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Difficulty level: ♦♦♦♢♢

# Files

> ❝ A nine mile walk is no joke, especially in the rain. ❞
> — Harry Kemelman, The Nine Mile Walk

## Diving In

My Windows laptop had 38,493 files before I installed a single application. Installing Python 3 added almost 3,000 files to that total. Files are the primary storage paradigm of every major operating system; the concept is so ingrained that most people would have trouble imagining an alternative. Your computer is, metaphorically speaking, drowning in files.

## Reading From Text Files

Before you can read from a file, you need to open it. Opening a file in Python couldn’t be easier:

    a_file = open('examples/chinese.txt', encoding='utf-8')

Python has a built-in `open()` function, which takes a filename as an argument. Here the filename is `'examples/chinese.txt'`. There are five interesting things about this filename:

1. It’s not just the name of a file; it’s a combination of a directory path and a filename. A hypothetical file-opening function could have taken two arguments — a directory path and a filename — but the `open()` function only takes one. In Python, whenever you need a “filename,” you can include some or all of a directory path as well.
2. The directory path uses a forward slash, but I didn’t say what operating system I was using. Windows uses backward slashes to denote subdirectories, while Mac OS X and Linux use forward slashes. But in Python, forward slashes always Just Work, even on Windows.
3. The directory path does not begin with a slash or a drive letter, so it is called a relative path. Relative to what, you might ask? Patience, grasshopper.
4. It’s a string. All modern operating systems (even Windows!) use Unicode to store the names of files and directories. Python 3 fully supports non-ASCII pathnames.
5. It doesn’t need to be on your local disk. You might have a network drive mounted. That “file” might be a figment of an entirely virtual filesystem. If your computer considers it a file and can access it as a file, Python can open it.

But that call to the `open()` function didn’t stop at the filename. There’s another argument, called `encoding`. Oh dear, that sounds dreadfully familiar.

### Character Encoding Rears Its Ugly Head

Bytes are bytes; characters are an abstraction. A string is a sequence of Unicode characters. But a file on disk is not a sequence of Unicode characters; a file on disk is a sequence of bytes. So if you read a “text file” from disk, how does Python convert that sequence of bytes into a sequence of characters? It decodes the bytes according to a specific character encoding algorithm and returns a sequence of Unicode characters (otherwise known as a string).

    # This example was created on Windows. Other platforms may
    # behave differently, for reasons outlined below.
    >>> file = open('examples/chinese.txt')
    >>> a_string = file.read()
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
      File "C:\Python31\lib\encodings\cp1252.py", line 23, in decode
        return codecs.charmap_decode(input,self.errors,decoding_table)[0]
    UnicodeDecodeError: 'charmap' codec can't decode byte 0x8f in position 28: character maps to <undefined>
    >>>

The default encoding is platform-dependent.

What just happened? You didn’t specify a character encoding, so Python is forced to use the default encoding. What’s the default encoding? If you look closely at the traceback, you can see that it’s dying in `cp1252.py`, meaning that Python is using CP-1252 as the default encoding here. (CP-1252 is a common encoding on computers running Microsoft Windows.) The CP-1252 character set doesn’t support the characters that are in this file, so the read fails with an ugly `UnicodeDecodeError`.

But wait, it’s worse than that! The default encoding is platform-dependent, so this code might work on your computer (if your default encoding is UTF-8), but then it will fail when you distribute it to someone else (whose default encoding is different, like CP-1252).

> ☞If you need to get the default character encoding, import the `locale` module and call `locale.getpreferredencoding()`. On my Windows laptop, it returns `'cp1252'`, but on my Linux box upstairs, it returns `'UTF8'`. I can’t even maintain consistency in my own house! Your results may be different (even on Windows) depending on which version of your operating system you have installed and how your regional/language settings are configured. This is why it’s so important to specify the encoding every time you open a file.

### Stream Objects

So far, all we know is that Python has a built-in function called `open()`. The `open()` function returns a stream object, which has methods and attributes for getting information about and manipulating a stream of characters.

