Skip to main content

Binary vs. Source Packages



Regardless of the package manager you’re using, you have two ways of installing programs on Linux. You either use a pre-built package, or compile it yourself. These days, the former usually wins out by default. There are, however, times when you should consider the alternative.


What Are Binary Packages?

Installing programs on Linux is usually quite different to installing on Windows. Rather than get the installers off a vendor’s website, the files are retrieved from a repository of programs, usually tailored for your operating system.

Files for separate programs are stored in an archive format. This bundles everything into a single file for easy access later. For example, Debian uses the DEB format to store their programs. These bundles are called binary packages.

Installing requires a special program to extract these files and put them onto your computer. That is to say, your package manager (e.g. APT, Yum, and so on). It also does other useful things, such as keep track of what files you have installed, and manage software updates.

Where do packages come from?

All software is written in lines of text called source code. They’re written in specific programming languages, such as C or C++. Generally however, you can’t just bundle that into an archive and call it a package. These lines need to be translated into a language your computer can understand and execute.

This process is called compiling, the end result creating binaries which your computer can run. It’s these binaries that are stored together inside a package, along with other things such as configuration files.

What Is Installing “From Source”?

Compiling source code isn’t just for making packages. In fact, creating such an archive from it is not even necessary. Basically, installing a program “from source” means installing something without using a package manager. You compile the source code and copy the binaries to your computer instead.
Most of the time, you can download a project’s source code from hosting services such as GitHub or BitBucket. Larger programs might even host it on a personal website. The code will usually be zipped up in an archive format (also known as a source package).

What you need to install this kind of archive is unarchive the package and paste it in your machine and most of the time you need to set the Path for the bin folder in order to execute the scripts at your will.

In this case you can find a README file or INSTALLATION file inside almost every archive and these files contain the appropriate instructions on installation. Installation and configuration is mostly based on terminal commands and remember to execute them as root.

Hope you learn something from this article. Thanks.
~ Chathumina Vimukthi

Comments

Post a Comment

Popular posts from this blog

Gitlab SSO implementation using Keycloak

  Prerequisites  Keycloak server should be up and running  By default Keycloak will start on http://localhost:8180 To install and configure Keycloak visit www.keycloak.org/docs/latest/getting_started/index.html. Gitlab must be installed locally By default Gitlab starts on http://localhost:3000 To install and configure Gitlab visit https://docs.gitlab.com/omnibus/manual_install.html Environment Gitlab Installed package - gitlab-ce_11.1.4-ce.0_amd64.deb (Omnibus package) Keycloak version - Version 4.2.1.Finalhttps://github.com/ChathuminaVimukthi/Gitlab-SSO-implementation-using-Keycloak SSO Configuration GitLab can be configured to act as a SAML 2.0 Service Provider (SP). This allows GitLab to consume assertions from a SAML 2.0 Identity Provider (IdP) to authenticate users. For this SSO implementation, Gitlab omnibus package is used. But the source package can be used as well. The configuration for the source packge is available on https:/...

Python vs AI

WHAT IS AI? From SIRI to self-driving cars, artificial intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons. WHY PYTHON FOR AI? Artificial intelligence today is properly known as narrow AI (or weak AI), in that it is designed to perform a narrow task (e.g. only facial recognition or only internet searches or only driving a car). However, the long-term goal of many researchers is to create general AI (AGI or strong AI). While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, AGI would outperform humans at nearly every cognitive task. For many years, we used Lisp, because it handled lists and trees really well, had garbage collection, and didn’t require type declarations. ...