Python and Docker: Building a Python Development Environment in Docker

Table of Contents

  1. Introduction
  2. Prerequisites
  3. Setup
  4. Creating a Dockerfile
  5. Building the Docker Image
  6. Running a Container
  7. Managing Python Dependencies
  8. Conclusion

Introduction

In this tutorial, we will learn how to build a Python development environment using Docker. Docker is a popular platform for containerization, which allows us to create and manage isolated environments for our applications. By the end of this tutorial, you will be able to set up a Python development environment using Docker and efficiently manage Python dependencies within the container.

Prerequisites

To follow this tutorial, you should have basic knowledge of Python programming. Additionally, you should have Docker installed on your machine. If you haven’t already installed Docker, please visit the official Docker website and follow the instructions to install it for your specific operating system.

Setup

Before we begin, let’s create a new directory called python-docker where we will keep all our project files. Open your terminal or command prompt and execute the following command to create the directory: bash mkdir python-docker Next, navigate to the newly created directory: bash cd python-docker

Creating a Dockerfile

A Dockerfile is a text file that contains all the commands necessary to build a Docker image. Let’s create a new file called Dockerfile in the python-docker directory. Use your favorite text editor to open the file. bash touch Dockerfile Add the following content to the Dockerfile: ```Dockerfile # Use an official Python runtime as the base image FROM python:3.9

# Set the working directory in the container
WORKDIR /app

# Copy the requirements file into the container
COPY requirements.txt .

# Install the Python dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of the application code into the container
COPY . .
``` Explanation of the Dockerfile:
  • FROM python:3.9 specifies the base image to use, which includes Python 3.9.
  • WORKDIR /app sets the working directory inside the container to /app.
  • COPY requirements.txt . copies the requirements.txt file from the host into the container’s /app directory.
  • RUN pip install --no-cache-dir -r requirements.txt installs the Python dependencies specified in requirements.txt into the container.
  • COPY . . copies the rest of the application code from the host into the container’s /app directory.

Save and close the Dockerfile.

Building the Docker Image

Now that we have our Dockerfile ready, we can build a Docker image based on it. From the terminal or command prompt, run the following command: bash docker build -t python-docker . Explanation:

  • The -t flag specifies the name and optionally a tag for our image. In this case, we named it python-docker.
  • The . indicates the build context, which is the current directory. Docker will look for the Dockerfile in the build context and use it to build the image.

Docker will now execute the instructions in the Dockerfile and build the image. This may take a few minutes depending on your internet connection speed and system resources.

Running a Container

Once the image is built successfully, we can run a container based on it. Run the following command in the terminal or command prompt: bash docker run -it --name python-dev python-docker

Published:

Related Articles