(2) When there is docker image for AMD64, you can pull them and use docker history --no-trunc to view the build commands
(3) And then create a Dockerfile to build it in your arm64 environment, it is also possibe to cross compile it in AMD64 CPU environment.
(4) For example, the creation Dockerfile to build for Quantlib juypter notebook server is as below.
P.S. You need more RAM to build using gcc, preferably 4GB to 8GB
- Shell script Select all
cd $HOME
mkdir -p my-quantlib
cd my-quantlib
# get helloworld.ipynb
wget https://raw.githubusercontent.com/lballabio/dockerfiles/master/quantlib-jupyter/Hello%20world.ipynb
cat >$HOME/my-quantlib/Dockerfile_ql_1.20 <<'HEREEOF'
# Dockerfile_ql_1.20
# docker build -f Dockerfile_ql_1.20 -t arm64v8/quantlib:1.20 .
# docker buildx build --platform linux/arm64 -t arm64v8/quantlib:1.20 .
# Build Quantlib libraries for arm64v8
ARG tag=latest
FROM arm64v8/ubuntu:20.04
MAINTAINER Luigi Ballabio <luigi.ballabio@gmail.com>
LABEL Description="Provide a building environment where the QuantLib Python jupyter-notebook"
RUN apt-get update \
&& DEBIAN_FRONTEND=noninteractive apt-get install -y build-essential wget libbz2-dev vim git
ENV boost_version=1.67.0
ENV boost_dir=boost_1_67_0
# Build boost
RUN echo 'Building boost ...'
#RUN wget https://dl.bintray.com/boostorg/release/${boost_version}/source/${boost_dir}.tar.gz \
RUN wget https://nchc.dl.sourceforge.net/project/boost/boost/${boost_version}/${boost_dir}.tar.gz \
&& tar xfz ${boost_dir}.tar.gz \
&& rm ${boost_dir}.tar.gz \
&& cd ${boost_dir} \
&& ./bootstrap.sh \
&& ./b2 --without-python --prefix=/usr -j 4 link=shared runtime-link=shared install \
&& cd .. && rm -rf ${boost_dir} && ldconfig
# Build Quantlib C++
RUN echo 'Building Quantlib C++ ...'
ENV quantlib_version=1.20
#RUN wget https://dl.bintray.com/quantlib/releases/QuantLib-${quantlib_version}.tar.gz \
RUN wget https://github.com/lballabio/QuantLib/releases/download/QuantLib-v1.20/QuantLib-${quantlib_version}.tar.gz \
&& tar xfz QuantLib-${quantlib_version}.tar.gz \
&& rm QuantLib-${quantlib_version}.tar.gz \
&& cd QuantLib-${quantlib_version} \
&& ./configure --prefix=/usr --disable-static CXXFLAGS=-O3 \
&& make -j 4 && make check && make install \
&& make clean \
&& cd .. && ldconfig
# && cd .. && rm -rf QuantLib-${quantlib_version} && ldconfig
# Build Quantlib-Python
RUN echo 'Build Quantlib-Python ...'
RUN apt-get update \
&& DEBIAN_FRONTEND=noninteractive apt-get install -y swig python3 python3-pip python-dev libgomp1
# Build Quantlib for Python3
RUN echo 'Install Quantlib Python'
ENV quantlib_swig_version=1.20
#RUN wget https://dl.bintray.com/quantlib/releases/QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
RUN wget https://github.com/lballabio/QuantLib-SWIG/releases/download/QuantLib-SWIG-v${quantlib_swig_version}/QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& tar xfz QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& rm QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& cd QuantLib-SWIG-${quantlib_swig_version} \
&& ./configure CXXFLAGS="--param ggc-min-expand=1 --param ggc-min-heapsize=32768" PYTHON=/usr/bin/python3 \
&& make -C Python && make -C Python check && make -C Python install \
&& cd .. && rm -rf QuantLib-SWIG-${quantlib_swig_version} && ldconfig
# Build jupyter-notebook server
RUN python3 -c "print('\033[91m Building jupyter-notebook server ... \033[0m')"
RUN pip3 install --no-cache-dir jupyter jupyterlab matplotlib numpy scipy pandas ipywidgets RISE
RUN jupyter-nbextension install rise --py --sys-prefix
RUN jupyter-nbextension install widgetsnbextension --py --sys-prefix \
&& jupyter-nbextension enable widgetsnbextension --py --sys-prefix
# Build Quantlib for Python2
RUN apt-get update \
&& DEBIAN_FRONTEND=noninteractive apt-get install -y python \
&& apt-get clean
RUN wget https://bootstrap.pypa.io/pip/2.7/get-pip.py \
&& python2 get-pip.py \
&& rm get-pip.py
#RUN wget https://dl.bintray.com/quantlib/releases/QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
RUN wget https://github.com/lballabio/QuantLib-SWIG/releases/download/QuantLib-SWIG-v${quantlib_swig_version}/QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& tar xfz QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& rm QuantLib-SWIG-${quantlib_swig_version}.tar.gz \
&& cd QuantLib-SWIG-${quantlib_swig_version} \
&& ./configure CXXFLAGS="--param ggc-min-expand=1 --param ggc-min-heapsize=32768" \
&& make -C Python && make -C Python check && make -C Python install \
&& cd .. && rm -rf QuantLib-SWIG-${quantlib_swig_version} && ldconfig
RUN pip2 install --no-cache-dir numpy
EXPOSE 8888
RUN mkdir /notebooks
VOLUME /notebooks
COPY *.ipynb /notebooks/
# Starting jupyter-notebook server
RUN python3 -c "print('\033[92m Starting jupyter-notebook server at port 8888 \033[0m')"
CMD jupyter notebook --no-browser --allow-root --ip=0.0.0.0 --port=8888 --notebook-dir=/notebooks
HEREEOF
# build image
docker build -f Dockerfile_ql_1.20 -t arm64v8/quantlib:1.20 .
