chore: remove dead code

.github/workflows/ci.yml

@@ -36,6 +36,8 @@ jobs:
       # without failing a release. `blocking` did exactly that.
       - run: cargo build --all-features
       - run: cargo test --no-run --all-features
+      # Only --doc: every other test needs a live backend.
+      - run: cargo test --doc --all-features
       - run: cargo publish --dry-run
 
   wheels:

AGENTS.md

@@ -42,7 +42,7 @@ rather than run unoptimised, and the same applies to the PyO3 module, which need
 Most tests are integration tests that call a live backend via `create_api_service()`. They read configuration from a local `.env` file (gitignored). Required:
 
 - `BASE_URL` — backend root, e.g. `http://localhost:8081`
-- Either `TOKEN` (bearer token used as-is, no expiry) **or** the OAuth2 client-credentials set: `CLIENT_ID`, `CLIENT_SECRET`, `TOKEN_URI` (optional: `PROJECT_NAME`)
+- Either `TOKEN` (bearer token used as-is, no expiry) **or** the OAuth2 client-credentials set: `CLIENT_ID`, `CLIENT_SECRET`, `TOKEN_URI`
 
 Tests that mutate backend state (create/delete) often `sleep` a few seconds between operations and are sensitive to race conditions — prefer running them serially or isolating by unique external IDs.
 
@@ -185,7 +185,7 @@ The API wraps collections in `{ "items": [...] }`. `DataWrapper<T>` mirrors that
 
 ### Entity → request-body conversion
 
-`DataHubEntity` is a marker trait (`ext_id()` + `Clone + Serialize`) that unlocks generic `From` impls so a `T`, `&T`, `Vec<T>`, or `&Vec<T>` can be passed to service methods and auto-wrapped into `DataWrapper<T>`. Service methods accept `&I where for<'a> &'a I: Into<DataWrapper<Event>>` (see `EventsService::create`) — implement `DataHubEntity` on new entity types to get this ergonomics for free. `IdAndExtId` has its own parallel set of `From` impls for delete/byids endpoints.
+`DataHubEntity` is a marker trait (`Clone + Serialize`, no methods) that unlocks generic `From` impls so a `T`, `&T`, `Vec<T>`, or `&Vec<T>` can be passed to service methods and auto-wrapped into `DataWrapper<T>`. Service methods accept `&I where for<'a> &'a I: Into<DataWrapper<Event>>` (see `EventsService::create`) — implement `DataHubEntity` on new entity types to get this ergonomics for free. `IdAndExtId` has its own parallel set of `From` impls for delete/byids endpoints.
 
 ### Auth (`src/datahub.rs`)
 
@@ -245,10 +245,10 @@ refusal, so a by-id 404 carries `type: …/errors/not-found` and **`slug()` matc
 stays as the regression guard.
 
 401s carry a problem document too, with `type: …/errors/unauthorized` and a `detail` naming the
-check that failed — a missing, empty, malformed or ambiguous `organization` claim. That is the
-reason `src/auth_diagnostics.rs` reconstructs from the token it just sent, so the SDK now appends
-a near-duplicate of what the server already said. Note every entry-point 401 shares the
-`unauthorized` slug, so the cause is in the prose and cannot be branched on.
+check that failed — a missing, empty, malformed or ambiguous `organization` claim. That retired
+the SDK's own `auth_diagnostics` module, which existed only to reconstruct the reason from the
+token it had just sent. Note every entry-point 401 shares the `unauthorized` slug, so the cause is
+in the prose and cannot be branched on.
 
 ### Filters (`src/filters.rs`)
 

Cargo.toml

@@ -20,6 +20,11 @@ exclude = [
 # Synchronous client (intellistream_datahub_sdk::blocking), same split as reqwest::blocking.
 blocking = []
 
+# docs.rs builds with default features only, which would leave `blocking` undocumented even
+# though the README points callers at it.
+[package.metadata.docs.rs]
+all-features = true
+
 [dependencies]
 maplit = "1"
 tokio = { version = "1", features = ["full"] }
@@ -39,9 +44,6 @@ infer = { version = "0.19", default-features = false, features = ["std"] }
 thiserror = "2.0.17"
 zstd = "0.13"
 geojson = "1"
-# Reading (never verifying) the payload of a JWT the SDK already holds, to explain an
-# otherwise-unexplained 401 — see `auth_diagnostics`.
-base64 = "0.22"
 arrow-array = "59.3"
 arrow-schema = "59.3"
 arrow-ipc = "59.3"

