We need to use a different version of numpy for py3.8 and py3.12 in
pyproject.
And so do projects that use that Python version range and import
langchain.
- **Twitter handle:** _cbornet
Will run all CI because of _test change, but future PRs against CLI will
only trigger the new CLI one
Has a bunch of file changes related to formatting/linting.
No mypy yet - coming soon
We don't use any of the new functionality at the moment. Just making
sure we don't fall back on versions and fail to benefit from new
patches. This is an easy upgrade and it's always harder to upgrade
across multiple major versions at once.
A test file was accidentally dropping a `results.json` file in the
current working directory as a result of running `make test`.
This is undesirable, since we don't want to risk accidentally adding
stray files into the repo if we run tests locally and then do `git add
.` without inspecting the file list very closely.
With this PR:
- All lint and test jobs use the exact same Python + Poetry installation
approach, instead of lints doing it one way and tests doing it another
way.
- The Poetry installation itself is cached, which saves ~15s per run.
- We no longer pass shell commands as workflow arguments to a workflow
that just runs them in a shell. This makes our actions more resilient to
shell code injection.
If y'all like this approach, I can modify the scheduled tests workflow
and the release workflow to use this too.
The previous approach was relying on `_test.yml` taking an input
parameter, and then doing almost completely orthogonal things for each
parameter value. I've separated out each of those test situations as its
own job or workflow file, which eliminated all the special-casing and,
in my opinion, improved maintainability by making it much more obvious
what code runs when.
Using `poetry add` to install `pydantic@2.1` was also causing poetry to
change its lockfile. This prevented dependency caching from working:
- When attempting to restore a cache, it would hash the lockfile in git
and use it as part of the cache key. Say this is a cache miss.
- Then, it would attempt to save the cache -- but the lockfile will have
changed, so the cache key would be *different* than the key in the
lookup. So the cache save would succeed, but to a key that cannot be
looked up in the next run -- meaning we never get a cache hit.
In addition to busting the cache, the lockfile update itself is also
non-trivially long, over 30s:
This PR fixes the problems by using `pip` to perform the installation,
avoiding the lockfile change.
* PR updates test.yml to test with both pydantic versions
* Code should be refactored to make it easier to do testing in matrix
format w/ packages
* Added steps to assert that pydantic version in the environment is as
expected
