Swimming with Elvis: Part 6
Environment and Package Management
It's critical to leverage the best available "tools that manage your tools" and your working environment reliably and efficiently.
Anaconda is a powerful tool for Python and R data science and machine learning. It's an open-source distribution that simplifies package management and deployment. Anaconda comes with a suite of over a thousand data science packages, and a package manager called Conda. Conda makes it easy to install both Python and non-Python packages, manage environments, and ensure all packages work together without conflicts. Anaconda also includes Jupyter Notebook, an environment for interactive computing, which is widely used in data analysis and scientific research.
Apt, or Advanced Package Tool, is the default package manager for Ubuntu and other Debian-based Linux distributions. It handles the installation and removal of software on your system. Apt simplifies the process of managing software on Unix-like computer systems by automating the retrieval, configuration, and installation of software packages. It also resolves and handles dependencies automatically. This means that if you want to install a software package that relies on other packages to function, Apt will identify these dependencies and install all necessary packages.
Pip, which stands for "Pip Installs Packages", is the standard package manager for Python. It allows you to install and manage additional libraries and dependencies that are not distributed as part of the standard Python library. Pip provides a simple way to install packages from the Python Package Index (PyPI) and other package directories. It also supports virtual environments, which is a key feature for Python developers as it allows them to create isolated Python environments for different projects, ensuring dependencies are kept separate and organized.
All for the wonderful low price of: free.
Next: Revision Control and Related Tools
