Écrire des tests pour les opérations de longue durée

Les bibliothèques clientes Google Cloud pour Rust fournissent des assistants qui simplifient l'interaction avec les opérations de longue durée (LRO). Pour simuler le comportement des LRO dans les tests unitaires, il faut comprendre les détails sous-jacents que ces assistants masquent. Ce guide vous explique comment écrire des tests unitaires pour l'interrogation automatique et manuelle des LRO, y compris pour les scénarios d'erreur.

Prérequis

Ce guide part du principe que vous connaissez les guides suivants :

• Travailler avec des opérations de longue durée
• Écrire des tests à l'aide d'un client fictif

Tester la détection automatique

Supposons que le code de votre application attende lro::Poller::until_done() (interrogation automatique) :

// An example application function that automatically polls.
//
// It starts an LRO, awaits the result, and processes it.
pub async fn my_automatic_poller(
    client: &speech::client::Speech,
    project_id: &str,
) -> Result<Option<wkt::Duration>> {
    use google_cloud_lro::Poller;
    client
        .batch_recognize()
        .set_recognizer(format!(
            "projects/{project_id}/locations/global/recognizers/_"
        ))
        .poller()
        .until_done()
        .await
        .map(|r| r.total_billed_duration)
}

Étant donné que l'application n'utilise que le résultat final de l'opération de longue durée, vous n'avez pas besoin de tester la façon dont elle gère les résultats d'interrogation intermédiaires. Votre test peut renvoyer le résultat final de la LRO directement à partir du simulacre.

Créer le longrunning::model::Operation

Supposons que vous souhaitiez que l'appel renvoie la réponse suivante :

fn expected_duration() -> Option<wkt::Duration> {
    Some(wkt::Duration::clamp(100, 0))
}

fn expected_response() -> BatchRecognizeResponse {
    BatchRecognizeResponse::new().set_or_clear_total_billed_duration(expected_duration())
}

Le bouchon renvoie un longrunning::model::Operation plutôt qu'un BatchRecognizeResponse. Empaquetez la réponse attendue dans Operation::result :

fn make_finished_operation(response: &BatchRecognizeResponse) -> Result<Response<Operation>> {
    let any = wkt::Any::from_msg(response).expect("test message should succeed");
    let operation = Operation::new()
        .set_done(true)
        .set_result(OperationResult::Response(any.into()));
    Ok(Response::from(operation))
}

Définissez le champ done sur true pour indiquer à Poller que l'opération est terminée, ce qui met fin à la boucle d'interrogation :

.set_done(true)

Écrire le test

1. Définissez la structure fictive, qui implémente le trait speech::stub::Speech :

   mockall::mock! {
       #[derive(Debug)]
       Speech {}
       impl speech::stub::Speech for Speech {
           async fn batch_recognize(&self, req: BatchRecognizeRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
       }
   }

2. Dans le test, créez le simulacre et définissez les attentes correspondantes :

   let mut mock = MockSpeech::new();
   mock.expect_batch_recognize()
       .return_once(|_, _| make_finished_operation(&expected_response()));

3. Créez un client à partir du simulacre, appelez la fonction et vérifiez la réponse :

   // Create a client, implemented by our mock.
   let client = speech::client::Speech::from_stub(mock);
   
   // Call our function which automatically polls.
   let billed_duration = my_automatic_poller(&client, "my-project").await?;
   
   // Verify the final result of the LRO.
   assert_eq!(billed_duration, expected_duration());

Tester l'interrogation manuelle avec des métadonnées intermédiaires

Supposons que le code de votre application interroge manuellement et traite les mises à jour partielles :

pub struct BatchRecognizeResult {
    pub progress_updates: Vec<i32>,
    pub billed_duration: Result<Option<wkt::Duration>>,
}

