---

🧭 Table of Contents

• Introduction
• Quick Start
• Features
• Performance
• Usage
• Design
• Caveats
• License

---

✨ Introduction

Quill is a high-performance asynchronous logging library written in C++. It is designed for low-latency, performance-critical applications where every microsecond counts.

• Performance-Focused: Quill consistently outperforms many popular logging libraries.
• Feature-Rich: Packed with advanced features to meet diverse logging needs.
• Metric Publishing: Publish pre-registered metric samples to Prometheus, StatsD, OpenTelemetry, or any in-process collector through the same asynchronous backend used for logs. See the Metrics guide.
• Battle-Tested: Proven in demanding production environments. Extensively tested with sanitizers (ASan, UBSan, LSan) and fuzzed across a wide range of inputs.
• Extensive Documentation: Comprehensive guides and examples available.
• Community-Driven: Open to contributions, feedback, and feature requests.

Try it on Compiler Explorer

---

⏩ Quick Start

Getting started is easy and straightforward. Follow these steps to integrate the library into your project:

Installation

You can install Quill using the package manager of your choice:

Package Manager	Installation Command
vcpkg	vcpkg install quill
Conan	conan install quill
Homebrew	brew install quill
Meson WrapDB	meson wrap install quill
Conda	conda install -c conda-forge quill
Bzlmod	bazel_dep(name = "quill", version = "x.y.z")
xmake	xrepo install quill
nix	nix-shell -p quill-log
build2	libquill

Setup

Quickest Setup

For the shortest path from zero to working logs, use simple_logger():

#include "quill/SimpleSetup.h"
#include "quill/LogMacros.h"

int main()
{
  // log to the console
  auto* logger = quill::simple_logger();
  LOG_INFO(logger, "Hello from {}!", "Quill");

  // log to a file
  auto* logger2 = quill::simple_logger("test.log");
  LOG_WARNING(logger2, "This message goes to a file");
}

Console output:

20:07:18.423476231 [48917] main.cpp:8                    LOG_INFO      Hello from Quill!

Detailed Setup

If you want explicit control over backend options, logger names, sinks, or formatters, use the Backend and Frontend APIs directly:

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/ConsoleSink.h"
#include <string_view>

int main()
{
  quill::Backend::start();

  quill::Logger* logger = quill::Frontend::create_or_get_logger(
    "root", quill::Frontend::create_or_get_sink<quill::ConsoleSink>("sink_id_1"));

  LOG_INFO(logger, "Hello from {}!", std::string_view{"Quill"});
}

Output:

20:07:18.423476231 [48917] main.cpp:15                   LOG_INFO      root         Hello from Quill!

You can also use the macro-free mode. The macro API (LOG_INFO) is the lowest-latency path. The function API (quill::info) reads more like ordinary code but is slightly slower. See here for the trade-offs.

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogFunctions.h"
#include "quill/Logger.h"
#include "quill/sinks/ConsoleSink.h"
#include <string_view>

int main()
{
  quill::Backend::start();

  quill::Logger* logger = quill::Frontend::create_or_get_logger(
    "root", quill::Frontend::create_or_get_sink<quill::ConsoleSink>("sink_id_1"));

  quill::info(logger, "Hello from {}!", std::string_view{"Quill"});
}

Publishing Metrics

Register MetricMetadata once, then publish double samples from hot threads through the same asynchronous backend used for logs. The bundled PrometheusSink handles counters, gauges, histograms, and summaries; custom sinks can route samples to StatsD, OpenTelemetry, or any in-process collector via Sink::write_metric().

// One-time registration — returns a stable pointer valid for program lifetime.
quill::MetricMetadata const* requests_total = quill::Frontend::create_metric(
  "requests_total_post_200", "requests_total", {{"method", "POST"}, {"status", "200"}});

// Hot path — no label serialization, just a pointer and a double.
logger->publish_metric(requests_total, 1.0);

See the Metrics guide for sink setup, custom sinks, and Prometheus integration.

