Managing Development Environments and Packages for Data Science Projects with Conda and Pip
Abstract
A talk presented on August 28, 2024, at PyCon Somalia 2024, organized by Zamzam University of Science and Technology.
Full text
Managing Development Environments and Packages for Data Science Projects with Conda and Pip Ahmed Unshur August 28, 2024 DOI: 10.5281/zenodo.14058297
About Ahmed Unshur -Psychologist and Data Scientist -Open Science Advocate 2
Agenda -Environments and Packages -Overview of Conda and Pip -Managing Environments and Packages Using Conda -Managing Packages Using Pip -Importance of Reproducibility -Best Practices and Tips 3
Environments and Packages -An environment is a self-contained directory that contains everything needed to run a project, including Python interpreter, libraries, and other dependencies. -A package is a collection of modules that provide set of related functionalities. 4
Why Environment and Package Management? -Project isolation -Dependency management -Reproducibility -Streamlined development -System stability 5
Conda is a powerful open source command line tool for package and environment management that runs on Windows, macOS, and Linux. 6
Conda vs. Miniconda vs. Anaconda Source: Planemo documentation 7
Pip -Pip is the standard package manager for Python. -It allows you to find, download, and install packages from PyPI. 8
9 Managing Environments and Packages Using Conda (Demo)