fix(binary): decide the stale-series retry from the problem document

AGENTS.md

@@ -125,7 +125,7 @@ When a datapoint/event send can't get through, ingestion spools to a segmented,
 
 ### Binary datapoint ingest (`src/timeseries/binary.rs`)
 
-`TimeSeriesService::insert_datapoints_binary` is the second ingest path, to `POST /timeseries/data/binary`: the same `DatapointsCollection<DatapointString>` input, resolved through `/timeseries/byids` (cached per service instance; needs read access on the dataset), checked against each series' value type locally, cut into Arrow IPC frames at the contract's caps, zstd-compressed per frame (mandatory: level 1, 3 or 9, default 9) and posted through `execute_post_bytes_request`. `FrameWriter` builds one frame and is public; `cut_into_writers` and `pack_requests` hold the caps. The byte layout is the platform's `binary_datapoints_format.md`. The arrow-rs crates (`arrow-array`, `arrow-schema`, `arrow-ipc`) exist for this path and are the seed of the Arrow read path. Not in the Python bindings yet. The ignored `timeseries::tests::test_datapoints_binary` is the live twin of `test_datapoints` and needs a backend that serves the endpoint; the writer's own tests in `binary.rs` run offline.
+`TimeSeriesService::insert_datapoints_binary` is the second ingest path, to `POST /timeseries/data/binary`: the same `DatapointsCollection<DatapointString>` input, resolved through `/timeseries/byids` (cached per service instance; needs read access on the dataset), checked against each series' value type locally, cut into Arrow IPC frames at the contract's caps, zstd-compressed per frame (mandatory: level 1, 3 or 9, default 9) and posted through `execute_post_bytes_request`. The api answers every refusal on this path with the single problem type `datapoint-block-rejected` and puts the actual cause in a `reason` extension, so here — unlike everywhere else — the slug is not the discriminant; `is_stale_series_rejection` reads `reason` to decide the one re-resolve-and-retry. `FrameWriter` builds one frame and is public; `cut_into_writers` and `pack_requests` hold the caps. The byte layout is the platform's `binary_datapoints_format.md`. The arrow-rs crates (`arrow-array`, `arrow-schema`, `arrow-ipc`) exist for this path and are the seed of the Arrow read path. The ignored `timeseries::tests::test_datapoints_binary` is the live twin of `test_datapoints` and needs a backend that serves the endpoint; the writer's own tests in `binary.rs` run offline.
 
 ### The `ApiServiceProvider` trait (`src/generic.rs`)
 

README.md

@@ -128,7 +128,10 @@ frame, 32 frames per request), compressed with zstd (level 9 by default, 1 and 3
 choices) and posted. A 204 means every frame was accepted.
 
 A series that does not exist is a 404 before anything is sent, a value that does not fit its
-type is a 422, and a 429 or a 5xx is retried. Resolving by external id goes through
+type is a 422, and a 429 or a 5xx is retried. Every refusal from the server is a problem
+document of type `datapoint-block-rejected`, so branch on its `reason` extension
+(`unknown-timeseries`, `value-type-mismatch`, `too-many-in-flight`, …) rather than on
+`problem_slug()`. Resolving by external id goes through
 `/timeseries/byids`, so the caller needs read access on the dataset as well as write access.
 The durable spool does not cover this path. `binary::FrameWriter` is public for producers that
 build frames themselves.

src/generic.rs

@@ -865,6 +865,7 @@ pub trait ApiServiceProvider {
                 ResponseError {
                     status: response.status(),
                     message: err.to_string(),
+                    content_type: None,
                 }
             });
         }

src/timeseries/binary.rs

@@ -737,16 +737,22 @@ fn unprocessable(message: String) -> ResponseError {
     ResponseError {
         status: StatusCode::UNPROCESSABLE_ENTITY,
         message,
+        content_type: None,
     }
 }
 
 /// The server rejected the request because the series named in a frame no longer match what the
 /// client resolved: unknown after a delete, or renamed since.
 fn is_stale_series_rejection(error: &ResponseError) -> bool {
-    let status = error.get_status();
-    (status == StatusCode::NOT_FOUND || status == StatusCode::UNPROCESSABLE_ENTITY)
-        && (error.message.contains("unknown-timeseries")
-            || error.message.contains("external-id-mismatch"))
+    let Some(problem) = error.problem() else {
+        return false;
+    };
+    // Every binary refusal shares this one type; what went wrong is in `reason`.
+    problem.slug() == Some("datapoint-block-rejected")
+        && matches!(
+            problem.extensions.get("reason").and_then(|reason| reason.as_str()),
+            Some("unknown-timeseries" | "external-id-mismatch")
+        )
 }
 
 impl TimeSeriesService {
@@ -931,6 +937,7 @@ impl TimeSeriesService {
             return Err(ResponseError {
                 status: StatusCode::NOT_FOUND,
                 message: format!("Could not find following timeseries: {}", missing.join(", ")),
+                content_type: None,
             });
         }
         Ok(resolved)
@@ -964,6 +971,44 @@ mod tests {
         (batches, schema)
     }
 
