# Fee Estimation

# Overview

LDK provides a FeeEstimator trait which, once implemented, assists in variety of on-chain and off-chain tasks. It's important to note that the FeeEstimator only describes the architectural requirements that must be satisfied to successfully incorporate LDK into your project. It does not, itself, provide the logic or implementation to calculate a feerate.

In LDK, feerates are separated into seven categories. Each category is known as a ConfirmationTarget. We'll provide a brief review of these shortly, but, for now, it's sufficient to understand that these categories represent various scenarios in which we need feerate information. For example, one ConfirmationTarget is ConfirmationTarget::MinAllowedAnchorChannelRemoteFee, which describes the lowest feerate we will allow our channel counterparty to have in an anchor channel.

Feerates and their functionality within LDK can be conceptually separated into on-chain (Bitcoin) and off-chain (Lightning Network) tasks.

# On-Chain

Lightning's security model is dependent on the ability to confirm a claim transaction under a variety of circumstances, such as before a timelock expires. To ensure that LDK is able to confirm claim transactions in a timely manner or bump the fee on an existing transaction, LDK utilizes the FeeEstimator to fetch feerates for high priority transactions. For example, the ConfirmationTarget::OnChainSweep specifies the feerate used when we have funds available on-chain that must be spent before a certain expiry time, beyond which our counterparty could potentially steal them. Additionally, the ConfirmationTarget::OutputSpendingFee is used by the OutputSweeper utility to ensure that, after channel closure, all funds are eventually swept to an onchain address controlled by the user.

# Off-Chain

From an off-chain perspective, the FeeEstimator provides vital information that is used when opening, closing, and operating channels with peers on the Lightning Network. For example, when opening an inbound channel or updating an existing channel with a counterparty, LDK will compare the counterparty's proposed feerate with the minimum feerate that is allowed for that type of channel (ex: anchor or non-anchor channel). If the proposed fee is too low, LDK may return an error and suggest closing the channel. During these operations, LDK will reference the ConfirmationTarget::MinAllowedAnchorChannelRemoteFee and the ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee. Therefore, it's recommended to ensure that the minimum allowable fees are not set too high, thus increasing the risk that a peer's proposed feerate is too low, potentially resulting in a force closure. See the Best Practices section in this documentation for more helpful tips when implementing LDK's FeeEstimator.

Another instance where LDK utilizes the FeeEstimator is during a cooperative channel closure. In this case, LDK references the ConfirmationTarget::ChannelCloseMinimum and ConfirmationTarget::NonAnchorChannelFee to estimate a feerate range, which is then proposed to the counterparty for closing the channel.

# The FeeEstimator

LDK's FeeEstimator trait (seen below) is at the heart of fee estimation within LDK.

You'll notice that it has one required method, get_est_sat_per_1000_weight. This method is referenced throughout LDK to fetch feerate information when performing actions such as opening lightning channels, closing lightning channels, or sweeping funds on-chain. You'll also notice that the get_est_sat_per_1000_weight has one required input: a ConfirmationTarget. The next section will describe the ConfirmationTarget in more detail. For now, it's important to note that the implementation of get_est_sat_per_1000_weight must be completed by the developer. Once completed, this method should return the estimated fee (in sats/KW) for the given ConfirmationTarget.

pub trait FeeEstimator {
	/// Gets estimated satoshis of fee required per 1000 Weight-Units.
	///
	/// LDK will wrap this method and ensure that the value returned is no smaller than 253
	/// (ie 1 satoshi-per-byte rounded up to ensure later round-downs don't put us below 1 satoshi-per-byte).
	///
	/// The following unit conversions can be used to convert to sats/KW:
	///  * satoshis-per-byte * 250
	///  * satoshis-per-kbyte / 4
	fn get_est_sat_per_1000_weight(&self, confirmation_target: ConfirmationTarget) -> u32;
}

# The ConfirmationTarget

The ConfirmationTarget enables the user to define the feerate that LDK will use for a variety of on-chain and off-chain tasks. For a detailed description of each ConfirmationTarget, please visit here (opens new window).

# Best Practices

# Estimating Fees

The end goal is to implement the function get_est_sat_per_1000_weight such that it will return a feerate in sats/KW (satoshis-per-byte * 250) for each of the ConfirmationTarget options. Therefore, the question is: how should we determine the right feerate to provide when get_est_sat_per_1000_weight is called?

