Files
lancedb/python/src/job.rs
T
Xuanwo 255da8a854 fix(python): resolve native job types in API docs (#4170)
Native job metadata types report `builtins` as their module, so Griffe
cannot resolve the public `lancedb.job` re-exports and the Python API
reference build fails. Set the PyO3 module metadata for `JobInfo`,
`JobDescription`, and `JobFailureInfo`, and cover import resolution in
the existing package metadata tests.

Reproduced the failure and validated the fix with the docs CI toolchain
(`griffe==0.49.0`, `mkdocstrings==0.25.2`, and
`mkdocstrings-python==1.10.9`). After rebuilding the native extension,
the full `PYTHONPATH=. mkdocs build` succeeds and all three classes and
their public members appear in the generated reference.
2026-09-14 15:09:29 +08:00

279 lines
8.7 KiB
Rust

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
use std::sync::Arc;
use crate::runtime::future_into_py;
use arrow::{
datatypes::Schema,
pyarrow::{IntoPyArrow, Table as PyArrowTable},
};
use lancedb::job::JobEventsRequest;
use pyo3::{
Bound, PyAny, PyRef, PyResult, Python,
exceptions::PyValueError,
pyclass, pymethods,
types::{PyAnyMethods, PyDict, PyDictMethods},
};
use serde::Serialize;
use crate::error::PythonErrorExt;
const REPR_INDENT: &str = " ";
/// Parse a stored JSON payload into Python data. The bindings carry these as
/// strings because that is what crosses the boundary cheaply; the public
/// Python surface is the parsed form.
fn parse_json_payload<'py>(
py: Python<'py>,
raw: Option<&str>,
) -> PyResult<Option<Bound<'py, PyAny>>> {
match raw {
None => Ok(None),
Some(raw) => Ok(Some(py.import("json")?.call_method1("loads", (raw,))?)),
}
}
/// A payload rendered as indented JSON, aligned under the field that holds it.
fn pretty_json_payload(py: Python<'_>, raw: Option<&str>) -> PyResult<Option<String>> {
let Some(parsed) = parse_json_payload(py, raw)? else {
return Ok(None);
};
let kwargs = PyDict::new(py);
kwargs.set_item("indent", 4)?;
let rendered: String = py
.import("json")?
.call_method("dumps", (parsed,), Some(&kwargs))?
.extract()?;
Ok(Some(rendered.replace('\n', &format!("\n{REPR_INDENT}"))))
}
#[pyclass]
pub struct Job {
inner: Arc<lancedb::Job<std::result::Result<Option<String>, String>>>,
}
impl Job {
pub(crate) fn new(inner: lancedb::Job) -> Self {
Self {
inner: Arc::new(inner.map(|()| Ok(None))),
}
}
pub(crate) fn new_typed<T>(inner: lancedb::Job<T>) -> Self
where
T: Clone + Serialize + Send + Sync + 'static,
{
Self {
inner: Arc::new(inner.map(|result| {
serde_json::to_string(&result)
.map(Some)
.map_err(|error| format!("failed to serialize typed job result: {error}"))
})),
}
}
}
#[pymethods]
impl Job {
#[getter]
pub fn id(&self) -> Option<String> {
self.inner.id().map(str::to_string)
}
pub fn status(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
future_into_py(
self_.py(),
async move { inner.status().await.infer_error() },
)
}
pub fn wait(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
future_into_py(self_.py(), async move {
let result = inner.wait().await.infer_error()?;
result
.map_err(|message| lancedb::Error::Runtime { message })
.infer_error()
})
}
pub fn cancel(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
future_into_py(self_.py(), async move {
inner.cancel().await.infer_error()?;
Ok(())
})
}
pub fn refresh(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
future_into_py(self_.py(), async move {
inner.refresh().await.infer_error()?;
Ok(())
})
}
/// The last observed lifecycle state, without contacting the backend.
#[getter]
pub fn _state(&self) -> Option<String> {
self.inner.state()
}
/// The last observed server-side record. `None` for an in-process job.
#[getter]
pub fn _description(&self) -> Option<JobDescription> {
self.inner.description().map(JobDescription::from)
}
#[pyo3(signature = (*, limit=None, filter=None))]
pub fn events(
self_: PyRef<'_, Self>,
limit: Option<u32>,
