Create Dockerfile

Dockerfile

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+# 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
+
+# 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