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Revision 19 as of 2011-01-21 21:23:11
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Revision 20 as of 2011-01-21 22:55:49
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Editor: henninge
Comment: The Great Clean-out by bac, lifeless, and henninge
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You should use ''fields'' to describe arguments, return values, and exceptions raised, as documented in [[http://epydoc.sourceforge.net/fields.html|epydoc]]. Avoid using synonym fields such as "returns" and "raises". You should use field names as defined in the [[http://epydoc.sourceforge.net/fields.html|epydoc]] documentation but with reST syntax.
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Here are some examples:

def example1(a, b):
    """Perform some calculation.

    It is a **very** complicated calculation.
Here is comprehensive example. Parameter descriptions are a good idea but not mandatory. Describe in as much or as little detail as necessary.
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def example3():
    """Call `example2` with sensible arguments."""

''There is some controversy about whether interface methods should get a docstring or not. OT1H, we want everything that '''can''' have a docstring '''to''' have a docstring. OTOH, this messes up `pydoctor` which can extract the method's docstring from the interface if the implementation doesn't have a docstring. We have no resolution on this yet, so for now, include the docstrings on such methods.''
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# Copyright 2004-2007 Canonical Ltd. All rights reserved. # Copyright 2009-2011 Canonical Ltd. All rights reserved.
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with a list of public names in the module.  See [#multiline the section on
multiline braces] for more details.
with a list of public names in the module.
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often than in general Python code.

Importing a module should not have side effects. This means that any code other than a function/class/constant declaration should be guarded by an {{{if __name__ == '__main__':}}} line.
often than in general Python code. {{{__all__}}} should be formatted like imports.
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 * Database code cannot be imported directly  * View code cannot import code from {{{canonical.launchpad.database}}}.
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Imports should not be circular. Bad:

# foo.py
import bar

# bar.py
import foo

This causes weird bugs. Find a different way to structure your code.
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We now discourage importing names from packages, where the package's
`__init__.py` has sub-module `import-*` statements. We used to do this quite
a bit for `canonical.launchpad.interfaces` and many other packages. This
style is discouraged now because

 * `import-*`'s obscure the actual location of names, making finding the
   objects much more difficult
 * their use tends to encourage hugantically ginormous multiline import
   statements, increasing the likelihood of merge conflicts
 * you also have to maintain the `__init__.py` files
 * this style can lead to circular import problems

Instead, we now recommend that you do not add `import-*`'s in a package's
`__init__.py`, and instead, use the more fully qualified import statements in
your code. E.g. instead of

from canonical.launchpad.interfaces import (
    CannotChangeSubscription, CannotSubscribe, CannotUnsubscribe,
    EmailAddressStatus, IEmailAddressSet, IHeldMessageDetails,
    ILaunchpadCelebrities, IMailingList, IMailingListSet,
    IMailingListSubscription, IMessageApproval, IMessageApprovalSet,
    IMessageSet, MailingListStatus, PostedMessageStatus)


from canonical.launchpad.interfaces.emailaddress import (
    EmailAddressStatus, IEmailAddressSet)
from canonical.launchpad.interfaces.launchpad import ILaunchpadCelebrities
from canonical.launchpad.interfaces.mailinglist import (
    CannotChangeSubscription, CannotSubscribe, CannotUnsubscribe,
    IHeldMessageDetails, IMailingList, IMailingListSet,
    IMailingListSubscription, IMessageApproval, IMessageApprovalSet,
from canonical.launchpad.interfaces.message import IMessageSet
We encourage importing names from the location they are defined in. This
seems to work better with large complex components.
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== Attributes ==

Trivial attribute getter/setter functions are not necessary. Python takes a "We're all consenting adults" view on encapsulation, so if you want to access an attribute on an instance, just do it.

Be careful when accessing attributes of attributes. E.g.:

x = foo.bar.baz * 2

If {{{foo.bar}}} is None, Bad Things will happen, so always check if you're not sure. This is sometimes referred to as the "two dots rule".

