# ML4T Benchmark Environment
# Storage benchmarks: Parquet, DuckDB, HDF5, database clients
#
# Usage:
#   docker compose build benchmark
#   docker compose run --rm benchmark python 02_financial_data_universe/18_storage_benchmark_database.py
#
# Note: ArcticDB excluded (no Linux ARM64 wheels on PyPI)
# Use benchmark-full profile on x86 systems for ArcticDB benchmarks

FROM python:3.14-slim

ENV DEBIAN_FRONTEND=noninteractive
ENV TZ=UTC

# Install system dependencies.
# A modern Rust toolchain is required to build the questdb python client from
# sdist on linux/arm64 (PyPI ships no Linux arm64 wheel for it). Debian's
# packaged `cargo` is too old, so we install rustup so questdb-rs compiles
# successfully both on amd64 (where a wheel exists) and on arm64 (sdist build).
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential \
    curl \
    git \
    libhdf5-dev \
    pkg-config \
    && rm -rf /var/lib/apt/lists/*

# Install rustup so we have an up-to-date Rust toolchain for questdb-rs builds.
ENV CARGO_HOME=/opt/cargo \
    RUSTUP_HOME=/opt/rustup \
    PATH=/opt/cargo/bin:$PATH
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | \
        sh -s -- -y --default-toolchain stable --profile minimal

# Install uv for fast package management
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv

# Create non-root user
RUN useradd -m -s /bin/bash ml4t

# Create venv
RUN python -m venv /opt/ml4t

# Copy and install dependencies
WORKDIR /build
COPY envs/benchmark/pyproject.toml /build/

# Install all dependencies in one go. We deliberately do NOT have a fallback
# that strips questdb on failure — a successful build must include every
# database client declared in pyproject.toml so users never hit a runtime
# `ModuleNotFoundError`.
RUN /opt/ml4t/bin/pip install --no-cache-dir pip setuptools wheel && \
    /opt/ml4t/bin/pip install --no-cache-dir /build && \
    /opt/ml4t/bin/pip install --no-cache-dir "pytest>=8.0" "pytest-timeout>=2.3" "papermill>=2.6" "jupytext>=1.16"

WORKDIR /app
ENV PATH="/opt/ml4t/bin:$PATH"
ENV PYTHONPATH="/app"

# Jupyter configuration
ENV JUPYTER_ENABLE_LAB=yes
RUN mkdir -p /etc/jupyter && \
    echo "c.ServerApp.token = ''" >> /etc/jupyter/jupyter_server_config.py && \
    echo "c.ServerApp.password = ''" >> /etc/jupyter/jupyter_server_config.py && \
    echo "c.ServerApp.allow_origin = '*'" >> /etc/jupyter/jupyter_server_config.py

# Platform detection script
RUN echo '#!/bin/bash\n\
ARCH=$(uname -m)\n\
echo "============================================"\n\
echo "ML4T Benchmark Environment"\n\
echo "============================================"\n\
echo "Platform: $(uname -s) $ARCH"\n\
echo ""\n\
if [ "$ARCH" = "aarch64" ] || [ "$ARCH" = "arm64" ]; then\n\
    echo "Running on ARM64 (Apple Silicon compatible)"\n\
    echo "ArcticDB: Not available (use benchmark-full on x86)"\n\
else\n\
    echo "Running on x86_64"\n\
    echo "ArcticDB: Use benchmark-full profile for full benchmarks"\n\
fi\n\
echo ""\n\
echo "Available benchmarks:"\n\
echo "  - Parquet (PyArrow)"\n\
echo "  - DuckDB"\n\
echo "  - HDF5 (PyTables)"\n\
echo "  - ClickHouse"\n\
echo "  - TimescaleDB"\n\
echo "  - QuestDB"\n\
echo "  - InfluxDB"\n\
echo "============================================"' > /usr/local/bin/benchmark-status && chmod +x /usr/local/bin/benchmark-status

CMD ["jupyter", "lab", "--ip=0.0.0.0", "--no-browser"]