---

🎯 Features

• High-Performance: Ultra-low latency performance.
• Asynchronous Processing: Background thread handles formatting and I/O, keeping your main thread responsive.
• Metric Publishing: Publish pre-registered metric samples to Prometheus, StatsD, OpenTelemetry, or any in-process collector through the same asynchronous backend. See Metrics.
• Minimal Header Includes:
  • Frontend: Only Logger.h and LogMacros.h needed for logging. Lightweight with minimal dependencies.
  • Backend: Single .cpp file inclusion. No backend code injection into other translation units.
• Compile-Time Optimization: Eliminate specific log levels at compile time.
• Custom Formatters: Define your own log output patterns. See Formatters.
• Timestamp-Ordered Logs: Simplify debugging of multithreaded applications with chronologically ordered logs.
• Flexible Timestamps: Support for rdtsc, chrono, or custom clocks - ideal for simulations and more.
• Backtrace Logging: Store messages in a ring buffer for on-demand display. See Backtrace Logging
• Multiple Output Sinks: Console (with color), files (with rotation), JSON, ability to create custom sinks and more.
• Log Filtering: Process only relevant messages. See Filters.
• JSON Logging: Structured log output. See JSON Logging
• Mapped Diagnostic Context (MDC): Thread-local key/value context attached automatically to subsequent log lines. See MDC.
• Rate-Limited Macros: LOG_*_LIMIT / LOGV_*_LIMIT emit at most once per configured interval per call site.
• Configurable Queue Modes: bounded/unbounded and blocking/dropping options with monitoring on dropped messages, queue reallocations, and blocked hot threads.
• Crash Handling: Built-in signal handler for log preservation during crashes.
• Huge Pages Support (Linux): Leverage huge pages on the hot path for optimized performance.
• Wide Character Support (Windows): Compatible with ASCII-encoded wide strings and STL containers consisting of wide strings.
• Exception-Free Option: Configurable builds with or without exception handling.
• Clean Codebase: Maintained to high standards, warning-free even at strict levels.
• Type-Safe API: Built on {fmt} library.

---

🚀 Performance

System Configuration

• OS: Linux RHEL 9.4

• CPU: Intel Core i5-12600 (12th Gen) @ 4.8 GHz

• Compiler: GCC 13.1

• Benchmark-Tuned System: The system is specifically tuned for benchmarking.

• Command Line Parameters:

  $ cat /proc/cmdline
  BOOT_IMAGE=(hd0,gpt2)/vmlinuz-5.14.0-427.13.1.el9_4.x86_64 root=/dev/mapper/rhel-root ro crashkernel=1G-4G:192M,4G-64G:256M,64G-:512M resume=/dev/mapper/rhel-swap rd.lvm.lv=rhel/root rd.lvm.lv=rhel/swap rhgb quiet nohz=on nohz_full=1-5 rcu_nocbs=1-5 isolcpus=1-5 mitigations=off transparent_hugepage=never intel_pstate=disable nosoftlockup irqaffinity=0 processor.max_cstate=1 nosoftirqd sched_tick_offload=0 spec_store_bypass_disable=off spectre_v2=off iommu=pt
  

You can find the benchmark code on the logger_benchmarks repository.

Latency

The results presented in the tables below are measured in nanoseconds (ns).

The tables are sorted by the 95th percentile (lower is better).

Logging Numbers

LOG_INFO(logger, "Logging int: {}, int: {}, double: {}", i, j, d).

1 Thread Logging

Library	50th	75th	90th	95th	99th	99.9th
XTR	7	7	8	8	9	47
PlatformLab NanoLog	8	8	8	8	9	203
Quill Bounded Dropping Queue	8	8	9	9	10	12
Quill Unbounded Queue	8	8	9	9	10	12
fmtlog	8	9	9	10	10	12
MS BinLog	23	23	23	24	77	124
Quill Unbounded Queue (Log Functions)	29	30	31	32	33	35
Reckless	26	28	31	32	35	43
Iyengar NanoLog	94	102	145	173	1149	2054
spdlog	242	249	257	262	274	294
Boost.Log	3057	3111	3221	3261	3409	3612
BqLog	4340	4564	4588	4618	8089	10536
g3log	5017	5055	5239	5289	5503	5876