README.md

@@ -68,7 +68,6 @@ environment:
 - `BASE_URL` — backend root, e.g. `http://localhost:8081` (required)
 - Either `TOKEN` (bearer token used as-is, never considered expired), **or** the OAuth2
   client-credentials set: `CLIENT_ID`, `CLIENT_SECRET`, `TOKEN_URI`
-- `PROJECT_NAME` — optional
 - `SCOPE` — against DataHub, needed when the realm uses Keycloak Organizations: that claim comes
   from a dynamic client scope, so the request must name it (`organization:*`, or
   `organization:<alias>` to pin one tenant). Without it the token carries no tenant and every call

datahub_python_bindings/src/datasets/async_service.rs

@@ -2,10 +2,9 @@ use crate::datasets::{
     DatasetIdentifiable, PyDataset, PyDatasetUpdate,
 };
 use crate::resources::PyResource;
-use crate::{DatahubIdentity, Identifiable, PyIdCollection};
 use intellistream_datahub_sdk::ApiService;
 use intellistream_datahub_sdk::datasets::{Dataset, DatasetUpdate};
-use intellistream_datahub_sdk::generic::{DataWrapper, IdAndExtId};
+use intellistream_datahub_sdk::generic::IdAndExtId;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 use pyo3_async_runtimes::tokio::future_into_py;
 use std::sync::Arc;

datahub_python_bindings/src/datasets/mod.rs

@@ -5,9 +5,8 @@ pub(crate) mod sync_service;
 use crate::PyIdCollection;
 use crate::events::{PyEvent, PyTimeFilter};
 use crate::resources::PyResourceNetwork;
-use crate::{PyFieldBool, PyFieldStr, PyListFieldStr, PyMapField};
+use crate::{PyFieldStr, PyListFieldStr, PyMapField};
 use intellistream_datahub_sdk::filters::{EventFilter, EventFilterForm};
-use intellistream_datahub_sdk::datahub::to_snake_lower_cased_allow_start_with_digits;
 use intellistream_datahub_sdk::datasets::{
     DatasetFilter, Dataset, DatasetFilterForm, DatasetUpdate, DatasetUpdateFields,
 };
@@ -19,7 +18,6 @@ use pyo3::{Bound, PyResult, pyclass, pymethods};
 use pyo3_async_runtimes::tokio::future_into_py;
 use std::collections::HashMap;
 use std::sync::Arc;
-use uuid::Uuid;
 
 #[pyclass(module = "intellistream_datahub_sdk", name = "Dataset", from_py_object)]
 #[derive(Clone)]

datahub_python_bindings/src/datasets/sync_service.rs

@@ -2,11 +2,10 @@ use crate::datasets::{
     DatasetIdentifiable, PyDataset, PyDatasetUpdate,
 };
 use crate::resources::PyResource;
-use crate::{PyIdCollection};
 use intellistream_datahub_sdk::datasets::{Dataset, DatasetUpdate};
 use intellistream_datahub_sdk::generic::IdAndExtId;
-use intellistream_datahub_sdk::{ApiService, Resource};
-use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
+use intellistream_datahub_sdk::ApiService;
+use pyo3::{PyResult, Python, pyclass, pymethods};
 use std::sync::Arc;
 
 #[pyclass(module = "intellistream_datahub_sdk", name = "DatasetsServiceSync")]

datahub_python_bindings/src/events/async_service.rs

@@ -1,13 +1,9 @@
 use crate::events::{
     EventIdentifyable, PyEventFilter, PyEvent, PyEventDimension, PyEventUpdate,
 };
-use crate::timeseries::async_service::PyTimeSeriesServiceAsync;
-use crate::timeseries::{PyTimeSeries, PyTimeSeriesUpdate};
-use crate::{PyIdCollection};
 use intellistream_datahub_sdk::events::{EventDimension, EventIdCollection, EventUpdate};
-use intellistream_datahub_sdk::generic::DataWrapper;
 use intellistream_datahub_sdk::{
-    ApiService, Event, TimeSeries, TimeSeriesUpdate, TimeSeriesUpdateCollection,
+    ApiService, Event,
 };
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 use pyo3_async_runtimes::tokio::future_into_py;