If you need to dynamically access an attribute, use {{{getattr}}} rather than {{{eval}}}. It is clearer and safer. For example:

callback = getattr(self, "handler_" + state)
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When you need to add a property, ensure that {{{__metaclass__ = type}}} is used as mentioned above. For a read-only property, use the following pattern:

class SomeClass:
    def foo(self):
        # Do some processing.
        return bar

You should rarely need to add a property that has a getter and a setter, but on those occasions, this is how to do it. The getter is the same as for the simple case. The setter is called {{{_setfoo}}}. The name {{{_setfoo}}} starts with an underscore to show that it is not meant to be used except via the property.

class SomeClass:
    def foo(self):
        """Docstrings are helpful."""
        # Do some processing.
        return bar
    def _setfoo(self, value):
        # Do something with 'value'.

    foo = property(foo, _setfoo, doc=foo.__doc__)

Note the order: getter, setter, make them into a property.

## TODO:
## mutable default arguments
## no __del__
## getattr rather than eval
## steal How should I format my docstrings? from HackingFAQ
## mention pychecker etc.
## mention use of RST in docstrings
Properties are expected to be cheap operations. It is surprising if a property is not cheap operation. For expensive operations use a method, usually named {{{getFoo()}}}. Using {{{cachedproperty}}} provides a work-around but it should not be overused.
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Launchpad style tests for boolean True only. False, None, and 0 are not the same, and tests that rely on them being the same are ambiguous. Tests of objects that may be None or 0 must be written as truth tests because either value will be interpreted as False by the test.

Let's say you have a sequence (e.g. a list or tuple) and you want test whether it's empty or not. Standard Python convention is just to use Python's rules that empty sequences are false:

    if not mylist:
 # sequence mylist is empty

However, Launchpad hackers consider it to be more explicit to test against the sequence's length:

    if len(mylist) == 0:
 # sequence mylist is empty

If the value could be `None` though, please check explicitly against that using an identity check. In other words, don't do this:

    if not foo:

and '''definitely''' don't do this:

    if foo == None:

do this instead:

    if foo is None:

Note though that `is` and `is not` comparisions should only be used for
comparing singletons, which include built-ins like `None` but also singleton
objects you create in your program:

missing = object()
thing = mydict.get('thing', missing)
if thing is missing:
   # etc...

You wouldn't use `==` in that case, but similarly, if you're not comparing
against singletons, you should not use `is`, but `==`:

if thing == 'foo':

You might think that because of string interning, it would be safe to use `is`
here, but remember that interning is an implementation detail and you should
not count on any particular string being interned. Always use `==` for
comparison against strings and numbers. Note too that because of the way we
use SQLObject, there may be some cases where you have to use `==` in places
you'd normally think to use `is'.

== If statements ==

The most commonly used patterns like

    if something:


    if something:

are perfectly fine.

However, if you do have some `elif` statements, we consider it a good practice to always include an `else` statement, even if it contains only a comment and a `pass` statement, or an `assert` statement with an appropriate failure message.

    if isinstance(fruit, apple):
    elif isinstance(fruit, pineapple):
        # We only eat apples and pineapples.

Similarly you may have empty elif blocks, like

    if 'foo' in request.form:
    elif 'bar' in request.form:
    elif 'goback' in request.form:
        # No need to do anything; we'll simply redirect the user.
        raise UnexpectedFormData()

This may be considered an example of the "Explicit is better than implicit." principle.

=== Negation ===

A simple `if ... else` statement already contains a negation of the condition,
so it is a good idea to avoid negating the condition because the `not` or `!`
can easily be overread. Try to do it this way.

    if counter.isFull():

Avoid this:

    if not counter.isFull():

'''But''' this is ''not'' a strict rule because there may be cases when the
program flow is better to read with the negation first, like when checking
an object for None before accessing its attributes.

    if froobob is not None:
        blachi = froobob.getIt()
        blachi = nonchi

Use your own judgement to achieve maximum readability.
Remember that False, None, [], and 0 are not the same although they all evaluate to False in a boolean context. If this matters in your code, be sure to check explicitly for either of them.