    >>> a_file = open('examples/chinese.txt', encoding='utf-8')
    >>> a_file.name                                              ①
    'examples/chinese.txt'
    >>> a_file.encoding                                          ②
    'utf-8'
    >>> a_file.mode                                              ③
    'r'

1. The `name` attribute reflects the name you passed in to the `open()` function when you opened the file. It is not normalized to an absolute pathname.
2. Likewise, `encoding` attribute reflects the encoding you passed in to the `open()` function. If you didn’t specify the encoding when you opened the file (bad developer!) then the `encoding` attribute will reflect `locale.getpreferredencoding()`.
3. The `mode` attribute tells you in which mode the file was opened. You can pass an optional mode parameter to the `open()` function. You didn’t specify a mode when you opened this file, so Python defaults to `'r'`, which means “open for reading only, in text mode.” As you’ll see later in this chapter, the file mode serves several purposes; different modes let you write to a file, append to a file, or open a file in binary mode (in which you deal with bytes instead of strings).

> ☞The documentation for the `open()` function lists all the possible file modes.

### Reading Data From A Text File

After you open a file for reading, you’ll probably want to read from it at some point.

    >>> a_file = open('examples/chinese.txt', encoding='utf-8')
    >>> a_file.read()                                            ①
    'Dive Into Python 是为有经验的程序员编写的一本 Python 书。\n'
    >>> a_file.read()                                            ②
    ''

1. Once you open a file (with the correct encoding), reading from it is just a matter of calling the stream object’s `read()` method. The result is a string.
2. Perhaps somewhat surprisingly, reading the file again does not raise an exception. Python does not consider reading past end-of-file to be an error; it simply returns an empty string.

Always specify an `encoding` parameter when you open a file.

What if you want to re-read a file?

    # continued from the previous example
    >>> a_file.read()                      ①
    ''
    >>> a_file.seek(0)                     ②
    0
    >>> a_file.read(16)                    ③
    'Dive Into Python'
    >>> a_file.read(1)                     ④
    ' '
    >>> a_file.read(1)
    '是'
    >>> a_file.tell()                      ⑤
    20

1. Since you’re still at the end of the file, further calls to the stream object’s `read()` method simply return an empty string.
2. The `seek()` method moves to a specific byte position in a file.
3. The `read()` method can take an optional parameter, the number of characters to read.
4. If you like, you can even read one character at a time.
5. 16 + 1 + 1 = … 20?

Let’s try that again.

    # continued from the previous example
    >>> a_file.seek(17)                    ①
    17
    >>> a_file.read(1)                     ②
    '是'
    >>> a_file.tell()                      ③
    20

1. Move to the 17th byte.
2. Read one character.
3. Now you’re on the 20th byte.

Do you see it yet? The `seek()` and `tell()` methods always count bytes, but since you opened this file as text, the `read()` method counts characters. Chinese characters require multiple bytes to encode in UTF-8. The English characters in the file only require one byte each, so you might be misled into thinking that the `seek()` and `read()` methods are counting the same thing. But that’s only true for some characters.

But wait, it gets worse!

    >>> a_file.seek(18)                         ①
    18
    >>> a_file.read(1)                          ②
    Traceback (most recent call last):
      File "<pyshell#12>", line 1, in <module>
        a_file.read(1)
      File "C:\Python31\lib\codecs.py", line 300, in decode
        (result, consumed) = self._buffer_decode(data, self.errors, final)
    UnicodeDecodeError: 'utf8' codec can't decode byte 0x98 in position 0: unexpected code byte

1. Move to the 18th byte and try to read one character.
2. Why does this fail? Because there isn’t a character at the 18th byte. The nearest character starts at the 17th byte (and goes for three bytes). Trying to read a character from the middle will fail with a `UnicodeDecodeError`.

### Closing Files

Open files consume system resources, and depending on the file mode, other programs may not be able to access them. It’s important to close files as soon as you’re finished with them.

    # continued from the previous example
    >>> a_file.close()

Well that was anticlimactic.

The stream object a_file still exists; calling its `close()` method doesn’t destroy the object itself. But it’s not terribly useful.