4 Threads Logging Simultaneously

Library	50th	75th	90th	95th	99th	99.9th
Quill Bounded Dropping Queue	13	13	14	14	17	23
Quill Unbounded Queue	11	11	13	14	15	21
fmtlog	14	14	15	15	16	19
XTR	12	13	14	15	18	192
PlatformLab NanoLog	15	15	16	16	20	24
MS BinLog	32	33	34	36	253	447
Quill Unbounded Queue (Log Functions)	36	40	45	47	52	61
Reckless	29	35	45	52	66	91
Iyengar NanoLog	75	81	285	298	473	1721
spdlog	528	555	585	607	669	973
Boost.Log	1600	2705	3126	3159	3816	4958
BqLog	249	276	4595	5152	5505	8711
g3log	1192	4236	5165	5214	6443	7844

Logging Large Strings

Logging std::string over 35 characters to prevent the short string optimization.

LOG_INFO(logger, "Logging int: {}, int: {}, string: {}", i, j, large_string).

1 Thread Logging

Library	50th	75th	90th	95th	99th	99.9th
XTR	8	8	8	9	10	46
PlatformLab NanoLog	11	11	12	12	13	210
Quill Bounded Dropping Queue	11	12	13	14	17	19
fmtlog	11	12	13	14	16	18
Quill Unbounded Queue	11	13	14	15	17	20
MS BinLog	24	25	25	26	78	125
Quill Unbounded Queue (Log Functions)	33	34	36	37	40	42
Reckless	91	104	112	116	122	130
Iyengar NanoLog	96	104	148	156	1034	1883
spdlog	216	223	230	236	247	259
Boost.Log	2871	3020	3045	3078	3169	3329
BqLog	3549	4482	4517	4576	5837	7392
g3log	4785	4822	5049	5099	5319	5688

4 Threads Logging Simultaneously

Library	50th	75th	90th	95th	99th	99.9th
Quill Bounded Dropping Queue	9	11	14	16	21	28
Quill Unbounded Queue	8	10	13	16	21	27
fmtlog	10	13	15	16	19	24
XTR	10	11	14	17	23	186
PlatformLab NanoLog	16	21	22	23	29	34
MS BinLog	32	33	35	38	255	449
Quill Unbounded Queue (Log Functions)	35	39	45	49	56	68
Reckless	43	81	129	141	162	179
Iyengar NanoLog	74	82	285	299	478	1693
spdlog	515	543	570	591	646	939
Boost.Log	1363	2518	2931	2977	3686	4756
g3log	837	3885	4900	4947	6040	7397
BqLog	248	275	4634	5055	5538	8843

Logging Complex Types

Logging std::vector<std::string> containing 16 large strings, each ranging from 50 to 60 characters.

Note: some of the previous loggers do not support passing a std::vector as an argument.

LOG_INFO(logger, "Logging int: {}, int: {}, vector: {}", i, j, v).

1 Thread Logging

Library	50th	75th	90th	95th	99th	99.9th
Quill Bounded Dropping Queue	56	58	61	63	68	94
MS BinLog	73	76	78	79	87	354
Quill Unbounded Queue	137	150	164	171	181	189
XTR	309	314	319	322	349	666
fmtlog	750	788	823	847	896	982
spdlog	6749	6833	6911	6967	7217	7863
Boost.Log	90879	91012	91164	91251	92676	93069

4 Threads Logging Simultaneously

Library	50th	75th	90th	95th	99th	99.9th
Quill Bounded Dropping Queue	82	89	99	106	115	123
Quill Unbounded Queue	101	110	120	128	142	158
MS BinLog	103	113	122	130	299	518
fmtlog	657	683	707	722	750	782
XTR	697	766	805	825	870	1027
spdlog	6822	7021	7230	7513	8048	8903
Boost.Log	36382	69081	91568	132626	173810	203865

The benchmark methodology involves logging 20 messages in a loop, calculating and storing the average latency for those 20 messages, then waiting around ~2 milliseconds, and repeating this process for a specified number of iterations.

In the Quill Bounded Dropping benchmarks, the dropping queue size is set to 262,144 bytes, which is double the default size of 131,072 bytes.

Throughput

Throughput is measured by calculating the maximum number of log messages the backend logging thread can write to a log file per second (higher is better).

The tests were run on the same system used for the latency benchmarks.

