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Build CSP from Source
CSP is written in Python and C++ with Python and C++ build dependencies. While prebuilt wheels are provided for end users, it is also straightforward to build CSP from either the Python source distribution or the GitHub repository.
- Table of Contents
- Make commands
- Prerequisites
- Building with Conda on Linux
- Building with a system package manager
- Using System Dependencies
- Lint and Autoformat
- Testing
- Troubleshooting
As a convenience, CSP uses a Makefile
for commonly used commands. You can print the main available commands by running make
with no arguments
> make
build build the library
clean clean the repository
fix run autofixers
install install library
lint run lints
test run the tests
CSP has a few system-level dependencies which you can install from your machine package manager. Other package managers like conda
, nix
, etc, should also work fine. Currently, CSP relies on the GNU
compiler toolchain only.
The easiest way to get started on a Linux machine is by installing the necessary dependencies in a self-contained conda environment.
Tweak this script to create a conda environment, install the build dependencies, build, and install a development version of csp
into the environment. Note that we use micromamba in this example, but Anaconda, Miniconda, Miniforge, etc, should all work fine.
# download and install micromamba for Linux/Mac
"${SHELL}" <(curl -L micro.mamba.pm/install.sh)
# on windows powershell
# Invoke-Expression ((Invoke-WebRequest -Uri https://micro.mamba.pm/install.ps1).Content)
git clone https://github.com/Point72/csp.git
cd csp
git submodule update --init --recursive
# Note the operating system, change as needed
# Linux and MacOS should use the unix dev environment spec
micromamba create -n csp -f conda/dev-environment-unix.yml
# uncomment below if the build fails because git isn't new enough
#
# micromamba install -y -n csp git
# uncomment below if the build fails because perl-ipc-system is missing
# (this happens on some RHEL7 systems)
#
# micromamba install -y -n csp perl-ipc-system-simple
micromamba activate csp
make build-conda
# finally install into the csp conda environment
make develop
In Conda, we pull our dependencies from the Conda environment by setting the environment variable CSP_USE_VCPKG=0
. This will force the build to not pull dependencies from vcpkg. This may or may not work in other environments or with packages provided by other package managers or built from source, but there is too much variability for us to support alternative patterns.
Clone the repo and submodules with:
git clone https://github.com/Point72/csp.git
cd csp
git submodule update --init --recursive
Debian/Ubuntu/etc
# for vcpkg
sudo make dependencies-debian
# or
# sudo apt-get install -y automake bison cmake curl flex ninja-build tar unzip zip
# for g++
sudo apt install build-essential
Fedora/RedHat/Centos/Rocky/Alma/etc
# for vcpkg
sudo make dependencies-fedora
# or
# yum install -y automake bison cmake curl flex perl-IPC-Cmd tar unzip zip
# for g++
sudo dnf group install "Development Tools"
Homebrew
# for vcpkg
make dependencies-mac
# or
# brew install bison cmake flex make ninja
Python build and develop dependencies are specified in the pyproject.toml
, but you can manually install them:
make requirements
# or
# python -m pip install toml
# python -m pip install `python -c 'import toml; c = toml.load("pyproject.toml"); print("\n".join(c["build-system"]["requires"]))'`
# python -m pip install `python -c 'import toml; c = toml.load("pyproject.toml"); print("\n".join(c["project"]["optional-dependencies"]["develop"]))'`
Note that these dependencies would otherwise be installed normally as part of PEP517 / PEP518.
Build the python project in the usual manner:
make build
# on aarch64 linux, comment the above command and use this instead
# VCPKG_FORCE_SYSTEM_BINARIES=1 make build
# or
# python setup.py build build_ext --inplace
On aarch64
Linux the VCPKG_FORCE_SYSTEM_BINARIES environment variable must be set before running make build
:
VCPKG_FORCE_SYSTEM_BINARIES=1 make build
By default, we pull and build dependencies with vcpkg. We only support non-vendored dependencies via Conda (see A note about dependencies above).
CSP has listing and auto formatting.