    # continued from the previous example
    >>> a_file.read()                           ①
    Traceback (most recent call last):
      File "<pyshell#24>", line 1, in <module>
        a_file.read()
    ValueError: I/O operation on closed file.
    >>> a_file.seek(0)                          ②
    Traceback (most recent call last):
      File "<pyshell#25>", line 1, in <module>
        a_file.seek(0)
    ValueError: I/O operation on closed file.
    >>> a_file.tell()                           ③
    Traceback (most recent call last):
      File "<pyshell#26>", line 1, in <module>
        a_file.tell()
    ValueError: I/O operation on closed file.
    >>> a_file.close()                          ④
    >>> a_file.closed                           ⑤
    True

1. You can’t read from a closed file; that raises an `IOError` exception.
2. You can’t seek in a closed file either.
3. There’s no current position in a closed file, so the `tell()` method also fails.
4. Perhaps surprisingly, calling the `close()` method on a stream object whose file has been closed does not raise an exception. It’s just a no-op.
5. Closed stream objects do have one useful attribute: the `closed` attribute will confirm that the file is closed.

### Closing Files Automatically

`try..finally` is good. `with` is better.

Stream objects have an explicit `close()` method, but what happens if your code has a bug and crashes before you call `close()`? That file could theoretically stay open for much longer than necessary. While you’re debugging on your local computer, that’s not a big deal. On a production server, maybe it is.

Python 2 had a solution for this: the `try..finally` block. That still works in Python 3, and you may see it in other people’s code or in older code that was ported to Python 3. But Python 2.5 introduced a cleaner solution, which is now the preferred solution in Python 3: the `with` statement.

    with open('examples/chinese.txt', encoding='utf-8') as a_file:
        a_file.seek(17)
        a_character = a_file.read(1)
        print(a_character)

This code calls `open()`, but it never calls `a_file.close()`. The `with` statement starts a code block, like an `if` statement or a `for` loop. Inside this code block, you can use the variable a_file as the stream object returned from the call to `open()`. All the regular stream object methods are available — `seek()`, `read()`, whatever you need. When the `with` block ends, Python calls `a_file.close()` automatically.

Here’s the kicker: no matter how or when you exit the `with` block, Python will close that file… even if you “exit” it via an unhandled exception. That’s right, even if your code raises an exception and your entire program comes to a screeching halt, that file will get closed. Guaranteed.

> ☞In technical terms, the `with` statement creates a runtime context. In these examples, the stream object acts as a context manager. Python creates the stream object a_file and tells it that it is entering a runtime context. When the `with` code block is completed, Python tells the stream object that it is exiting the runtime context, and the stream object calls its own `close()` method. See Appendix B, “Classes That Can Be Used in a `with` Block” for details.

There’s nothing file-specific about the `with` statement; it’s just a generic framework for creating runtime contexts and telling objects that they’re entering and exiting a runtime context. If the object in question is a stream object, then it does useful file-like things (like closing the file automatically). But that behavior is defined in the stream object, not in the `with` statement. There are lots of other ways to use context managers that have nothing to do with files. You can even create your own, as you’ll see later in this chapter.

### Reading Data One Line At A Time

A “line” of a text file is just what you think it is — you type a few words and press `ENTER`, and now you’re on a new line. A line of text is a sequence of characters delimited by… what exactly? Well, it’s complicated, because text files can use several different characters to mark the end of a line. Every operating system has its own convention. Some use a carriage return character, others use a line feed character, and some use both characters at the end of every line.

Now breathe a sigh of relief, because Python handles line endings automatically by default. If you say, “I want to read this text file one line at a time,” Python will figure out which kind of line ending the text file uses and and it will all Just Work.

> ☞If you need fine-grained control over what’s considered a line ending, you can pass the optional `newline` parameter to the `open()` function. See the `open()` function documentation for all the gory details.

So, how do you actually do it? Read a file one line at a time, that is. It’s so simple, it’s beautiful.

[download `oneline.py`]

    line_number = 0
    with open('examples/favorite-people.txt', encoding='utf-8') as a_file:  ①
        for a_line in a_file:                                               ②
            line_number += 1
            print('{:>4} {}'.format(line_number, a_line.rstrip()))          ③

1. Using the `with` pattern, you safely open the file and let Python close it for you.
2. To read a file one line at a time, use a `for` loop. That’s it. Besides having explicit methods like `read()`, the stream object is also an iterator which spits out a single line every time you ask for a value.
3. Using the `format()` string method, you can print out the line number and the line itself. The format specifier `{:>4}` means “print this argument right-justified within 4 spaces.” The a_line variable contains the complete line, carriage returns and all. The `rstrip()` string method removes the trailing whitespace, including the carriage return characters.

    you@localhost:~/diveintopython3$ python3 examples/oneline.py
       1 Dora
       2 Ethan
       3 Wesley
       4 John
       5 Anne
       6 Mike
       7 Chris
       8 Sarah
       9 Alex
      10 Lizzie

> Did you get this error?

