Singularity is a software solution designed to bring containers and reproducibility to scientific computing. It allows developers to work in reproducible environments and easily copy and execute these environments on different platforms. Singularity is an open-source initiative that integrates seamlessly into common workflows for both system and software engineers and researchers. Its primary use case is providing mobility of computing for users and HPC centers, ensuring secure capture and distribution of software and compute environments. This capability addresses a previously unmet need in computational science, making Singularity a game-changing development. The introduction highlights the evolving landscape of scientific computing, where virtualization has become essential for managing large-scale computational resources. However, the static nature of traditional HPC environments often limits the scope of computational science. Singularity aims to address this by enabling portable and reproducible environments, which are crucial for scientific reproducibility. The paper discusses the problems that Singularity solves, including the limitations of existing container solutions like Docker, virtual machines, and other container systems. Singularity offers mobility of compute by encapsulating the entire container and stack into a single image file, making it portable across different hosts and operating systems. It also ensures reproducibility by allowing users to snapshot and archive container images, and provides user freedom by allowing users to define their own working environments without impacting the host system. Singularity supports various container formats and integrates seamlessly with existing HPC resources, including different Linux distributions and resource managers. It also supports Docker images and can run Docker containers on demand. The paper provides detailed usage workflows, command examples, and best practices for creating and managing Singularity containers. The demonstrated validity of Singularity is evident from its rapid adoption, with over 36 research clusters across the world adopting it, and a significant number of jobs running on the Open Science Grid using Singularity containers.Singularity is a software solution designed to bring containers and reproducibility to scientific computing. It allows developers to work in reproducible environments and easily copy and execute these environments on different platforms. Singularity is an open-source initiative that integrates seamlessly into common workflows for both system and software engineers and researchers. Its primary use case is providing mobility of computing for users and HPC centers, ensuring secure capture and distribution of software and compute environments. This capability addresses a previously unmet need in computational science, making Singularity a game-changing development. The introduction highlights the evolving landscape of scientific computing, where virtualization has become essential for managing large-scale computational resources. However, the static nature of traditional HPC environments often limits the scope of computational science. Singularity aims to address this by enabling portable and reproducible environments, which are crucial for scientific reproducibility. The paper discusses the problems that Singularity solves, including the limitations of existing container solutions like Docker, virtual machines, and other container systems. Singularity offers mobility of compute by encapsulating the entire container and stack into a single image file, making it portable across different hosts and operating systems. It also ensures reproducibility by allowing users to snapshot and archive container images, and provides user freedom by allowing users to define their own working environments without impacting the host system. Singularity supports various container formats and integrates seamlessly with existing HPC resources, including different Linux distributions and resource managers. It also supports Docker images and can run Docker containers on demand. The paper provides detailed usage workflows, command examples, and best practices for creating and managing Singularity containers. The demonstrated validity of Singularity is evident from its rapid adoption, with over 36 research clusters across the world adopting it, and a significant number of jobs running on the Open Science Grid using Singularity containers.