datahub_python_bindings/src/events/general.rs

@@ -1,7 +1,6 @@
 use crate::PyEvent;
 use crate::PyIdCollection;
 use crate::datetime::py_datetime_to_utc;
-use crate::resources::PyResource;
 use chrono::{DateTime, Utc};
 use intellistream_datahub_sdk::generic::IdAndExtId;
 use pyo3::prelude::*;

datahub_python_bindings/src/events/mod.rs

@@ -1,17 +1,12 @@
 use crate::{DataSetRef, PyIdCollection, StringOrList, opt_data_set_refs, opt_patterns};
 use crate::datetime::opt_py_datetime_to_utc;
-use crate::timeseries::datapoints::{
-    PyDatapointString, PyDatapointsCollectionDatapoints, PyDatapointsCollectionString,
-    PyRetrieveFilter,
-};
-use crate::timeseries::{PyDeleteFilter, PyTimeSeries, PyTimeSeriesUpdate};
 use crate::{PyFieldStr, PyFieldU64, PyListFieldIdCollection, PyMapField};
 use intellistream_datahub_sdk::filters::{EventFilter, DataSort, EventFilterForm, TimeFilter};
 use intellistream_datahub_sdk::events::{
     EventDimension, EventIdCollection, EventUpdate, EventUpdateFields,
 };
 use intellistream_datahub_sdk::generic::IdAndExtId;
-use intellistream_datahub_sdk::{ApiService, Event, TimeSeries};
+use intellistream_datahub_sdk::{ApiService, Event};
 use std::sync::Arc;
 use pyo3::exceptions::PyValueError;
 use pyo3::prelude::*;

datahub_python_bindings/src/events/sync_service.rs

@@ -1,17 +1,12 @@
 use crate::events::{
     EventIdentifyable, PyEventFilter, PyEvent, PyEventDimension, PyEventUpdate,
 };
-use crate::{PyIdCollection};
 use intellistream_datahub_sdk::events::{EventDimension, EventIdCollection, EventUpdate};
-use intellistream_datahub_sdk::filters::EventFilterForm;
-use intellistream_datahub_sdk::generic::DataWrapper;
 use intellistream_datahub_sdk::{
-    ApiService, Event, TimeSeries, TimeSeriesUpdate, TimeSeriesUpdateCollection,
+    ApiService, Event,
 };
-use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
-use pyo3_async_runtimes::tokio::future_into_py;
+use pyo3::{PyResult, Python, pyclass, pymethods};
 use std::sync::Arc;
-use tokio::runtime;
 use uuid::Uuid;
 
 #[pyclass(module = "intellistream_datahub_sdk", name = "EventsServiceSync")]
@@ -96,8 +91,7 @@ impl PyEventsServiceSync {
             input.iter().map(|u| EventIdCollection::from(u.clone())).collect();
 
         py.detach(|| {
-            let result = self
-                .runtime
+            self.runtime
                 .block_on(service.events.delete(&input_ids))
                 .map_err(|e| crate::datahub_err(e))?;
 

datahub_python_bindings/src/files/mod.rs

@@ -2,15 +2,13 @@ pub mod async_service;
 pub mod sync_service;
 
 use crate::datetime::opt_py_datetime_to_utc;
-use crate::resources::PyResource;
 use chrono::{DateTime, Utc};
 use intellistream_datahub_sdk::files::{FileDownload, FileUpdate};
 use intellistream_datahub_sdk::generic::{INode, IdAndExtId};
 use intellistream_datahub_sdk::{ApiService, FileUpload};
 use pyo3::prelude::*;
 use pyo3::types::{PyBytes, PyType};
 use pyo3_async_runtimes::tokio::future_into_py;
-use serde::{Deserialize, Serialize};
 use std::collections::HashMap;
 use std::sync::Arc;
 

datahub_python_bindings/src/files/sync_service.rs

@@ -72,8 +72,7 @@ impl PyFilesServiceSync {
         let input_ids: Vec<IdAndExtId> = input.into_iter().map(|u| IdAndExtId::from(u)).collect();
 
         py.detach(|| {
-            let result = self
-                .runtime
+            self.runtime
                 .block_on(service.files.delete(&DataWrapper::from_vec(input_ids)))
                 .map_err(|e| crate::datahub_err(e))?;
 

datahub_python_bindings/src/lib.rs

@@ -12,7 +12,6 @@ pub mod timeseries;
 pub mod units;
 mod functions;
 