# run image
docker run -d -p 8888:8888 --name myquantlibtesting arm64v8/quantlib:1.20
# list the token of the jupyter-notebook server
docker container exec -it myquantlibtesting jupyter notebook list
(5) Testing QuantLib C++ libraries and Quantlib for Python2 and Python3
- Shell script Select all
#create and start container for testing
docker run -it --rm --name myquantlib arm64v8/quantlib:1.20 /bin/bash
#Create testql.cpp
cd $HOME
cat > testql.cpp << 'testqlEOF'
#include <ql/quantlib.hpp>
int main() {
std::cout << "BOOST version is " << BOOST_VERSION << std::endl;
std::cout << "QL version is " << QL_VERSION << std::endl;
#if __x86_64__ || __WORDSIZE == 64
std::cout << "This is 64 bits" << std::endl;
#elif __i386__ || __WORDSIZE == 32
std::cout << "This is 32 bits" << std::endl;
#else
std::cout << "This is something else" << std::endl;
#endif
return 0;
}
testqlEOF
g++ testql.cpp -lQuantLib -o testql
./testql
# Test QuantLib C++ Examples
cd $HOME
g++ /QuantLib-*/Examples/Bonds/Bonds.cpp -lQuantLib -o testBonds
./testBonds
cd $HOME
g++ /QuantLib-*/Examples/FRA/FRA.cpp -lQuantLib -o testFRA
./testFRA
# Test python 3 QuantLib
cd $HOME
cat > $HOME/swap.py <<EOF
from __future__ import print_function
import numpy as np
import QuantLib as ql
print("QuantLib version is", ql.__version__)
# Set Evaluation Date
today = ql.Date(31,3,2015)
ql.Settings.instance().setEvaluationDate(today)
# Setup the yield termstructure
rate = ql.SimpleQuote(0.03)
rate_handle = ql.QuoteHandle(rate)
dc = ql.Actual365Fixed()
disc_curve = ql.FlatForward(today, rate_handle, dc)
disc_curve.enableExtrapolation()
hyts = ql.YieldTermStructureHandle(disc_curve)
discount = np.vectorize(hyts.discount)
start = ql.TARGET().advance(today, ql.Period('2D'))
end = ql.TARGET().advance(start, ql.Period('10Y'))
nominal = 1e7
typ = ql.VanillaSwap.Payer
fixRate = 0.03
fixedLegTenor = ql.Period('1y')
fixedLegBDC = ql.ModifiedFollowing
fixedLegDC = ql.Thirty360(ql.Thirty360.BondBasis)
index = ql.Euribor6M(ql.YieldTermStructureHandle(disc_curve))
spread = 0.0
fixedSchedule = ql.Schedule(start, end, fixedLegTenor, index.fixingCalendar(), fixedLegBDC, fixedLegBDC, ql.DateGeneration.Backward, False)
floatSchedule = ql.Schedule(start, end, index.tenor(), index.fixingCalendar(), index.businessDayConvention(), index.businessDayConvention(), ql.DateGeneration.Backward, False)
swap = ql.VanillaSwap(typ, nominal, fixedSchedule, fixRate, fixedLegDC, floatSchedule, index, spread, index.dayCounter())
engine = ql.DiscountingSwapEngine(ql.YieldTermStructureHandle(disc_curve))
swap.setPricingEngine(engine)
print(swap.NPV())
print(swap.fairRate())
EOF
# Test python3
cd $HOME
python3 swap.py
# Test python2
cd $HOME
git clone git://github.com/mmport80/QuantLib-with-Python-Blog-Examples.git
cd QuantLib-with-Python-Blog-Examples/
python2 blog_frn_example.py
cd $HOME
python2 swap.py