// An example application function that manually polls.
//
// It starts an LRO. It consolidates the polling results, whether full or
// partial.
//
// In this case, it is the `BatchRecognize` RPC. If we get a partial update,
// we extract the `progress_percent` field. If we get a final result, we
// extract the `total_billed_duration` field.
pub async fn my_manual_poller(
    client: &speech::client::Speech,
    project_id: &str,
) -> BatchRecognizeResult {
    use google_cloud_lro::{Poller, PollingResult};
    let mut progress_updates = Vec::new();
    let mut poller = client
        .batch_recognize()
        .set_recognizer(format!(
            "projects/{project_id}/locations/global/recognizers/_"
        ))
        .poller();
    while let Some(p) = poller.poll().await {
        match p {
            PollingResult::Completed(r) => {
                let billed_duration = r.map(|r| r.total_billed_duration);
                return BatchRecognizeResult {
                    progress_updates,
                    billed_duration,
                };
            }
            PollingResult::InProgress(m) => {
                if let Some(metadata) = m {
                    // This is a silly application. Your application likely
                    // performs some task immediately with the partial
                    // update, instead of storing it for after the operation
                    // has completed.
                    progress_updates.push(metadata.progress_percent);
                }
            }
            PollingResult::PollingError(e) => {
                return BatchRecognizeResult {
                    progress_updates,
                    billed_duration: Err(e),
                };
            }
        }
        tokio::time::sleep(std::time::Duration::from_millis(500)).await;
    }

    // We can only get here if `poll()` returns `None`, but it only returns
    // `None` after it returned `PollingResult::Completed`. Therefore this
    // is never reached.
    unreachable!("loop should exit via the `Completed` branch.");
}

Vous pouvez simuler le comportement de l'application lorsqu'elle reçoit des métadonnées intermédiaires en renvoyant des opérations en cours à partir du simulacre.

Créer le longrunning::model::Operation

Le RPC BatchRecognize renvoie des résultats partiels sous la forme d'un speech::model::OperationMetadata. Empaquetez ces métadonnées dans le champ Operation::metadata de l'élément longrunning::model::Operation renvoyé :

fn make_partial_operation(progress: i32) -> Result<Response<Operation>> {
    let metadata = OperationMetadata::new().set_progress_percent(progress);
    let any = wkt::Any::from_msg(&metadata).expect("test message should succeed");
    let operation = Operation::new().set_metadata(any);
    Ok(Response::from(operation))
}

Écrire le test

1. Définissez la structure fictive, qui implémente le trait speech::stub::Speech et remplace get_operation() :

   mockall::mock! {
       #[derive(Debug)]
       Speech {}
       impl speech::stub::Speech for Speech {
           async fn batch_recognize(&self, req: BatchRecognizeRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
           async fn get_operation(&self, req: GetOperationRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
       }
   }

2. Dans le test, créez le simulacre et définissez des attentes pour qu'il renvoie des résultats partiels (25 %, 50 %, 75 %), suivis du résultat final :

   let mut seq = mockall::Sequence::new();
   let mut mock = MockSpeech::new();
   mock.expect_batch_recognize()
       .once()
       .in_sequence(&mut seq)
       .returning(|_, _| make_partial_operation(25));
   mock.expect_get_operation()
       .once()
       .in_sequence(&mut seq)
       .returning(|_, _| make_partial_operation(50));
   mock.expect_get_operation()
       .once()
       .in_sequence(&mut seq)
       .returning(|_, _| make_partial_operation(75));
   mock.expect_get_operation()
       .once()
       .in_sequence(&mut seq)
       .returning(|_, _| make_finished_operation(&expected_response()));

   Notez les détails suivants sur la configuration des attentes :

   • RPC initiales et ultérieures : la première attente est définie sur batch_recognize(), tandis que toutes les attentes ultérieures sont définies sur get_operation(). Le RPC BatchRecognize initial démarre l'opération de longue durée sur le serveur et renvoie un identifiant d'opération dans le champ name (omis du code de test par souci de concision). À partir de ce moment, la bibliothèque cliente interroge l'état de cette LRO à l'aide du RPC GetOperation.
   • Ordre des appels : les attentes sont enregistrées dans un Sequence. Cela permet à mockall de vérifier l'ordre des appels et de déterminer quelle attente expect_get_operation correspond à chaque interrogation.