A popular approach is to fetch feerate information from a third-party such as mempool.space by sending a GET request to their get-recommended-fees (opens new window) endpoint. Another option is to connect to your own local mempool. Depending on which approach you take, you may get fee estimates that are already separated into categories (ex: high, medium, low), or you may have to request fee estimates with a specific confirmation target in mind (ex: fetching fees for a transaction that you want to be mined within the next 6 blocks). Regardless of your approach, you will ultimately have to map the feerate estimate back to each ConfirmationTarget. To help make this easier, a table has been provided below with recommendations for how you could map each ConfirmationTarget to both a mempool.space fee category and the estimated number of blocks each ConfirmationTarget may represent. Please keep in mind, these are only recommendations. In practice, confirmation targets are influenced by each developer's fee strategy and risk-tolerance and may change accordingly.

ConfirmationTarget mempool.space Category Number of Blocks
OnChainSweep hour_fee 6
MinAllowedAnchorChannelRemoteFee minimum_fee 1008
MinAllowedNonAnchorChannelRemoteFee economy_fee 144
AnchorChannelFee minimum_fee 1008
NonAnchorChannelFee economy_fee 12
ChannelCloseMinimum economy_fee 144
OutputSpendingFee economy_fee 12

NOTE: Setting ConfirmationTarget::MinAllowedAnchorChannelRemoteFee or ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee too high, will increase the risk that a peer's proposed feerate is, comparatively, too low, potentially resulting in a force closure. Similarly, setting ConfirmationTarget::AnchorChannelFee or ConfirmationTarget::NonAnchorChannelFee too low, will increase the risk that your node's proposed feerate is, comparatively, too low, potentially resulting in a force closure.

# General Architecture Approaches

Now that we've seen a few approaches towards retrieving feerate estimates such that we can return a recommended fee for each ConfirmationTarget, let's review some best practices for FeeEstimator architecture.

First, let's circle back to get_est_sat_per_1000_weight function. While there are many ways to develop logic to determine which feerate to provide for a specific ConfirmationTarget, a popular approach is to fetch this information using a tiered methodology. This will help ensure that, if there is a failure in retrieving fees from one method, another method can serve as a backup and ensure that normal node operations are not impacted. For example, one approach to populating fees is the following:

  • If mempool.space successfully returns fee estimates, use those.
  • Otherwise, fetch fee estimates from your local mempool
  • If both of the above fail, use hard-coded fall-back fees, mapped to each ConfirmationTarget.

Please note, if you're using a third-party fee estimator, there are a few things you should keep in mind:

  • Third parties often rate-limit users such that they can only access a limited number of fee estimates within a given timeframe. If you require a certain service level agreement (SLA), it's recommended to run your own Bitcoin node or explore paid services with SLA guarantees, such as mempool.space enterprise accounts (opens new window).
  • Leveraging third-party providers may leave you more exposed to a griefing attack, where your fee estimator purposely overestimates the feerate, causing you to accept more dust HTLCs than you would otherwise.
  • Third-party fee estimates may affect the propagation of your pre-signed transactions at any time and, therefore, endanger the safety of channel funds.

Running your own Bitcoin node can relieve some of these concerns, but it may require additional technical expertise and maintenance to operate properly. These trade-offs should be considered carefully when deciding how your application will retrieve fee estimates.

A savvy reader may have noticed that the above architecture is not very performant. LDK may generate a substantial number of fee-estimation calls in some cases. So, if we have to call an API every time we want a fee estimate, we'll add a significant amount of additional load to our application, and we may substantially slow HTLC handling. To ensure your application remains performant, you should pre-calculate and cache the fee estimates so that they can simply be retrieved when needed. Additionally, it's recommended to refresh fee estimates every 5-10 minutes so that your application has access to fresh freerates.

# Feerate API Options

While mempool.space serves as the primary example in this documentation, it is not the only third-party option for retrieving feerate estimates. A few more options are listed below. For completeness, mempool.space is also included below.