>     you@localhost:~/diveintopython3$ python3 examples/oneline.py
>     Traceback (most recent call last):
>       File "examples/oneline.py", line 4, in <module>
>         print('{:>4} {}'.format(line_number, a_line.rstrip()))
>     ValueError: zero length field name in format

> If so, you’re probably using Python 3.0. You should really upgrade to Python 3.1.

> Python 3.0 supported string formatting, but only with explicitly numbered format specifiers. Python 3.1 allows you to omit the argument indexes in your format specifiers. Here is the Python 3.0-compatible version for comparison:

>     print('{0:>4} {1}'.format(line_number, a_line.rstrip()))

⁂

## Writing to Text Files

Just open a file and start writing.

You can write to files in much the same way that you read from them. First you open a file and get a stream object, then you use methods on the stream object to write data to the file, then you close the file.

To open a file for writing, use the `open()` function and specify the write mode. There are two file modes for writing:

- “Write” mode will overwrite the file. Pass `mode='w'` to the `open()` function.
- “Append” mode will add data to the end of the file. Pass `mode='a'` to the `open()` function.

Either mode will create the file automatically if it doesn’t already exist, so there’s never a need for any sort of fiddly “if the file doesn’t exist yet, create a new empty file just so you can open it for the first time” function. Just open a file and start writing.

You should always close a file as soon as you’re done writing to it, to release the file handle and ensure that the data is actually written to disk. As with reading data from a file, you can call the stream object’s `close()` method, or you can use the `with` statement and let Python close the file for you. I bet you can guess which technique I recommend.

    >>> with open('test.log', mode='w', encoding='utf-8') as a_file:  ①
    ...     a_file.write('test succeeded')                            ②
    >>> with open('test.log', encoding='utf-8') as a_file:
    ...     print(a_file.read())
    test succeeded
    >>> with open('test.log', mode='a', encoding='utf-8') as a_file:  ③
    ...     a_file.write('and again')
    >>> with open('test.log', encoding='utf-8') as a_file:
    ...     print(a_file.read())
    test succeededand again                                           ④

1. You start boldly by creating the new file `test.log` (or overwriting the existing file), and opening the file for writing. The `mode='w'` parameter means open the file for writing. Yes, that’s all as dangerous as it sounds. I hope you didn’t care about the previous contents of that file (if any), because that data is gone now.
2. You can add data to the newly opened file with the `write()` method of the stream object returned by the `open()` function. After the `with` block ends, Python automatically closes the file.
3. That was so fun, let’s do it again. But this time, with `mode='a'` to append to the file instead of overwriting it. Appending will never harm the existing contents of the file.
4. Both the original line you wrote and the second line you appended are now in the file `test.log`. Also note that carriage returns are not included. Since you didn’t write them explicitly to the file either time, the file doesn’t include them. You can write a carriage return with the `'\n'` character. Since you didn’t do this, everything you wrote to the file ended up on one line.

### Character Encoding Again

Did you notice the `encoding` parameter that got passed in to the `open()` function while you were opening a file for writing? It’s important; don’t ever leave it out! As you saw in the beginning of this chapter, files don’t contain strings, they contain bytes. Reading a “string” from a text file only works because you told Python what encoding to use to read a stream of bytes and convert it to a string. Writing text to a file presents the same problem in reverse. You can’t write characters to a file; characters are an abstraction. In order to write to the file, Python needs to know how to convert your string into a sequence of bytes. The only way to be sure it’s performing the correct conversion is to specify the `encoding` parameter when you open the file for writing.

⁂

## Binary Files

Not all files contain text. Some of them contain pictures of my dog.

    >>> an_image = open('examples/beauregard.jpg', mode='rb')                ①
    >>> an_image.mode                                                        ②
    'rb'
    >>> an_image.name                                                        ③
    'examples/beauregard.jpg'
    >>> an_image.encoding                                                    ④
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    AttributeError: '_io.BufferedReader' object has no attribute 'encoding'

1. Opening a file in binary mode is simple but subtle. The only difference from opening it in text mode is that the `mode` parameter contains a `'b'` character.
2. The stream object you get from opening a file in binary mode has many of the same attributes, including `mode`, which reflects the `mode` parameter you passed into the `open()` function.
3. Binary stream objects also have a `name` attribute, just like text stream objects.
4. Here’s one difference, though: a binary stream object has no `encoding` attribute. That makes sense, right? You’re reading (or writing) bytes, not strings, so there’s no conversion for Python to do. What you get out of a binary file is exactly what you put into it, no conversion necessary.

