This post continues a series
on “Pythonic” code.
Pythonic code is code
that fits well
with the design
of the Python language.
I wrote about
as a powerful way to manipulate Python’s list data structure.
This post will cover the
- The list comprehension
- The with statement
- The property decorator
- Built-in functions
- Using the standard library
- Leveraging packages
One task that you are likely to encounter
while programming Python
is the need to open a file.
That file might contain tables of data
or pictures of kittens.
Whatever you find yourself doing,
you’ll come across the
Let’s work through a thought experiment
which can help explain why you should use
If you’re brand new to Python, you might open a file like so:
f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture.
After speaking with a friend with more Python experience than you, you learn that you’re supposed to close files or else the operating system will eventually run into trouble (because it can only track a limited number of open files). You rewrite your code:
f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture. f.close()
Then you learn that errors can happen. Being a good developer, you attempt to handle any errors.
try: f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture. f.close() except: print('oops, something went wrong.')
Your friend tells you that you’ve added a bug.
How could that be?
She tells you
that an error can happen
before the file is closed.
You go read more Python documentation
and learn about
The code is reworked again to look like:
try: f = open('kitteh.jpg', 'rb') cat_pic = f.read() # Do other stuff with the cat picture. except: print('oops, something went wrong.') finally: f.close()
This code is not stellar. If you had to write 200 lines of extra code for “doing other stuff,” then there is a lot of distance between opening and closing the file. Viewed another way, there is a lot space between setting something up and tearing it down later.
This is a perfect place to use
Let’s restate the code with the
with open('kitteh.jpg', 'rb') as f: cat_pic = f.read() try: # Do other stuff with the cat picture. except: print('oops, something went wrong.')
you might be suspect
of this code.
Where did the
close call go?
with statement used an extra concept
Context managers are designed
to handle setup and tear down
for anything that needs it.
A context manager is some code
that implements an
open is used with a
a special context manager is called.
After the scope of the
with block passes
(i.e., reading the file content into
the interpreter will execute an
method on the context manager.
open context manager will close the file
All of this work is neatly tucked away
from the developer.
You have the guarantee
that the file gets closed
and do not have to do that work
on your own.
open context manager is probably the most common usage
Other uses of
with can include threading locks,
or even nicer interfaces for unit testing exceptions.
Python let’s you create your own context managers.
Check out contextlib
for more info.
I’ve included this example to give you a quick idea in action.
>>> from contextlib import contextmanager >>> @contextmanager ... def praise(): ... print('You can do it.') ... yield ... print('You made it.') ... >>> with praise(): ... print('I am trying to code.') ... You can do it. I am trying to code. You made it.
with statement is another valuable tool
for your Python programmer toolbelt.
The key thing to remember is that it can help you clean up any code
where you need to set things up
or tear things down.
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