
chance to fix the problem, or try again, or at least end the program
gracefully.

## Databases

A **database** is a file that is organized for storing data. Most
databases are organized like a dictionary in the sense that they map
from keys to values. The biggest difference is that the database is on
disk (or other permanent storage), so it persists after the program
ends.

The module `anydbm` provides an interface for creating and updating
database files. As an example, I'll create a database that contains
captions for image files.

Opening a database is similar to opening other files:

``` python
>>> import anydbm
>>> db = anydbm.open('captions.db', 'c')
```

The mode `'c'` means that the database should be created if it doesn't
already exist. The result is a database object that can be used (for
most operations) like a dictionary. If you create a new item, `anydbm`
updates the database file.

``` python
>>> db['cleese.png'] = 'Photo of John Cleese.'
```

When you access one of the items, `anydbm` reads the file:

``` python
>>> print db['cleese.png']
Photo of John Cleese.
```

If you make another assignment to an existing key, `anydbm` replaces the
old value:

``` python
>>> db['cleese.png'] = 'Photo of John Cleese doing a silly walk.'
>>> print db['cleese.png']
Photo of John Cleese doing a silly walk.
```

Many dictionary methods, like `keys` and `items`, also work with
database objects. So does iteration with a `for` statement.

``` python
for key in db:
     print key
```

As with other files, you should close the database when you are done:

``` python
>>> db.close()
```

## Pickling

A limitation of `anydbm` is that the keys and values have to be strings.
If you try to use any other type, you get an error.

The `pickle` module can help. It translates almost any type of object
into a string suitable for storage in a database, and then translates
strings back into objects.

`pickle.dumps` takes an object as a parameter and returns a string
representation (`dumps` is short for "dump string"):

``` python
>>> import pickle
>>> t = [1, 2, 3]
>>> pickle.dumps(t)
'(lp0\nI1\naI2\naI3\na.'
```

The format isn't obvious to human readers; it is meant to be easy for
`pickle` to interpret. `pickle.loads` ("load string") reconstitutes the
object:

``` python
>>> t1 = [1, 2, 3]
>>> s = pickle.dumps(t1)
>>> t2 = pickle.loads(s)
>>> print t2
[1, 2, 3]
```

Although the new object has the same value as the old, it is not (in
general) the same object:

``` python
>>> t == t2
True
>>> t is t2
False
```

In other words, pickling and then unpickling has the same effect as
copying the object.

You can use `pickle` to store non-strings in a database. In fact, this
combination is so common that it has been encapsulated in a module
called `shelve`.

```{=html}
<DIV CLASS="theorem">
```
**Exercise 3**  

*If you did Exercise **\'12.4**\', modify your solution so that it
creates a database that maps from each word in the list to a list of
words that use the same set of letters.*

*Write a different program that opens the database and prints the
contents in a human-readable format.*

```{=html}
</DIV>
```
## Pipes

Most operating systems provide a command-line interface, also known as a
**shell**. Shells usually provide commands to navigate the file system
and launch applications. For example, in Unix, you can change
directories with `cd`, display the contents of a directory with `ls`,
and launch a web browser by typing (for example) `Firefox`.

Any program that you can launch from the shell can also be launched from
Python using a **pipe**. A pipe is an object that represents a running
process.

For example, the Unix command `ls -l` normally displays the contents of
the current directory (in long format). You can launch `ls` with
`os.popen`:

``` python
>>> cmd = 'ls -l'
>>> fp = os.popen(cmd)
```

The argument is a string that contains a shell command. The return value
is a file pointer that behaves just like an open file. You can read the
output from the `ls` process one line at a time with `readline` or get
the whole thing at once with `read`:

``` python
>>> res = fp.read()
```

When you are done, you close the pipe like a file:

``` python
>>> stat = fp.close()
>>> print stat
None
```

The return value is the final status of the `ls` process; `None` means
that it ended normally (with no errors).

A common use of pipes is to read a compressed file incrementally; that
is, without uncompressing the whole thing at once. The following
function takes the name of a compressed file as a parameter and returns
a pipe that uses `gzip` to decompress the contents:

``` python
def open_gzip(filename):
    cmd = 'gunzip -c ' + filename
    fp = os.popen(cmd)
    return fp
```

If you read lines from `fp` one at a time, you never have to store the
uncompressed file in memory or on disk.

## Writing modules

Any file that contains Python code can be imported as a module. For
example, suppose you have a file named `wc.py` with the following code:

``` python
def linecount(filename):
    count = 0
    for line in open(filename):
        count += 1
    return count

print linecount('wc.py')
```

If you run this program, it reads itself and prints the number of lines
in the file, which is 7. You can also import it like this:

``` python
>>> import wc
7
```

Now you have a module object `wc`:

``` python
>>> print wc
&lt;module 'wc' from 'wc.py'>
```

That provides a function called `linecount`:

``` python
>>> wc.linecount('wc.py')
7
```

So that's how you write modules in Python.

The only problem with this example is that when you import the module it
executes the test code at the bottom. Normally when you import a module,
it defines new functions but it doesn't execute them.