Third Party API Documentation Response Type
Mempool.space API Docs (opens new window) Categories (ex: fastestFee, halfHourFee, hourFee, economyFee, minimumFee)
Blockstream API Docs (opens new window) Confirmation Targets (in blocks)
bitcoiner.live API Docs (opens new window) Confirmation Targets (in minutes)
BitGo API Docs (opens new window) Confirmation Targets (in blocks)
blockchain.info Missing Documentation. API is here: https://api.blockchain.info/mempool/fees Categories (ex: regular, priority)

# Coding Example

Now that we've reviewed the basic architecture, let's code up an example to demonstrate how you can implement the FeeEstimator in your project.

# Optional: Set Up

If you'd like to follow along with this demo, you can set up a new Rust project using cargo new followed by the name of the project. We'll call this ldk-fee-estimator.

$ cargo new ldk-fee-estimator
$ cd ldk-fee-estimator

Once you've created the directory, open the Cargo.toml file, which Cargo uses to manage version and package dependencies, and copy/paste the following code into that file.

[package]
name = "ldk-fee-estimator"
version = "0.1.0"
edition = "2021"

[dependencies]
lightning = { version = "0.0.123", features = ["max_level_trace"] }
lightning-block-sync = { version = "0.0.123", features = [ "rpc-client" ] }
lightning-invoice = { version = "0.31.0" }
lightning-net-tokio = { version = "0.0.123" }
lightning-persister = { version = "0.0.123" }
lightning-background-processor = { version = "0.0.123" }
lightning-rapid-gossip-sync = { version = "0.0.123" }
reqwest = { version = "0.11", features = ["json", "blocking"] }
serde = { version = "1.0", features = ["derive"] }
tokio = { version = "1", features = ["full"] }  # Async runtime, required for reqwest

Finally, go to main.rs and place the following code at the top of the file.

use lightning::chain::chaininterface::{
    ConfirmationTarget, FeeEstimator, FEERATE_FLOOR_SATS_PER_KW,
};
use reqwest::Client;
use reqwest::Error;
use serde::Deserialize;
use std::collections::HashMap;
use std::cmp;

# Defining MyAppFeeEstimator

First, we'll start by defining a structure, called MyAppFeeEstimator, which will be used to store feerates associated with each ConfirmationTarget. The field fee_rate_cache will contain a HashMap where the keys are of type ConfirmationTarget and the values are the feerates (type u32) in sats/KW. We'll store them in sats/KW because, as we saw earlier, the get_est_sat_per_1000_weight method in LDK's FeeEstimator expects fees to be provided in 1000 Weight-Units (opens new window), so we'll store them in sats/KW.

pub struct MyAppFeeEstimator {
    fee_rate_cache: HashMap<ConfirmationTarget, u32>,
}

# Retrieving Fees From mempool.space And Implementing MyAppFeeEstimator

Now that we have our basic structure for MyAppFeeEstimator, let's write some code to fetch the feerates themselves. For this example, we'll fetch feerates from mempool.space. To do this, we'll start by defining a MempoolFeeRate structure. Since mempool's recommmended fees API (opens new window) returns five different feerates (fastestFee, halfHourFee, hourFee, economyFee, minimumFee), we'll create a field for each rate. Also, since this structure will have to deserialize "camalCase" JSON data fetched from the API, we'll have to add those attributes to our structure.

#[derive(Deserialize, Debug)]
#[serde(rename_all = "camelCase")]
pub struct MempoolFeeRate {
    pub fastest_fee: u32,
    pub half_hour_fee: u32,
    pub hour_fee: u32,
    pub economy_fee: u32,
    pub minimum_fee: u32,
}

Now that our MempoolFeeRate structure is defined, we can begin building out the MyAppFeeEstimator. We'll start by implementing the MyAppFeeEstimator and adding our first function to this structure: fetch_fee_from_mempool. This function will fetch the feerates from mempool's API, process the response according to our MempoolFeeRate structure, and return the result. Since we'll be making an HTTP request using Rust's reqwest crate, we'll tag this function as asynchronous (async).

impl MyAppFeeEstimator {
    async fn fetch_fee_from_mempool() -> Result<MempoolFeeRate, reqwest::Error> {
        let url = "https://mempool.space/api/v1/fees/recommended";
        reqwest::Client::new()
                    .get(url)
                    .send()
                    .await?
                    .json::<MempoolFeeRate>()
                    .await
    }
}

# Retrieving Default Fees

Great, we now have a function that will return mempool.space feerates! However, as discussed earlier, we don't want to rely on only one source for our fee estimates. In a real production environment, we'd likely have a local mempool that we're sourcing feerates from and, perhaps, one or more third-party services. For this demo, we'll hard-code fallback feerates and return those if we're unable to retrieve a feerate from mepool.space.

