This library is based on @jupp0r prometheus-cpp library (https://github.com/jupp0r/prometheus-cpp). It offers a quick way to instantiate an object to ease metrics creation and management from every program module.
This image is already available at github container registry
and docker hub
for every repository tag
, and also for master as latest
:
$ docker pull ghcr.io/testillano/metrics:<tag>
You could also build it using the script ./build.sh
located at project root:
$ ./build.sh --project-image
This image is built with ./Dockerfile
.
To run compilation over this image, just run with docker
. The entrypoint
(check it at ./deps/build.sh
) will fall back from cmake
(looking for CMakeLists.txt
file at project root, i.e. mounted on working directory /code
to generate makefiles) to make
, in order to build your source code. There are two available environment variables used by the builder script of this image: BUILD_TYPE
(for cmake
) and MAKE_PROCS
(for make
):
$ envs="-e MAKE_PROCS=$(grep processor /proc/cpuinfo -c) -e BUILD_TYPE=Release"
$ docker run --rm -it -u $(id -u):$(id -g) ${envs} -v ${PWD}:/code -w /code \
ghcr.io/testillano/metrics:<tag>
This image is already available at github container registry
and docker hub
for every repository tag
, and also for master as latest
:
$ docker pull ghcr.io/testillano/metrics_builder:<tag>
You could also build it using the script ./build.sh
located at project root:
$ ./build.sh --builder-image
This image is built with ./Dockerfile.build
.
Builder image is used to build the project library. To run compilation over this image, again, just run with docker
:
$ envs="-e MAKE_PROCS=$(grep processor /proc/cpuinfo -c) -e BUILD_TYPE=Release"
$ docker run --rm -it -u $(id -u):$(id -g) ${envs} -v ${PWD}:/code -w /code \
ghcr.io/testillano/metrics_builder:<tag>
You could generate documentation passing extra arguments to the entry point behind:
$ docker run --rm -it -u $(id -u):$(id -g) ${envs} -v ${PWD}:/code -w /code \
ghcr.io/testillano/metrics_builder::<tag>-build "" doc
You could also build the library using the script ./build.sh
located at project root:
$ ./build.sh --project
This is a cmake-based building library, so you may install cmake:
$ sudo apt-get install cmake
And then generate the makefiles from project root directory:
$ cmake .
You could specify type of build, 'Debug' or 'Release', for example:
$ cmake -DCMAKE_BUILD_TYPE=Debug .
$ cmake -DCMAKE_BUILD_TYPE=Release .
You could also change the compilers used:
$ cmake -DCMAKE_CXX_COMPILER=/usr/bin/g++ -DCMAKE_C_COMPILER=/usr/bin/gcc
or
$ cmake -DCMAKE_CXX_COMPILER=/usr/bin/clang++ -DCMAKE_C_COMPILER=/usr/bin/clang
$ make
$ make clean
$ make doc
$ cd docs/doxygen
$ tree -L 1
.
├── Doxyfile
├── html
├── latex
└── man
$ sudo make install
Optionally you could specify another prefix for installation:
$ cmake -DMY_OWN_INSTALL_PREFIX=$HOME/mylibs/ert_metrics
$ make install
$ cat install_manifest.txt | sudo xargs rm
To embed the library directly into an existing CMake project, place the entire source tree in a subdirectory and call add_subdirectory()
in your CMakeLists.txt
file:
add_subdirectory(ert_metrics)
...
add_library(foo ...)
...
target_link_libraries(foo PRIVATE ert_metrics::ert_metrics)
Since CMake v3.11, FetchContent can be used to automatically download the repository as a dependency at configure type.
Example:
include(FetchContent)
FetchContent_Declare(ert_metrics
GIT_REPOSITORY https://github.com/testillano/metrics.git
GIT_TAG vx.y.z)
FetchContent_GetProperties(ert_metrics)
if(NOT ert_json_POPULATED)
FetchContent_Populate(ert_metrics)
add_subdirectory(${ert_metrics_SOURCE_DIR} ${ert_metrics_BINARY_DIR} EXCLUDE_FROM_ALL)
endif()
target_link_libraries(foo PRIVATE ert_metrics::ert_metrics)
Please, execute astyle
formatting (using frankwolf image) before any pull request:
$ sources=$(find . -name "*.hpp" -o -name "*.cpp")
$ docker run -i --rm -v $PWD:/data frankwolf/astyle ${sources}