Also, checking the length may be an expensive operation. Casting to bool may avoid this if the object specializes by implementing __nonzero__.
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Use of the built-in `hasattr` function should be avoided since it swallows exceptions. Instead use:
    if getattr(obj, 'attrname', None) is not None:

  However, if `None` is a valid value for the attribute, you have to do this instead:

    missing = object()
    if getattr(obj, 'attrname', missing) is not missing:
Use `safe_hasattr` from `lazr.restful.utils` instead of the built-in `hasattr` function because the latter swallows exceptions.
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== Unpacking assignment ==

  val_1, val_2 = multival_func()

And for 1-tuples

  assert (len(vals) == 1,
      "Expected 1 value, but received %s" % len(vals))
  val_1 = vals[0]

Python Style Guide

This document describes expected practices when writing Python code. There are occasions when you can break these rules, but be prepared to justify doing so when your code gets reviewed.

Existing Conventions

There are well-established conventions in the Python community, and in general we should follow these. General Python conventions, and required reading:

  • PEP 8: Style Guide for Python Code

  • PEP 257: Docstring Conventions

  • The Zen of Python: python -c "import this"

Note that our standards differ slightly from PEP-8 in some cases.

Coding standards other projects use:

Whitespace and Wrapping

  • Code should fit within 78 columns, so as to fit nicely in an 80 column terminal, even when quoted in an email.
  • Indents should be 4 spaces.
  • No tabs. This is not negotiable.

Multiline braces

There are lots of cases where you might have a list, tuple or dictionary literal that spans multiple lines. In these cases, you should consider formatting these literals as follows. This format makes changes to the list clearer to read in a diff. Note the trailing comma on the last element.

   1     mydict = {
   2         'first': 1,
   3         'second': 2,
   4         'third': 3,
   5         }
   7     mylist = [
   8         'this is the first line',
   9         'this is the second line',
  10         'this is the third line',
  11         ]


Consistency with existing code is the top priority. We follow PEP-8 with the following exceptions:

  • CamelCase: classes, interfaces (beginning with I)

  • initialCamelCase: methods

  • lowercase_underscores: functions, non-method attributes, properties, local variables

  • ALL_CAPS: constants

Private names are private

You should never call a non-public attribute or method from another class. In other words, if class A has a method _foo(), don't call it from anywhere outside class A.


  • If you haven't already, read PEP 257

  • In general, everything that can have a docstring should: modules, classes, methods, functions.
  • Docstrings should always be enclosed in triple double quotes: """Like this."""

  • When a class or a method implements an interface, the docstring should say """See `IFoo`."""

Docstrings should be valid reST (with all the painful indentation rules that implies) so that tools such as pydoctor can be used to automatically generate API documentation.

You should use field names as defined in the epydoc documentation but with reST syntax.

Using `name` outputs a link to the documentation of the named object, if pydoctor can figure out what it is. For an example of pydoctor's output, see http://starship.python.net/crew/mwh/hacks/example.html.

Here is comprehensive example. Parameter descriptions are a good idea but not mandatory. Describe in as much or as little detail as necessary.

   1 def example2(a, b):
   2     """Perform some calculation.
   4     It is a **very** complicated calculation.
   6     :param a: The number of gadget you think this
   7               function should frobnozzle.
   8     :type a: ``int``
   9     :param b: The name of the thing.
  10     :type b: ``str``
  11     :return: The answer!
  12     :rtype: ``str``.
  13     :raise ZeroDivisionError: when ``a`` is 0.
  14     """


Each module should look like this:

   1 # Copyright 2009-2011 Canonical Ltd.  All rights reserved.
   3 """Module docstring goes here."""
   5 __metaclass__ = type
   6 __all__ = [
   7     ...
   8     ]

The file standard_template.py has most of this already, so save yourself time by copying that when starting a new module. The "..." should be filled in with a list of public names in the module.