Another reason we need default fee estimates is so that we can create instances of MyAppFeeEstimator without waiting for the feerates to be fetched from mempool.space (or any async operation). Therefore, we'll write a function that will return a hard-coded feerate for a given ConfirmationTarget. For simplicity, feerates below are presented as sats/vByte * 250 so that they are easier to read but, ultimately, they are stored within the cache as sats/KW. Note that this function is also a method within MyAppFeeEstimator.

pub fn default_fee_from_conf_target(confirmation_target: ConfirmationTarget) -> u32 {
    match confirmation_target {
        ConfirmationTarget::MinAllowedAnchorChannelRemoteFee => 10 * 250,
        ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee => 10 * 250,
        ConfirmationTarget::ChannelCloseMinimum => 20 * 250,
        ConfirmationTarget::AnchorChannelFee => 20 * 250,
        ConfirmationTarget::NonAnchorChannelFee => 30 * 250,
        ConfirmationTarget::OnChainSweep => 50 * 250,
        ConfirmationTarget::OutputSpendingFee => 10 * 250,
    }
}

# Creating a MyAppFeeEstimator Instance

Now that we've built the functionality to fetch feerates, we can start linking everything together. Let's begin by writing a new method, which we'll call each time we initialize a fee estimator. The new method will initialize an empty HashMap called fee_rate_cache, which we defined in our MyAppFeeEstimator structure earlier. It will then proceed to populate each of the required ConfirmationTarget fields with its respective feerate. Remember, to ensure our application is performant and does not have to wait for network operations when initializing a fee estimator, we will originally load the feerates with our default values.

pub fn new() -> Self {
    let mut fee_rate_cache = HashMap::new();
    use ConfirmationTarget::*;
    for target in &[MinAllowedAnchorChannelRemoteFee, MinAllowedNonAnchorChannelRemoteFee,
                    ChannelCloseMinimum, AnchorChannelFee, NonAnchorChannelFee,
                    OnChainSweep, OutputSpendingFee] {
        let default_fee = Self::default_fee_from_conf_target(*target);
        fee_rate_cache.insert(*target, default_fee);
    }

    MyAppFeeEstimator {
        fee_rate_cache
    }
}

# Updating Fees

Great, we now have a new function that will populate each instance of our fee estimator with the default rates.

However, we're not done yet! We already wrote code to fetch feerates from mempool.space, but we haven't inserted them into our cache. Let's do that now. We'll accomplish this by writing an update_fees method. A keen eye will likely notice that the feerates are multiplied by 250 before being added to the cache. This is because mempool.space returns feerates in sats/vByte, but we need them in sats/KW, so we can multiply them by 250 to convert them to sats/KW and then store them within our cache. Make sure both update_fees and new are added as methods within MyAppFeeEstimator!

pub async fn update_fees(&mut self) -> Result<(), reqwest::Error> {
    let fee_rates = Self::fetch_fee_from_mempool().await;

    match fee_rates {
        Ok(rates) => {
            self.fee_rate_cache.insert(ConfirmationTarget::OnChainSweep, rates.fastest_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::OutputSpendingFee, rates.fastest_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::NonAnchorChannelFee, rates.economy_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::AnchorChannelFee, rates.minimum_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::ChannelCloseMinimum, rates.minimum_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee, rates.minimum_fee * 250 as u32);
            self.fee_rate_cache.insert(ConfirmationTarget::MinAllowedAnchorChannelRemoteFee, rates.minimum_fee * 250 as u32);
        },
        Err(_) => {
            // If the API call fails, the fallback fees are already in cache
        }
    }

    Ok(())
}

# Retrieving Fees Based On A ConfirmationTarget

We're making solid progress! Remember, the end goal here is to build out a robust fee estimation logic that we can link back to the get_est_sat_per_1000_weight function in LDK's FeeEstimator. Since get_est_sat_per_1000_weight takes one input, a ConfirmationTarget, we'll have to write a function that returns the feerate for a specific ConfirmationTarget. Now that we have mempool.space fees cached within the MyAppFeeEstimator, we can do just that. Also, to ensure that fee estimates are not too low such that they run the risk of never being mined, we'll check that the fee we return is at least 253 sats/KW. This fee is also enforced within LDK's implementation of the FeeEstimator and is defined here (opens new window). We'll import this constant and use it in our function as well.