+    #[test]
+    fn only_a_stale_series_problem_rebuilds_the_request() {
+        let error = |status: StatusCode, body: &str| ResponseError {
+            status,
+            message: body.to_string(),
+            content_type: Some("application/problem+json".to_string()),
+        };
+        let rejected = |reason: &str| {
+            format!(
+                r#"{{"type":"https://intellistream.ai/errors/datapoint-block-rejected","title":"Datapoint block rejected","reason":"{reason}","timeseriesIds":[3]}}"#
+            )
+        };
+
+        assert!(is_stale_series_rejection(&error(
+            StatusCode::NOT_FOUND,
+            &rejected("unknown-timeseries")
+        )));
+        assert!(is_stale_series_rejection(&error(
+            StatusCode::UNPROCESSABLE_ENTITY,
+            &rejected("external-id-mismatch")
+        )));
+        assert!(!is_stale_series_rejection(&error(
+            StatusCode::UNPROCESSABLE_ENTITY,
+            &rejected("value-type-mismatch")
+        )));
+        assert!(!is_stale_series_rejection(&error(
+            StatusCode::NOT_FOUND,
+            r#"{"type":"https://intellistream.ai/errors/not-found","reason":"unknown-timeseries"}"#
+        )));
+        // The SDK's own 404 names the series it could not resolve, and an external id can spell a
+        // reason: matching on the body text retried this.
+        assert!(!is_stale_series_rejection(&ResponseError {
+            status: StatusCode::NOT_FOUND,
+            message: "Could not find following timeseries: unknown-timeseries-pump".to_string(),
+            content_type: None,
+        }));
+    }
+
     #[test]
     fn float_frame_is_sorted_deduplicated_and_readable_by_arrow() {
         let mut writer = FrameWriter::new(DatapointValueType::Float);

src/timeseries/test.rs

@@ -1573,6 +1573,54 @@ mod tests {
         Ok(())
     }
 
+    /// Recreating a series under the same external id gives it a new id, so the server refuses the
+    /// one this service cached as `unknown-timeseries`; the call must re-resolve and succeed.
+    #[tokio::test]
+    async fn test_insert_datapoints_binary_re_resolves_a_recreated_series() -> Result<(), Box<dyn std::error::Error>> {
+        let api_service = create_api_service();
+        let ext_id = unique_id("ts_binary_recreated");
+        let mut ts_cleanup = cleanup_timeseries(vec![ext_id.clone()]);
+
+        let mut ts_collection = DataWrapper::new();
+        ts_collection.add_item(
+            TimeSeries::builder()
+                .set_external_id(&ext_id)
+                .set_name(&ext_id)
+                .set_unit("celsius")
+                .set_value_type("float")
+                .clone(),
+        );
+        let mut data_request: DataWrapper<DatapointsCollection<DatapointString>> = DataWrapper::new();
+        let mut dp_collection = DatapointsCollection::from_external_id(&ext_id);
+        dp_collection.datapoints = vec![
+            DatapointString::from_datetime(Utc.with_ymd_and_hms(2025, 1, 1, 0, 0, 0).unwrap(), "42.0"),
+        ];
+        data_request.add_item(dp_collection);
+
+        api_service.time_series.create(&ts_collection).await.expect("could not create the series");
+        api_service
+            .time_series
+            .insert_datapoints_binary(&data_request, &BinaryIngestOptions::default())
+            .await
+            .expect("the first binary insert failed");
+
+        delete_timeseries(&api_service, &[&ext_id]).await;
+        api_service.time_series.create(&ts_collection).await.expect("could not recreate the series");
+
+        match api_service
+            .time_series
+            .insert_datapoints_binary(&data_request, &BinaryIngestOptions::default())
+            .await
+        {
+            Ok(r) => assert_eq!(r.get_http_status_code().unwrap(), StatusCode::NO_CONTENT.as_u16()),
+            Err(e) => panic!("the cached id was not re-resolved: {}: {}", e.get_status(), e.get_message()),
+        }
+
+        delete_timeseries(&api_service, &[&ext_id]).await;
+        ts_cleanup.disarm();
+        Ok(())
+    }
+
     fn validate_data_insertion(result: Result<DataWrapper<String>, ResponseError>) {
         match result {
             Ok(r) => {