Although Quill’s primary focus is not on maximizing throughput, it efficiently manages log messages across multiple threads. Benchmarking throughput of asynchronous logging libraries presents certain challenges. Some libraries may drop log messages, leading to smaller-than-expected log files, while others only provide asynchronous flushing, making it difficult to verify when the backend thread has fully processed all messages.

For comparison, we benchmark against other asynchronous logging libraries that offer guaranteed logging with a flush-and-wait mechanism.

Note that MS BinLog writes log data to a binary file, which requires offline formatting with an additional program—this makes it an unfair comparison, but it is included for reference.

Similarly, BqLog (binary log) uses the compressed binary log appender, and its log files are not human-readable unless processed offline. However, it is included for reference. The other version of BqLog is using a text appender and produces human-readable log files.

In the same way, Platformlab Nanolog also outputs binary logs and is expected to deliver high throughput. However, for reasons unexplained, the benchmark runs significantly slower (10x longer) than the other libraries, so it is excluded from the table.

XTR uses FMT_COMPILE for message formatting in this benchmark. Quill does not currently use that optimisation: decoded arguments are formatted through the runtime fmt APIs, and the final log line then passes through Quill's runtime-configurable PatternFormatter.

Logging 4 million times the message "Iteration: {} int: {} double: {}"

Library	million msg/second	elapsed time
MS BinLog (binary log)	57.72	69 ms
BqLog (binary log)	13.85	288 ms
XTR	7.54	530 ms
BqLog	5.40	740 ms
Quill	4.62	866 ms
spdlog	3.46	1156 ms
fmtlog	2.65	1508 ms
Reckless	2.57	1555 ms
Quill - Macro Free Mode	2.23	1789 ms
Boost.Log	0.33	12152 ms

Compilation Time

Compile times are measured on the system above using clean Release builds of BENCHMARK_quill_compile_time, which compiles 2000 auto-generated log statements with varied argument types.

The measurements below were taken with -march=x86-64-v3 for Release, running one clean build at a time with -j4. Clang builds additionally enable -ftime-trace.

Quill intentionally keeps call-site metadata such as file, line, format string, and tags out of the frontend template identity. In the common macro-based path, that information is stored in a MacroMetadata object and passed as a regular function argument. As a result, multiple log statements with the same argument type pack can reuse the same log_statement instantiation; changing only the call-site metadata does not create a new frontend template instantiation.

Compiler	Clean Build Time	Benchmark Binary	Main TU Object
clang 17.0.6	30.64 s	5.87 MB	10.10 MB
gcc 13.3.1	61.20 s	6.22 MB	9.28 MB

Header include profile — shows the additional headers pulled in when logging, following the recommended_usage example:

**Open in Speedscope ** ↗

Compile-time benchmark — measures compilation of 2000 auto-generated log statements with various arguments:

**Open in Speedscope ** ↗

To generate these profiles yourself:

cmake -G Ninja -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_BUILD_TYPE=Release \
  -DQUILL_BUILD_BENCHMARKS=ON -DQUILL_ENABLE_TIME_TRACE=ON \
  -DCMAKE_CXX_FLAGS='-march=x86-64-v3' ..
cmake --build . --target BENCHMARK_quill_compile_time -j 4
# Load the resulting .cpp.json files into https://www.speedscope.app

Verdict

Quill excels in hot path latency benchmarks and supports high throughput, offering a rich set of features that outshines other logging libraries.

The human-readable log files facilitate easier debugging and analysis. While initially larger, they compress efficiently, with the size difference between human-readable and binary logs becoming minimal once zipped.

For example, for the same amount of messages:

ms_binlog_backend_total_time.blog (binary log): 177 MB
ms_binlog_backend_total_time.zip (zipped binary log): 35 MB

quill_backend_total_time.log (human-readable log): 448 MB
quill_backend_total_time.zip (zipped human-readable log): 47 MB

If you prefer a binary-log workflow, MS BinLog is a strong alternative. It delivers excellent hot-path latency and smaller raw files, but it trades away immediate readability and requires offline processing tools.

---

🧩 Usage

Also, see the Quick Start Guide for a brief introduction.