Note that although PEP-8 says to "put any relevant __all__ specification after the imports", Launchpad code should have the __all__ before the imports. This makes it easy to see what a module contains and exports, and avoids the problem that differing amounts of imports among files means that the __all__ list is in a different place each time. Given that we have the Import Fascist utility (see Imports), we use __all__ more often than in general Python code. __all__ should be formatted like imports.



There are restrictions on which imports can happen in Launchpad. Namely:

  • View code cannot import code from canonical.launchpad.database.

  • import * cannot be used if the module being imported from does not have an __all__

  • Database code may not import zope.exceptions.NotFoundError -- it must instead use canonical.launchpad.interfaces.NotFoundError

These restrictions are enforced by the Import Fascist, which will cause your tests not to pass if you don't abide by the rules.

Imports should be fully qualified. Good:

   1 # foo/bar.py
   2 import foo.baz


   1 # foo/bar.py
   2 import baz

I.e. if foo.bar imports foo.baz, it should say import foo.baz, not import baz.

Multiline imports

Sometimes import lines must span multiple lines, either because the package path is very long or because there are multiple names inside the module that you want to import.

Never use backslashes in import statements! Use parenthesized imports:

   1 from foo import (
   2    That, 
   3    TheOther, 
   4    This,
   5 )

Like other lists, imports should list one item per line. The exception is if only one symbol is being imported from a given module.

   1 from canonical.widgets.itemswidgets import CheckBoxMatrixWidget

But if you import two or more, then each item needs to be on a line by itself. Note the trailing comma on the last import and that the closing paren is on a line by itself.

   1 from canonical.widgets.itemswidgets import (
   2     CheckBoxMatrixWidget,
   3     LaunchpadRadioWidget,
   4     )

Also, 'make lint' is a very good tool for helping you maintain your imports.

Import scope

We encourage importing names from the location they are defined in. This seems to work better with large complex components.

Circular imports

With the increased use of native Storm APIs, you may encounter more circular import situations. For example, a MailingList method may need a reference to the EmailAddress class for a query, and vice versa. The classic way to solve this is to put one of the imports inside a method instead of at module global scope (a "nested import").

Short of adopting something like Zope's lazy imports (which has issues of its own), you can't avoid this, so here are some tips to make it less painful.

  • Do the nested import in the least common case. For example, if 5 methods

    in database/mailinglist.py need access to EmailAddress but only one method in database/emailaddress.py needs access to MailingList, put the import inside the emailaddres.py method, so you have fewer overall nested imports.

  • Clearly comment that the nested import is for avoiding a circular import, using the example below.
  • Put the nested import at the top of the method.

   1         def doFooWithBar(self, ...):
   2             # Import this here to avoid circular imports.
   3             from canonical.launchpad.database.bar import Bar
   4             # ...
   5             return store.find((Foo, Bar), ...)

Circular imports and webservice exports

One of the largest sources of pain from circular imports is caused when you need to export an interface on the webservice. Generally, the only way around this is to specify generic types (like the plain old Interface) at declaration time and then later patch the webservice's data structures at the bottom of the interface file.

Fortunately there are some helper functions to make this less painful, in components/apihelpers.py. These are simple functions where you can some info about your exported class/method/parameters and they do the rest for you.

For example:

   1     from canonical.launchpad.components.apihelpers import (
   2         patch_entry_return_type, patch_collection_return_type)
   3     patch_collection_return_type(
   4         IArchive, 'getComponentsForQueueAdmin', IArchivePermission)
   5     patch_entry_return_type(
   6         IArchive, 'newPackageUploader', IArchivePermission)


Properties are expected to be cheap operations. It is surprising if a property is not cheap operation. For expensive operations use a method, usually named getFoo(). Using cachedproperty provides a work-around but it should not be overused.

Truth conditionals

Remember that False, None, [], and 0 are not the same although they all evaluate to False in a boolean context. If this matters in your code, be sure to check explicitly for either of them.

Also, checking the length may be an expensive operation. Casting to bool may avoid this if the object specializes by implementing nonzero.

Chaining method calls

Since in some cases (e.g. class methods and other objects that rely on descriptor get() behaviour) it's not possible to use the old style of chaining method calls (SuperClass.method(self, ...)), we should always use the super() builtin when we want that.

