Breezy Code Style Guide

Code layout

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, set expandtab.)

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.:


or indented by four spaces:


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:


but rather



    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 import (

There should be spaces between function parameters, but not between the keyword name and the value:

call(1, 3, cheese=quark)

Python versions

Code should be written such that it runs on all versions of Python that Breezy support. See for what versions those are.

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, such as addCleanup or 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 thing.

Imitating standard objects

Don’t provide methods that imitate built-in classes (eg __in__, __call__, __int__, __getitem__) unless the class you’re implementing really does act like the builtin class, in semantics and performance.

For example, old code lets you say file_id in inv but we no longer consider this good style. Instead, say more explicitly inv.has_id(file_id).

__repr__, __cmp__, __str__ are usually fine.

Module Imports

  • 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. breezy.hashcache not just hashcache.


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 (TestCase) and variables, methods and functions to be lowercase words joined by underscores (revision_id, get_revision).

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.

Standard Names

revision_id not rev_id or revid

Functions that transform one thing to another should be named x_to_y (not 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.

  1. 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.

  2. Never rely on a __del__ method running. If there is code that must run, instead have a finally block or an addCleanup call an explicit close method.

  3. Never import from inside a __del__ method, or you may crash the interpreter!!

  4. 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 __del__.

Cleanup methods

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. breezy has some facilities you can use to mitigate this.

  • In Command subclasses, prefer the add_cleanup method to using try/finally blocks. 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.

  • Use the only_raises decorator (from breezy.decorators) when defining methods that are typically called in finally blocks, such as unlock methods. 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 OperationWithCleanups helper from breezy.cleanup anywhere else you have a finally block 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 FooBar should create an instance of FooBar. A factory method that might create a FooBar or might make something else should be called foo_factory.


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

The 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. InterRepository. Calling .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)

InterRepository also acts as a registry-like object for its subclasses, and they can be added through .register_optimizer. The right one to run is selected by asking each class, in reverse order of registration, whether it .is_compatible with the relevant objects.

Lazy Imports

To make startup time faster, we use the breezy.lazy_import module to delay importing modules until they are actually used. lazy_import uses 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 (
   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 ImportReplacer 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 revision-id is null:, and its tree is the empty tree. When referring to the null revision, please use breezy.revision.NULL_REVISION. Old 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 wrong.

If you add a new class you should generally add a __repr__ method 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 use %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__,

Exception handling

A bare except statement will catch all exceptions, including ones that really should terminate the program such as MemoryError and 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 be better.

The __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.

Test coverage

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 AssertionError.


  • 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.

emacs setup

In emacs:

;(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.

Portability Tips

The 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. Use breezy.osutils.rmtree instead.

Using the open(..).read(..) or 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. Use try/finally to explictly close the file. E.g.:

f = open('foo.txt', 'w')

Dynamic imports

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 __import__, e.g. __import__(module_name).

  • In all other cases, prefer breezy.pyutils.get_named_object to the built-in __import__. __import__ has some subtleties and unintuitive behaviours that make it hard to use correctly.