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/ConsoleSink.h"
#include "quill/std/Array.h"

#include <string>
#include <utility>

int main()
{
  // Backend  
  quill::BackendOptions backend_options;
  quill::Backend::start(backend_options);

  // Frontend
  auto console_sink = quill::Frontend::create_or_get_sink<quill::ConsoleSink>("sink_id_1");
  quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(console_sink));

  // Change the LogLevel to print everything
  logger->set_log_level(quill::LogLevel::TraceL3);

  // A log message with number 123
  int a = 123;
  std::string l = "log";
  LOG_INFO(logger, "A {} message with number {}", l, a);

  // libfmt formatting language is supported 3.14e+00
  double pi = 3.141592653589793;
  LOG_INFO(logger, "libfmt formatting language is supported {:.2e}", pi);

  // Logging STD types is supported [1, 2, 3]
  std::array<int, 3> arr = {1, 2, 3};
  LOG_INFO(logger, "Logging STD types is supported {}", arr);

  // Logging STD types is supported [arr: [1, 2, 3]]
  LOGV_INFO(logger, "Logging STD types is supported", arr);

  // A message with two variables [a: 123, b: 3.17]
  double b = 3.17;
  LOGV_INFO(logger, "A message with two variables", a, b);

  for (uint32_t i = 0; i < 10; ++i)
  {
    // Will only log the message once per second
    LOG_INFO_LIMIT(std::chrono::seconds{1}, logger, "A {} message with number {}", l, a);
    LOGV_INFO_LIMIT(std::chrono::seconds{1}, logger, "A message with two variables", a, b);
  }

  LOG_TRACE_L3(logger, "Support for floats {:03.2f}", 1.23456);
  LOG_TRACE_L2(logger, "Positional arguments are {1} {0} ", "too", "supported");
  LOG_TRACE_L1(logger, "{:>30}", std::string_view {"right aligned"});
  LOG_DEBUG(logger, "Debugging foo {}", 1234);
  LOG_INFO(logger, "Welcome to Quill!");
  LOG_WARNING(logger, "A warning message.");
  LOG_ERROR(logger, "An error message. error code {}", 123);
  LOG_CRITICAL(logger, "A critical error.");
}

Output

External CMake

Building and Installing Quill

To get started with Quill, clone the repository and install it using CMake:

git clone https://github.com/odygrd/quill.git
cd quill
mkdir cmake_build
cd cmake_build
cmake ..
make install

• Custom Installation: Specify a custom directory with -DCMAKE_INSTALL_PREFIX=/path/to/install/dir.
• Build Examples: Include examples with -DQUILL_BUILD_EXAMPLES=ON.

Next, add Quill to your project using find_package():

find_package(quill REQUIRED)
target_link_libraries(your_target PUBLIC quill::quill)

Sample Directory Structure

Organize your project directory like this:

my_project/
├── CMakeLists.txt
├── main.cpp

Sample CMakeLists.txt

Here is a minimal CMakeLists.txt:

# If Quill is in a non-standard directory, specify its path.
set(CMAKE_PREFIX_PATH /path/to/quill)

# Find and link the Quill library.
find_package(quill REQUIRED)
add_executable(example main.cpp)
target_link_libraries(example PUBLIC quill::quill)

Embedded CMake

If you prefer to vendor Quill directly, add it as a subdirectory:

Sample Directory Structure

my_project/
├── quill/            # Quill repo folder
├── CMakeLists.txt
├── main.cpp

Sample CMakeLists.txt

Use this CMakeLists.txt to include Quill directly:

cmake_minimum_required(VERSION 3.8)
project(my_project)

set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)

add_subdirectory(quill)
add_executable(my_project main.cpp)
target_link_libraries(my_project PUBLIC quill::quill)

Android NDK

Android usually works without special handling. If your toolchain does not support thread names, configure with:

-DQUILL_NO_THREAD_NAME_SUPPORT:BOOL=ON

For timestamps, use quill::ClockSourceType::System. Quill also includes an AndroidSink for Android's logging system.

