Follow-up to #8540, which turned on `PLC0415` (import-outside-top-level)
for checkpoint-postgres and checkpoint-sqlite. This does the remaining
six packages: checkpoint, checkpoint-conformance, langgraph, prebuilt,
cli, sdk-py.
Scoped to tests, per @sydney-runkle's call on #8540: library code is
exempted with `per-file-ignores`, since it still has deferred imports
nobody has reviewed and mixing that in would make this hard to read.
## What changed
Function-level imports across 56 test files moved to module level. Nine
could not move and carry an explicit `# noqa: PLC0415` with a reason:
| File | Why it stays local |
|---|---|
| `libs/langgraph/tests/test_deprecation.py` (4) | the import has to run
inside `pytest.warns` for the warning to be observed |
| `libs/langgraph/tests/test_serde_allowlist.py` | try/except guard,
skips when langchain_core is absent |
| `libs/langgraph/tests/test_delta_channel_benchmark.py` | optional
psycopg probe |
| `libs/checkpoint/tests/test_conformance_delta.py` (3) | protected by a
module-level `pytest.importorskip`; hoisting past the guard turns a skip
into a collection error |
That last one is the trap: an import moved above `pytest.importorskip`
silently defeats the guard. I hit it locally and it turned the skip into
a `ModuleNotFoundError` at collection. Every file with an `importorskip`
or `except ImportError` was checked by hand for this.
## Verification
`make lint` and `make test` in each of the six:
| Package | Tests |
|---|---|
| checkpoint | 156 passed, 17 skipped |
| checkpoint-conformance | 1 passed |
| langgraph | 1968 passed, 4 skipped |
| prebuilt | 284 passed |
| cli | 336 passed |
| sdk-py | 493 passed |
Also confirmed the rule actually fires: a throwaway test file with a
function-level import is flagged in all six packages, and the source
exemption holds.
Resolves https://github.com/langchain-ai/langchain/issues/35585
This would previously raise KeyError:
```python
from typing import Annotated
from langchain_core.tools import tool
from langchain.agents import create_agent
from typing_extensions import NotRequired
from langgraph.prebuilt import InjectedState
from langchain.agents import AgentState
class CustomAgentState(AgentState):
city: NotRequired[str]
@tool
def get_weather(city: Annotated[str | None, InjectedState("city")] = None) -> str:
"""Get weather for a given city."""
if city is None:
city = "Boston"
return f"It's always sunny in {city}!"
agent = create_agent(
model="claude-sonnet-4-6",
tools=[get_weather],
system_prompt="You are a helpful assistant",
state_schema=CustomAgentState,
)
input_message = {
"role": "user",
"content": "What's the weather?",
}
result = agent.invoke({"messages": [input_message]})
for m in result["messages"]:
m.pretty_print()
```
---------
Co-authored-by: Sydney Runkle <sydneymarierunkle@gmail.com>
