Note: In preparation of v3 of HighFive, we've started merging breaking changes into the main branch. More information and opportunity to comment can be found at: #864

HighFive - HDF5 header-only C++ Library

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

Brief

HighFive is a modern header-only C++14 friendly interface for libhdf5.

HighFive supports STL vector/string, Boost::UBLAS, Boost::Multi-array and Xtensor. It handles C++ from/to HDF5 with automatic type mapping. HighFive does not require additional libraries (see dependencies).

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

Design

• Simple C++-ish minimalist interface
• Only hard dependency is libhdf5
• Zero/low overhead, when possible
• RAII for opening/closing files, groups, datasets, etc.
• Written in C++14

Feature support

• 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- or fixed-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)

Dependencies

• HDF5 or pHDF5, including headers
• boost (optional)
• eigen3 (optional)
• xtensor (optional)
• half (optional)

Versioning & Code Stability

We use semantic versioning. Currently, we're preparing v3 which contains a limited set of breaking changes required to eliminate undesireable behaviour or modernize outdated patterns. We provide a Migration Guide, please report any missing or incorrect information to help others make the switch more easily.

• v2.x.y are stable and any API breaking changes are considered bugs. There's like not going to be very many releases of the v2 line once v3 is stable.

• v3.0.0-beta? are pre-releases of v3.0.0. We predict that one more breaking changes might happen: the string handling is confusing to some of the maintainers and the default encoding is inconsistent (and will likely be made consistent).

  For codes that either use std::string when dealing with strings, or that don't use strings with HDF5 at all, we don't currently have any additional breaking changes planned for 3.0.0.

Known flaws

• HighFive is not thread-safe. At best it has the same limitations as the HDF5 library. However, HighFive objects modify their members without protecting these writes. Users have reported that HighFive is not thread-safe even when using the threadsafe HDF5 library, e.g., #675.
• Eigen support in core HighFive was broken until v3.0. See #532. H5Easy was not affected.
• The support of fixed length strings isn't ideal.

Examples

Write a std::vector to 1D HDF5 dataset and read it back

#include <highfive/highfive.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: As of 2.8.0, one can use highfive/highfive.hpp to include everything HighFive. Prior to 2.8.0 one would include highfive/H5File.hpp.

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.

Write a 2 dimensional C double float array to a 2D HDF5 dataset

See create_dataset_double.cpp

Write and read a matrix of double float (boost::ublas) to a 2D HDF5 dataset

See boost_ublas_double.cpp

Write and read a subset of a 2D double dataset

See select_partial_dataset_cpp11.cpp

Create, write and list HDF5 attributes

See create_attribute_string_integer.cpp

And others

See src/examples/ subdirectory for more info.

H5Easy

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),
  • xt::xarray and xt::xtensor (optional).
  • cv::Mat_ (optional).

• Getting in a single line:

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

Example

#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.

CMake integration

There's two common paths of integrating HighFive into a CMake based project. The first is to "vendor" HighFive, the second is to install HighFive as a normal C++ library. Since HighFive makes choices about how to integrate HDF5, sometimes following the third Bailout Approach is needed.

Regular HDF5 CMake variables can be used. Interesting variables include:

• HDF5_USE_STATIC_LIBRARIES to link statically against the HDF5 library.
• HDF5_PREFER_PARALLEL to prefer pHDF5.
• HDF5_IS_PARALLEL to check if HDF5 is parallel.

Please consult tests/cmake_integration for examples of how to write libraries or applications using HighFive.

Vendoring HighFive

In this approach the HighFive sources are included in a subdirectory of the project (typically as a git submodule), for example in third_party/HighFive.

The projects CMakeLists.txt add the following lines

add_subdirectory(third_party/HighFive)
target_link_libraries(foo HighFive)

Note: add_subdirectory(third_party/HighFive) will search and "link" HDF5 but wont search or link any optional dependencies such as Boost.

Regular Installation of HighFive

Alternatively, HighFive can be install and "found" like regular software.

The project's CMakeLists.txt should add the following:

find_package(HighFive REQUIRED)
target_link_libraries(foo HighFive)

Note: find_package(HighFive) will search for HDF5. "Linking" to HighFive includes linking with HDF5. The two commands will not search for or "link" to optional dependencies such as Boost.

Bailout Approach

To prevent HighFive from searching or "linking" to HDF5 the project's CMakeLists.txt should contain the following:

# Prevent HighFive CMake code from searching for HDF5:
set(HIGHFIVE_FIND_HDF5 Off)

# Then "find" HighFive as usual:
find_package(HighFive REQUIRED)
# alternatively, when vendoring:
# add_subdirectory(third_party/HighFive)

# Finally, use the target `HighFive::Include` which
# doesn't add a dependency on HDF5.
target_link_libraries(foo HighFive::Include)

# Proceed to find and link HDF5 as required.

Optional Dependencies

HighFive does not attempt to find or "link" to any optional dependencies, such as Boost, Eigen, etc. Any project using HighFive with any of the optional dependencies must include the respective header:

#include <highfive/boost.hpp>
#include <highfive/eigen.hpp>

and add the required CMake code to find and link against the dependencies. For Boost the required lines might be

find_package(Boost REQUIRED)
target_link_libraries(foo PUBLIC Boost::headers)

Questions?

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.

For bugs and issues please use Issues.

Funding & Acknowledgment

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.

HighFive releases are uploaded to Zenodo. If you wish to cite HighFive in a scientific publication you can use the DOIs for the Zenodo records.

Copyright © 2015-2022 Blue Brain Project/EPFL

License

Boost Software License 1.0