Martin-Molinero
78647d3a1d
* Update python 3.11 * Update ARM foundation image and minor improvements
251 lines
10 KiB
Plaintext
251 lines
10 KiB
Plaintext
# This is a version of DockerfileLeanFoundation for ARM
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# Some packages from the AMD image are excluded because they are not available on ARM or take too long to build
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# Use base system for cleaning up wayward processes
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FROM phusion/baseimage:jammy-1.0.1
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MAINTAINER QuantConnect <contact@quantconnect.com>
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# Use baseimage-docker's init system.
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CMD ["/sbin/my_init"]
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# Install OS Packages:
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# Misc tools for running Python.NET and IB inside a headless container.
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RUN add-apt-repository ppa:ubuntu-toolchain-r/test && apt-get update \
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&& apt-get install -y git libgtk2.0.0 bzip2 curl unzip wget python3-pip python3-opengl zlib1g-dev \
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xvfb libxrender1 libxtst6 libxi6 libglib2.0-dev libopenmpi-dev libstdc++6 openmpi-bin \
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r-base pandoc libcurl4-openssl-dev \
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openjdk-11-jdk openjdk-11-jre bbe \
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&& apt-get clean && apt-get autoclean && apt-get autoremove --purge -y \
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&& rm -rf /var/lib/apt/lists/*
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# Install dotnet 6 sdk & runtime
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# The .deb packages don't support ARM, the install script does
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ENV PATH="/root/.dotnet:${PATH}"
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RUN wget https://dot.net/v1/dotnet-install.sh && \
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chmod 777 dotnet-install.sh && \
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./dotnet-install.sh -c 6.0 && \
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rm dotnet-install.sh
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ENV DOTNET_ROOT="/root/.dotnet"
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# Set PythonDLL variable for PythonNet
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ENV PYTHONNET_PYDLL="/opt/miniconda3/lib/libpython3.11.so"
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# Install miniconda
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ENV CONDA="Miniconda3-py311_24.1.2-0-Linux-aarch64.sh"
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ENV PATH="/opt/miniconda3/bin:${PATH}"
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RUN wget -q https://cdn.quantconnect.com/miniconda/${CONDA} && \
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bash ${CONDA} -b -p /opt/miniconda3 && rm -rf ${CONDA}
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# Install java runtime for h2o lib
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RUN apt-get update && apt-get install -y alien dpkg-dev debhelper build-essential && wget https://download.oracle.com/java/17/latest/jdk-17_linux-aarch64_bin.rpm \
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&& alien -i jdk-17_linux-aarch64_bin.rpm \
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&& update-alternatives --install /usr/bin/java java /usr/lib/jvm/jdk-17-oracle-aarch64/bin/java 1 \
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&& rm jdk-17_linux-aarch64_bin.rpm
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# Avoid pip install read timeouts
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ENV PIP_DEFAULT_TIMEOUT=120
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# Install numpy first to avoid it not being resolved when installing libraries that depend on it next
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RUN pip install --no-cache-dir numpy==1.26.4
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# Install newer (than provided by ubuntu) cmake required by scikit build process
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RUN conda install -c conda-forge cmake==3.28.4 && conda clean -y --all
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# The list of packages in this image is shorter than the list in the AMD images
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# This list only includes packages that can be installed within 2 minutes on ARM
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RUN pip install --no-cache-dir \
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cython==3.0.9 \
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pandas==2.1.4 \
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scipy==1.11.4 \
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numpy==1.26.4 \
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wrapt==1.16.0 \
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astropy==6.0.0 \
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beautifulsoup4==4.12.3 \
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dill==0.3.8 \
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jsonschema==4.21.1 \
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lxml==5.1.0 \
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msgpack==1.0.8 \
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numba==0.59.0 \
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xarray==2024.2.0 \
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plotly==5.20.0 \
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jupyterlab==4.1.5 \
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tensorflow==2.16.1 \
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docutils==0.20.1 \
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gensim==4.3.2 \
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keras==3.0.5 \
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lightgbm==4.3.0 \
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nltk==3.8.1 \
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graphviz==0.20.1 \
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cmdstanpy==1.2.1 \
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copulae==0.7.9 \
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featuretools==1.30.0 \
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PuLP==2.8.0 \
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pymc==5.10.4 \
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rauth==0.7.3 \
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scikit-learn==1.4.1.post1 \
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scikit-optimize==0.10.0 \
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aesara==2.9.3 \
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tsfresh==0.20.2 \
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tslearn==0.6.3 \
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tweepy==4.14.0 \
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PyWavelets==1.5.0 \
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umap-learn==0.5.5 \
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fastai==2.7.14 \
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arch==6.3.0 \
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copulas==0.10.1 \
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cufflinks==0.17.3 \
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gym==0.26.2 \
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ipywidgets==8.1.2 \
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deap==1.4.1 \
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pykalman==0.9.7 \
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cvxpy==1.4.2 \
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pyro-ppl==1.9.0 \
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sklearn-json==0.1.0 \
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dtw-python==1.3.1 \
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gluonts==0.14.4 \
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gplearn==0.4.2 \
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jax==0.4.25 \
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pennylane==0.35.1 \
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PennyLane-Lightning==0.35.1 \
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pennylane-qiskit==0.35.1 \
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mplfinance==0.12.10b0 \
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hmmlearn==0.3.2 \
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ta==0.11.0 \
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seaborn==0.13.2 \
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optuna==3.5.0 \
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findiff==0.10.0 \
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sktime==0.27.1 \
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hyperopt==0.2.7 \
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bayesian-optimization==1.4.3 \
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matplotlib==3.7.5 \
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sdeint==0.3.0 \
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pandas_market_calendars==4.4.0 \
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ruptures==1.1.9 \
