Breezy Code Style Guide¶
Please write PEP-8 compliant code.
One often-missed requirement is that the first line of docstrings should be a self-contained one-sentence summary.
We use 4 space indents for blocks, and never use tab characters. (In vim,
Trailing white space should be avoided, but is allowed. You should however not make lots of unrelated white space changes.
Unix style newlines (LF) are used.
Each file must have a newline at the end of it.
Lines should be no more than 79 characters if at all possible. Lines that continue a long statement may be indented in either of two ways:
within the parenthesis or other character that opens the block, e.g.:
my_long_method(arg1, arg2, arg3)
or indented by four spaces:
my_long_method(arg1, arg2, arg3)
The first is considered clearer by some people; however it can be a bit harder to maintain (e.g. when the method name changes), and it does not work well if the relevant parenthesis is already far to the right. Avoid this:
self.legbone.kneebone.shinbone.toebone.shake_it(one, two, three)
self.legbone.kneebone.shinbone.toebone.shake_it(one, two, three)
self.legbone.kneebone.shinbone.toebone.shake_it( one, two, three)
For long lists, we like to add a trailing comma and put the closing character on the following line. This makes it easier to add new items in future:
from breezy.goo import ( jam, jelly, marmalade, )
There should be spaces between function parameters, but not between the keyword name and the value:
call(1, 3, cheese=quark)
Breezy supports Python 2.7 and Python 3.5 or later.
hasattr and getattr¶
hasattr should not be used because it swallows exceptions including
KeyboardInterrupt. Instead, say something like
if getattr(thing, 'name', None) is None
**kwargs in the prototype of a function should be used sparingly.
It can be good on higher-order functions that decorate other functions,
assertRaises, or on functions that take only
(or almost only) kwargs, where any kwargs can be passed.
Otherwise, be careful: if the parameters to a function are a bit complex
and might vary over time (e.g. the
commit API) then we prefer to pass an
object rather than a bag of positional and/or keyword args. If you have
an arbitrary set of keys and values that are different with each use (e.g.
string interpolation inputs) then again that should not be mixed in with
the regular positional/keyword args, it seems like a different category of
Imitating standard objects¶
Don’t provide methods that imitate built-in classes (eg
__getitem__) unless the class you’re
implementing really does act like the builtin class, in semantics and
For example, old code lets you say
file_id in inv but we no longer
consider this good style. Instead, say more explicitly
__str__ are usually fine.
Imports should be done at the top-level of the file, unless there is a strong reason to have them lazily loaded when a particular function runs. Import statements have a cost, so try to make sure they don’t run inside hot functions.
Module names should always be given fully-qualified, i.e.
Functions, methods or members that are relatively private are given a leading underscore prefix. Names without a leading underscore are public not just across modules but to programmers using breezy as an API.
We prefer class names to be concatenated capital words (
and variables, methods and functions to be lowercase words joined by
For the purposes of naming some names are treated as single compound words: “filename”, “revno”.
Consider naming classes as nouns and functions/methods as verbs.
Try to avoid using abbreviations in names, because there can be inconsistency if other people use the full name.
Functions that transform one thing to another should be named
x2y as occurs in some old code.)
Python destructors (
__del__) work differently to those of other
languages. In particular, bear in mind that destructors may be called
immediately when the object apparently becomes unreferenced, or at some
later time, or possibly never at all. Therefore we have restrictions on
what can be done inside them.
If you think you need to use a
__del__method ask another developer for alternatives. If you do need to use one, explain why in a comment.
Never rely on a
__del__method running. If there is code that must run, instead have a
finallyblock or an
addCleanupcall an explicit
importfrom inside a
__del__method, or you may crash the interpreter!!
Prior to bzr 2.4, we sometimes used to raise warnings from del methods that the object was not cleaned up or closed. We no longer do this: failure to close the object doesn’t cause a test failure; the warning appears an arbitrary long time after the problem occurred (the object being leaked); merely having a del method inhibits Python gc; the warnings appear to users and upset them; they can also break tests that are checking what appears on stderr.