Minimal Example to Start Logging on Android

quill::Backend::start();

auto sink = quill::Frontend::create_or_get_sink<quill::AndroidSink>("app", [](){
    quill::AndroidSinkConfig asc;
    asc.set_tag("app");
    asc.set_format_message(true);
    return asc;
}());

auto logger = quill::Frontend::create_or_get_logger("root", std::move(sink),
                                                    quill::PatternFormatterOptions {}, 
                                                    quill::ClockSourceType::System);

LOG_INFO(logger, "Test {}", 123);

Meson

Using WrapDB

Install Quill from Meson's wrapdb with:

meson wrap install quill

Manual Integration

Or copy the repository into subprojects and add the following to meson.build:

quill = subproject('quill')
quill_dep = quill.get_variable('quill_dep')
my_build_target = executable('name', 'main.cpp', dependencies : [quill_dep], install : true)

Bazel

Using Bzlmod

Quill is available on Bzlmod.

Manual Integration

For manual setup, add Quill to your BUILD.bazel file like this:

cc_binary(name = "app", srcs = ["main.cpp"], deps = ["//quill_path:quill"])

---

📐 Design

Quill is split into a hot frontend and a cold backend.

• Each frontend thread owns a lock-free SPSC queue. LOG_* macros binary-serialize arguments directly into that queue — no shared state, no contention between threads, no formatting work on the caller.
• A single backend worker drains all queues, merges events in timestamp order, invokes the per-argument-pack decode function to reconstruct arguments, runs {fmt} formatting and the PatternFormatter, and writes the resulting log lines or metric samples to the attached Sinks.

Frontend (caller-thread)

When invoking a LOG_ macro:

1. Creates a static constexpr metadata object containing the format string and source location.

2. Pushes the event into the SPSC lock-free queue. For each log message, Quill enqueues:

Variable	Description
timestamp	Current timestamp
Metadata*	Pointer to metadata information
Logger*	Pointer to the logger instance
DecodeFunc	A pointer to a templated function containing all the log message argument types, used for decoding the message
Args...	A serialized binary copy of each log message argument that was passed to the LOG_ macro

When invoking METRIC(...) or logger->publish_metric():

1. Reuses pre-registered MetricMetadata, so metric names and labels are not serialized again on the hot path.

2. Pushes a compact fixed-size sample record to the same SPSC queue.

Variable	Description
timestamp	Current timestamp
MetricMetadata*	Pointer to the pre-registered metric name and labels
Logger*	Pointer to the logger instance
value	The actual sample value as a double (counter delta, latency, gauge)

Backend

The backend thread drains the SPSC queue, reconstructs log events, forwards metric samples to Sink::write_metric(), and fans each log or metric event out to the sinks attached to the logger.

Architecture Overview

The diagram below shows the end-to-end flow from hot frontend threads to the backend worker and sinks.

---

🚨 Caveats

Do not log from destructors of static or global objects. Quill's internal singletons are function-local statics destroyed in reverse construction order. If a static object's constructor triggers the first log call, the library singletons are constructed after that object and destroyed before it. Logging from that destructor will then touch already-destroyed state.

Use fork() with care. Quill starts a background thread, and fork() interacts poorly with multithreaded processes. If you need logging in child processes, call quill::Backend::start() after fork() in each process that should log, and write parent and child output to different files.

Example:

#include "quill/Backend.h"
#include "quill/Frontend.h"
#include "quill/LogMacros.h"
#include "quill/Logger.h"
#include "quill/sinks/FileSink.h"

int main()
{
  // DO NOT CALL THIS BEFORE FORK
  // quill::Backend::start();

  if (fork() == 0)
  {
    quill::Backend::start();

    // Write child output to its own file.
    auto file_sink = quill::Frontend::create_or_get_sink<quill::FileSink>("child.log");
    
    quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(file_sink));

    LOG_INFO(logger, "Hello from Child {}", 123);
  }
  else
  {
    quill::Backend::start();

    // Write parent output to its own file.
    auto file_sink = quill::Frontend::create_or_get_sink<quill::FileSink>("parent.log");

    quill::Logger* logger = quill::Frontend::create_or_get_logger("root", std::move(file_sink));

    LOG_INFO(logger, "Hello from Parent {}", 123);
  }
}

---

📝 License

Quill is licensed under the MIT License.

Quill depends on third party libraries with separate copyright notices and license terms. Your use of the source code for these subcomponents is subject to the terms and conditions of the following licenses.

• (MIT License) {fmt}
• (MIT License) doctest