Did I mention you’re reading bytes? Oh yes you are.

    # continued from the previous example
    >>> an_image.tell()
    0
    >>> data = an_image.read(3)  ①
    >>> data
    b'\xff\xd8\xff'
    >>> type(data)               ②
    <class 'bytes'>
    >>> an_image.tell()          ③
    3
    >>> an_image.seek(0)
    0
    >>> data = an_image.read()
    >>> len(data)
    3150

1. Like text files, you can read binary files a little bit at a time. But there’s a crucial difference…
2. …you’re reading bytes, not strings. Since you opened the file in binary mode, the `read()` method takes the number of bytes to read, not the number of characters.
3. That means that there’s never an unexpected mismatch between the number you passed into the `read()` method and the position index you get out of the `tell()` method. The `read()` method reads bytes, and the `seek()` and `tell()` methods track the number of bytes read. For binary files, they’ll always agree.

⁂

## Stream Objects From Non-File Sources

To read from a fake file, just call `read()`.

Imagine you’re writing a library, and one of your library functions is going to read some data from a file. The function could simply take a filename as a string, go open the file for reading, read it, and close it before exiting. But you shouldn’t do that. Instead, your API should take an arbitrary stream object.

In the simplest case, a stream object is anything with a `read()` method which takes an optional size parameter and returns a string. When called with no size parameter, the `read()` method should read everything there is to read from the input source and return all the data as a single value. When called with a size parameter, it reads that much from the input source and returns that much data. When called again, it picks up where it left off and returns the next chunk of data.

That sounds exactly like the stream object you get from opening a real file. The difference is that you’re not limiting yourself to real files. The input source that’s being “read” could be anything: a web page, a string in memory, even the output of another program. As long as your functions take a stream object and simply call the object’s `read()` method, you can handle any input source that acts like a file, without specific code to handle each kind of input.

    >>> a_string = 'PapayaWhip is the new black.'
    >>> import io                                  ①
    >>> a_file = io.StringIO(a_string)             ②
    >>> a_file.read()                              ③
    'PapayaWhip is the new black.'
    >>> a_file.read()                              ④
    ''
    >>> a_file.seek(0)                             ⑤
    0
    >>> a_file.read(10)                            ⑥
    'PapayaWhip'
    >>> a_file.tell()
    10
    >>> a_file.seek(18)
    18
    >>> a_file.read()
    'new black.'

1. The `io` module defines the `StringIO` class that you can use to treat a string in memory as a file.
2. To create a stream object out of a string, create an instance of the `io.StringIO()` class and pass it the string you want to use as your “file” data. Now you have a stream object, and you can do all sorts of stream-like things with it.
3. Calling the `read()` method “reads” the entire “file,” which in the case of a `StringIO` object simply returns the original string.
4. Just like a real file, calling the `read()` method again returns an empty string.
5. You can explicitly seek to the beginning of the string, just like seeking through a real file, by using the `seek()` method of the `StringIO` object.
6. You can also read the string in chunks, by passing a size parameter to the `read()` method.

> ☞`io.StringIO` lets you treat a string as a text file. There’s also a `io.BytesIO` class, which lets you treat a byte array as a binary file.

### Handling Compressed Files

The Python standard library contains modules that support reading and writing compressed files. There are a number of different compression schemes; the two most popular on non-Windows systems are gzip and bzip2. (You may have also encountered PKZIP archives and GNU Tar archives. Python has modules for those, too.)

The `gzip` module lets you create a stream object for reading or writing a gzip-compressed file. The stream object it gives you supports the `read()` method (if you opened it for reading) or the `write()` method (if you opened it for writing). That means you can use the methods you’ve already learned for regular files to directly read or write a gzip-compressed file, without creating a temporary file to store the decompressed data.

