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https://github.com/ess-dmsc/h5cpp

C++ wrapper for the HDF5 C-library
https://github.com/ess-dmsc/h5cpp

h5cpp hdf5 hierarchical-data wrapper

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C++ wrapper for the HDF5 C-library

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# A modern C++ interface for HDF5



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*h5cpp* is a modern C++ wrapper for HDF5's C-API. 



## Motivation



[HDF5](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) is a powerful binary format. There is virtually nothing that cannot be stored in an HDF5 file. You can either use the C-API or one of the wrappers for a scripting language (for Python there is for instance [h5py](http://www.h5py.org/) or [pytables](http://www.pytables.org/)). To keep their interfaces simple, many of these wrappers do not provide the full functionality HDF5 has to offer. If you want to use all features available, you must use the C-API, which is, however, quite unwieldy and not conducive to modern C++ idioms. 



**h5cpp** provides a domain-agnostic and easy-to-use modern C++ interface to the full functionality of HDF5. 



We currently support:

* Linux

* Windows

* macOS



Although this and [Steven Varga's h5cpp project](https://github.com/steven-varga/h5cpp)

share the same name they are entirely unrelated.



## How to use *h5cpp*



You may bring in *h5cpp* as a [conan package](https://github.com/ess-dmsc/conan-h5cpp) or build and install the library manually [as described below](#how-to-build-h5cpp). 



In either case, you can bring it into your program by adding something like this in your `CMakeLists.txt` file:

```cmake

find_package(h5cpp REQUIRED)

.

.

.

add_executable(some_target some_code.cpp)

target_link_libraries(some_target h5cpp::h5cpp)

```

and adding the following:

```cpp

#include 

```

to your your source file.

Here is a small example of how to make use of the library in code:



```cpp



using namespace hdf5;



// create a file

file::File f = file::create("writing_vector.h5",file::AccessFlags::Truncate);



// create a group

node::Group root_group = f.root();

node::Group my_group = root_group.create_group("my_group");



// create a dataset

using data_type = std::vector;

data_type data{1,2,3,4};

node::Dataset dataset = my_group.create_dataset("data",

                                                datatype::create(),

                                                dataspace::create(data));



// write to dataset

dataset.write(data);

```



For more, please see the full [API documentation](https://ess-dmsc.github.io/h5cpp/index.html).



## How to build *h5cpp*



The minimum requirements for building the library are:



* a C++ compiler, gcc>=4.9 should do well

* the HDF5 C library (>=1.8.13 would do but >=1.10.0 is prefered)

* cmake >= 3.10

* _either_ the boost libraries _or_ a compiler with std::filesystem or std::experimental::filesystem (and specify H5CPP_WITH_BOOST=OFF to CMake)

* [sphinx](http://www.sphinx-doc.org/en/stable/), [breathe](https://github.com/michaeljones/breathe) (with python) and  [doxygen](https://www.doxygen.nl/index.html) for the documentation build

* [catch2](https://github.com/catchorg/catch2) to build the unit tests



The external library dependencies can be acquired and built using [Conan](https://conan.io/). Conan can be installed with PyPI: 

```

pip install conan

```

and that's it, CMake will handle the rest!



Alternatively you can manually install the dependencies to typical system locations. In this case please disable Conan by using the `-DH5CPP_CONAN=DISABLE` option when you run CMake. 



Building the library is standard cmake & make fare, out of source. For example,

in linux shell, you would do the following:



```bash

git clone https://github.com/ess-dmsc/h5cpp.git

cd h5cpp

mkdir build

cd build

cmake ..

make

```



In any case you should run the tests after the build.



```bash

$ make test

```



To install the library to system, you would follow this up with:

```bash

sudo make install

```



### Alternate install directory



If you do not wish to install *h5cpp* to your system folders you can slightly modify the

above steps. When building the library, invoke CMake with the following option:



```bash

cmake -DCMAKE_INSTALL_PREFIX=/home/user1/some/path ..

```

and accordingly, when building the client program:

```bash

cmake -Dh5cpp_DIR=/home/user1/some/path/lib/cmake/h5cpp-0.6.0 path/to/your/source

```

where version number may vary.



For OSX and Windows instructions, as well as instructions for building tests and documentation,

see the [online documentation](https://ess-dmsc.github.io/h5cpp/index.html).