Programs that will be imported as modules often use the following idiom:

``` python
if __name__ == '__main__':
    print linecount('wc.py')
```

`__name__` is a built-in variable that is set when the program starts.
If the program is running as a script, `__name__` has the value
`__main__`; in that case, the test code is executed. Otherwise, if the
module is being imported, the test code is skipped.

```{=html}
<DIV CLASS="theorem">
```
**Exercise 4**  *Type this example into a file named **\'`wc.py`**\' and
run it as a script. Then run the Python interpreter and
**\'`import wc`**\'. What is the value of`__name__`when the module is
being imported?* *Warning: If you import a module that has already been
imported, Python does nothing. It does not re-read the file, even if it
has changed.*

*If you want to reload a module, you can use the built-in function
**\'`reload`**\', but it can be tricky, so the safest thing to do is
restart the interpreter and then import the module again.*

```{=html}
</DIV>
```
## Debugging

When you are reading and writing files, you might run into problems with
whitespace. These errors can be hard to debug because spaces, tabs and
newlines are normally invisible:

``` python
>>> s = '1 2\t 3\n 4'
>>> print s
1 2  3
 4
```

The built-in function `repr` can help. It takes any object as an
argument and returns a string representation of the object. For strings,
it represents whitespace characters with backslash sequences:

``` python
>>> print repr(s)
'1 2\t 3\n 4'
```

This can be helpful for debugging.

One other problem you might run into is that different systems use
different characters to indicate the end of a line. Some systems use a
newline, represented `\n`. Others use a return character, represented
`\r`. Some use both. If you move files between different systems, these
inconsistencies might cause problems.

For most systems, there are applications to convert from one format to
another. You can find them (and read more about this issue) at
`wikipedia.org/wiki/Newline`. Or, of course, you could write one
yourself.

## Glossary

```{=html}
<DL CLASS="description">
```
```{=html}
<DT CLASS="dt-description">
```
**persistent:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
Pertaining to a program that runs indefinitely and keeps at least some
of its data in permanent storage.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**format operator:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
An operator, `%`, that takes a format string and a tuple and generates a
string that includes the elements of the tuple formatted as specified by
the format string.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**format string:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A string, used with the format operator, that contains format sequences.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**format sequence:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A sequence of characters in a format string, like `%d`, that specifies
how a value should be formatted.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**text file:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A sequence of characters stored in permanent storage like a hard drive.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**directory:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A named collection of files, also called a folder.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**path:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A string that identifies a file.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**relative path:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A path that starts from the current directory.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**absolute path:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A path that starts from the topmost directory in the file system.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**catch:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
To prevent an exception from terminating a program using the `try` and
`except` statements.

```{=html}
</DD>
```
```{=html}
<DT CLASS="dt-description">
```
**database:**

```{=html}
</DT>
```
```{=html}
<DD CLASS="dd-description">
```
A file whose contents are organized like a dictionary with keys that
correspond to values.

```{=html}
</DD>
```
```{=html}
</DL>
```
## Exercises

```{=html}
<DIV CLASS="theorem">
```
**Exercise 5**  The **\'`urllib`**\' module provides methods for
manipulating URLs and downloading information from the web. The
following example downloads and prints a secret message from
**\'`thinkpython.com`**\':\'\'

``` python
import urllib

conn = urllib.urlopen('http://thinkpython.com/secret.html')
for line in conn.fp:
    print line.strip()
```

*Run this code and follow the instructions you see there.*

```{=html}
</DIV>
```
```{=html}
<DIV CLASS="theorem">
```
**Exercise 6**  

*In a large collection of MP3 files, there may be more than one copy of
the same song, stored in different directories or with different file
names. The goal of this exercise is to search for these duplicates.*

-   \'\'Write a program that searches a directory and all of its

subdirectories, recursively, and returns a list of complete paths for
all files with a given suffix (like **\'`.mp3`**\'). Hint:
**\'`os.path`**\' provides several useful functions for manipulating
file and path names.\'\'

-   \'\'To recognize duplicates, you can use a hash function that

reads the file and generates a short summary of the contents. For
example, MD5 (Message-Digest algorithm 5) takes an arbitrarily-long
"message" and returns a 128-bit "checksum." The probability is very
small that two files with different contents will return the same
checksum.You can read about MD5 at **\'`wikipedia.org/wiki/Md5`**\'. On
a Unix system you can use the program **\'`md5sum`**\' and a pipe to
compute checksums from Python.\'\'

```{=html}
</DIV>
```
```{=html}
<DIV CLASS="theorem">
```
**Exercise 7**  

*The Internet Movie Database (IMDb) is an online collection of
information about movies. Their database is available in plain text
format, so it is reasonably easy to read from Python. For this exercise,
the files you need are **\'`actors.list.gz`**\' and
**\'`actresses.list.gz`**\'; you can download them from
**\'`www.imdb.com/interfaces#plain`**\'.*

*I have written a program that parses these files and splits them into
actor names, movie titles, etc. You can download it from
**\'`thinkpython.com/code/imdb.py`**\'.*

*If you run **\'`imdb.py`**\' as a script, it reads
**\'`actors.list.gz`**\' and prints one actor-movie pair per line. Or,
if you **\'`import imdb`**\' you can use the function`process_file`to,
well, process the file. The arguments are a filename, a function object
and an optional number of lines to process. Here is an example:*

``` python
''import imdb

def print_info(actor, date, title, role):
    print actor, date, title, role

imdb.process_file('actors.list.gz', print_info)
''
```

*When you call`process_file`, it opens **\'`filename`**\', reads the
contents, and calls`print_info`once for each line in the
file.`print_info`takes an actor, date, movie title and role as arguments
and prints them.*

-   \'\'Write a program that reads **\'`actors.list.gz`**\' and
    **\'`actresses.list.gz`**\' and uses **\'`shelve`**\' to build a
    database

that maps from each actor to a list of his or her films. \'\'

-   \'\'Two actors are "costars" if they have been in at least one

movie together. Process the database you built in the previous step and
build a second database that maps from each actor to a list of his or
her costars. \'\'

-   \'\'Write a program that can play the "Six Degrees of Kevin

Bacon," which you can read about at
**\'`wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon`**\'. This problem is
challenging because it requires you to find the shortest path in a
graph. You can read about shortest path algorithms at
**\'`wikipedia.org/wiki/Shortest_path_problem`**\'.\'\'

```{=html}
</DIV>
```