3. Créez un client à partir du simulacre, appelez la fonction et vérifiez la réponse :

   // Create a client, implemented by our mock.
   let client = speech::client::Speech::from_stub(mock);
   
   // Call our function which manually polls.
   let result = my_manual_poller(&client, "my-project").await;
   
   // Verify the partial metadata updates, and the final result.
   assert_eq!(result.progress_updates, [25, 50, 75]);
   assert_eq!(result.billed_duration?, expected_duration());

Simuler des erreurs

Des erreurs peuvent se produire à plusieurs moments au cours d'une LRO.

Si votre application utilise l'interrogation automatique, toutes les sources d'erreur sont équivalentes : until_done() renvoie l'erreur dans Result, quelle que soit son origine. Simuler une erreur lors du démarrage d'une LRO produit le test le plus simple.

Remarque : Un client créé à partir d'un bouchon ne dispose pas de stratégie de nouvelle tentative ni d'interrogation. Dans tous les cas, la boucle d'interrogation se termine à la première erreur, même si l'erreur est normalement considérée comme temporaire.

Simuler une erreur lors du démarrage d'une opération de longue durée

Pour simuler une erreur lors du démarrage d'une LRO, configurez la requête initiale pour qu'elle échoue avec une erreur :

mock.expect_batch_recognize().return_once(|_, _| {
    use gax::error::Error;
    use gax::error::rpc::{Code, Status};
    let status = Status::default()
        .set_code(Code::Aborted)
        .set_message("Resource exhausted");
    Err(Error::service(status))
});

Pour l'interrogation manuelle, la branche PollingResult::Completed reçoit l'erreur liée au démarrage de la LRO, ce qui met fin à la boucle d'interrogation :

PollingResult::Completed(r) => {

Simuler une LRO entraînant une erreur

Pour simuler une LRO qui échoue après avoir renvoyé des métadonnées intermédiaires, renvoyez l'erreur dans le longrunning::model::Operation final :

fn make_failed_operation(status: rpc::model::Status) -> Result<Response<Operation>> {
    let operation = Operation::new()
        .set_done(true)
        .set_result(OperationResult::Error(status.into()));
    Ok(Response::from(operation))
}

Définissez les attentes pour renvoyer l'échec de Operation à partir de get_operation :

mock.expect_get_operation()
    .once()
    .in_sequence(&mut seq)
    .returning(|_, _| {
        // This is a common error for `Create*` RPCs, which are often
        // LROs. It is less applicable to `BatchRecognize` in practice.
        let status = rpc::model::Status::default()
            .set_code(gax::error::rpc::Code::AlreadyExists as i32)
            .set_message("resource already exists");
        make_failed_operation(status)
    });

Dans l'interrogation manuelle, la branche PollingResult::Completed reçoit le résultat de l'erreur, ce qui met fin à la boucle d'interrogation :

PollingResult::Completed(r) => {

Simuler une erreur d'interrogation

Les boucles d'interrogation peuvent également se terminer lorsque la règle d'interrogation est épuisée. Dans ce cas, la bibliothèque cliente ne peut pas déterminer de manière définitive si l'opération de longue durée est terminée.

Si votre application dispose d'une logique personnalisée pour gérer les erreurs d'interrogation, vous pouvez la tester en renvoyant une erreur directement à partir de l'attente get_operation :

mock.expect_get_operation()
    .once()
    .in_sequence(&mut seq)
    .returning(|_, _| {
        use gax::error::Error;
        use gax::error::rpc::{Code, Status};
        let status = Status::default()
            .set_code(Code::Aborted)
            .set_message("Operation was aborted");
        Err(Error::service(status))
    });

Dans l'interrogation manuelle, la branche PollingResult::PollingError reçoit l'erreur d'interrogation simulée :

PollingResult::PollingError(e) => {

Code de test complet

Les sections suivantes présentent le code complet des tests décrits dans ce guide.

