What is the python "with" statement designed for?

Question

I came across the Python with statement for the first time today. I've been using Python lightly for several months and didn't even know of its existence! Given its somewhat obscure status, I thought it would be worth asking:

1. What is the Python with statement designed to be used for?
2. What do you use it for?
3. Are there any gotchas I need to be aware of, or common anti-patterns associated with its use? Any cases where it is better use try..finally than with?
4. Why isn't it used more widely?
5. Which standard library classes are compatible with it?

Answer 1

1. I believe this has already been answered by other users before me, so I only add it for the sake of completeness: the with statement simplifies exception handling by encapsulating common preparation and cleanup tasks in so-called context managers. More details can be found in PEP 343. For instance, the open statement is a context manager in itself, which lets you open a file, keep it open as long as the execution is in the context of the with statement where you used it, and close it as soon as you leave the context, no matter whether you have left it because of an exception or during regular control flow. The with statement can thus be used in ways similar to the RAII pattern in C++: some resource is acquired by the with statement and released when you leave the with context.

2. Some examples are: opening files using with open(filename) as fp:, acquiring locks using with lock: (where lock is an instance of threading.Lock). You can also construct your own context managers using the contextmanager decorator from contextlib. For instance, I often use this when I have to change the current directory temporarily and then return to where I was:

   from contextlib import contextmanager
   import os
   
   @contextmanager
   def working_directory(path):
       current_dir = os.getcwd()
       os.chdir(path)
       try:
           yield
       finally:
           os.chdir(current_dir)
   
   with working_directory("data/stuff"):
       # do something within data/stuff
   # here I am back again in the original working directory
   

   Here's another example that temporarily redirects sys.stdin, sys.stdout and sys.stderr to some other file handle and restores them later:

   from contextlib import contextmanager
   import sys
   
   @contextmanager
   def redirected(**kwds):
       stream_names = ["stdin", "stdout", "stderr"]
       old_streams = {}
       try:
           for sname in stream_names:
               stream = kwds.get(sname, None)
               if stream is not None and stream != getattr(sys, sname):
                   old_streams[sname] = getattr(sys, sname)
                   setattr(sys, sname, stream)
           yield
       finally:
           for sname, stream in old_streams.iteritems():
               setattr(sys, sname, stream)
   
   with redirected(stdout=open("/tmp/log.txt", "w")):
        # these print statements will go to /tmp/log.txt
        print "Test entry 1"
        print "Test entry 2"
   # back to the normal stdout
   print "Back to normal stdout again"
   

   And finally, another example that creates a temporary folder and cleans it up when leaving the context:

   from tempfile import mkdtemp
   from shutil import rmtree
   
   @contextmanager
   def temporary_dir(*args, **kwds):
       name = mkdtemp(*args, **kwds)
       try:
           yield name
       finally:
           shutil.rmtree(name)
   
   with temporary_dir() as dirname:
       # do whatever you want
   

Answer 2

I would suggest two interesting lectures:

• PEP 343 The "with" Statement
• Effbot Understanding Python's "with" statement

1. The with statement is used to wrap the execution of a block with methods defined by a context manager. This allows common try...except...finally usage patterns to be encapsulated for convenient reuse.

2. You could do something like:

with open("foo.txt") as foo_file:
    data = foo_file.read()

OR

from contextlib import nested
with nested(A(), B(), C()) as (X, Y, Z):
   do_something()

OR (Python 3.1)

with open('data') as input_file, open('result', 'w') as output_file:
   for line in input_file:
     output_file.write(parse(line))

OR

lock = threading.Lock()
with lock:
    # Critical section of code

3. I don't see any Antipattern here.
Quoting Dive into Python:

try..finally is good. with is better.

4. I guess it's related to programmers's habit to use try..catch..finally statement from other languages.

Answer 3

The Python with statement is built-in language support of the Resource Acquisition Is Initialization idiom commonly used in C++. It is intended to allow safe acquisition and release of operating system resources.

