#
#   LEAN Foundation Docker Container 20201214
#   Cross platform deployment for multiple brokerages
#   Intended to be used in conjunction with Dockerfile. This is just the foundation common OS+Dependencies required.
#

# Use base system for cleaning up wayward processes
FROM phusion/baseimage:focal-1.0.0

MAINTAINER QuantConnect <contact@quantconnect.com>

# Use baseimage-docker's init system.
CMD ["/sbin/my_init"]

# Have to add env TZ=UTC. See https://github.com/dotnet/coreclr/issues/602
RUN env TZ=UTC

# Install OS Packages:
# Misc tools for running Python.NET and IB inside a headless container.
RUN add-apt-repository ppa:ubuntu-toolchain-r/test \
   && echo deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ >> /etc/apt/sources.list \
   && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9 \
   && add-apt-repository ppa:apt-fast/stable && apt-get update && apt-get -y install apt-fast \
   && apt-fast install -y git bzip2 curl unzip wget python3-pip python-opengl zlib1g-dev \
   xvfb libxrender1 libxtst6 libxi6 libglib2.0-dev libopenmpi-dev libstdc++6 openmpi-bin \
   pandoc libcurl4-openssl-dev libgtk2.0.0 r-base \
   && apt-fast clean && apt-get remove -y apt-fast && apt-get clean && apt-get autoclean && apt-get autoremove --purge -y \
   && rm -rf /var/lib/apt/lists/*

# Install IB Gateway: Installs to /root/ibgateway
RUN mkdir -p /root/ibgateway && \
    wget https://cdn.quantconnect.com/interactive/ibgateway-latest-standalone-linux-x64.v10.12.2d.sh && \
    chmod 777 ibgateway-latest-standalone-linux-x64.v10.12.2d.sh && \
    ./ibgateway-latest-standalone-linux-x64.v10.12.2d.sh -q -dir /root/ibgateway && \
    rm ibgateway-latest-standalone-linux-x64.v10.12.2d.sh

# Install dotnet 6 sdk & runtime
RUN wget https://packages.microsoft.com/config/ubuntu/20.04/packages-microsoft-prod.deb -O packages-microsoft-prod.deb && \
    dpkg -i packages-microsoft-prod.deb && \
    apt-get update; \
    apt-get install -y apt-transport-https && \
    apt-get update && \
    apt-get install -y dotnet-sdk-6.0 && \
    rm packages-microsoft-prod.deb && \
    apt-get clean && apt-get autoclean && apt-get autoremove --purge -y && rm -rf /var/lib/apt/lists/*

# Set PythonDLL variable for PythonNet
ENV PYTHONNET_PYDLL="/opt/miniconda3/lib/libpython3.8.so"

# Install miniconda
ENV CONDA="Miniconda3-4.5.12-Linux-x86_64.sh"
ENV PATH="/opt/miniconda3/bin:${PATH}"
RUN wget https://cdn.quantconnect.com/miniconda/${CONDA} && \
    bash ${CONDA} -b -p /opt/miniconda3 && rm -rf ${CONDA} && \
    conda install -y conda=4.10.3 && \
    pip install --upgrade --no-cache-dir pip==22.2.2 && \
    conda install -y python=3.8.13 && conda install -y -c conda-forge pip=22.2.2 && conda clean -y --all

# Avoid pip install read timeouts
ENV PIP_DEFAULT_TIMEOUT=120

# Install all packages
RUN pip install --no-cache-dir      \
    cython==0.29.30                 \
    pandas==1.4.3                   \
    scipy==1.8.1                    \
    numpy==1.22.4                   \
    wrapt==1.14.1                   \
    astropy==5.1                    \
    beautifulsoup4==4.11.1          \
    dill==0.3.5.1                   \
    jsonschema==4.9.1               \
    lxml==4.9.1                     \
    msgpack==1.0.4                  \
    numba==0.56.0                   \
    xarray==2022.6.0                \
    plotly==5.9.0                   \
    jupyterlab==3.4.4               \
    tensorflow==2.9.1               \
    docutils==0.19                  \
    cvxopt==1.3.0                   \
    gensim==4.2.0                   \
    keras==2.9.0                    \
    lightgbm==3.3.2                 \
    mpi4py==3.1.3                   \
    nltk==3.7                       \
    graphviz==0.8.4                 \
    cmdstanpy==1.0.4                \
    copulae==0.7.7                  \
    featuretools==0.18.1            \
    PuLP==2.6.0                     \
    pymc==4.1.4                     \
    rauth==0.7.3                    \
    scikit-learn==1.0.2             \
    scikit-multiflow==0.5.3         \
    scikit-optimize==0.9.0          \
    aesara==2.7.9                   \
    tsfresh==0.15.1                 \
    tslearn==0.5.2                  \
    tweepy==4.10.0                  \
    PyWavelets==1.3.0               \
    umap-learn==0.5.3               \
    fastai==2.7.7                   \
    arch==5.3.1                     \
    copulas==0.7.0                  \
    creme==0.6.1                    \
    cufflinks==0.17.3               \
    gym==0.25.1                     \
    ipywidgets==8.0.0rc1            \
    deap==1.3.3                     \
    cvxpy==1.2.1                    \
    pykalman==0.9.5                 \
    pyportfolioopt==1.5.1           \
    pmdarima==1.8.5                 \
    pyro-ppl==1.8.1                 \
    riskparityportfolio==0.3        \
    sklearn-json==0.1.0             \
    statsmodels==0.13.2             \
    QuantLib==1.27                  \
    xgboost==1.6.1                  \
    dtw-python==1.2.2               \
    mxnet==1.9.1                    \
    gluonts==0.7.7                  \
    gplearn==0.4.2                  \
    jax==0.3.16                     \
    jaxlib==0.3.15                  \
    keras-rl==0.4.2                 \
    pennylane==0.25.1               \
    neural-tangents==0.6.0          \
    mplfinance==0.12.9b1            \
    hmmlearn==0.2.7                 \
    catboost==1.0.6                 \
    fastai2==0.0.30                 \
    scikit-tda==1.0.0               \
    ta==0.10.1                      \
    seaborn==0.11.2                 \
    optuna==2.10.1                  \
    findiff==0.9.2                  \
    sktime==0.13.1                  \
    hyperopt==0.2.7                 \
    bayesian-optimization==1.2.0    \
    rpy2==3.5.3                     \
    pingouin==0.5.2                 \
    quantecon==0.5.3                \
    matplotlib==3.5.3               \
    sdeint==0.3.0                   \
    pandas_market_calendars==3.5    \
    dgl==0.9.0                      \
    ruptures==1.1.7                 \
    simpy==4.0.1                    \
    scikit-learn-extra==0.2.0       \
    ray==1.13                       \
    fastText==0.9.2                 \
    tigramite==5.0.0.1              \
    h2o==3.36.1.4                   \
    prophet==1.1                    \
    Riskfolio-Lib==3.3.0            \
    nbeats-keras==1.7.0             \
    nbeats-pytorch==1.6.0           \
    torch==1.12.1                   \
    torchvision==0.13.1             \
    ax-platform==0.2.6

