#![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)]
//! IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight.
//!
//! Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources.
//!
//! IoT Analytics automates the steps required to analyze data from IoT devices. IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can set up the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.
//!
//! ## 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-iotanalytics` to
//! your project, add the following to your **Cargo.toml** file:
//!
//! ```toml
//! [dependencies]
//! aws-config = { version = "1.0.1", features = ["behavior-version-latest"] }
//! aws-sdk-iotanalytics = "1.2.0"
//! tokio = { version = "1", features = ["full"] }
//! ```
//!
//! Then in code, a client can be created with the following:
//!
//! ```rust,no_run
//! use aws_sdk_iotanalytics as iotanalytics;
//!
//! #[::tokio::main]
//! async fn main() -> Result<(), iotanalytics::Error> {
//!     let config = aws_config::load_from_env().await;
//!     let client = aws_sdk_iotanalytics::Client::new(&config);
//!
//!     // ... make some calls with the client
//!
//!     Ok(())
//! }
//! ```
//!
//! See the [client documentation](https://docs.rs/aws-sdk-iotanalytics/latest/aws_sdk_iotanalytics/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 IoT Analytics. 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 IoT Analytics.
/// ## 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_iotanalytics::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_iotanalytics::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 [`BatchPutMessage`](crate::operation::batch_put_message) operation has
/// a [`Client::batch_put_message`], function which returns a builder for that operation.
/// The fluent builder ultimately has a `send()` function that returns an async future that
/// returns a result, as illustrated below:
///
/// ```rust,ignore
/// let result = client.batch_put_message()
///     .channel_name("example")
///     .send()
///     .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 IoT Analytics.
pub mod config;

/// 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;

mod auth_plugin;

pub(crate) mod protocol_serde;

mod serialization_settings;

mod lens;

mod endpoint_lib;

mod json_errors;

mod serde_util;

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