Of course, these packages need to exist somewhere in your server, and installing them can be problematic without the right tools. Fortunately, that is a problem the Python developers have invested significant time investigating and correcting.
Django is a Python-based web framework that is used for developing complex, database-driven websites. It also operated under an open-source license indicating it is free to use. Django is ultra-fast and encourages security, and it is exceptionally adaptable, which is the cause of its immense popularity.
In this article, we will explore the newest methods to install or update to the latest version of Python on our Ubuntu system.
What is Python?
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. It’s high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development and use as a scripting or glue language to connect existing components together. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.
Kubectl is a command-line tool for Kubernetes. It allows us to execute Kubernetes operations via the API. We can use Kubectl to deploy apps, check logs as well as manage all the other resources of the cluster.
Kubernetes uses an HTTP-based REST API which is the actual Kubernetes user interface employed to manage it. This means that every Kubernetes operation is represented as an API endpoint and can be carried out based on an HTTP-request sent to the endpoint.
In this article, we will review Kubectl, and outline its installation, configuration, and use.
Pip is one of the best tools to install and manage Python packages. Pip has earned its fame by the number of applications using this tool. Used for its capabilities in handling binary packages over the easily installed package manager, Pip enables 3rd party package installations. Though the newest versions of Python come with pip installed as a default, this tutorial will show how to install Pip, check its version, and show some basic commands for its use. Watch the video below or review the following article for additional instructions.
A virtual machine is a simulated computer system which runs on a physical computer. In other words, a virtual machine is a computer inside a computer. Virtual machines allocate memory, a virtual CPU, disk storage space, and a network interface. This means that we can have a Windows computer that runs multiple virtual machines composed of Ubuntu Linux, macOS, Windows 10, Solaris, and CentOS, and they will all be completely separate from our parent Windows operating system.
Taiga is a free, open-source project management system. The back end consists of an API written in Python3 and Django, and the front end is written in AngularJS and CoffeeScript. Taiga can manage simple and complex projects, and also monitors the progress of a project. Taiga maintains logs that are displayed in the form of a worklist with all the functions and user stories added to the project.
Pyenv is an outstanding tool for managing multiple Python installations. Pyenv-virtualenv is a pyenv plugin that facilitates the creation and management of Python virtual environments with pyenv. This is a compelling proposition, making it possible to manage multiple Python versions with pyenv and provide the means to control the Python environment in a more granular manner.
Minikube is the name of a software program written in Go, which can build a local Kubernetes cluster on a single host. It uses a meager amount of resources to run a mini Kubernetes deployment. Minikube is mainly used for testing purposes using different scenarios or versions of Kubernetes
Virtualenv is a tool that creates an isolated environment separate from other projects. In this instance, we will be installing different Python versions, including their dependencies. Creating a virtual environment allows us to work on a Python project without affecting other projects that also use Python. It will utilize Python’s core files on the global environment to run, thus saving you disk space while providing the freedom to use different Python versions for separate apps or projects.