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Semi-automated code-level dependency tracking for python.
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README.rst

codedep

This package provides a simple, semi-automated way to do code-level dependency tracking for python projects.

Problem

The central idea is to be able to compute, for a given function or class, a hash of all the python source code that the function or class depends on. A given function or class is considered to depend on its immediate source code definition, on the source code defining functions or classes referred to in its immediate definition, and so on. For example if a class Foo uses a function bar in one of its methods, then the hash value for Foo is based on the source code defining both Foo and bar.

The ability to compute such a hash value allows automated tracking of when the behaviour of a given function or class changes (or rather, might have changed). For example the author's original use case was for distributing jobs on a compute grid, where it was useful to be able to determine automatically when a job needed to be re-run because of changes to the source code.

Approach used by codedep

Computing such a hash value is presumably very difficult to do in a fully automated way, partly because of the dynamic nature of python. The approach taken in this package is to require an explicit annotation for each function fn (or class) giving the list of functions or classes that are referred to in the definition of fn. For example if a class Foo uses functions bar and baz in its methods, then Foo could be decorated with @codeDeps(bar, baz). Everything else required to compute the hash value is looked-up automatically using existing tools such as the inspect module. To help with the burden of maintaining the @codeDeps lists, an automated tool is provided which suggests dependencies which may have been forgotten or may have been added unnecessarily. This semi-automated approach has the advantage that it can cope with the common cases easily while allowing the user control when they know better than the tool.

There are a few limitations on what the scheme used here can do:

  • It only allows dependencies to be specified and hash values to be computed for top-level functions and classes, not nested ones.
  • Behind the scenes the decorators add special values to the dictionary of the thing being decorated, so the thing being decorated has to have such a dictionary. This is the case for standard functions and classes.
  • Global (module-level) variables cannot be declared as dependencies since it is not possible to find their source code definitions using inspect. For safety it is therefore recommended to have no global variables (other than function and class definitions) when using this package.

The scheme used here has the advantage of being relatively simple. The entire code to do the decoration and compute hashes is around 200 lines. It is hoped that this simplicity will allow reasoning about how the scheme will operate in any tricky edge cases.

Installation

For most purposes the simplest way to install codedep is to use pip. For example in Debian and Ubuntu:

sudo pip install codedep

This installs the latest released version of codedep on PyPI, together with any currently uninstalled python packages required by codedep.

codedep can also be installed in a virtualenv:

virtualenv env
env/bin/pip install codedep

The latest development version of codedep is available from a github repository (see below).

Usage

A sample python project is provided in the example directory. The file example/foo.py defines some functions and classes. The script example/print_hash.py prints some of the computed hashes for the functions and classes, together with some values computed by the functions and classes.

Typing:

python -m example.print_hash

should give the output:

hash of baz = 1a0ebbff92a8a8691c17a460b8eeb4cb38399c60
hash of Foo = 96a9e852464e99d68d2769655a8113de33ee0721
value1 = 6
value2 = 0

If you now change the definition of qux in example/foo.py to multiply by 3 instead of 2, then the above command will output:

hash of baz = 0c955f9963b6acb422501d5ee64e6bdedc5c204b
hash of Foo = 572f8685fde1670fa720df6ebbf89a6cc8dd1e4c
value1 = 9
value2 = 0

Suitable @codeDeps decorator lines can be suggested using an automated tool. Running:

bin/codedep_check example/foo.py

or, if codedep has been installed, running:

codedep_check example/foo.py

should print (no change) as one of its lines of output. If you now change the definition of baz in example/foo.py to return qux(bar(x) - 2) and re-run the automated tool then you should be taken to a vimdiff of the original and suggested files. The tool picks up the fact that baz now depends on bar.

Note that bin/codedep_check is a wrapper around codedep/check_deps.py. The wrapper makes certain assumptions about the structure of the project (see bin/codedep_check for details). In complicated cases it is intended that this wrapper be copied and customized to a version suitable for the specific project.

License

Please see the file License for details of the license and warranty for codedep.

Source

The source code is hosted in the codedep github repository. To obtain the latest source code using git:

git clone git://github.com/MattShannon/codedep.git

Development is in fact done using darcs, with the darcs repository converted to a git repository using darcs-to-git.

To install any currently uninstalled python packages required by codedep:

sudo pip install -r requirements.txt

Bugs

Please use the issue tracker to submit bug reports.

Contact

The author of codedep is Matt Shannon.

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