As an added bonus, it supports the `with` statement too, so you can let Python automatically close your gzip-compressed file when you’re done with it.

    you@localhost:~$ python3

    >>> import gzip
    >>> with gzip.open('out.log.gz', mode='wb') as z_file:                                      ①
    ...   z_file.write('A nine mile walk is no joke, especially in the rain.'.encode('utf-8'))
    ...
    >>> exit()

    you@localhost:~$ ls -l out.log.gz                                                           ②
    -rw-r--r--  1 mark mark    79 2009-07-19 14:29 out.log.gz
    you@localhost:~$ gunzip out.log.gz                                                          ③
    you@localhost:~$ cat out.log                                                                ④
    A nine mile walk is no joke, especially in the rain.

1. You should always open gzipped files in binary mode. (Note the `'b'` character in the `mode` argument.)
2. I constructed this example on Linux. If you’re not familiar with the command line, this command is showing the “long listing” of the gzip-compressed file you just created in the Python Shell. This listing shows that the file exists (good), and that it is 79 bytes long. That’s actually larger than the string you started with! The gzip file format includes a fixed-length header that contains some metadata about the file, so it’s inefficient for extremely small files.
3. The `gunzip` command (pronounced “gee-unzip”) decompresses the file and stores the contents in a new file named the same as the compressed file but without the `.gz` file extension.
4. The `cat` command displays the contents of a file. This file contains the string you originally wrote directly to the compressed file `out.log.gz` from within the Python Shell.

> Did you get this error?

>     >>> with gzip.open('out.log.gz', mode='wb') as z_file:
>     ...         z_file.write('A nine mile walk is no joke, especially in the rain.'.encode('utf-8'))
>     ...
>     Traceback (most recent call last):
>      File "<stdin>", line 1, in <module>
>     AttributeError: 'GzipFile' object has no attribute '__exit__'

> If so, you’re probably using Python 3.0. You should really upgrade to Python 3.1.

> Python 3.0 had a `gzip` module, but it did not support using a gzipped-file object as a context manager. Python 3.1 added the ability to use gzipped-file objects in a `with` statement.

⁂

## Standard Input, Output, and Error

`sys.stdin`, `sys.stdout`, `sys.stderr`.

Command-line gurus are already familiar with the concept of standard input, standard output, and standard error. This section is for the rest of you.

Standard output and standard error (commonly abbreviated `stdout` and `stderr`) are pipes that are built into every UNIX-like system, including Mac OS X and Linux. When you call the `print()` function, the thing you’re printing is sent to the `stdout` pipe. When your program crashes and prints out a traceback, it goes to the `stderr` pipe. By default, both of these pipes are just connected to the terminal window where you are working; when your program prints something, you see the output in your terminal window, and when a program crashes, you see the traceback in your terminal window too. In the graphical Python Shell, the `stdout` and `stderr` pipes default to your “Interactive Window”.

    >>> for i in range(3):
    ...     print('PapayaWhip')        ①
    PapayaWhip
    PapayaWhip
    PapayaWhip
    >>> import sys
    >>> for i in range(3):
    ... sys.stdout.write('is the')     ②
    is theis theis the
    >>> for i in range(3):
    ... sys.stderr.write('new black')  ③
    new blacknew blacknew black

1. The `print()` function, in a loop. Nothing surprising here.
2. `stdout` is defined in the `sys` module, and it is a stream object. Calling its `write()` function will print out whatever string you give it. In fact, this is what the `print` function really does; it adds a carriage return to the end of the string you’re printing, and calls `sys.stdout.write`.
3. In the simplest case, `sys.stdout` and `sys.stderr` send their output to the same place: the Python IDE (if you’re in one), or the terminal (if you’re running Python from the command line). Like standard output, standard error does not add carriage returns for you. If you want carriage returns, you’ll need to write carriage return characters.

`sys.stdout` and `sys.stderr` are stream objects, but they are write-only. Attempting to call their `read()` method will always raise an `IOError`.

    >>> import sys
    >>> sys.stdout.read()
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    IOError: not readable

### Redirecting Standard Output

`sys.stdout` and `sys.stderr` are stream objects, albeit ones that only support writing. But they’re not constants; they’re variables. That means you can assign them a new value — any other stream object — to redirect their output.