Détection automatique : test complet

use gax::Result;
use gax::response::Response;
use google_cloud_gax as gax;
use google_cloud_longrunning as longrunning;
use google_cloud_speech_v2 as speech;
use google_cloud_wkt as wkt;
use longrunning::model::Operation;
use longrunning::model::operation::Result as OperationResult;
use speech::model::{BatchRecognizeRequest, BatchRecognizeResponse};

// Example application code that is under test
mod my_application {
    use super::*;

    // An example application function that automatically polls.
    //
    // It starts an LRO, awaits the result, and processes it.
    pub async fn my_automatic_poller(
        client: &speech::client::Speech,
        project_id: &str,
    ) -> Result<Option<wkt::Duration>> {
        use google_cloud_lro::Poller;
        client
            .batch_recognize()
            .set_recognizer(format!(
                "projects/{project_id}/locations/global/recognizers/_"
            ))
            .poller()
            .until_done()
            .await
            .map(|r| r.total_billed_duration)
    }
}

#[cfg(test)]
mod tests {
    use super::my_application::*;
    use super::*;

    mockall::mock! {
        #[derive(Debug)]
        Speech {}
        impl speech::stub::Speech for Speech {
            async fn batch_recognize(&self, req: BatchRecognizeRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
        }
    }

    fn expected_duration() -> Option<wkt::Duration> {
        Some(wkt::Duration::clamp(100, 0))
    }

    fn expected_response() -> BatchRecognizeResponse {
        BatchRecognizeResponse::new().set_or_clear_total_billed_duration(expected_duration())
    }

    fn make_finished_operation(response: &BatchRecognizeResponse) -> Result<Response<Operation>> {
        let any = wkt::Any::from_msg(response).expect("test message should succeed");
        let operation = Operation::new()
            .set_done(true)
            .set_result(OperationResult::Response(any.into()));
        Ok(Response::from(operation))
    }

    #[tokio::test]
    async fn automatic_polling() -> Result<()> {
        // Create a mock, and set expectations on it.
        let mut mock = MockSpeech::new();
        mock.expect_batch_recognize()
            .return_once(|_, _| make_finished_operation(&expected_response()));

        // Create a client, implemented by our mock.
        let client = speech::client::Speech::from_stub(mock);

        // Call our function which automatically polls.
        let billed_duration = my_automatic_poller(&client, "my-project").await?;

        // Verify the final result of the LRO.
        assert_eq!(billed_duration, expected_duration());

        Ok(())
    }
}

Sondage manuel avec métadonnées intermédiaires : test complet

use gax::Result;
use gax::response::Response;
use google_cloud_gax as gax;
use google_cloud_longrunning as longrunning;
use google_cloud_speech_v2 as speech;
use google_cloud_wkt as wkt;
use longrunning::model::operation::Result as OperationResult;
use longrunning::model::{GetOperationRequest, Operation};
use speech::model::{BatchRecognizeRequest, BatchRecognizeResponse, OperationMetadata};

// Example application code that is under test
mod my_application {
    use super::*;

    pub struct BatchRecognizeResult {
        pub progress_updates: Vec<i32>,
        pub billed_duration: Result<Option<wkt::Duration>>,
    }

    // An example application function that manually polls.
    //
    // It starts an LRO. It consolidates the polling results, whether full or
    // partial.
    //
    // In this case, it is the `BatchRecognize` RPC. If we get a partial update,
    // we extract the `progress_percent` field. If we get a final result, we
    // extract the `total_billed_duration` field.
    pub async fn my_manual_poller(
        client: &speech::client::Speech,
        project_id: &str,
    ) -> BatchRecognizeResult {
        use google_cloud_lro::{Poller, PollingResult};
        let mut progress_updates = Vec::new();
        let mut poller = client
            .batch_recognize()
            .set_recognizer(format!(
                "projects/{project_id}/locations/global/recognizers/_"
            ))
            .poller();
        while let Some(p) = poller.poll().await {
            match p {
                PollingResult::Completed(r) => {
                    let billed_duration = r.map(|r| r.total_billed_duration);
                    return BatchRecognizeResult {
                        progress_updates,
                        billed_duration,
                    };
                }
                PollingResult::InProgress(m) => {
                    if let Some(metadata) = m {
                        // This is a silly application. Your application likely
                        // performs some task immediately with the partial
                        // update, instead of storing it for after the operation
                        // has completed.
                        progress_updates.push(metadata.progress_percent);
                    }
                }
                PollingResult::PollingError(e) => {
                    return BatchRecognizeResult {
                        progress_updates,
                        billed_duration: Err(e),
                    };
                }
            }
            tokio::time::sleep(std::time::Duration::from_millis(500)).await;
        }

