{"id":3958,"date":"2023-11-04T23:13:57","date_gmt":"2023-11-04T23:13:57","guid":{"rendered":"http:\/\/localhost:10003\/working-with-docker-containers\/"},"modified":"2023-11-05T05:48:27","modified_gmt":"2023-11-05T05:48:27","slug":"working-with-docker-containers","status":"publish","type":"post","link":"http:\/\/localhost:10003\/working-with-docker-containers\/","title":{"rendered":"Working with Docker Containers"},"content":{"rendered":"
Docker is a platform that enables developers to package, ship, and run applications in containers. Containers are lightweight virtualized environments that provide a consistent runtime environment for applications. Docker containers can be used to develop, deploy, test, and run applications in any environment, on any machine, with minimal overhead. This tutorial will cover the basics of working with Docker containers, including creating, building, and running Docker images.<\/p>\n
To follow along with this tutorial, you will need the following:<\/p>\n
To create a new Docker container, we need to use a Dockerfile. A Dockerfile is a simple text file that contains a set of instructions that Docker uses to build a Docker image. Let’s create a Dockerfile for our application.<\/p>\n
Create a new file named This Dockerfile describes the steps required to build a Docker image for a Python application. Here’s a brief explanation of what’s happening in each step:<\/p>\n Now that we’ve created our Dockerfile, we’re ready to build the Docker image. Run the following command in your project directory:<\/p>\n This command will build a Docker image with the tag This output indicates that the Docker image was successfully built with the name Now that we’ve built our Docker image, we can use it to create a Docker container. Run the following command:<\/p>\n This will start a new Docker container from the This output indicates that the application is running and can be accessed at `http:\/\/localhost:8080` in your web browser.<\/p>\n To stop a Docker container, run the following command:<\/p>\n You can get the To remove a Docker container, run the following command:<\/p>\n You can get the To remove a Docker image, run the following command:<\/p>\n You can get the Docker containers provide a simple, consistent runtime environment for applications that can be used to develop, deploy, test, and run applications in any environment. In this tutorial, we covered the basics of working with Docker containers, including creating a Dockerfile, building a Docker image, and running a Docker container. We also covered how to stop and remove Docker containers and images. With these skills, you should be well on your way to working with Docker containers in your own projects.<\/p>\n","protected":false},"excerpt":{"rendered":" Introduction Docker is a platform that enables developers to package, ship, and run applications in containers. Containers are lightweight virtualized environments that provide a consistent runtime environment for applications. Docker containers can be used to develop, deploy, test, and run applications in any environment, on any machine, with minimal overhead. Continue Reading<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","footnotes":""},"categories":[1],"tags":[199,572,568,567,569,570,571,566],"yoast_head":"\nDockerfile<\/code> in your project directory and paste the following code:<\/p>\n
# Use an official Python runtime as a parent image\nFROM python:3.7-slim\n\n# Set the working directory\nWORKDIR \/app\n\n# Copy the requirements file into the container\nCOPY requirements.txt .\n\n# Install dependencies\nRUN pip install --no-cache-dir -r requirements.txt\n\n# Copy the rest of the application code\nCOPY . .\n\n# Expose port 8080 for our application\nEXPOSE 8080\n\n# Start the application\nCMD [ \"python\", \".\/app.py\" ]\n<\/code><\/pre>\n
\n
FROM python:3.7-slim<\/code>: This instruction is used to specify the base image for our Docker container. In this case, it’s the official Python 3.7 image.<\/li>\n
WORKDIR \/app<\/code>: This instruction sets the working directory for our application to
\/app<\/code>.<\/li>\n
COPY requirements.txt .<\/code>: This instruction copies the
requirements.txt<\/code> file from our local machine to the
\/app<\/code> directory in the container.<\/li>\n
RUN pip install --no-cache-dir -r requirements.txt<\/code>: This instruction installs the dependencies specified in the
requirements.txt<\/code> file.<\/li>\n
COPY . .<\/code>: This instruction copies the rest of the application code from our local machine to the
\/app<\/code> directory in the container.<\/li>\n
EXPOSE 8080<\/code>: This instruction exposes port 8080 for our application.<\/li>\n
CMD [ \"python\", \".\/app.py\" ]<\/code>: This instruction specifies the command to start the application.<\/li>\n<\/ul>\n
docker build -t myapp .\n<\/code><\/pre>\n
myapp<\/code> from the
Dockerfile<\/code> located in the current directory (
.<\/code>). You should see output similar to the following:<\/p>\n
Sending build context to Docker daemon 5.632kB\nStep 1\/6 : FROM python:3.7-slim\n...\nSuccessfully built 1234567890ab\nSuccessfully tagged myapp:latest\n<\/code><\/pre>\n
myapp<\/code> and the tag
latest<\/code>.<\/p>\n
Running a Docker Container<\/h2>\n
docker run -p 8080:8080 myapp\n<\/code><\/pre>\n
myapp<\/code> image we just built. The
-p<\/code> option is used to map port 8080 in the container to port 8080 on your local machine. You should see output similar to the following:<\/p>\n
* Serving Flask app \"app\" (lazy loading)\n * Environment: production\n WARNING: This is a development server. Do not use it in a production deployment.\n Use a production WSGI server instead.\n * Debug mode: off\nINFO:werkzeug: * Running on http:\/\/0.0.0.0:8080\/ (Press CTRL+C to quit)\n<\/code><\/pre>\n
Stopping a Docker Container<\/h2>\n
docker stop <container_id>\n<\/code><\/pre>\n
container_id<\/code> by running
docker ps<\/code>. This will list all running Docker containers along with their container IDs. Simply copy the ID of the container you want to stop and paste it into the command.<\/p>\n
Cleaning Up<\/h2>\n
docker rm <container_id>\n<\/code><\/pre>\n
container_id<\/code> by running
docker ps -a<\/code>, which lists all Docker containers, including those that are stopped.<\/p>\n
docker rmi <image_name>:<tag>\n<\/code><\/pre>\n
<image_name><\/code> and
<tag><\/code> by running
docker images<\/code>, which lists all Docker images on your local machine.<\/p>\n
Conclusion<\/h2>\n