# The Universe of Discourse

Wed, 05 Dec 2018

A couple of days ago I described a strange bug in my “Greenlight” project that was causing Git to fail unpredictably, saying:

    fatal: this operation must be run in a work tree


The problem seemed to go away when I changed

    with env_var("GIT_DIR", self.repo_dir):
with env_var("GIT_WORK_TREE", self.work_dir):
result = subprocess.run(command, ...)


to

    with env_var("GIT_DIR", self.repo_dir, "GIT_WORK_TREE", self.work_dir):
result = subprocess.run(command, ...)


but I didn't understand why. I said:

This was so unexpected that I wondered if the real problem was nondeterministic and if some of the debugging messages had somehow perturbed it. But I removed everything but the context manager change and ran another test, which succeeded. By then I was five and half hours into the debugging and I didn't have any energy left to actually understand what the problem had been. I still don't know.

The problem re-manifested again today, and this time I was able to track it down and fix it. The context manager code I mentioned above was not the issue.

That subprocess.run call is made inside a git_util object which, as you can see in the tiny excerpt above, has a self.work_dir attribute that tells it where to find the working tree. Just before running a Git command, the git_util object installs self.work_dir into the environment to tell Git where the working tree is.

The git_util object is originally manufactured by Greenlight itself, which sets the work_dir attribute to a path that contains the current process ID number. Just before the process exits, Greenlight destroys the working tree. This way, concurrent processes never try to use the same working tree, which would be a mess.

When Greenlight needs to operate on the repository, it uses its git_util object directly. It also creates a submission object to represent the submitted branch, and it installs the git_util object into the submission object, so that the submission object can also operate on the repository. For example, the submission object may ask its git_util object if it needs to be rebased onto some other branch, and if so to please do it. So:

• Greenlight has a submission.
• submission.git is the git_util object that deals with Git.
• submission.git.work_dir is the path to the per-process temporary working tree.

Greenlight's main purpose is to track these submission objects, and it has a database of them. To save time when writing the initial implementation, instead of using a real database, I had Greenlight use Python's “pickle” feature to pickle the list of submissions.

Someone would submit a branch, and Greenlight would pickle the submission. The submission contained its git_util object, and that got pickled along with the rest. Then Greenlight would exit and, just before doing so, it would destroy its temporary working tree.

Then later, when someone else wanted to approve the submission for publication, Greenlight would set up a different working tree with its new process ID, and unpickle the submission. But the submission's git.work_dir had been pickled with the old path, which no longer existed.

The context manager was working just fine. It was setting GIT_WORK_TREE to the work_dir value in the git_util object. But the object was obsolete and its work_dir value pointed to a directory that had been destroyed!

1. Greenlight's own git_util object was always fresh and had the right path in it, so Git commands run directly by Greenlight all worked properly.

2. Any new submission objects created by Greenlight would have the right path, so Git commands run by fresh submissions also worked properly.

3. Greenlight doesn't always destroy the working tree when it exits. If it exits abnormally, it leaves the working tree intact, for a later autopsy. And the unpickled submission would work perfectly if the working tree still existed, and it would be impossible to reproduce the problem!

Toward the end of the previous article, I said:

I suspect I'm being sabotaged somewhere by Python's weird implicit ideas of scope and variable duration, but I don't know. Yet.

For the record, then: The issue was indeed one of variable duration. But Python's weird implicit ideas were, in this instance, completely blameless. Instead the issue was cause by a software component even more complex and more poorly understood: “Dominus”.

This computer stuff is amazingly complicated. I don't know how anyone gets anything done.