Below is a function that takes a ConfirmationTarget as an input, fetches the feerate for that ConfirmationTarget from our cache, and returns the result. If the fetched feerate is lower than the minimum feerate defined in LDK, FEERATE_FLOOR_SATS_PER_KW, we'll return FEERATE_FLOOR_SATS_PER_KW instead. As with the above, make sure this is added as a method within MyAppFeeEstimator!

pub fn get_fee_rate(&self, confirmation_target: ConfirmationTarget) -> u32 {
    self.fee_rate_cache.get(&confirmation_target)
        .map(|rate| cmp::max(*rate, FEERATE_FLOOR_SATS_PER_KW))
        .expect("all ConfirmationTarget should be present in the cache")
}

# Linking Our Code To LDK's FeeEstimator

Finally, we'll link our code to LDK's FeeEstimator by specifying that the MyAppFeeEstimator is a concrete implementation of the FeeEstimator and we have satisfied the trait requirement that get_est_sat_per_1000_weight is implemented.

Since we've already done most of the work, all we have to do is call the get_fee_rate in our MyAppFeeEstimator, and it will retrieve the feerate for the specified ConfirmationTarget, returning the value in sats/KW (satoshis-per-byte * 250), as specified by the LDK documentation.

impl FeeEstimator for MyAppFeeEstimator {
    fn get_est_sat_per_1000_weight(&self, confirmation_target: ConfirmationTarget) -> u32 {
        self.get_fee_rate(confirmation_target)
    }
}

# Testing And Improving Our Code

Now that the MyAppFeeEstimator has been completed, we can create an instance of the MyAppFeeEstimator and run a few tests.

In the below code, we start by creating fee_estimator, an instance of the MyAppFeeEstimator. Remember, since the fee_estimator is originally initialized with default values, we'll have to call update_fees() to fetch feerates from mempool.space and insert those updates into our cache.

We then define two fee targets, high_fee_target and low_fee_target for the ConfirmationTarget::OnChainSweep and ConfirmationTarget::MinAllowedAnchorChannelRemoteFee. Finally, we'll pass these confirmation targets into fee_estimator.get_est_sat_per_1000_weight and print the feerates (sats/KW) to the terminal.

One best-practice that was not implemented in this demo but is left as an exercise to the developer is refreshing the updates every 5-10 minutes. One approach toward accomplishing that would be to keep track of the last time the fee_estimator fees were refreshed and create a background process to update those fees periodically. Another exercise that is left to the reader is to create additional functionality within the MyAppFeeEstimator to retrieve the feerate for custom circumstances. For example, you could create a function called get_high_feerate, which takes no arguments and, instead, returns the feerate that should be used for a high-priority transaction. If you'd like to review a production-quality implementation of a FeeEstimator, you can review LDK Node's implementation here (opens new window).

#[tokio::main]
async fn main() {
    let mut fee_estimator = MyAppFeeEstimator::new();

    if let Err(e) = fee_estimator.update_fees().await {
        eprintln!("Failed to update fees: {}", e);
    }

    // Example of calling 'get_est_sat_per_1000_weight' with a specific confirmation target
    let high_fee_target = ConfirmationTarget::OnChainSweep;
    let low_fee_target = ConfirmationTarget::MinAllowedAnchorChannelRemoteFee;
    println!("Feerate for {:?}: {:?}", high_fee_target, fee_estimator.get_est_sat_per_1000_weight(high_fee_target));
    println!("Feerate for {:?}: {:?}", low_fee_target, fee_estimator.get_est_sat_per_1000_weight(low_fee_target));
}

# Demo Codebase

If you've been following the demo or would like to run/experiment with this code yourself, the entire main.rs file is provided below.