        // We can only get here if `poll()` returns `None`, but it only returns
        // `None` after it returned `PollingResult::Completed`. Therefore this
        // is never reached.
        unreachable!("loop should exit via the `Completed` branch.");
    }
}

#[cfg(test)]
mod tests {
    use super::my_application::*;
    use super::*;

    mockall::mock! {
        #[derive(Debug)]
        Speech {}
        impl speech::stub::Speech for Speech {
            async fn batch_recognize(&self, req: BatchRecognizeRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
            async fn get_operation(&self, req: GetOperationRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
        }
    }

    fn expected_duration() -> Option<wkt::Duration> {
        Some(wkt::Duration::clamp(100, 0))
    }

    fn expected_response() -> BatchRecognizeResponse {
        BatchRecognizeResponse::new().set_or_clear_total_billed_duration(expected_duration())
    }

    fn make_finished_operation(
        response: &BatchRecognizeResponse,
    ) -> Result<gax::response::Response<Operation>> {
        let any = wkt::Any::from_msg(response).expect("test message should succeed");
        let operation = Operation::new()
            .set_done(true)
            .set_result(OperationResult::Response(any.into()));
        Ok(Response::from(operation))
    }

    fn make_partial_operation(progress: i32) -> Result<Response<Operation>> {
        let metadata = OperationMetadata::new().set_progress_percent(progress);
        let any = wkt::Any::from_msg(&metadata).expect("test message should succeed");
        let operation = Operation::new().set_metadata(any);
        Ok(Response::from(operation))
    }

    #[tokio::test]
    async fn manual_polling_with_metadata() -> Result<()> {
        let mut seq = mockall::Sequence::new();
        let mut mock = MockSpeech::new();
        mock.expect_batch_recognize()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(25));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(50));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(75));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_finished_operation(&expected_response()));

        // Create a client, implemented by our mock.
        let client = speech::client::Speech::from_stub(mock);

        // Call our function which manually polls.
        let result = my_manual_poller(&client, "my-project").await;

        // Verify the partial metadata updates, and the final result.
        assert_eq!(result.progress_updates, [25, 50, 75]);
        assert_eq!(result.billed_duration?, expected_duration());

        Ok(())
    }
}

Simuler des erreurs : tests complets

use gax::Result;
use gax::response::Response;
use google_cloud_gax as gax;
use google_cloud_longrunning as longrunning;
use google_cloud_rpc as rpc;
use google_cloud_speech_v2 as speech;
use google_cloud_wkt as wkt;
use longrunning::model::operation::Result as OperationResult;
use longrunning::model::{GetOperationRequest, Operation};
use speech::model::{BatchRecognizeRequest, OperationMetadata};

// Example application code that is under test
mod my_application {
    use super::*;

    pub struct BatchRecognizeResult {
        pub progress_updates: Vec<i32>,
        pub billed_duration: Result<Option<wkt::Duration>>,
    }

    // An example application function that manually polls.
    //
    // It starts an LRO. It consolidates the polling results, whether full or
    // partial.
    //
    // In this case, it is the `BatchRecognize` RPC. If we get a partial update,
    // we extract the `progress_percent` field. If we get a final result, we
    // extract the `total_billed_duration` field.
    pub async fn my_manual_poller(
        client: &speech::client::Speech,
        project_id: &str,
    ) -> BatchRecognizeResult {
        use google_cloud_lro::{Poller, PollingResult};
        let mut progress_updates = Vec::new();
        let mut poller = client
            .batch_recognize()
            .set_recognizer(format!(
                "projects/{project_id}/locations/global/recognizers/_"
            ))
            .poller();
        while let Some(p) = poller.poll().await {
            match p {
                PollingResult::Completed(r) => {
                    let billed_duration = r.map(|r| r.total_billed_duration);
                    return BatchRecognizeResult {
                        progress_updates,
                        billed_duration,
                    };
                }
                PollingResult::InProgress(m) => {
                    if let Some(metadata) = m {
                        // This is a silly application. Your application likely
                        // performs some task immediately with the partial
                        // update, instead of storing it for after the operation
                        // has completed.
                        progress_updates.push(metadata.progress_percent);
                    }
                }
                PollingResult::PollingError(e) => {
                    return BatchRecognizeResult {
                        progress_updates,
                        billed_duration: Err(e),
                    };
                }
            }
            tokio::time::sleep(std::time::Duration::from_millis(500)).await;
        }