The with statement creates resources within a scope/block. You write your code using the resources within the block. When the block exits the resources are cleanly released regardless of the outcome of the code in the block (that is whether the block exits normally or because of an exception).

Many resources in the Python library that obey the protocol required by the with statement and so can used with it out-of-the-box. However anyone can make resources that can be used in a with statement by implementing the well documented protocol: PEP 0343

Use it whenever you acquire resources in your application that must be explicitly relinquished such as files, network connections, locks and the like.

Answer 4

Again for completeness I'll add my most useful use-case for with statements.

I do a lot of scientific computing and for some activities I need the Decimal library for arbitrary precision calculations. Some part of my code I need high precision and for most other parts I need less precision.

I set my default precision to a low number and then use with to get a more precise answer for some sections:

from decimal import localcontext

with localcontext() as ctx:
    ctx.prec = 42   # Perform a high precision calculation
    s = calculate_something()
s = +s  # Round the final result back to the default precision

I use this a lot with the Hypergeometric Test which requires the division of large numbers resulting form factorials. When you do genomic scale calculations you have to be careful of round-off and overflow errors.

Answer 5

An example of an antipattern might be to use the with inside a loop when it would be more efficient to have the with outside the loop

for example

for row in lines:
    with open("outfile","a") as f:
        f.write(row)

vs

with open("outfile","a") as f:
    for row in lines:
        f.write(row)

The first way is opening and closing the file for each row which may cause performance problems compared to the second way with opens and closes the file just once.

Answer 6

See PEP 343 - The 'with' statement, there is an example section at the end.

... new statement "with" to the Python language to make it possible to factor out standard uses of try/finally statements.

Answer 7

points 1, 2, and 3 being reasonably well covered:

4: it is relatively new, only available in python2.6+ (or python2.5 using from __future__ import with_statement)

Answer 8

The with statement works with so-called context managers:

http://docs.python.org/release/2.5.2/lib/typecontextmanager.html

The idea is to simplify exception handling by doing the necessary cleanup after leaving the 'with' block. Some of the python built-ins already work as context managers.

Answer 9

Another example for out-of-the-box support, and one that might be a bit baffling at first when you are used to the way built-in open() behaves, are connection objects of popular database modules such as:

• sqlite3
• psycopg2
• cx_oracle

The connection objects are context managers and as such can be used out-of-the-box in a with-statement, however when using the above note that:

When the with-block is finished, either with an exception or without, the connection is not closed. In case the with-block finishes with an exception, the transaction is rolled back, otherwise the transaction is commited.

This means that the programmer has to take care to close the connection themselves, but allows to acquire a connection, and use it in multiple with-statements, as shown in the psycopg2 docs:

conn = psycopg2.connect(DSN)

with conn:
    with conn.cursor() as curs:
        curs.execute(SQL1)

with conn:
    with conn.cursor() as curs:
        curs.execute(SQL2)

conn.close()

In the example above, you'll note that the cursor objects of psycopg2 also are context managers. From the relevant documentation on the behavior:

When a cursor exits the with-block it is closed, releasing any resource eventually associated with it. The state of the transaction is not affected.

Answer 10

In python generally “with” statement is used to open a file, process the data present in the file, and also to close the file without calling a close() method. “with” statement makes the exception handling simpler by providing cleanup activities.

General form of with:

with open(“file name”, “mode”) as file-var:
    processing statements

note: no need to close the file by calling close() upon file-var.close()

Answer 11

In similar vein to that use mentioned by @JudoWill, it can be used to provide a local variable that is automatically destroyed at the end of the block, without having to explicitly delete resources.

example:

function1(<complex and deep expression>)
function2(<same complex and deep expression>)

could be rewritten as:

expr = <complex and deep expression>
function1(expr)
function1(expr)
expr = None   # to delete all resources, or wait till end of function

or as:

with <complex and deep expression> as expr:
  function1(expr)
  function1(expr)

# expr is out of scope, hence any resources are deleted