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simpy==4.1.1 \
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scikit-learn-extra==0.3.0 \
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ray==2.9.3 \
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"ray[tune]"==2.9.3 \
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"ray[rllib]"==2.9.3 \
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fastText==0.9.2 \
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h2o==3.46.0.1 \
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prophet==1.1.5 \
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Riskfolio-Lib==6.0.0 \
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torch==2.2.1 \
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torchvision==0.17.1 \
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ax-platform==0.3.7 \
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alphalens-reloaded==0.4.3 \
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pyfolio-reloaded==0.9.5 \
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altair==5.2.0 \
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modin==0.26.1 \
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persim==0.3.5 \
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ripser==0.6.8 \
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pydmd==1.0.0 \
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EMD-signal==1.6.0 \
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spacy==3.7.4 \
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pandas-ta==0.3.14b \
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pytorch-ignite==0.4.13 \
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tensorly==0.8.1 \
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mlxtend==0.23.1 \
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shap==0.45.0 \
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lime==0.2.0.1 \
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mpmath==1.3.0 \
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polars==0.20.15 \
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stockstats==0.6.2 \
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QuantStats==0.0.62 \
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hurst==0.0.5 \
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numerapi==2.18.0 \
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pymdptoolbox==4.0-b3 \
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panel==1.3.8 \
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hvplot==0.9.2 \
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py-heat==0.0.6 \
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py-heat-magic==0.0.2 \
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bokeh==3.3.4 \
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river==0.21.0 \
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stumpy==1.12.0 \
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pyvinecopulib==0.6.4 \
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ijson==3.2.3 \
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jupyter-resource-usage==1.0.2 \
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injector==0.21.0 \
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openpyxl==3.1.2 \
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xlrd==2.0.1 \
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mljar-supervised==1.1.6 \
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dm-tree==0.1.8 \
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lz4==4.3.3 \
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ortools==9.9.3963 \
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py_vollib==1.0.1 \
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thundergbm==0.3.17 \
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yellowbrick==1.5 \
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livelossplot==0.5.5 \
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gymnasium==0.28.1 \
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interpret==0.5.1 \
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DoubleML==0.7.1 \
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jupyter-bokeh==4.0.0 \
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imbalanced-learn==0.12.0 \
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openai==1.14.3 \
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lazypredict-nightly==0.3.0 \
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darts==0.28.0 \
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fastparquet==2024.2.0 \
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tables==3.9.2 \
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dimod==0.12.14 \
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dwave-samplers==1.2.0 \
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python-statemachine==2.1.2 \
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pymannkendall==1.4.3 \
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Pyomo==6.7.1 \
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gpflow==2.9.1 \
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pyarrow==15.0.1 \
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dwave-ocean-sdk==6.9.0 \
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chardet==5.2.0 \
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stable-baselines3==2.2.1 \
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Shimmy==1.3.0 \
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FixedEffectModel==0.0.5 \
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transformers==4.38.2 \
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langchain==0.1.12 \
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pomegranate==1.0.4 \
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MAPIE==0.8.3 \
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mlforecast==0.12.0 \
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x-transformers==1.27.19 \
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Werkzeug==3.0.1
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# Install dwave tool
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RUN dwave install --all -y
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# Install 'ipopt' solver for 'Pyomo'
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RUN conda install -c conda-forge ipopt==3.14.14 \
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&& conda clean -y --all
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# We install need to install separately else fails to find numpy
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RUN pip install --no-cache-dir iisignature==0.24
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# Install spacy models
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RUN python -m spacy download en_core_web_md && python -m spacy download en_core_web_sm
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RUN conda config --set solver classic && conda install -y -c conda-forge \
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openmpi=5.0.2 \
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&& conda clean -y --all
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# Install nltk data
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RUN python -m nltk.downloader -d /usr/share/nltk_data punkt && \
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python -m nltk.downloader -d /usr/share/nltk_data vader_lexicon && \
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python -m nltk.downloader -d /usr/share/nltk_data stopwords && \
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python -m nltk.downloader -d /usr/share/nltk_data wordnet
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# Install Pyrb
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RUN wget -q https://cdn.quantconnect.com/pyrb/pyrb-master-250054e.zip && \
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unzip -q pyrb-master-250054e.zip && cd pyrb-master && \
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pip install . && cd .. && rm -rf pyrb-master && rm pyrb-master-250054e.zip
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# Install SSM
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RUN wget -q https://cdn.quantconnect.com/ssm/ssm-master-646e188.zip && \
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unzip -q ssm-master-646e188.zip && cd ssm-master && \
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pip install . && cd .. && rm -rf ssm-master && rm ssm-master-646e188.zip
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RUN echo "{\"argv\":[\"python\",\"-m\",\"ipykernel_launcher\",\"-f\",\"{connection_file}\"],\"display_name\":\"Foundation-Py-Default\",\"language\":\"python\",\"metadata\":{\"debugger\":true}}" > /opt/miniconda3/share/jupyter/kernels/python3/kernel.json
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# Install wkhtmltopdf and xvfb to support HTML to PDF conversion of reports
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RUN apt-get update && apt install -y xvfb wkhtmltopdf && \
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apt-get clean && apt-get autoclean && apt-get autoremove --purge -y && rm -rf /var/lib/apt/lists/*
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# Install fonts for matplotlib
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RUN wget -q https://cdn.quantconnect.com/fonts/foundation.zip && unzip -q foundation.zip && rm foundation.zip \
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&& mv "lean fonts/"* /usr/share/fonts/truetype/ && rm -rf "lean fonts/" "__MACOSX/" |