docker-setup/Dockerfile at main · CyrusDioun/docker-setup · GitHub

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# Multi-stage build for optimized image size
FROM python:3.11-slim as base

# Install system dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    curl \
    git \
    vim \
    wget \
    libgomp1 \
    # For pandas/numpy optimization
    libblas-dev \
    liblapack-dev \
    gfortran \
    # For PostgreSQL connections
    libpq-dev \
    # For image processing
    libpng-dev \
    libjpeg-dev \
    # For Claude Code
    ca-certificates \
    gnupg \
    lsb-release \
    # Clean up
    && rm -rf /var/lib/apt/lists/*

# Install Node.js (required for Claude Code)
RUN curl -fsSL https://deb.nodesource.com/setup_20.x | bash - \
    && apt-get install -y nodejs \
    && rm -rf /var/lib/apt/lists/*

# Install Stata (Note: You'll need to provide your Stata license)
# Uncomment and modify the following lines when you have Stata installation files
# COPY stata17-linux.tar.gz /tmp/
# RUN cd /tmp && tar -xzf stata17-linux.tar.gz && \
#     cd stata17 && ./install && \
#     rm -rf /tmp/stata*

# Set up Python environment
WORKDIR /workspace

# Install core Python packages first (for better caching)
RUN pip install --no-cache-dir \
    "numpy<2.0" \
    "pandas>=2.0,<2.2" \
    "scipy>=1.10,<1.12" \
    matplotlib \
    seaborn \
    jupyter \
    jupyterlab \
    ipython

# Install ML/NLP libraries with compatible versions
RUN pip install --no-cache-dir \
    "scikit-learn>=1.3,<1.4" \
    fuzzywuzzy \
    python-Levenshtein \
    "spacy>=3.6,<3.8" \
    nltk

# Install PyTorch (CPU version)
RUN pip install --no-cache-dir \
    torch==2.0.1 --index-url https://download.pytorch.org/whl/cpu

# Install TensorFlow (try latest available version)
RUN pip install --no-cache-dir tensorflow || \
    pip install --no-cache-dir tensorflow-cpu || \
    echo "TensorFlow installation failed, continuing without it"

# Download spaCy language model
RUN python -m spacy download en_core_web_sm

# Install additional useful libraries
RUN pip install --no-cache-dir \
    plotly==5.15.0 \
    dash==2.11.1 \
    requests==2.31.0 \
    beautifulsoup4==4.12.2 \
    sqlalchemy==2.0.19 \
    openpyxl==3.1.2 \
    xlrd==2.0.1 \
    pyarrow==12.0.1 \
    fastparquet==2023.7.0 \
    tqdm==4.65.0 \
    black==23.7.0 \
    pylint==2.17.4 \
    pytest==7.4.0

# Install Claude Code CLI
RUN npm install -g @anthropic-ai/claude-code

# Configure Jupyter
RUN jupyter notebook --generate-config && \
    echo "c.NotebookApp.token = ''" >> ~/.jupyter/jupyter_notebook_config.py && \
    echo "c.NotebookApp.password = ''" >> ~/.jupyter/jupyter_notebook_config.py

# Set environment variables for better performance with large datasets
ENV PYTHONUNBUFFERED=1
ENV OMP_NUM_THREADS=4
ENV MKL_NUM_THREADS=4
ENV NUMEXPR_NUM_THREADS=4

# Create directories for data and notebooks
RUN mkdir -p /workspace/data /workspace/notebooks /workspace/code

# Expose ports for Jupyter and any web apps
EXPOSE 8888 8050

# Default command
CMD ["/bin/bash"]