filter: Option<String>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner.clone();
let request = JobEventsRequest { limit, filter };
future_into_py(self_.py(), async move {
let batches = inner.events(request).await.infer_error()?;
Python::attach(|py| {
let schema = batches
.first()
.map(|batch| batch.schema())
.unwrap_or_else(|| Arc::new(Schema::empty()));
let table = PyArrowTable::try_new(batches, schema)
.map_err(|err| PyValueError::new_err(err.to_string()))?;
table.into_pyarrow(py).map(|table| table.unbind())
})
})
}
}
/// A row from `Connection.list_jobs`: one server-side job.
#[pyclass(module = "lancedb._lancedb", get_all, skip_from_py_object)]
#[derive(Clone)]
pub struct JobInfo {
job_id: String,
table: String,
job_type: String,
state: String,
created_at_millis: i64,
}
#[pymethods]
impl JobInfo {
fn __repr__(&self) -> String {
format!(
"JobInfo(job_id={:?}, table={:?}, job_type={:?}, state={:?}, created_at_millis={})",
self.job_id, self.table, self.job_type, self.state, self.created_at_millis
)
}
}
impl From<lancedb::database::JobInfo> for JobInfo {
fn from(info: lancedb::database::JobInfo) -> Self {
Self {
job_id: info.job_id,
table: info.table,
job_type: info.job_type,
state: info.state,
created_at_millis: info.created_at_millis,
}
}
}
/// The server's account of why a job failed.
#[pyclass(module = "lancedb._lancedb", get_all, skip_from_py_object)]
#[derive(Clone)]
pub struct JobFailureInfo {
phase: Option<String>,
message: Option<String>,
retryable: Option<bool>,
}
#[pymethods]
impl JobFailureInfo {
fn __repr__(&self) -> String {
format!(
"JobFailureInfo(phase={:?}, message={:?}, retryable={:?})",
self.phase, self.message, self.retryable
)
}
}
/// The server-side record behind a `Job` handle.
#[pyclass(module = "lancedb._lancedb", get_all, skip_from_py_object)]
#[derive(Clone)]
pub struct JobDescription {
job_id: String,
job_type: String,
state: String,
creation_ms: i64,
/// Internal: the wire form behind the `spec` property.
_spec_json: Option<String>,
/// Internal: the wire form behind the `result` property.
_result_json: Option<String>,
failure: Option<JobFailureInfo>,
}
#[pymethods]
impl JobDescription {
/// The job-type-specific specification it was submitted with.
#[getter]
fn spec<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
parse_json_payload(py, self._spec_json.as_deref())
}
/// The job-type-specific terminal result. `None` until the job succeeds.
#[getter]
fn result<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
parse_json_payload(py, self._result_json.as_deref())
}
fn __repr__(&self, py: Python<'_>) -> PyResult<String> {
let mut fields = vec![
format!("job_id={:?}", self.job_id),
format!("job_type={:?}", self.job_type),
format!("state={:?}", self.state),
format!("creation_ms={}", self.creation_ms),
];
// Lay the payloads out as indented JSON, the same way the `Job` repr
// does, so the two agree on how the same data looks.
for (name, payload) in [("spec", &self._spec_json), ("result", &self._result_json)] {
if let Some(rendered) = pretty_json_payload(py, payload.as_deref())? {
fields.push(format!("{name}={rendered}"));
}
}
if let Some(failure) = &self.failure {
fields.push(format!("failure={}", failure.__repr__()));
}
let body = fields
.iter()
.map(|field| format!("\n{REPR_INDENT}{field},"))
.collect::<String>();
Ok(format!("JobDescription({body}\n)"))
}
}
impl From<lancedb::database::JobDescription> for JobDescription {
fn from(description: lancedb::database::JobDescription) -> Self {
Self {
job_id: description.job_id,
job_type: description.job_type,
state: description.state,
creation_ms: description.creation_ms,
_spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
_result_json: description
.result
.filter(|result| !result.is_null())
.map(|result| result.to_string()),
failure: description.failure.map(|failure| JobFailureInfo {
phase: failure.phase,
message: failure.message,
retryable: failure.retryable,
}),
}
}
}