In this chapter, we'll pack into the container not only Python and Python script but also several Python libraries.

Dockerfile
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FROM python:3.9-slim

# Installing additional packages
RUN pip install numpy pandas scikit-learn

COPY . .
CMD ["python", "app.py"]

After specifying the base image, you use the RUN pip install command to install additional Python packages using the pip package manager. In this case, you're installing the numpy, pandas, and scikit-learn packages, which for example, might be crucial for data analysis and machine learning.

This Dockerfile demonstrates how to install dependencies and additional files in your Docker container for use in your data analysis or machine learning projects.

Installing Requirements

Here's the revised Dockerfile where libraries are installed using a requirements file:

Dockerfile
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FROM python:3.9-slim

# Copying all files 
COPY . .

# Installing dependencies from requirements file
RUN pip3 install -r requirements.txt

CMD ["python", "app.py"]

You also need to create a requirements.txt file listing the libraries you want to install. For example:

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numpy
pandas
scikit-learn

After that, you can build the Docker image using the command docker build -t <image_name> ., where <image_name> is the name you want to give to your image.