Dockerfile

# Start with a lightweight Linux Anaconda image
FROM continuumio/miniconda3

# Update all packages and install nano unzip and curl
RUN apt-get update
RUN apt-get install nano unzip curl -y

# THIS IS SPECIFIC TO HUGGINFACE
# We create a new user named "user" with ID of 1000
RUN useradd -m -u 1000 user
# We switch from "root" (default user when creating an image) to "user" 
USER user
# We set two environment variables 
# so that we can give ownership to all files in there afterwards
# we also add /home/user/.local/bin in the $PATH environment variable 
# PATH environment variable sets paths to look for installed binaries
# We update it so that Linux knows where to look for binaries if we were to install them with "user".
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH

# We set working directory to $HOME/app (<=> /home/user/app)
WORKDIR $HOME/app

# Install basic dependencies
RUN pip install boto3 pandas gunicorn streamlit scikit-learn matplotlib seaborn plotly openpyxl

# Copy all local files to /home/user/app with "user" as owner of these files
# Always use --chown=user when using HUGGINGFACE to avoid permission errors
COPY --chown=user . $HOME/app

# THIS IS SPECIFIC TO HUGGINGFACE AS WELL
# expose port 7860 which is the port used by HuggingFace for Web Applications
EXPOSE 7860

# Run streamlit server
CMD streamlit run --server.port 7860 app.py