Python watchdog: what is the 'empty' directory snapshot?

Question

Watchdog is pretty awesome at letting you take recursive snapshots of a particular directory. It even lets you compare snapshots with a function called DirectorySnapshotDiff.

My program watches as a directory evolves in real-time, and thus has been made to consume the output of this function. This is very reasonable.

Let's say I take snapshots s1, s2... of the file system at arbitrary times. We compare the last snapshot with the latest one to create difference objects.

        d1    d2           # detected differences (my app eats these up)
     s1 -> s2 -> s3        # evolving states (snapshots taken) of the file system.

t=0 -------------------> time

Omnomnomnom. That's great.

But, the first time I run my app, I need to know the current state. I want to pretend that there was a null state s0, which transitions into s1; thus I can diff format. i.e.

     d0                # I want to create this 'bootstrapping' difference set
(s0) -> s1             # Assume s0 is the empty snapshot: it reports everything is an addition

How do I do that?

The motivation behind this is: I love functional programming. Instead of writing code to consume snapshots AND snapshot diffs (both considerable work) I like to keep reuse high and code minimal.

Answer 1

For versions of python >= 2.6 watchdog uses it's OrderedSet.

Modify fatuhoku's paths function as follows;

@property
def paths(self):
    if sys.version_info >= (2, 6, 0):
        return watchdog.utils.bricks.OrderedSet()
    return set()

Answer 2

I've come up with a solution by making a class that mimics watchdog.utils.dirsnapshot.DirectorySnapshot, returning empty values where appropriate.

class EmptyDirectorySnapshot(object):
    """
    For use as the zeroth snapshot in a chain of DirectorySnapshotDiffs
    """

    @property
    def stat_snapshot(self):
        return {}

    def stat_info(self, path):
        return None

    @property
    def paths(self):
        return set()

The two properties stat_snapshot and paths, as well as the method stat_info given above are used in the diffing function. This works fairly well and yields intended results. Hurrah.