        // We can only get here if `poll()` returns `None`, but it only returns
        // `None` after it returned `PollingResult::Completed`. Therefore this
        // is never reached.
        unreachable!("loop should exit via the `Completed` branch.");
    }
}

#[cfg(test)]
mod tests {
    use super::my_application::*;
    use super::*;

    mockall::mock! {
        #[derive(Debug)]
        Speech {}
        impl speech::stub::Speech for Speech {
            async fn batch_recognize(&self, req: BatchRecognizeRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
            async fn get_operation(&self, req: GetOperationRequest, _options: gax::options::RequestOptions) -> Result<Response<Operation>>;
        }
    }

    fn make_partial_operation(progress: i32) -> Result<Response<Operation>> {
        let metadata = OperationMetadata::new().set_progress_percent(progress);
        let any = wkt::Any::from_msg(&metadata).expect("test message should succeed");
        let operation = Operation::new().set_metadata(any);
        Ok(Response::from(operation))
    }

    fn make_failed_operation(status: rpc::model::Status) -> Result<Response<Operation>> {
        let operation = Operation::new()
            .set_done(true)
            .set_result(OperationResult::Error(status.into()));
        Ok(Response::from(operation))
    }

    #[tokio::test]
    async fn error_starting_lro() -> Result<()> {
        let mut mock = MockSpeech::new();
        mock.expect_batch_recognize().return_once(|_, _| {
            use gax::error::Error;
            use gax::error::rpc::{Code, Status};
            let status = Status::default()
                .set_code(Code::Aborted)
                .set_message("Resource exhausted");
            Err(Error::service(status))
        });

        // Create a client, implemented by our mock.
        let client = speech::client::Speech::from_stub(mock);

        // Call our function which manually polls.
        let result = my_manual_poller(&client, "my-project").await;

        // Verify the the final result.
        assert!(
            result.billed_duration.is_err(),
            "{:?}",
            result.billed_duration
        );

        Ok(())
    }

    #[tokio::test]
    async fn lro_ending_in_error() -> Result<()> {
        let mut seq = mockall::Sequence::new();
        let mut mock = MockSpeech::new();
        mock.expect_batch_recognize()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(25));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(50));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(75));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| {
                // This is a common error for `Create*` RPCs, which are often
                // LROs. It is less applicable to `BatchRecognize` in practice.
                let status = rpc::model::Status::default()
                    .set_code(gax::error::rpc::Code::AlreadyExists as i32)
                    .set_message("resource already exists");
                make_failed_operation(status)
            });

        // Create a client, implemented by our mock.
        let client = speech::client::Speech::from_stub(mock);

        // Call our function which manually polls.
        let result = my_manual_poller(&client, "my-project").await;

        // Verify the partial metadata updates, and the final result.
        assert_eq!(result.progress_updates, [25, 50, 75]);
        assert!(
            result.billed_duration.is_err(),
            "{:?}",
            result.billed_duration
        );

        Ok(())
    }

    #[tokio::test]
    async fn polling_loop_error() -> Result<()> {
        let mut seq = mockall::Sequence::new();
        let mut mock = MockSpeech::new();
        mock.expect_batch_recognize()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| make_partial_operation(25));
        mock.expect_get_operation()
            .once()
            .in_sequence(&mut seq)
            .returning(|_, _| {
                use gax::error::Error;
                use gax::error::rpc::{Code, Status};
                let status = Status::default()
                    .set_code(Code::Aborted)
                    .set_message("Operation was aborted");
                Err(Error::service(status))
            });

        // Create a client, implemented by our mock.
        let client = speech::client::Speech::from_stub(mock);

        // Call our function which manually polls.
        let result = my_manual_poller(&client, "my-project").await;

        // Verify the partial metadata updates, and the final result.
        assert_eq!(result.progress_updates, [25]);
        assert!(
            result.billed_duration.is_err(),
            "{:?}",
            result.billed_duration
        );

        Ok(())
    }
}