RUN conda install -y -c conda-forge \
    openmpi=4.1.4                   \
    && conda clean -y --all

# Install PyTorch Geometric
RUN TORCH=$(python -c "import torch; print(torch.__version__)") && \
    CUDA=$(python -c "import torch; print('cu' + torch.version.cuda.replace('.', ''))") && \
    pip install --no-cache-dir -f https://pytorch-geometric.com/whl/torch-${TORCH}+${CUDA}.html \
    torch-scatter==2.0.9 torch-sparse==0.6.14 torch-cluster==1.6.0 torch-spline-conv==1.2.1 torch-geometric==2.0.4

RUN python -m nltk.downloader -d /usr/share/nltk_data punkt && \
    python -m nltk.downloader -d /usr/share/nltk_data vader_lexicon && \
    python -m nltk.downloader -d /usr/share/nltk_data stopwords

# Install ppscore
RUN wget https://cdn.quantconnect.com/ppscore/ppscore-master-ce93fa3.zip && \
    unzip -q ppscore-master-ce93fa3.zip && cd ppscore-master && \
    pip install . && cd .. && rm -rf ppscore-master && rm ppscore-master-ce93fa3.zip

# Install DX Analytics
RUN wget https://cdn.quantconnect.com/dx/dx-master-69922c0.zip && \
    unzip -q dx-master-69922c0.zip && cd dx-master && \
    pip install . && cd .. && rm -rf dx-master && rm dx-master-69922c0.zip

# Install Pyrb
RUN wget https://cdn.quantconnect.com/pyrb/pyrb-master-250054e.zip && \
    unzip -q pyrb-master-250054e.zip && cd pyrb-master && \
    pip install . && cd .. && rm -rf pyrb-master && rm pyrb-master-250054e.zip

# Install SSM
RUN wget https://cdn.quantconnect.com/ssm/ssm-master-646e188.zip && \
    unzip -q ssm-master-646e188.zip && cd ssm-master && \
    pip install . && cd .. && rm -rf ssm-master && rm ssm-master-646e188.zip

# Install TA-lib for python
RUN wget https://cdn.quantconnect.com/ta-lib/ta-lib-0.4.0-src.tar.gz && \
    tar -zxvf ta-lib-0.4.0-src.tar.gz && cd ta-lib && \
    ./configure --prefix=/usr && make && make install && \
    wget https://cdn.quantconnect.com/ta-lib/TA_Lib-0.4.18.zip && \
    unzip -q TA_Lib-0.4.18.zip && cd ta-lib-TA_Lib-0.4.18 && \
    python setup.py install && cd ../.. && rm -rf ta-lib && rm ta-lib-0.4.0-src.tar.gz

# Due to conflicts install 'pomegranate' virtual environment package
RUN python -m venv /Foundation-Pomegranate --system-site-packages && . /Foundation-Pomegranate/bin/activate \
    && pip install --no-cache-dir       \
    pomegranate==0.14.8                 \
    && python -m ipykernel install --name=Foundation-Pomegranate \
    && deactivate

# Due to conflicts install 'tensorforce' virtual environment package with older tensorflow
RUN python -m venv /Foundation-Tensorforce && . /Foundation-Tensorforce/bin/activate \
    && pip install --no-cache-dir       \
    tensorflow==2.6.0                   \
    keras==2.6.0                        \
    tensorforce==0.6.5                  \
    gym==0.21                           \
    jupyterlab==3.4.4                   \
    stable-baselines3==1.6.0            \
    && python -m ipykernel install --name=Foundation-Tensorforce \
    && deactivate

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

# List all packages
RUN conda list