nvidia-gpu-dataset / Dockerfile
Niladri Das
Add NVIDIA GPU dataset files
0bfbee7
# ───────────────────────────────────────
# πŸš€ 1️⃣ Multi-Stage Build for Smallest Image
# ───────────────────────────────────────
FROM python:3.9-slim AS builder
# Set a fixed working directory
WORKDIR /app
# Install essential build tools
RUN apt-get update && apt-get install -y gcc g++ python3-dev libffi-dev && \
python3 -m venv venv && \
. venv/bin/activate && \
pip install --no-cache-dir --upgrade pip setuptools wheel
# Copy only requirements first for better caching
COPY requirements.txt .
RUN apt-get install -y gfortran libopenblas-dev && \
. venv/bin/activate && \
pip install --no-cache-dir -r requirements.txt
# Copy the rest of the app files
COPY . .
# ───────────────────────────────────────
# πŸš€ 2️⃣ Runtime Image - Minimal & Secure
# ───────────────────────────────────────
FROM python:3.9-slim
# Set working directory
WORKDIR /app
# Copy virtual environment from builder stage
COPY --from=builder /app/venv /app/venv
# Environment Variables for Performance & Security
ENV PATH="/app/venv/bin:$PATH" \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
APP_USER=appuser
# Security: Create and use non-root user
RUN addgroup appgroup && adduser appuser && \
adduser appuser appgroup && \
chown -R appuser:appgroup /app
USER $APP_USER
# Copy application code (Ensures proper permissions)
COPY --chown=$APP_USER:appgroup . .
# Debugging commands to check working directory and list files
RUN pwd && ls -l /app
# Use a health check to ensure the container is running correctly
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s \
CMD python3 -c 'import os; exit(0 if os.path.exists("summary.py") else 1)'
# Use ENTRYPOINT instead of CMD for better runtime control
ENTRYPOINT ["python3", "summary.py"]