[download `stdout.py`]

    import sys

    class RedirectStdoutTo:
        def __init__(self, out_new):
            self.out_new = out_new

        def __enter__(self):
            self.out_old = sys.stdout
            sys.stdout = self.out_new

        def __exit__(self, *args):
            sys.stdout = self.out_old

    print('A')
    with open('out.log', mode='w', encoding='utf-8') as a_file, RedirectStdoutTo(a_file):
        print('B')
    print('C')

Check this out:

    you@localhost:~/diveintopython3/examples$ python3 stdout.py
    A
    C
    you@localhost:~/diveintopython3/examples$ cat out.log
    B

> Did you get this error?

>     you@localhost:~/diveintopython3/examples$ python3 stdout.py
>       File "stdout.py", line 15
>         with open('out.log', mode='w', encoding='utf-8') as a_file, RedirectStdoutTo(a_file):
>                                                                   ^
>     SyntaxError: invalid syntax

> If so, you’re probably using Python 3.0. You should really upgrade to Python 3.1.

> Python 3.0 supported the `with` statement, but each statement can only use one context manager. Python 3.1 allows you to chain multiple context managers in a single `with` statement.

Let’s take the last part first.

    print('A')
    with open('out.log', mode='w', encoding='utf-8') as a_file, RedirectStdoutTo(a_file):
        print('B')
    print('C')

That’s a complicated `with` statement. Let me rewrite it as something more recognizable.

    with open('out.log', mode='w', encoding='utf-8') as a_file:
        with RedirectStdoutTo(a_file):
            print('B')

As the rewrite shows, you actually have two `with` statements, one nested within the scope of the other. The “outer” `with` statement should be familiar by now: it opens a UTF-8-encoded text file named `out.log` for writing and assigns the stream object to a variable named a_file. But that’s not the only thing odd here.

    with RedirectStdoutTo(a_file):

Where’s the `as` clause? The `with` statement doesn’t actually require one. Just like you can call a function and ignore its return value, you can have a `with` statement that doesn’t assign the `with` context to a variable. In this case, you’re only interested in the side effects of the `RedirectStdoutTo` context.

What are those side effects? Take a look inside the `RedirectStdoutTo` class. This class is a custom context manager. Any class can be a context manager by defining two special methods: `__enter__()` and `__exit__()`.

    class RedirectStdoutTo:
        def __init__(self, out_new):    ①
            self.out_new = out_new

        def __enter__(self):            ②
            self.out_old = sys.stdout
            sys.stdout = self.out_new

        def __exit__(self, *args):      ③
            sys.stdout = self.out_old

1. The `__init__()` method is called immediately after an instance is created. It takes one parameter, the stream object that you want to use as standard output for the life of the context. This method just saves the stream object in an instance variable so other methods can use it later.
2. The `__enter__()` method is a special class method; Python calls it when entering a context (i.e. at the beginning of the `with` statement). This method saves the current value of `sys.stdout` in self.out_old, then redirects standard output by assigning self.out_new to sys.stdout.
3. The `__exit__()` method is another special class method; Python calls it when exiting the context (i.e. at the end of the `with` statement). This method restores standard output to its original value by assigning the saved self.out_old value to sys.stdout.

Putting it all together:

    print('A')                                                                             ①
    with open('out.log', mode='w', encoding='utf-8') as a_file, RedirectStdoutTo(a_file):  ②
        print('B')                                                                         ③
    print('C')                                                                             ④

1. This will print to the IDE “Interactive Window” (or the terminal, if running the script from the command line).
2. This `with` statement takes a comma-separated list of contexts. The comma-separated list acts like a series of nested `with` blocks. The first context listed is the “outer” block; the last one listed is the “inner” block. The first context opens a file; the second context redirects `sys.stdout` to the stream object that was created in the first context.
3. Because this `print()` function is executed with the context created by the `with` statement, it will not print to the screen; it will write to the file `out.log`.
4. The `with` code block is over. Python has told each context manager to do whatever it is they do upon exiting a context. The context managers form a last-in-first-out stack. Upon exiting, the second context changed `sys.stdout` back to its original value, then the first context closed the file named `out.log`. Since standard output has been restored to its original value, calling the `print()` function will once again print to the screen.

Redirecting standard error works exactly the same way, using `sys.stderr` instead of `sys.stdout`.

⁂

## Further Reading

- Reading and writing files in the Python.org tutorial
- `io` module
- Stream objects
- Context manager types
- `sys.stdout` and `sys.stderr`
- FUSE on Wikipedia

☜ ☞

© 2001–9 Mark Pilgrim