Postmodern immutable and persistent data structures for C++ — value semantics at scale
Under Boost Software License 1.0
By arximboldi

immutable data-structures cpp14 modern-cpp persistent rrb-tree postmodernism value-semantics hamt

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.. include:introduction/start

immer is a library of persistent_ and immutable_ data structures
written in C++. These enable whole new kinds of architectures for
interactive and concurrent programs of striking simplicity,
correctness, and performance.

.. _persistent:
.. _immutable:

.. _contents:
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.. _preprint:

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This library has full months of pro bono research and development
invested in it. This is just the first step in a long-term vision
of making interactive and concurrent C++ programs easier to
write. Put your logo here and help this project's long term
sustainability by buying a sponsorship package:
[email protected]

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example is copy pasted from example/vector/intro.cpp

.. code-block:: c++

int main()
const auto v0 = immer::vector{};
const auto v1 = v0.push_back(13);
assert(v0.size() == 0 && v1.size() == 1 && v1[0] == 13);

   const auto v2 = v1.set(0, 42);
assert(v1[0] == 13 && v2[0] == 42);


For a complete example check Ewig, a simple didactic
text-editor <>
built with this
library. You may also wanna check Lager, a Redux-like library
for writting interactive
software in C++ using a value-oriented design.


In the last few years, there has been a growing interest in immutable
data structures, motivated by the horizontal scaling of our processing
power and the ubiquity of highly interactive systems. Languages like
Clojure_ and Scala_ provide them by default, and implementations
for JavaScript like Mori_ and Immutable.js_ are widely used,
specially in combination with modern UI frameworks like React_.

Thanks to persistence and structural sharing, new values can
be efficiently compared with old ones. This enables simpler ways of
reasoning about change that sit at the core of modern
interactive systems programming paradigms like reactive

Passing immutable data structures by value does not need to copy
any data. In the absence of mutation, data can be safely read
from multiple concurrent processes, and enable concurrency
patterns like share by communicating_ efficiently.

Some recent immutable data structures have interesting properties
like :math:O(log(n)) concatenation, which enable new kinds of
parallelization algorithms_.

.. _clojure:
.. _scala:

.. _mori:
.. _immutable.js:
.. _react:

.. _reactive programming:
.. _share by communicating:
.. _parallelization algorithms:


This library doesn't pretend that it is written in Haskell. It
leverages features from recent standards to provide an API that is
both efficient and natural for a C++ developer.

You use C++ because you need this. Immer implements state of
the art data structures with efficient cache utilization and have
been proven production ready in other languages. It also includes
our own improvements over that are only possible because of the
C++'s ability to abstract over memory layout. We monitor the
performance impact of every change by collecting benchmark
_ directly from CI.

.. _benchmark results:

We leverage templates and policy-based design to build
data-structures that can be adapted to work efficiently for
various purposes and architectures, for example, by choosing among
various memory management strategies. This turns
immer into a good foundation to provide immutable data
structures to higher level languages with a C runtime, like
or Guile_.

.. _python:
.. _guile:
.. _policy-based design:
.. _memory management strategies:


This library is written in C++14 and a compliant compiler is
necessary. It is continuously tested_ with Clang 3.8 and GCC 6, but
it might work with other compilers and versions.

No external library is necessary and there are no other requirements.

.. _continuously tested:


This is a header only library. You can just copy the immer
subfolder somewhere in your include path.

If you are using the Nix package manager_ (we strongly recommend it)
you can just::

nix-env -if

Alternatively, you can use CMake_ to install the library in your
system once you have manually cloned the repository::

mkdir -p build && cd build
cmake .. && sudo make install

.. _nix package manager:
.. _cmake:


In order to develop the library, you will need to compile and run the
examples, tests and benchmarks. These require some additional tools.
The easiest way to install them is by using the Nix package
_. At the root of the repository just type::


This will download all required dependencies and create an isolated
environment in which you can use these dependencies, without polluting
your system.

Then you can proceed to generate a development project using CMake_::

mkdir build && cd build
cmake ..

From then on, one may build and run all tests by doing::

make check

In order to build and run all benchmarks when running make check,
run cmake again with the option -DCHECK_BENCHMARKS=1. The
results of running the benchmarks will be saved to a folder
reports/ in the project root.


This software is licensed under the Boost Software License 1.0.

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:alt: Boost logo
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The full text of the license is can be accessed via this link
_ and is also included
in the LICENSE file of this software package.