Documentation: https://bluebrain.github.io/HighFive/

HighFive is a modern header-only C++11 friendly interface for libhdf5.

HighFive supports STL vector/string, Boost::UBLAS, Boost::Multi-array, Eigen and Xtensor. It handles C++ from/to HDF5 with automatic type mapping. HighFive does not require additional libraries (see dependencies) and supports both HDF5 thread safety and Parallel HDF5 (contrary to the official hdf5 cpp)

It integrates nicely with other CMake projects by defining (and exporting) a HighFive target.

• Simple C++-ish minimalist interface
• No other dependency than libhdf5
• Zero overhead
• Support C++11

• create/read/write files, datasets, attributes, groups, dataspaces.
• automatic memory management / ref counting
• automatic conversion of std::vector and nested std::vector from/to any dataset with basic types
• automatic conversion of std::string to/from variable length string dataset
• selection() / slice support
• parallel Read/Write operations from several nodes with Parallel HDF5
• Advanced types: Compound, Enum, Arrays of Fixed-length strings, References
• half-precision (16-bit) floating-point datasets
• std::byte in C++17 mode (with -DCMAKE_CXX_STANDARD=17 or higher)
• etc... (see ChangeLog)

• hdf5 (dev)
• hdf5-mpi (optional, opt-in with -DHIGHFIVE_PARALLEL_HDF5=ON)
• boost >= 1.41 (recommended, opt-out with -DHIGHFIVE_USE_BOOST=OFF)
• eigen3 (optional, opt-in with -DHIGHFIVE_USE_EIGEN=ON)
• xtensor (optional, opt-in with -DHIGHFIVE_USE_XTENSOR=ON)
• half (optional, opt-in with -DHIGHFIVE_USE_HALF_FLOAT=ON)

#include <highfive/H5File.hpp>

using namespace HighFive;

std::string filename = "/tmp/new_file.h5";

{
    // We create an empty HDF55 file, by truncating an existing
    // file if required:
    File file(filename, File::Truncate);

    std::vector<int> data(50, 1);
    file.createDataSet("grp/data", data);
}

{
    // We open the file as read-only:
    File file(filename, File::ReadOnly);
    auto dataset = file.getDataSet("grp/data");

    // Read back, with allocating:
    auto data = dataset.read<std::vector<int>>();

    // Because `data` has the correct size, this will
    // not cause `data` to be reallocated:
    dataset.read(data);
}

Note: H5File.hpp is the top-level header of HighFive core which should be always included.

Note: For advanced usecases the dataset can be created without immediately writing to it. This is common in MPI-IO related patterns, or when growing a dataset over the course of a simulation.

See create_dataset_double.cpp

See boost_ublas_double.cpp

See select_partial_dataset_cpp11.cpp

See create_attribute_string_integer.cpp

See src/examples/ subdirectory for more info.

c++ -o program -I/path/to/highfive/include source.cpp  -lhdf5

For several 'standard' use cases the highfive/H5Easy.hpp interface is available. It allows:

• Reading/writing in a single line of:

  • scalars (to/from an extendible DataSet),
  • strings,
  • vectors (of standard types),
  • Eigen::Matrix (optional, enable CMake option HIGHFIVE_USE_EIGEN),
  • xt::xarray and xt::xtensor (optional, enable CMake option HIGHFIVE_USE_XTENSOR).
  • cv::Mat_ (optional, enable CMake option HIGHFIVE_USE_OPENCV).

• Getting in a single line:

  • the size of a DataSet,
  • the shape of a DataSet.

#include <highfive/H5Easy.hpp>

int main() {
    H5Easy::File file("example.h5", H5Easy::File::Overwrite);

    int A = ...;
    H5Easy::dump(file, "/path/to/A", A);

    A = H5Easy::load<int>(file, "/path/to/A");
}

whereby the int type of this example can be replaced by any of the above types. See easy_load_dump.cpp for more details.

Note: Classes such as H5Easy::File are just short for the regular HighFive classes (in this case HighFive::File). They can thus be used interchangeably.

HighFive can easily be used by other C++ CMake projects.

You may use HighFive from a folder in your project (typically a git submodule).

cmake_minimum_required(VERSION 3.1 FATAL_ERROR)
project(foo)
set(CMAKE_CXX_STANDARD 11)

add_subdirectory(highfive_folder)
add_executable(bar bar.cpp)
target_link_libraries(bar HighFive)

Alternativelly you can install HighFive once and use it in several projects via find_package().

A HighFive target will bring the compilation settings to find HighFive headers and all chosen dependencies.

# ...
find_package(HighFive REQUIRED)
add_executable(bar bar.cpp)
target_link_libraries(bar HighFive)

Note: Like with other libraries you may need to provide CMake the location to find highfive: CMAKE_PREFIX_PATH=<highfive_install_dir>

Note: find_package(HighFive) will search dependencies as well (e.g. Boost if requested). In order to use the same dependencies found at HighFive install time (e.g. for system deployments) you may set HIGHFIVE_USE_INSTALL_DEPS=YES

When installing via CMake, besides the headers, a HighFiveConfig.cmake is generated which provides the HighFive target, as seen before. Note: You may need to set CMAKE_INSTALL_PREFIX:

mkdir build && cd build
# Look up HighFive CMake options, consider inspecting with `ccmake`
cmake .. -DHIGHFIVE_EXAMPLES=OFF -DCMAKE_INSTALL_PREFIX="<highfive_install_dir>"
make install

As a header-only library, HighFive doesn't require compilation. You may however build tests and examples.

mkdir build && cd build
cmake ../
make  # build tests and examples
make test  # build and run unit tests

Note: Unit tests require Boost. In case it's unavailable you may use -DHIGHFIVE_USE_BOOST=OFF. HighFive with disable support for Boost types as well as unit tests (though most examples will build).

If you want to propose pull requests to this project, do not forget to format code with clang-format version 12. The .clang-format is at the root of the git repository.

Do you have questions on how to use HighFive? Would you like to share an interesting example or discuss HighFive features? Head over to the Discussions forum and join the community.

The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government's ETH Board of the Swiss Federal Institutes of Technology.

Copyright © 2015-2022 Blue Brain Project/EPFL

Boost Software License 1.0