-use crate::datasets::PyDataset;
 use crate::datasets::async_service::PyDatasetsServiceAsync;
 use crate::datasets::sync_service::PyDatasetsServiceSync;
 use crate::files::async_service::PyFilesServiceAsync;
@@ -33,7 +32,7 @@ use crate::subscriptions::sync_service::PySubscriptionsServiceSync;
 use crate::timeseries::async_service::PyTimeSeriesServiceAsync;
 use crate::timeseries::datapoints::PyRetrieveFilter;
 use crate::timeseries::sync_service::PyTimeSeriesServiceSync;
-use crate::timeseries::{PyDeleteFilter, PyTimeSeries};
+use crate::timeseries::PyTimeSeries;
 use crate::units::PyUnit;
 use crate::assets::async_service::PyAssetsServiceAsync;
 use crate::assets::sync_service::PyAssetsServiceSync;
@@ -52,11 +51,9 @@ use pyo3::create_exception;
 use pyo3::exceptions::{PyException, PyValueError};
 use pyo3::prelude::*;
 use pyo3::types::PyType;
-use pyo3_async_runtimes::tokio::future_into_py;
 use std::collections::HashMap;
 use std::sync::Arc;
 use std::sync::OnceLock;
-use units::*;
 
 create_exception!(
     intellistream_datahub_sdk,
@@ -153,7 +150,6 @@ fn build_buffered_config(
     token_url: Option<String>,
     client_id: Option<String>,
     client_secret: Option<String>,
-    project_name: Option<String>,
     enable_buffering: bool,
     buffer_retention_secs: Option<i64>,
     buffer_max_bytes: Option<u64>,
@@ -174,7 +170,6 @@ fn build_buffered_config(
         token_url,
         client_id,
         client_secret,
-        project_name,
     );
     if let Some(secs) = buffer_retention_secs {
         config.set_buffer_retention_secs(secs);
@@ -229,7 +224,6 @@ impl PySyncClient {
         token_url=None,
         client_id=None,
         client_secret=None,
-        project_name=None,
         enable_buffering=false,
         buffer_retention_secs=None,
         buffer_max_bytes=None,
@@ -250,7 +244,6 @@ impl PySyncClient {
         token_url: Option<String>,
         client_id: Option<String>,
         client_secret: Option<String>,
-        project_name: Option<String>,
         enable_buffering: bool,
         buffer_retention_secs: Option<i64>,
         buffer_max_bytes: Option<u64>,
@@ -272,7 +265,6 @@ impl PySyncClient {
                 token_url,
                 client_id,
                 client_secret,
-                project_name,
                 enable_buffering,
                 buffer_retention_secs,
                 buffer_max_bytes,
@@ -291,14 +283,14 @@ impl PySyncClient {
         }
     }
     #[classmethod]
-    fn from_env(py: Py<PyType>) -> PyResult<Self> {
+    fn from_env(_py: Py<PyType>) -> PyResult<Self> {
         Ok(Self {
             inner: ApiService::new(DataHubConfig::from_env().unwrap()),
             runtime: Arc::new(tokio::runtime::Runtime::new().unwrap()),
         })
     }
     #[classmethod]
-    fn from_envfile(py: Py<PyType>, path: Option<&str>) -> PyResult<Self> {
+    fn from_envfile(_py: Py<PyType>, path: Option<&str>) -> PyResult<Self> {
         Ok(Self {
             inner: ApiService::new(DataHubConfig::from_envfile(path).unwrap()),
             runtime: Arc::new(tokio::runtime::Runtime::new().unwrap()),
@@ -407,7 +399,6 @@ impl PyAsyncClient {
         token_url=None,
         client_id=None,
         client_secret=None,
-        project_name=None,
         enable_buffering=false,
         buffer_retention_secs=None,
         buffer_max_bytes=None,
@@ -428,7 +419,6 @@ impl PyAsyncClient {
         token_url: Option<String>,
         client_id: Option<String>,
         client_secret: Option<String>,
-        project_name: Option<String>,
         enable_buffering: bool,
         buffer_retention_secs: Option<i64>,
         buffer_max_bytes: Option<u64>,
@@ -450,7 +440,6 @@ impl PyAsyncClient {
                 token_url,
                 client_id,
                 client_secret,
-                project_name,
                 enable_buffering,
                 buffer_retention_secs,
                 buffer_max_bytes,
@@ -468,13 +457,13 @@ impl PyAsyncClient {
         }
     }
     #[classmethod]
-    fn from_env(py: Py<PyType>) -> PyResult<Self> {
+    fn from_env(_py: Py<PyType>) -> PyResult<Self> {
         Ok(Self {
             inner: ApiService::new(DataHubConfig::from_env().unwrap()),
         })
     }
     #[classmethod]
-    fn from_envfile(py: Py<PyType>, path: Option<&str>) -> PyResult<Self> {
+    fn from_envfile(_py: Py<PyType>, path: Option<&str>) -> PyResult<Self> {
         Ok(Self {
             inner: ApiService::new(DataHubConfig::from_envfile(path).unwrap()),
         })

