#![allow(deprecated)]
#![allow(clippy::module_inception)]
#![allow(clippy::upper_case_acronyms)]
#![allow(clippy::large_enum_variant)]
#![allow(clippy::wrong_self_convention)]
#![allow(clippy::should_implement_trait)]
#![allow(clippy::disallowed_names)]
#![allow(clippy::vec_init_then_push)]
#![allow(clippy::type_complexity)]
#![allow(clippy::needless_return)]
#![allow(clippy::derive_partial_eq_without_eq)]
#![allow(clippy::result_large_err)]
#![allow(rustdoc::bare_urls)]
#![warn(missing_docs)]
//! **Please Note: The SDK is currently in Developer Preview and is intended strictly for
//! feedback purposes only. Do not use this SDK for production workloads.**
//!
//! AWS Data Pipeline configures and manages a data-driven workflow called a pipeline. AWS Data Pipeline handles the details of scheduling and ensuring that data dependencies are met so that your application can focus on processing the data.
//!
//! AWS Data Pipeline provides a JAR implementation of a task runner called AWS Data Pipeline Task Runner. AWS Data Pipeline Task Runner provides logic for common data management scenarios, such as performing database queries and running data analysis using Amazon Elastic MapReduce (Amazon EMR). You can use AWS Data Pipeline Task Runner as your task runner, or you can write your own task runner to provide custom data management.
//!
//! AWS Data Pipeline implements two main sets of functionality. Use the first set to create a pipeline and define data sources, schedules, dependencies, and the transforms to be performed on the data. Use the second set in your task runner application to receive the next task ready for processing. The logic for performing the task, such as querying the data, running data analysis, or converting the data from one format to another, is contained within the task runner. The task runner performs the task assigned to it by the web service, reporting progress to the web service as it does so. When the task is done, the task runner reports the final success or failure of the task to the web service.
//!
//! ## Getting Started
//!
//! > Examples are available for many services and operations, check out the
//! > [examples folder in GitHub](https://github.com/awslabs/aws-sdk-rust/tree/main/examples).
//!
//! The SDK provides one crate per AWS service. You must add [Tokio](https://crates.io/crates/tokio)
//! as a dependency within your Rust project to execute asynchronous code. To add `aws-sdk-datapipeline` to
//! your project, add the following to your **Cargo.toml** file:
//!
//! ```toml
//! [dependencies]
//! aws-config = "0.55.1"
//! aws-sdk-datapipeline = "0.26.0"
//! tokio = { version = "1", features = ["full"] }
//! ```
//!
//! Then in code, a client can be created with the following:
//!
//! ```rust,no_run
//! use aws_sdk_datapipeline as datapipeline;
//!
//! #[tokio::main]
//! async fn main() -> Result<(), datapipeline::Error> {
//!     let config = aws_config::load_from_env().await;
//!     let client = datapipeline::Client::new(&config);
//!
//!     // ... make some calls with the client
//!
//!     Ok(())
//! }
//! ```
//!
//! See the [client documentation](https://docs.rs/aws-sdk-datapipeline/latest/aws_sdk_datapipeline/client/struct.Client.html)
//! for information on what calls can be made, and the inputs and outputs for each of those calls.
//!
//! ## Using the SDK
//!
//! Until the SDK is released, we will be adding information about using the SDK to the
//! [Developer Guide](https://docs.aws.amazon.com/sdk-for-rust/latest/dg/welcome.html). Feel free to suggest
//! additional sections for the guide by opening an issue and describing what you are trying to do.
//!
//! ## Getting Help
//!
//! * [GitHub discussions](https://github.com/awslabs/aws-sdk-rust/discussions) - For ideas, RFCs & general questions
//! * [GitHub issues](https://github.com/awslabs/aws-sdk-rust/issues/new/choose) - For bug reports & feature requests
//! * [Generated Docs (latest version)](https://awslabs.github.io/aws-sdk-rust/)
//! * [Usage examples](https://github.com/awslabs/aws-sdk-rust/tree/main/examples)
//!
//!
//! # Crate Organization
//!
//! The entry point for most customers will be [`Client`], which exposes one method for each API
//! offered by AWS Data Pipeline. The return value of each of these methods is a "fluent builder",
//! where the different inputs for that API are added by builder-style function call chaining,
//! followed by calling `send()` to get a [`Future`](std::future::Future) that will result in
//! either a successful output or a [`SdkError`](crate::error::SdkError).
//!
//! Some of these API inputs may be structs or enums to provide more complex structured information.
//! These structs and enums live in [`types`](crate::types). There are some simpler types for
//! representing data such as date times or binary blobs that live in [`primitives`](crate::primitives).
//!
//! All types required to configure a client via the [`Config`](crate::Config) struct live
//! in [`config`](crate::config).
//!
//! The [`operation`](crate::operation) module has a submodule for every API, and in each submodule
//! is the input, output, and error type for that API, as well as builders to construct each of those.
//!
//! There is a top-level [`Error`](crate::Error) type that encompasses all the errors that the
//! client can return. Any other error type can be converted to this `Error` type via the
//! [`From`](std::convert::From) trait.
//!
//! The other modules within this crate are not required for normal usage.

