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Learn how to install Pymysql in Alpine Linux for your Python Docker projects. This guide provides clear Dockerfile instructions and code examples.

Python Docker - Install Pymysql in Alpine

Install Pymysql in Alpine Linux for Docker

This guide demonstrates how to install the pymysql library within an Alpine Linux-based Python Docker image. Alpine Linux is a popular choice for Docker images due to its small size, which helps in creating efficient and lightweight containers.

To install pymysql in Alpine, you need to ensure that the necessary build dependencies are present before installing the Python package. This often involves installing development headers for the underlying C libraries that mysqlclient (a common dependency for pymysql) relies on.

Here is a sample Dockerfile that accomplishes this:

FROM --platform=amd64 python:3.8-alpine

RUN apk add --no-cache mariadb-connector-c-dev && \
    apk add --no-cache --virtual .build-deps \
        build-base \
        mariadb-dev && \
    pip install mysqlclient && \
    apk del .build-deps

# You can then import pymysql in your Python code
# import pymysql
# pymysql.install_as_MySQLdb()

Explanation of the Dockerfile:

The Dockerfile uses a multi-stage build approach implicitly by installing build dependencies and then removing them. This keeps the final image size minimal.

  • FROM --platform=amd64 python:3.8-alpine: Specifies the base Python image, using a specific version and the Alpine variant.
  • RUN apk add --no-cache mariadb-connector-c-dev: Installs the MariaDB connector C development files, which are often required for mysqlclient.
  • apk add --no-cache --virtual .build-deps build-base mariadb-dev: Installs essential build tools and MariaDB development headers as temporary build dependencies.
  • pip install mysqlclient: Installs the mysqlclient package, which provides a Python interface for MySQL databases.
  • apk del .build-deps: Removes the temporary build dependencies to reduce the final image size.

This method ensures that pymysql can be installed and used effectively within your Alpine-based Python Docker environment.

Further Resources: