Is it challenging to deploy to production, discuss your Python code with coworkers, or compile it from a source? The best technology to handle this for your Python project is Docker. It is one of the most widely used containerization technologies used by Python developers. . It enables the packaging of a program along with each of its dependencies into a solitary, small-footprint container. Containerization is the name of this procedure.
Why you should containerize your app
Now the important question arises why you should containerize your app? Well, it has a simple logic let’s understand.
A minor update in an external library’s version can alter your application’s functionality and cause it to act differently. Because of this, containerizing a program enables it to run consistently regardless of the workspace or device that it is installed on.
What Exactly Is Docker?
Now let’s have some basics of docker. What it is and how it can help in the containerization process of an app.
Docker is an open development, distribution, and execution environment for distributed applications. It provides the common toolbox needed by programmers, software developers, and operations professionals to benefit from the distributed and interconnected nature of modern systems.
How to containerize a Python application
Making a Docker image with the source code, dependencies, and configuration which is necessary to run a Python program is known as containerizing it. It’s a process.
- Decide which base image to utilize.
- Decide which files to copy into the Docker image.
- Install the application’s prerequisites.
Base image
The FROM command specifies a base image, which can be either a private or a public image.
We will utilize the official Python Docker image in this instance, which is accessible via the Docker hub.
The image name consists of two distinct components: picture: tag. In this instance, the tag is 3.8.5-slim-buster and the picture is python.
Copy the Application’s file
We’ll use the COPY command to copy the application inside the Docker image:
The specified files (or folder) are copied into the Docker image by this command. In this instance, we want to put all of the files from our local folder into the /src path of the Docker image.
Install dependencies
One thing to note is that requirements.txt’s path has changed since we ran the pip install for the first time.
Build and Run a Docker
Now that our Dockerfile is finished, we can use it to create a Docker image.
In this command, a Docker image named movie-recommender is created from the current folder (at the end specify which building context we will use).
How is that even doable? Why are we unable to connect to our container-running application?
We failed to make our application’s port accessible to the local machine, which is the cause.
Using the -p HostPort: ContainerPort flag, we can accomplish that.
Therefore, let’s try running the program once more while indicating that we wish to locally expose port 8888:
Now the curl localhost:8888
Just now, a Python application is containerized.
Wrapping Up
In this blog, we have learned how you can containerize your python applications in simple steps.
Originally published by: https://www.inexture.com/containerize-python-application-using-docker/
May 15, 2019: The global application container market size is expected to reach USD 8.2 billion by 2025, according to a new report by Grand View Research, Inc., registering a 26.5% CAGR during the forecast period.
Application containerization is used to deploy and run applications without launching separate Virtual Machines (VMs).
VMs and containers have similar resource allocation and isolation advantages; however, containers help virtualize the Operating System (OS) in place of hardware.
These solutions are more portable and efficient as compared to VMs owing to the requirement of fewer operating systems and minimum space.Request a Free Sample Copy of Application Container Market Report @ https://www.radiantinsights.com/research/application-container-market/request-sampleThe application container market has also been gaining prominence as a result of increasing adoption of containerization technology, particularly in retail, healthcare, banking and finance, and telecommunication sectors.
The banking, financial services, and insurance (BFSI) sector is one of the early adopters of this technology, which offers benefits such as administration ease and cost-effectiveness.The Docker datacenter is implemented in the banking sector as it provides benefits such as platform portability, higher security and smooth workflow of data, and efficient usage of infrastructure.
The BFSI sector has adopted the Docker platform due to the challenging environment of digital disruption, wherein the use of application containers enables improvements in software delivery capabilities.The report “Application Container Market” is available now at https://www.radiantinsights.com/research/application-container-market Further key findings from the report suggest:• The on-premise deployment segment is expected to exhibit a CAGR of around 25.0% over the forecast period• The large enterprises segment dominated the market by organization size in 2018, a trend that is expected to continue through 2025• By platform, the Docker segment was estimated at a value of over USD 700.0 million in 2018• On the basis of service, the monitoring and security segment is projected to account for over 30.0% of the overall market revenue by 2025, which can be credited to the containers' ability to prevent system breakdown by proactively identifying errors• North America accounted for the largest revenue share in 2018 and is projected to remain the dominant region over the forecast period, which is primarily attributed to high degree implementation of cloud technologies by vendors in the region• Prominent players in the application container market include Amazon Web Services, Inc.; Cisco Systems, Inc.; Google, Inc.; International Business Machines Corporation (IBM); and Red Hat, Inc.About Radiant Insights, IncRadiant Insights is a market research and consulting company offering syndicated research studies, customized reports, and consulting services.