Language | Linter | Autoformatter | Description |
---|---|---|---|
C++ | clang-format |
clang-format |
Style |
Python | ruff |
ruff |
Style |
Python | isort |
isort |
Imports |
C++ Linting
make lint-cpp
# or
# clang-format --dry-run -Werror -i -style=file `find ./cpp/ -name "*.*pp"`
C++ Autoformatting
make fix-cpp
# or
# clang-format -i -style=file `find ./cpp/ -name "*.*pp"`
Python Linting
make lint-py
# or
# python -m isort --check csp/ setup.py
# python -m ruff check csp/ setup.py
# python -m ruff format --check csp/ setup.py
Python Autoformatting
make fix-py
# or
# python -m isort csp/ setup.py
# python -m ruff format csp/ setup.py
Documentation Linting
make lint-docs
# or
# python -m mdformat --check docs/wiki/ README.md examples/README.md
# python -m codespell_lib docs/wiki/ README.md examples/README.md
Documentation Autoformatting
make fix-docs
# or
# python -m mdformat docs/wiki/ README.md examples/README.md
# python -m codespell_lib --write docs/wiki/ README.md examples/README.md
CSP has both Python and C++ tests. The bulk of the functionality is tested in Python, which can be run via pytest
. First, install the Python development dependencies with
make develop
For full test coverage including certain adapters and integration/regression tests, you will need to install some additional dependencies and spin up some services. These dependencies include:
- Graphviz: for generating static diagrams of graph structure
- Docker Compose: for spinning up self-contained services against which to integration-test adapters
On Debian/Ubuntu Linux, run
sudo apt-get install -y graphviz
On Fedora/RedHat/Centos/Rocky/Alma/etc, run
yum install -y graphviz
On MacOS using Homebrew, run
brew install graphviz
Python
make test-py
# or
# python -m pytest -v csp/tests --junitxml=junit.xml
make coverage-py
# or python -m pytest -v csp/tests --junitxml=junit.xml --cov=csp --cov-report xml --cov-report html --cov-branch --cov-fail-under=80 --cov-report term-missing
Adapters might rely on external services. For example, the kafka
adapter requires a cluster against which to test. We rely on docker compose for these services. We store docker compose files in the ci
directory, and convenience Makefile
commands are available:
make dockerup ADAPTER=kafka
# or
# docker compose -f ci/kafka/docker-compose.yml up -d
make dockerps ADAPTER=kafka
# or
# docker compose -f ci/kafka/docker-compose.yml ps
make dockerdown ADAPTER=kafka
# or
# docker compose -f ci/kafka/docker-compose.yml down
Note that tests may be skipped by default, so run with:
CSP_TEST_KAFKA=1 make test
# or
# CSP_TEST_KAFKA=1 python -m pytest -v csp/tests --junitxml=junit.xml
There are a few test flags available:
CSP_TEST_KAFKA
-
CSP_TEST_SKIP_EXAMPLES
: skip tests of examples folder
Check the vcpkg-manifest-install.log
files, and install the corresponding packages if needed.
For example, you may need to brew install pkg-config
.
Thrift requires bison > 2.5, but the default `/usr/bin/bison` is version 2.3.
Ensure the homebrew-installed bison (version >= 3.8) is before /usr/bin/bison
on $PATH
On ARM: export PATH="/opt/homebrew/opt/bison/bin:$PATH"
On Intel: export PATH="/usr/local/opt/bison/bin:$PATH"
Complete error message:
CMake Error: CMake was unable to find a build program corresponding to "Unix Makefiles". CMAKE_MAKE_PROGRAM is not set. You probably need to select a different build tool.
CMake Error: CMAKE_C_COMPILER not set, after EnableLanguage
vcpkg-manifest-install.log
:
CMake Error at scripts/cmake/vcpkg_execute_build_process.cmake:134
install-arm64-osx-dbg-out.log
:
ld: Assertion failed: (resultIndex < sectData.atoms.size()), function findAtom, file Relocations.cpp, line 1336.
collect2: error: ld returned 1 exit status
This is a known bug: https://github.com/Homebrew/homebrew-core/issues/145991
Retry the build with CXXFLAGS='-Wl,-ld_classic'
.
Apple Silicon (ARM):
CXX=/opt/homebrew/bin/g++-13 CXXFLAGS='-Wl,-ld_classic' make build
Intel:
CXX=/usr/local/opt/gcc/bin/g++-13 CXXFLAGS='-Wl,-ld_classic' make build
This wiki is autogenerated. To made updates, open a PR against the original source file in docs/wiki
.
Get Started (Tutorials)
Concepts
- CSP Node
- CSP Graph
- Historical Buffers
- Execution Modes
- Adapters
- Feedback and Delayed Edge
- Common Mistakes
How-to guides
- Use Statistical Nodes
- Create Dynamic Baskets
- Write Adapters:
- Profile CSP Code
References
- API Reference
- Glossary of Terms
- Examples
Developer Guide