In short, just don’t use
Often when something has failed later code will fail too, including
cleanups invoked from
finally blocks. These secondary failures are
generally uninteresting compared to the original exception.
has some facilities you can use to mitigate this.
Commandsubclasses, prefer the
add_cleanupmethod to using
finallyblocks. E.g. to acquire a lock and ensure it will always be released when the command is done:
This also avoids heavily indented code. It also makes it easier to notice mismatched lock/unlock pairs (and other kinds of resource acquire/release) because there isn’t a large block of code separating them.
breezy.decorators) when defining methods that are typically called in
finallyblocks, such as
unlockmethods. For example,
@only_raises(LockNotHeld, LockBroken). All errors that are unlikely to be a knock-on failure from a previous failure should be allowed.
Consider using the
breezy.cleanupanywhere else you have a
finallyblock that might fail.
In some places we have variables which point to callables that construct
new instances. That is to say, they can be used a lot like class objects,
but they shouldn’t be named like classes. Things called
create an instance of
FooBar. A factory method that might create a
FooBar or might make something else should be called
Several places in Breezy use (or will use) a registry, which is a mapping from names to objects or classes. The registry allows for loading in registered code only when it’s needed, and keeping associated information such as a help string or description.
InterObject and multiple dispatch¶
InterObject provides for two-way multiple dispatch: matching
up for example a source and destination repository to find the right way
to transfer data between them.
There is a subclass
InterObject classes for each type of object that is
dispatched this way, e.g.
.get() on this
class will return an
InterObject instance providing the best match for
those parameters, and this instance then has methods for operations
between the objects.
inter = InterRepository.get(source_repo, target_repo) inter.fetch(revision_id)
InterRepository also acts as a registry-like object for its
subclasses, and they can be added through
right one to run is selected by asking each class, in reverse order of
registration, whether it
.is_compatible with the relevant objects.
To make startup time faster, we use the
breezy.lazy_import module to
delay importing modules until they are actually used.
the same syntax as regular python imports. So to import a few modules in a
lazy fashion do:
from breezy.lazy_import import lazy_import lazy_import(globals(), """ import os import subprocess import sys import time from breezy import ( errors, transport, revision as _mod_revision, ) import breezy.transport import breezy.xml5 """)
At this point, all of these exist as a
ImportReplacer object, ready to
be imported once a member is accessed. Also, when importing a module into
the local namespace, which is likely to clash with variable names, it is
recommended to prefix it as
_mod_<module>. This makes it clearer that
the variable is a module, and these object should be hidden anyway, since
they shouldn’t be imported into other namespaces.
While it is possible for
lazy_import() to import members of a module
when using the
from module import member syntax, it is recommended to
only use that syntax to load sub modules
from module import submodule.
This is because variables and classes can frequently be used without
needing a sub-member for example:
lazy_import(globals(), """ from module import MyClass """) def test(x): return isinstance(x, MyClass)
This will incorrectly fail, because
MyClass is a
object, rather than the real class.
It also is incorrect to assign
ImportReplacer objects to other variables.
Because the replacer only knows about the original name, it is unable to
replace other variables. The
ImportReplacer class will raise an
IllegalUseOfScopeReplacer exception if it can figure out that this
happened. But it requires accessing a member more than once from the new
variable, so some bugs are not detected right away.
The Null revision¶
The null revision is the ancestor of all revisions. Its revno is 0, its
null:, and its tree is the empty tree. When referring
to the null revision, please use
code sometimes uses
None for the null revision, but this practice is
being phased out.
Object string representations¶
Python prints objects using their
__repr__ method when they are
written to logs, exception tracebacks, or the debugger. We want
objects to have useful representations to help in determining what went
If you add a new class you should generally add a
unless there is an adequate method in a parent class. There should be a
test for the repr.