Just run $ cargo run in the terminal (from the root directory of this project), and you'll see live fee estimates print to your terminal!

use lightning::chain::chaininterface::{
    ConfirmationTarget, FeeEstimator, FEERATE_FLOOR_SATS_PER_KW,
};

use reqwest::Client;
use reqwest::Error;
use serde::Deserialize;
use std::collections::HashMap;
use std::cmp;

pub struct MyAppFeeEstimator {
    fee_rate_cache: HashMap<ConfirmationTarget, u32>,
}

#[derive(Deserialize, Debug)]
#[serde(rename_all = "camelCase")]
pub struct MempoolFeeRate {
    pub fastest_fee: u32,
    pub half_hour_fee: u32,
    pub hour_fee: u32,
    pub economy_fee: u32,
    pub minimum_fee: u32,
}

impl MyAppFeeEstimator {
    async fn fetch_fee_from_mempool() -> Result<MempoolFeeRate, reqwest::Error> {
        let url = "https://mempool.space/api/v1/fees/recommended";
        reqwest::Client::new()
                    .get(url)
                    .send()
                    .await?
                    .json::<MempoolFeeRate>()
                    .await
    }

    pub fn new() -> Self {
        let mut fee_rate_cache = HashMap::new();
        use ConfirmationTarget::*;
        for target in &[MinAllowedAnchorChannelRemoteFee, MinAllowedNonAnchorChannelRemoteFee, ChannelCloseMinimum, AnchorChannelFee, NonAnchorChannelFee, OnChainSweep, OutputSpendingFee] {
            let default_fee = Self::default_fee_from_conf_target(*target);
            fee_rate_cache.insert(*target, default_fee);
        }

        MyAppFeeEstimator {
            fee_rate_cache
        }
    }

    pub async fn update_fees(&mut self) -> Result<(), reqwest::Error> {
        let fee_rates = Self::fetch_fee_from_mempool().await;

        match fee_rates {
            Ok(rates) => {
                self.fee_rate_cache.insert(ConfirmationTarget::OnChainSweep, rates.fastest_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::OutputSpendingFee, rates.fastest_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::NonAnchorChannelFee, rates.economy_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::AnchorChannelFee, rates.minimum_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::ChannelCloseMinimum, rates.minimum_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee, rates.minimum_fee * 250 as u32);
                self.fee_rate_cache.insert(ConfirmationTarget::MinAllowedAnchorChannelRemoteFee, rates.minimum_fee * 250 as u32);
            },
            Err(_) => {
                // If the API call fails, the fallback fees are alreadyy in cache
            }
        }

        Ok(())
    }

    pub fn get_fee_rate(&self, confirmation_target: ConfirmationTarget) -> u32 {
        self.fee_rate_cache.get(&confirmation_target)
            .map(|rate| cmp::max(*rate, FEERATE_FLOOR_SATS_PER_KW))
            .expect("all ConfirmationTarget should be present in the cache")
    }

    pub fn default_fee_from_conf_target(confirmation_target: ConfirmationTarget) -> u32 {
        match confirmation_target {
            ConfirmationTarget::MinAllowedAnchorChannelRemoteFee => 3 * 250,
            ConfirmationTarget::MinAllowedNonAnchorChannelRemoteFee => 3 * 250,
            ConfirmationTarget::ChannelCloseMinimum => 10 * 250,
            ConfirmationTarget::AnchorChannelFee => 10 * 250,
            ConfirmationTarget::NonAnchorChannelFee => 20 * 250,
            ConfirmationTarget::OnChainSweep => 50 * 250,
            ConfirmationTarget::OutputSpendingFee => 50 * 250,
        }
    }

}

impl FeeEstimator for MyAppFeeEstimator {
    fn get_est_sat_per_1000_weight(&self, confirmation_target: ConfirmationTarget) -> u32 {
        self.get_fee_rate(confirmation_target)
    }
}


#[tokio::main]
async fn main() {
    let mut fee_estimator = MyAppFeeEstimator::new();

    if let Err(e) = fee_estimator.update_fees().await {
        eprintln!("Failed to update fees: {}", e);
    }

    // Example of calling 'get_est_sat_per_1000_weight' with a specific confirmation target
    let high_fee_target = ConfirmationTarget::OnChainSweep;
    let low_fee_target = ConfirmationTarget::MinAllowedAnchorChannelRemoteFee;
    println!("Feerate for {:?}: {:?}", high_fee_target, fee_estimator.get_est_sat_per_1000_weight(high_fee_target));
    println!("Feerate for {:?}: {:?}", low_fee_target, fee_estimator.get_est_sat_per_1000_weight(low_fee_target));
}

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