Containerizing Python Scripts for Beginners
This is a tutorial explaining how to containerize a python script.
Containerization is a powerful tool for developers, especially when working with Python scripts. It helps package code and dependencies in a lightweight container image that can run consistently on any system. This guide walks you through containerizing a simple Python script using Docker.
Sample Python Script
Here's a basic Python script that performs a time-delayed computation using sleep and logs the process. It also uses pandas to simulate a dependency.
from time import sleep
from random import randint
import pandas as pd
def compute(seconds: int):
print(f"Compute Time : {seconds}")
print("Starting Computation.")
sleep(seconds)
print("Completed Computation.")
return
if __name__ == "__main__":
compute_time = randint(1, 9)
compute(compute_time)
Dockerfile
FROM python:3.10
ENV PYTHONUNBUFFERED=1
WORKDIR /myapp
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY app.py .
CMD ["python3", "app.py"]
🔍 What’s Happening Here?
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FROM python:3.10: Starts with an official Python base image.
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ENV PYTHONUNBUFFERED=1: Ensures that all output is immediately printed to the logs (useful for debugging in containers).
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WORKDIR /myapp: Sets the working directory inside the container.
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COPY requirements.txt .: Copies the dependency list.
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RUN pip install -r requirements.txt: Installs Python dependencies.
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COPY app.py .: Adds your script into the container.
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CMD ["python3", "app.py"]: Sets the default command to run the script.