Representations should typically look like Python constructor syntax, but
they don’t need to include every value in the object and they don’t need
to be able to actually execute. They’re to be read by humans, not
machines. Don’t hardcode the classname in the format, so that we get the
correct value if the method is inherited by a subclass. If you’re
printing attributes of the object, including strings, you should normally
%r syntax (to call their repr in turn).
Try to avoid the representation becoming more than one or two lines long. (But balance this against including useful information, and simplicity of implementation.)
Because repr methods are often called when something has already gone wrong, they should be written somewhat more defensively than most code. They shouldn’t have side effects like doing network or disk IO. The object may be half-initialized or in some other way in an illegal state. The repr method shouldn’t raise an exception, or it may hide the (probably more useful) underlying exception.
def __repr__(self): return '%s(%r)' % (self.__class__.__name__, self._transport)
except statement will catch all exceptions, including ones that
really should terminate the program such as
KeyboardInterrupt. They should rarely be used unless the exception is
later re-raised. Even then, think about whether catching just
Exception (which excludes system errors in Python2.5 and later) would
__str__ method on exceptions should be small and have no side
effects, following the rules given for Object string representations.
In particular it should not do any network IO, or complicated
introspection of other objects. All the state needed to present the
exception to the user should be gathered before the error is raised.
In other words, exceptions should basically be value objects.
All code should be exercised by the test suite. See the Breezy Testing Guide for detailed information about writing tests.
Do not use the Python
assert statement, either in tests or elsewhere.
A source test checks that it is not used. It is ok to explicitly raise
It makes the behaviour vary depending on whether brz is run with -O or not, therefore giving a chance for bugs that occur in one case or the other, several of which have already occurred: assertions with side effects, code which can’t continue unless the assertion passes, cases where we should give the user a proper message rather than an assertion failure.
It’s not that much shorter than an explicit if/raise.
It tends to lead to fuzzy thinking about whether the check is actually needed or not, and whether it’s an internal error or not
It tends to cause look-before-you-leap patterns.
It’s unsafe if the check is needed to protect the integrity of the user’s data.
It tends to give poor messages since the developer can get by with no explanatory text at all.
We can’t rely on people always running with -O in normal use, so we can’t use it for tests that are actually expensive.
Expensive checks that help developers are better turned on from the test suite or a -D flag.
If used instead of
self.assert*()in tests it makes them falsely pass with -O.
;(defface my-invalid-face ; '((t (:background "Red" :underline t))) ; "Face used to highlight invalid constructs or other uglyties" ; ) (defun my-python-mode-hook () ;; setup preferred indentation style. (setq fill-column 79) (setq indent-tabs-mode nil) ; no tabs, never, I will not repeat ; (font-lock-add-keywords 'python-mode ; '(("^\\s *\t" . 'my-invalid-face) ; Leading tabs ; ("[ \t]+$" . 'my-invalid-face) ; Trailing spaces ; ("^[ \t]+$" . 'my-invalid-face)); Spaces only ; ) ) (add-hook 'python-mode-hook 'my-python-mode-hook)
The lines beginning with ‘;’ are comments. They can be activated if one want to have a strong notice of some tab/space usage violations.
breezy.osutils module has many useful helper functions, including
some more portable variants of functions in the standard library.
In particular, don’t use
shutil.rmtree unless it’s acceptable for it
to fail on Windows if some files are readonly or still open elsewhere.
open(..).write(..) style chaining
of methods for reading or writing file content relies on garbage collection
to close the file which may keep the file open for an undefined period of
time. This may break some follow up operations like rename on Windows.
try/finally to explictly close the file. E.g.:
f = open('foo.txt', 'w') try: f.write(s) finally: f.close()
If you need to import a module (or attribute of a module) named in a variable:
If importing a module, not an attribute, and the module is a top-level module (i.e. has no dots in the name), then it’s ok to use the builtin
In all other cases, prefer
breezy.pyutils.get_named_objectto the built-in
__import__has some subtleties and unintuitive behaviours that make it hard to use correctly.