/!\ The exception to this rule is when we have class hierarchies outside of our control that are known not to use super() and that we want to use for diamond-shaped inheritance.

Use of lambda, and operator.attrgetter

Prefer operator.attrgetter to lambda. Remember that giving functions names makes the code that calls, passes and returns them easier to debug.

Use of hasattr

Use safe_hasattr from lazr.restful.utils instead of the built-in hasattr function because the latter swallows exceptions.


We use two database ORM (object-relational mapper) APIs in Launchpad, the older and deprecated SQLObject API and the new and improved Storm API. All new code should use the Storm API, and you are encourages to convert existing code to Storm as part of your tech-debt payments.


  • The SQLObject and Storm ResultSet interfaces are not compatible, so e.g. if you need to UNION between these two, you will run into trouble. We are looking into ways to address this.

  • Using the native Storm API can be verbose and inconvenient for some folks. There is a (somewhat) experimental Sugar base class in lib/canonical/launchpad/database/stormsugar.py which provides many convenient APIs to make your use of Storm easier.

Field attributes

When you need to add ID attributes to your database class, use field_id as the attribute name instead of fieldID.

Multi-line SQL

SQL doesn't care about whitespace, so use triple quotes for large SQL queries or fragments, e.g.:

   1     query = """
   2         SELECT TeamParticipation.team, Person.name, Person.displayname
   3         FROM TeamParticipation
   4         INNER JOIN Person ON TeamParticipation.team = Person.id
   5         WHERE TeamParticipation.person = %s
   6         """ % sqlvalues(personID)

This also easy to cut-and-paste into psql for interactive testing, unlike if you use several lines of single quoted strings.

Creating temporary files

We should use the most convenient method of the tempfile module, never taint '/tmp/' or any other 'supposed to be there' path.

Despite of being developed and deployed on Ubuntu systems, turning it into restriction might not be a good idea.

When using tempfile.mkstemp remember it returns an open file-descriptor which has to be closed or bound to the open file, otherwise they will leak and eventually hit the default Linux limit (1024).

There are 2 good variations according to the scope of the temporary file.

   1     fd, filename = mkstemp()
   2     os.close(fd)
   3     ...
   4     act_on_filename(filename)


   1     fd, filename = mkstemp()
   2     temp_file = os.fdopen(fd, 'w')
   3     ...
   4     temp_file.write('foo')
   5     temp_file.close()

Never use:

   1     fd, filename = mkstemp()
   2     temp_file = open(filename)
   3     temp_file.write('foo')
   4     temp_file.close()
   5     # BOOM! 'fd' leaked.

It's also important to mention that in testing context, specially if you are using the lp.testing.TestCase (or one of its specializations) you can simply create a brand new temporary directory (using mkdtemp). Create as many files you need within it and register a cleanup function to purge the temporary directory recursively.

   1 class TestFoo(TestCase):
   2 ...
   3     def test_foo(self):
   4         tempdir = mkdtemp()
   5         self.addCleanup(shutils.rmtree, tempdir)
   6         ...
   7         do_something(os.path.join(tempdir, 'test.log'))
   8         ...

Configuration hints


To make wrapping and tabs fit the above standard, you can add the following to your .vimrc:

autocmd BufNewFile,BufRead *.py set tw=78 ts=4 sts=4 sw=4 et

To make trailing whitespace visible:

set list
set listchars=tab:>.,trail:-

This will also make it obvious if you accidentally introduce a tab.

To make long lines show up:

match Error /\%>79v.\+/

For an even more in-depth Vim configuration, have a look at UltimateVimPythonSetup for a complete vim file you can copy to your local setup.


There are actually two Emacs Python modes. Emacs comes with python.el which (IMO) has some quirks and does not seem to be as popular among hardcore Python programmers. python-mode.el comes with XEmacs and is supported by a group of hardcore Python programmers. Even though it's an add-on, it works with Emacs just fine.

PythonStyleGuide (last edited 2021-11-25 16:16:21 by cjwatson)