datahub_python_bindings/src/resources/sync_service.rs

@@ -3,7 +3,6 @@ use crate::relations::{PyGraphResult, PyRelForm};
 use crate::resources::{PyResourceFilter, ResourceIdentifiable};
 use crate::resources::{PyResourceNetwork, PyResourceUpdate};
 use intellistream_datahub_sdk::resources::ResourceUpdate;
-use crate::resources::async_service::PyResourcesServiceAsync;
 use crate::{DataSetRef, StringOrList, opt_data_set_refs, opt_patterns};
 use intellistream_datahub_sdk::filters::NodeFilter;
 use intellistream_datahub_sdk::generic::IdAndExtId;

datahub_python_bindings/src/timeseries/async_service.rs

@@ -1,18 +1,17 @@
 use crate::timeseries::datapoints::{
-    PyDatapoint, PyDatapointsCollectionDatapoints, PyDatapointsCollectionString,
+    PyDatapointsCollectionDatapoints, PyDatapointsCollectionString,
 };
 use crate::timeseries::{
     PyDeleteFilter, PyTimeSeries, PyTimeSeriesUpdate, PyTimeseriesIdentifiable,
 };
 use crate::{
-    DatahubIdentity, Identifiable, PyIdCollection, PyRetrieveFilter,
+    DatahubIdentity, Identifiable, PyRetrieveFilter,
 };
 use crate::datetime::py_datetime_to_utc;
 use intellistream_datahub_sdk::generic::{
     DataWrapper, DatapointString, DatapointsCollection, DeleteFilter, IdAndExtId, RetrieveFilter,
 };
 use intellistream_datahub_sdk::{ApiService, TimeSeries, TimeSeriesUpdate, TimeSeriesUpdateCollection};
-use pyo3::prelude::*;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 use pyo3_async_runtimes::tokio::future_into_py;
 use std::sync::Arc;
@@ -236,7 +235,6 @@ impl PyTimeSeriesServiceAsync {
                 .insert_datapoints(&mut wrapper)
                 .await
                 .map_err(|e| crate::datahub_err(e))?;
-            let val = result.get_items().clone();
             Ok(result.get_items().clone())
         })
     }
@@ -274,7 +272,6 @@ impl PyTimeSeriesServiceAsync {
                 .insert_datapoints(&mut wrapper)
                 .await
                 .map_err(|e| crate::datahub_err(e))?;
-            let val = result.get_items().clone();
             Ok(result.get_items().clone())
         })
     }
@@ -309,7 +306,7 @@ impl PyTimeSeriesServiceAsync {
         let wrapper =
             DataWrapper::<DeleteFilter>::from_vec(input.into_iter().map(|f| f.into()).collect());
         future_into_py(py, async move {
-            let result = service
+            service
                 .time_series
                 .delete_datapoints(&wrapper)
                 .await