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use error_meta::Error;

#[doc(inline)]
pub use config::Config;

/// Client for calling AWS Data Pipeline.
/// ## Constructing a `Client`
///
/// A [`Config`] is required to construct a client. For most use cases, the [`aws-config`]
/// crate should be used to automatically resolve this config using
/// [`aws_config::load_from_env()`], since this will resolve an [`SdkConfig`] which can be shared
/// across multiple different AWS SDK clients. This config resolution process can be customized
/// by calling [`aws_config::from_env()`] instead, which returns a [`ConfigLoader`] that uses
/// the [builder pattern] to customize the default config.
///
/// In the simplest case, creating a client looks as follows:
/// ```rust,no_run
/// # async fn wrapper() {
/// let config = aws_config::load_from_env().await;
/// let client = aws_sdk_datapipeline::Client::new(&config);
/// # }
/// ```
///
/// Occasionally, SDKs may have additional service-specific that can be set on the [`Config`] that
/// is absent from [`SdkConfig`], or slightly different settings for a specific client may be desired.
/// The [`Config`] struct implements `From<&SdkConfig>`, so setting these specific settings can be
/// done as follows:
///
/// ```rust,no_run
/// # async fn wrapper() {
/// let sdk_config = aws_config::load_from_env().await;
/// let config = aws_sdk_datapipeline::config::Builder::from(&sdk_config)
/// # /*
///     .some_service_specific_setting("value")
/// # */
///     .build();
/// # }
/// ```
///
/// See the [`aws-config` docs] and [`Config`] for more information on customizing configuration.
///
/// _Note:_ Client construction is expensive due to connection thread pool initialization, and should
/// be done once at application start-up.
///
/// [`Config`]: crate::Config
/// [`ConfigLoader`]: https://docs.rs/aws-config/*/aws_config/struct.ConfigLoader.html
/// [`SdkConfig`]: https://docs.rs/aws-config/*/aws_config/struct.SdkConfig.html
/// [`aws-config` docs]: https://docs.rs/aws-config/*
/// [`aws-config`]: https://crates.io/crates/aws-config
/// [`aws_config::from_env()`]: https://docs.rs/aws-config/*/aws_config/fn.from_env.html
/// [`aws_config::load_from_env()`]: https://docs.rs/aws-config/*/aws_config/fn.load_from_env.html
/// [builder pattern]: https://rust-lang.github.io/api-guidelines/type-safety.html#builders-enable-construction-of-complex-values-c-builder
/// # Using the `Client`
///
/// A client has a function for every operation that can be performed by the service.
/// For example, the [`ActivatePipeline`](crate::operation::activate_pipeline) operation has
/// a [`Client::activate_pipeline`], function which returns a builder for that operation.
/// The fluent builder ultimately has a `call()` function that returns an async future that
/// returns a result, as illustrated below:
///
/// ```rust,ignore
/// let result = client.activate_pipeline()
///     .pipeline_id("example")
///     .call()
///     .await;
/// ```
///
/// The underlying HTTP requests that get made by this can be modified with the `customize_operation`
/// function on the fluent builder. See the [`customize`](crate::client::customize) module for more
/// information.
pub mod client;

/// Configuration for AWS Data Pipeline.
pub mod config;

/// Endpoint resolution functionality.
pub mod endpoint;

/// Common errors and error handling utilities.
pub mod error;

mod error_meta;

/// Information about this crate.
pub mod meta;

/// All operations that this crate can perform.
pub mod operation;

/// Primitives such as `Blob` or `DateTime` used by other types.
pub mod primitives;

/// Data structures used by operation inputs/outputs.
pub mod types;

///
pub mod middleware;

///
mod no_credentials;

mod lens;

pub(crate) mod protocol_serde;

mod endpoint_lib;

mod json_errors;

#[doc(inline)]
pub use client::Client;