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//! # Leaky Bucket Rate-Limiting (as a meter) in Rust
//!
//! This crate provides generic rate-limiting interfaces and implements a
//! few rate-limiting algorithms. The generic rate-limiting interfaces
//! are extendable to persistence-based rate limiting schemes such as
//! databases.
//!
//! This crate currently provides in-memory implementations of a by-key
//! (limits enforced per key, e.g. an IP address or a customer ID) and a
//! simple (one limit per object) state tracker.
//!
//! ## Interface
//!
//! This crate implements two "serious" rate-limiting/traffic-shaping
//! algorithms:
//! [GCRA](https://en.wikipedia.org/wiki/Generic_cell_rate_algorithm)
//! and a [Leaky
//! Bucket](https://en.wikipedia.org/wiki/Leaky_bucket#As_a_meter). An
//! "unserious" implementation is provided also: The
//! [`Allower`](example_algorithms/struct.Allower.html), which returns
//! "Yes" to all rate-limiting queries.
//!
//! The Generic Cell Rate Algorithm can be used by in an in-memory
//! rate limiter like so:
//!
//! ``` rust
//! use std::num::NonZeroU32;
//! use ratelimit_meter::{DirectRateLimiter, GCRA};
//!
//! # #[macro_use] extern crate nonzero_ext;
//! # extern crate ratelimit_meter;
//! # fn main () {
//! let mut lim = DirectRateLimiter::<GCRA>::per_second(nonzero!(50u32)); // Allow 50 units per second
//! assert_eq!(Ok(()), lim.check());
//! # }
//! ```
//!
//! The rate-limiter interface is intentionally geared towards only
//! providing callers with the information they need to make decisions
//! about what to do with each cell. Deciders return additional
//! information about why a cell should be denied alongside the
//! decision. This allows callers to e.g. provide better error
//! messages to users.
//!
//! As a consequence, the `ratelimit_meter` crate does not provide any
//! facility to wait until a cell would be allowed - if you require
//! this, you should use the
//! [`NonConformance`](struct.NonConformance.html) returned with
//! negative decisions and have the program wait using the method best
//! suited for this, e.g. an event loop.
//!
//! ## Using this crate effectively
//!
//! Many of the parameters in use by this crate are `NonZeroU32` -
//! since they are not very ergonomic to construct from constants
//! using stdlib means, I recommend using the
//! [nonzero_ext](https://crates.io/crates/nonzero_ext) crate, which
//! comes with a macro `nonzero!()`. This macro makes it far easier to
//! construct rate limiters without cluttering your code.
//!
//! ## Rate-limiting Algorithms
//!
//! ### Design and implementation of GCRA
//!
//! The GCRA limits the rate of cells by determining when the "next"
//! cell is expected to arrive; any cells that arrive before that time
//! are classified as non-conforming; the methods for checking cells
//! also return an expected arrival time for these cells, so that
//! callers can choose to wait (adding jitter), or reject the cell.
//!
//! Since using the GCRA results in a much smoother usage pattern, it
//! appears to be very useful for "outgoing" traffic behaviors,
//! e.g. throttling API call rates, or emails sent to a person in a
//! period of time.
//!
//! Unlike token or leaky bucket algorithms, the GCRA assumes that all
//! units of work are of the same "weight", and so allows some
//! optimizations which result in much more concise and fast code (it
//! does not even use multiplication or division in the "hot" path).
//!
//! See [the documentation of the GCRA type](algorithms/gcra/struct.GCRA.html) for
//! more details on its implementation and on trade-offs that apply to
//! it.
//!
//! ### Design and implementation of the leaky bucket
//!
//! In contrast to the GCRA, the leaky bucket algorithm does not place
//! any constraints on the next cell's arrival time: Whenever there is
//! capacity left in the bucket, it can be used. This means that the
//! distribution of "yes" decisions from heavy usage on the leaky
//! bucket rate-limiter will be clustered together. On average, the
//! cell rates of both the GCRA and the leaky bucket will be the same,
//! but in terms of observable behavior, the leaky bucket will appear
//! to allow requests at a more predictable rate.
//!
//! This kind of behavior is usually what people of online APIs expect
//! these days, which makes the leaky bucket a very popular technique
//! for rate-limiting on these kinds of services.
//!
//! The leaky bucket algorithm implemented in this crate is fairly
//! standard: It only updates the bucket fill gauge when a cell is
//! checked, and supports checking "batches" of cells in a single call
//! with no problems.
//!
//! ## Thread-safe operation
//!
//! The in-memory implementations in this crate use parking_lot
//! mutexes to ensure rate-limiting operations can happen safely
//! across threads.
//!
//! Example:
//!
//! ```
//! use std::thread;
//! use std::num::NonZeroU32;
//! use std::time::Duration;
//! use ratelimit_meter::{DirectRateLimiter, GCRA};
//!
//! # #[macro_use] extern crate nonzero_ext;
//! # extern crate ratelimit_meter;
//! # fn main () {
//! // Allow 50 units/second across all threads:
//! let mut lim = DirectRateLimiter::<GCRA>::per_second(nonzero!(50u32));
//! let mut thread_lim = lim.clone();
//! thread::spawn(move || { assert_eq!(Ok(()), thread_lim.check());});
//! assert_eq!(Ok(()), lim.check());
//! # }
//! ```

#![cfg_attr(feature = "cargo-clippy", deny(warnings))]

pub mod algorithms;
pub mod example_algorithms;
pub mod state;
pub mod test_utilities;
mod thread_safety;

extern crate failure;
#[macro_use]
extern crate failure_derive;
extern crate evmap;
#[macro_use]
extern crate nonzero_ext;
extern crate parking_lot;

use failure::Fail;
use std::num::NonZeroU32;

pub use self::algorithms::LeakyBucket;
pub use self::algorithms::NonConformance;
pub use self::algorithms::GCRA;

pub use self::state::DirectRateLimiter;
pub use self::state::KeyedRateLimiter;

/// Gives additional information about the negative outcome of a batch
/// cell decision.
///
/// Since batch queries can be made for batch sizes bigger than the
/// rate limiter parameter could accomodate, there are now two
/// possible negative outcomes:
///
///   * `BatchNonConforming` - the query is valid but the Decider can
///     not accomodate them.
///
///   * `InsufficientCapacity` - the query was invalid as the rate
///     limite parameters can never accomodate the number of cells
///     queried for.
#[derive(Fail, Debug, PartialEq)]
pub enum NegativeMultiDecision<E: Fail> {
    /// A batch of cells (the first argument) is non-conforming and
    /// can not be let through at this time. The second argument gives
    /// information about when that batch of cells might be let
    /// through again (not accounting for thundering herds and other,
    /// simultaneous decisions).
    #[fail(display = "{} cells: {}", _0, _1)]
    BatchNonConforming(u32, E),

    /// The number of cells tested (the first argument) is larger than
    /// the bucket's capacity, which means the decision can never have
    /// a conforming result.
    #[fail(
        display = "bucket does not have enough capacity to accomodate {} cells",
        _0
    )]
    InsufficientCapacity(u32),
}

/// An error that is returned when initializing a rate limiter that is
/// too small to let a single cell through.
#[derive(Fail, Debug)]
#[fail(
    display = "bucket capacity {} too small for a single cell with weight {}",
    capacity,
    cell_weight
)]
pub struct InconsistentCapacity {
    capacity: NonZeroU32,
    cell_weight: NonZeroU32,
}